Геоморфометрия сегодня

https://doi.org/10.35595/2414-9179-2021-2-27-394-448

Посмотреть или загрузить статью (Rus)

Об авторе

И.В. Флоринский

Институт математических проблем биологии РАН — филиал Института прикладной математики им. М.В. Келдыша РАН,
Пущино, Московская обл., 142290, Россия;
E-mail: iflor@mail.ru

Аннотация

Рельеф является важнейшим компонентом географической оболочки, одним из основных элементов геосистем, каркасом ландшафта. Геоморфометрия — научная дисциплина, предметом которой является моделирование и анализ рельефа, а также взаимосвязей между ним и другими компонентами геосистем. В настоящее время аппарат геоморфометрии широко применяется для решения различных разномасштабных задач в науках о Земле. В рамках конкурса РФФИ «Экспансия» представлен аналитический обзор развития теории, методов и приложений геоморфометрии за период 2016–2021 гг. Для анализа использовалась выборка из 485 наиболее сильных и оригинальных работ, опубликованных в международных журналах I и II квартиля (Q1–Q2) JCR Web of Science Core Collection, а также монографии ведущих международных издательств. Проанализированы факторы, вызвавшие прогресс геоморфометрии: распространение беспилотной аэрофотосъемки, развитие средств и методов съемки подводного рельефа, появление новых глобальных цифровых моделей рельефа (ЦМР), разработка новых методов предобработки ЦМР для их фильтрации и подавления шума, развитие методов двумерной и трехмерной визуализации ЦМР, внедрение методов машинного обучения и др. Рассмотрены аспекты геоморфометрической теории, получившие развитие в 2016–2021 гг. В частности, представлена новая классификация морфометрических величин. Обсуждаются новые вычислительные методы, позволяющие рассчитывать по ЦМР модели морфометрических величин, а также проблемы, стоящие перед разработчиками и пользователями таких методов. Рассмотрено применение аппарата геоморфометрии для решения задач геоморфологии, гидрологии, почвоведения, геологии, гляциологии, спелеологии, геоботаники, лесоведения, зоогеографии, океанологии, планетологии, оползневедения, дистанционного зондирования, урбанистики и археологии.

Ключ. слова

геоморфометрия, обзор, рельеф, цифровое моделирование рельефа.

Список литературы

  1. Abdel-Fattah M., Saber M., Kantoush S.A., Khalil M.F., Sumi T., Sefelnasr A.M. A hydrological and geomorphometric approach to understanding the generation of wadi flash floods. Water, 2017. V. 9. No. 7. # 553. DOI: 10.3390/w9070553.
  2. Abrams M., Crippen R., Fujisada H. ASTER Global Digital Elevation Model (GDEM) and ASTER Global Water Body Dataset (ASTWBD). Remote Sensing, 2020. V. 12. No. 7. # 1156. DOI: 10.3390/rs12071156.
  3. Agrafiotis P., Skarlatos D., Georgopoulos A., Karantzalos K. DepthLearn: learning to correct the refraction on point clouds derived from aerial imagery for accurate dense shallow water bathymetry based on SVMs-fusion with LiDAR point clouds. Remote Sensing, 2019. V. 11. No. 19. # 2225. DOI: 10.3390/rs11192225.
  4. Akpa S.I.C., Odeh I.O.A., Bishop T.F.A., Hartemink A.E., Amapu I.Y. Total soil organic carbon and carbon sequestration potential in Nigeria. Geoderma, 2016. V. 271. P. 202–215. DOI: 10.1016/j.geoderma.2016.02.021.
  5. Alexander C., Deák B., Heilmeier H. Micro-topography driven vegetation patterns in open mosaic landscapes. Ecological Indicators, 2016. V. 60. P. 906–920. DOI: 10.1016/j.ecolind.2015.08.030.
  6. Alifu H., Johnson B.A., Tateishi R. Delineation of debris-covered glaciers based on a combination of geomorphometric parameters and a TIR/NIR/SWIR band ratio. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016. V. 9. No. 2. P. 781–792. DOI: 10.1109/JSTARS.2015.2500906.
  7. Alifu H., Vuillaume J.-F., Johnson B.A., Hirabayashi Y. Machine-learning classification of debris-covered glaciers using a combination of Sentinel-1/-2 (SAR/optical), Landsat 8 (thermal) and digital elevation data. Geomorphology, 2020. V. 369. # 107365. DOI: 10.1016/j.geomorph.2020.107365.
  8. Alonso-Sarría F., Gomariz-Castillo F., Cánovas-García F. A new approach to the openness index for landform characterisation. Computers and Geosciences, 2018. V. 119. P. 68–79. DOI: 10.1016/j.cageo.2018.06.010.
  9. Alvarez L., Moreno H., Segales A., Pham T., Pillar-Little E., Chilson P. Merging unmanned aerial systems (UAS) imagery and echo soundings with an adaptive sampling technique for bathymetric surveys. Remote Sensing, 2018. V. 10. No. 9. # 1362. DOI: 10.3390/rs10091362.
  10. Alvioli M., Guzzetti F., Marchesini I. Parameter-free delineation of slope units and terrain subdivision of Italy. Geomorphology, 2020. V. 358. # 107124. DOI: 10.1016/j.geomorph.2020.107124.
  11. Amatulli G., Domisch S., Tuanmu M.N., Parmentier B., Ranipeta A., Malczyk J., Jetz W. A suite of global, cross-scale topographic variables for environmental and biodiversity modeling. Scientific Data, 2018. V. 5. # 180040. DOI: 10.1038/sdata.2018.40.
  12. Amatulli G., McInerney D., Sethi T., Strobl P., Domisch S. Geomorpho90m, empirical evaluation and accuracy assessment of global high-resolution geomorphometric layers. Scientific Data, 2020. V. 7. # 162. DOI: 10.1038/s41597-020-0479-6.
  13. Anderson K., Westoby M.J., James M.R. Low-budget topographic surveying comes of age: structure from motion photogrammetry in geography and the geosciences. progress in physical geography, 2019. V. 43. No. 2. P. 163–173. DOI: 10.1177/0309133319837454.
  14. Andreani L., Gloaguen R. Geomorphic analysis of transient landscapes in the Sierra Madre de Chiapas and Maya Mountains (northern Central America): implications for the North American–Caribbean–Cocos plate boundary. Earth Surface Dynamics, 2016. V. 4. No. 2. P. 71–102. DOI: 10.5194/esurf-4-71-2016.
  15. Angelini M.E., Heuvelink G.B.M., Kempen B., Morrás H.J.M. Mapping the soils of an Argentine pampas region using structural equation modelling. Geoderma, 2016. V. 281. P. 102–118. DOI: 10.1016/j.geoderma.2016.06.031.
  16. Angelini M.E., Heuvelink G.B.M., Kempen B. Multivariate mapping of soil with structural equation modelling. European Journal of Soil Science, 2017. V. 68. No. 5. P. 575–591. DOI: 10.1111/ejss.12446.
  17. Argyriou A.V., Sarris A., Teeuw R.M. Using geoinformatics and geomorphometrics to quantify the geodiversity of Crete, Greece. International Journal of Applied Earth Observation and Geoinformation, 2016. V. 51. P. 47–59. DOI: 10.1016/j.jag.2016.04.006.
  18. Argyriou A.V., Teeuw R.M., Rust D., Sarris A. GIS multi-criteria decision analysis for assessment and mapping of neotectonic landscape deformation: a case study from Crete. Geomorphology, 2016. V. 253. P. 262–274. DOI: 10.1016/j.geomorph.2015.10.018.
  19. Argyriou A.V., Teeuw R.M., Sarris A. GIS-based landform classification of Bronze Age archaeological sites on Crete Island. PLoS ONE, 2017a. V. 12. No. 2. # e0170727. DOI: 10.1371/journal.pone.0170727.
  20. Argyriou A.V., Teeuw R.M., Soupios P., Sarris A. Neotectonic control on drainage systems: GIS-based geomorphometric and morphotectonic assessment for Crete, Greece. Journal of Structural Geology, 2017b. V. 104. P. 93–111. DOI: 10.1016/j.jsg.2017.10.002.
  21. Arundel S.T., Sinha G. Validating the use of object-based image analysis to map commonly recognized landform features in the United States. Cartography and Geographic Information Science, 2019. V. 46. No. 5. P. 441–455. DOI: 10.1080/15230406.2018.1526652.
  22. Arundel S.T., Thiem P.T., Constance E.W. Automated extraction of hydrographically corrected contours for the conterminous United States: the US Geological Survey US Topo Product. Cartography and Geographic Information Science, 2018. V. 45. No. 1. P. 31–55. DOI: 10.1080/17538947.2020.1754936.
  23. Atkinson J., de Clercq W., Rozanov A. Multi-resolution soil-landscape characterisation in KwaZulu Natal: using geomorphons to classify local soilscapes for improved digital geomorphological modelling. Geoderma Regional, 2020. V. 22. # e00291. DOI: 10.1016/j.geodrs.2020.e00291.
  24. Avanzi F., Bianchi A., Cina A., de Michele C., Maschio P., Pagliari D., Passoni D., Pinto L., Piras M., Rossi L. Centimetric accuracy in snow depth using unmanned aerial system photogrammetry and a MultiStation. Remote Sensing, 2018. V. 10. No. 5. # 765. DOI: 10.3390/rs10050765.
  25. Bailey J.J., Boyd D.S., Hjort J., Lavers C.P., Field R. Modelling native and alien vascular plant species richness: at which scales is geodiversity most relevant? Global Ecology and Biogeography, 2017. V. 26. No. 7. P. 763–776. DOI: 10.1111/geb.12574.
  26. Bailey J.J., Boyd D.S., Field R. Models of upland species’ distributions are improved by accounting for geodiversity. Landscape Ecology, 2018. V. 33. No. 12. P. 2071–2087. DOI: 10.1007/s10980-018-0723-z.
  27. Bakker M., Lane S.N. Archival photogrammetric analysis of river-floodplain systems using Structure from Motion (SfM) methods. Earth Surface Processes and Landforms, 2017. V. 42. No. 8. P. 1274–1286. DOI: 10.1002/esp.4085.
  28. Baldwin D., Naithani K.J., Lin H. Combined soil-terrain stratification for characterizing catchment-scale soil moisture variation. Geoderma, 2017. V. 285. P. 260–269. DOI: 10.1016/j.geoderma.2016.09.031.
  29. Ballabio C., Panagos P., Monatanarella L. Mapping topsoil physical properties at European scale using the LUCAS database. Geoderma, 2016. V. 261. P. 110–123. DOI: 10.1016/j.geoderma.2015.07.006.
  30. Bargain A., Marchese F., Savini A., Taviani M., Fabri M.-C. Santa Maria di Leuca Province (Mediterranean Sea): identification of suitable mounds for cold-water coral settlement using geomorphometric proxies and maxent methods. Frontiers in Marine Science, 2017. V. 4. # 338. DOI: fmars.2017.00338.
  31. Parallel Priority-Flood depression filling for trillion cell digital elevation models on desktops or clusters. Computers and Geosciences, 2016. V. 96. P. 56–68. DOI: 10.1016/j.cageo.2016.07.001.
  32. Bash E.A., Moorman B.J. Surface melt and the importance of water flow—an analysis based on high-resolution unmanned aerial vehicle (UAV) data for an Arctic glacier. Cryosphere, 2020. V. 14. No. 2. P. 549–563. DOI: 10.5194/tc-14-549-2020.
  33. Bash E.A., Moorman B.J., Gunther A. Detecting short-term surface melt on an Arctic glacier using UAV surveys. Remote Sensing, 2018. V. 10. No. 10. # 1547. DOI: 10.3390/rs10101547.
  34. Behrens T., MacMillan R.A., Rossel R.A.V., Schmidt K., Lee J. Teleconnections in spatial modelling. Geoderma, 2019. V. 354. # 113854. DOI: 10.1016/j.geoderma.2019.07.012.
  35. Behrens T., Schmidt K., Macmillan R.A., Viscarra Rossel R.A. Multiscale contextual spatial modelling with the gaussian scale space. Geoderma, 2018a. V. 310. P. 128–137. DOI: 10.1016/j.geoderma.2017.09.015.
  36. Behrens T., Schmidt K., MacMillan R.A., Viscarra Rossel R.A. Multi-scale digital soil mapping with deep learning. Scientific Reports, 2018b. V. 8. # 15244. DOI: 10.1038/s41598-018-33516-6.
  37. Belgiu M., Drăguţ L. Random forest in remote sensing: a review of applications and future directions. ISPRS Journal of Photogrammetry and Remote Sensing, 2016. V. 114. P. 24–31. DOI: 10.1016/j.isprsjprs.2016.01.011.
  38. Bernhardson M., Alexanderson H. Early holocene dune field development in Dalarna, central Sweden: a geomorphological and geophysical case study. Earth Surface Processes and Landforms, 2017. V. 42. No. 12. P. 1847–1859. DOI: 10.1002/esp.4141.
  39. Bergonse R., Reis E. Controlling factors of the size and location of large gully systems: a regression-based exploration using reconstructed pre-erosion topography. Catena, 2016. V. 147. P. 621–631. DOI: 10.1016/j.catena.2016.08.014.
  40. Beven K.J., Kirkby M.J., Freer J.E., Lamb R. A history of TOPMODEL. Hydrology and Earth System Sciences, 2021. V. 25. No. 2. P. 527–549. DOI: 10.5194/hess-25-527-2021.
  41. Bhardwaj A., Sam L., Bhardwaj A., Martín-Torres F.J. LiDAR remote sensing of the cryosphere: present applications and future prospects. Remote Sensing of Environment, 2016a. V. 177. P. 125–143. DOI: 10.1016/j.rse.2016.02.031.
  42. Bhardwaj A., Sam L., Akanksha, Martín-Torres F.J., Kumar R. UAVs as remote sensing platform in glaciology: present applications and future prospects. Remote Sensing of Environment, 2016b. V. 175. P. 196–204. DOI: 10.1016/j.rse.2015.12.029.
  43. Bhardwaj A., Sam L., Martin-Torres F.J., Zorzano M.-P. Distribution and morphologies of transverse aeolian ridges in ExoMars 2020 Rover landing site. Remote Sensing, 2019a. V. 11. No. 8. # 912. DOI: 10.3390/rs11080912.
  44. Bhardwaj A., Sam L., Martín-Torres F.J., Zorzano M.-P., Ramírez Luque J.A. UAV imaging of a Martian brine analogue environment in a fluvio-aeolian setting. Remote Sensing, 2019b. V. 11. No. 18. # 2104. DOI: 10.3390/rs11182104.
  45. Bigelow P., Benda L., Pearce S. Delineating incised stream sediment sources within a San Francisco Bay tributary basin. Earth Surface Dynamics, 2016. V. 4. No. 2. P. 531–547. DOI: 10.5194/esurf-4-531-2016.
  46. Bispo P.d.C., dos Santos J.R., Valeriano M.d.M., Graça P.M.L.d.A., Balzter H., França H., Bispo P.d.C. Predictive models of primary tropical forest structure from geomorphometric variables based on SRTM in the Tapajós Region, Brazilian Amazon. PLoS ONE, 2016. V. 11. No. 6. # e0152009. DOI: 10.1371/journal.pone.0152009.
  47. Bispo P.d.C., Balzter H., Malhi Y., Slik J.W.F., dos Santos J.R., Rennó C.D., Espírito-Santo F.D., Aragão L.E.O.C., Ximenes A.C., Bispo P.d.C. Drivers of metacommunity structure diverge for common and rare Amazonian tree species. PLoS ONE, 2017. V. 12. No. 11. # e0188300. DOI: 10.1371/journal.pone.0188300.
  48. Björk G., Jakobsson M., Assmann K., Andersson L.G., Nilsson J., Stranne C., Mayer L. Bathymetry and oceanic flow structure at two deep passages crossing the lomonosov Ridge. ocean Science, 2018. V. 14. No. 1. P. 1–13. DOI: 10.5194/os-14-1-2018.
  49. Bladin K., Axelsson E., Broberg E., Emmart C., Ljung P., Bock A., Ynnerman A. Globe browsing: contextualized spatio-temporal planetary surface visualization. IEEE Transactions on Visualization and Computer Graphics, 2018. V. 24. No. 1. P. 802–811. DOI: 10.1109/TVCG.2017.2743958.
  50. Bliakharskii D.P., Florinsky I.V., Skrypitsyna T.N. Modelling glacier topography in Antarctica using unmanned aerial survey: assessment of opportunities. International Journal of Remote Sensing, 2019. V. 40. No. 7. P. 2517–2541. DOI: 10.1080/01431161.2019.1584926.
  51. Blomdin R., Stroeven A.P., Harbor J.M., Gribenski N., Caffee M.W., Heyman J., Rogozhina I., Ivanov M.N., Petrakov D.A., Walther M., Rudoy A.N., Zhang W., Orkhonselenge A., Hättestrand C., Lifton N.A., Jansson K.N. Timing and dynamics of glaciation in the Ikh Turgen Mountains, Altai region, High Asia. Quaternary Geochronology, 2018. V. 47. P. 54–71. DOI: 10.1016/j.quageo.2018.05.008.
  52. Bock M., Conrad O., Günther A., Gehrt E., Baritz R., Böhner J. SaLEM (v1.0)—the Soil and Landscape Evolution Model (SaLEM) for simulation of regolith depth in periglacial environments. Geoscientific Model Development, 2018. V. 11. P. 1641–1652. DOI: 10.5194/gmd-11-1641-2018.
  53. Bonetti S., Bragg A.D., Porporato A. On the theory of drainage area for regular and nonregular points. Proceedings of the Royal Society A—Mathematical Physical and Engineering Sciences, 2018. V. 474. No. 2211. # 20170693. DOI: 10.1098/rspa.2017.0693.
  54. Booysen R., Zimmerman R., Lorenz S., Gloaguen R., Nex P.A.M., Andreani L., Mockel R. Towards multiscale and multisource remote sensing mineral exploration using RPAS: a case study in the Lofdal carbonatite-hosted REE deposit, Namibia. Remote Sensing, 2019. V. 11. No. 21. # 2500. DOI: 10.3390/rs11212500.
  55. Boulton S.J., Stokes M. Which DEM is best for analyzing fluvial landscape development in mountainous terrains? Geomorphology, 2018. V. 310. P. 168–187. DOI: 10.1016/J.GEOMORPH.2018.03.002.
  56. Brecheisen Z.S., Cook C.W., Heine P.R., Richter D. deB. Micro-topographic roughness analysis (MTRA) highlights minimally eroded terrain in a landscape severely impacted by historic agriculture. Remote Sensing of Environment, 2019. V. 222. P. 78–89. DOI: 10.1016/j.rse.2018.12.025.
  57. Břežný M., Pánek T. Deep-seated landslides affecting monoclinal flysch morphostructure: Evaluation of LiDAR-derived topography of the highest range of the Czech Carpathians. Geomorphology, 2017. V. 285. P. 44–57. DOI: 10.1016/j.geomorph.2017.02.007.
  58. Brun F., Berthier E., Wagnon P., Kääb A., Treichler D. A spatially resolved estimate of high Mountain Asia glacier mass balances from 2000 to 2016. Nature Geoscience, 2017. V. 10, 9. P. 668–673. DOI: 10.1038/ngeo2999.
  59. Brun F., Buri P., Miles E.S., Wagnon P., Steiner J., Berthier E., Ragettli S., Kraaijenbrink P., Immerzeel W.W., Pellicciotti F. Quantifying volume loss from ice cliffs on debris-covered glaciers using high-resolution terrestrial and aerial photogrammetry. Journal of Glaciology, 2016. V. 62. No. 234. P. 684–695. DOI: 10.1017/jog.2016.54.
  60. Brun F., Wagnon P., Berthier E., Shea J.M., Immerzeel W.W., Kraaijenbrink P.D.A., Vincent C., Reverchon C., Shrestha D., Arnaud Y. Ice cliffs contribution to the tonguewide ablation of Changri Nup Glacier, Nepal, central Himalaya. Cryosphere, 2018. V. 12. No. 11. P. 3439–3457. DOI: 10.5194/tc-12-3439-2018.
  61. Brunier G., Fleury J., Anthony E.J., Gardel A., Dussouillez P. Close-range airborne structure-from-motion photogrammetry for high-resolution beach morphometric surveys: examples from an embayed rotating beach. Geomorphology, 2016. V. 261. P. 76–88. DOI: 10.1016/j.geomorph.2016.02.025.
  62. Brusnikin E.S., Kreslavsky M.A., Zubarev A.E., Patratiy V.D., Krasilnikov S.S., Head J.W., Karachevtseva I.P. Topographic measurements of slope streaks on Mars. Icarus, 2016. V. 278. P. 52–61. DOI: 10.1016/j.icarus.2016.06.005.
  63. Bugnicourt P., Guitet S., Santos V.F., Blanc L., Sotta E.D., Barbier N., Couteron P. Using textural analysis for regional landform and landscape mapping, Eastern Guiana Shield. Geomorphology, 2018. V. 317. P. 23–44. DOI: 10.1016/j.geomorph.2018.03.017.
  64. Bühler Y., Adams M.S., Bösch R., Stoffel A. Mapping snow depth in alpine terrain with unmanned aerial systems (UASs): potential and limitations. Cryosphere, 2016. V. 10. No. 3. P. 1075–1088. DOI: 10.5194/tc-10-1075-2016.
  65. Bühler Y., Adams M., Stoffel A., Boesch R. Photogrammetric reconstruction of homogenous snow surfaces in alpine terrain applying near-infrared UAS imagery. International Journal of Remote Sensing, 2017. V. 38. No. 8/10. P. 3135–3158. DOI: 10.1080/01431161.2016.1275060.
  66. Bühler Y., von Rickenbach D., Stoffel A., Margreth S., Stoffel L., Christen M. Automated snow avalanche release area delineation—validation of existing algorithms and proposition of a new object-based approach for large scale hazard indication mapping. Natural Hazards and Earth System Sciences, 2018. V. 18. No. 12. P. 3235–3251. DOI: 10.5194/nhess-18-3235-2018.
  67. Buri P., Pellicciotti F., Steiner J.F., Miles E.S., Immerzeel W.W. A grid-based model of backwasting of supraglacial ice cliffs on debris-covered glaciers. Annals of glaciology, 2016. V. 57. No. 71. P. 199–211. DOI: 10.3189/2016AoG71A059.
  68. Caglar B., Becek K., Mekik C., Ozendi M. On the vertical accuracy of the ALOS World 3D-30m digital elevation model. Remote Sensing Letters, 2018. V. 9. No. 6. P. 607–615. DOI: 10.1080/2150704X.2018.1453174.
  69. Canuto M.A., Estrada-Belli F., Garrison T.G., Houston S.D., Acuna M.J., Kovac M., Marken D., Nondedeo P., Auld-Thomas L., Castanet C., Chatelain D., Chiriboga C.R., Drapela T., Lieskovsky T., Tokovinine A., Velasquez A., Fernandez-Diaz J.C., Shrestha R. Ancient lowland Maya complexity as revealed by airborne laser scanning of northern Guatemala. Science, 2018. V. 361. No. 6409. # eaau0137. DOI: 10.1126/science.aau0137.
  70. Cao W., Sofia G., Tarolli P. Geomorphometric characterisation of natural and anthropogenic land covers. Progress in Earth and Planetary Science, 2020. V. 7. # 2. DOI: 10.1186/s40645-019-0314.
  71. Cardinale M., Silvestro S., Vaz D.A., Michaels T., Bourke M.C., Komatsu G., Marinangeli L. Present-day aeolian activity in Herschel Crater, Mars. Icarus, 2016. V. 265. P. 139–148. DOI: 10.1016/j.icarus.2015.10.022.
  72. Carless D., Kulessa B., Booth A.D., Drocourt Y., Sinnadurai P., Street-Perrott F.A., Jansson P. An integrated geophysical and GIS based approach improves estimation of peatland carbon stocks. Geoderma, 2021. V. 402. # 115176. DOI: 10.1016/j.geoderma.2021.115176.
  73. Carreno-Luengo H., Luzi G., Crosetto M. First evaluation of topography on GNSS-R: an empirical study based on a digital elevation model. Remote Sensing, 2019. V. 11. No. 21. # 2556. DOI: 10.3390/rs11212556.
  74. Caubet M., Dobarco M.R., Arrouays D., Minasny B., Saby N.P. Merging country, continental and global predictions of soil texture: lessons from ensemble modelling in France. Geoderma, 2019. V. 337. P. 99–110. DOI: 10.1016/j.geoderma.2018.09.007.
  75. Cavalli M., Goldin B., Comiti F., Brardinoni F., Marchi L. Assessment of erosion and deposition in steep mountain basins by differencing sequential digital terrain models. geomorphology, 2017. V. 291. P. 4–16. DOI: 10.1016/j.geomorph.2016.04.009.
  76. Čeru T., Šegina E., Gosar A. Geomorphological dating of pleistocene conglomerates in central Slovenia based on spatial analyses of dolines using liDAR and ground penetrating radar. Remote Sensing, 2017. V. 9. No. 12. # 1213. DOI: 10.3390/rs9121213.
  77. Cervilla A.R., Tabik S., Vías J., Mérida M., Romero L.F. Total 3D-viewshed map: quantifying the visible volume in digital elevation models. Transactions in GIS, 2017. V. 21. No. 3. P. 591–607. DOI: 10.1111/tgis.12216.
  78. Chaney N.W., Wood E.F., McBratney A.B., Hempel J.W., Nauman T.W., Brungard C.W., Odgers N.P. POLARIS: a 30-meter probabilistic soil series map of the contiguous United States. Geoderma, 2016. V. 274. P. 54–67. DOI: 10.1016/j.geoderma.2016.03.025.
  79. Chang J.M.-H., Lam Y.F., Lau S.P.-W., Wong W.-K. Development of fine-scale spatiotemporal temperature forecast model with urban climatology and geomorphometry in Hong Kong. Urban Climate, 2021. V. 37. # 100816. DOI: j.uclim.2021.100816.
  80. Chang K.-T., Merghadi A., Yunus A.P., Pham B.T., Dou J. Evaluating scale effects of topographic variables in landslide susceptibility models using GIS-based machine learning techniques. Scientific Reports, 2019. V. 9. # 12296. DOI: 10.1038/s41598-019-48773-2.
  81. Chase D.Z., Chase A.F. Caracol, Belize, and changing perceptions of Ancient Maya society. Journal of Archaeological Research, 2017. V. 25. No. 3. P. 185–249. DOI: 10.1007/s10814-016-9101-z.
  82. Chen Q., Liu G., Ma X., Mariethoz G., He Z., Tian Y., Weng Z. Local curvature entropy-based 3D terrain representation using a comprehensive Quadtree. ISPRS Journal of Photogrammetry and Remote Sensing, 2018. V. 139. P. 30–45. DOI: 10.1016/j.isprsjprs.2018.03.001.
  83. Chen W., Xie X., Wang J., Pradhan B., Hong H., Tien Bui D., Duan Z., Ma J. A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility. Catena, 2017. V. 151. P. 147–160. DOI: 10.1016/j.catena.2016.11.032.
  84. Chu H.-J., Chen Y.-C., Ali M.Z., Höfle B. Multi-parameter relief map from high-resolution DEMs: a case study of mudstone badland. International Journal of Environmental Research and Public Health, 2019. V. 16. No. 7. # 1109. DOI: 10.3390/ijerph16071109.
  85. Chudley T.R., Christoffersen P., Doyle S.H., Abellan A., Snooke N. High accuracy UAV photogrammetry of ice sheet dynamics with no ground control. Cryosphere, 2019. V. 13. No. 3. P. 955–968. DOI: 10.5194/tc-2018-256.
  86. Cimoli E., Marcer M., Vandecrux B., Bøggild C.E., Williams G., Simonsen S.B. Application of low-cost UASs and digital photogrammetry for high-resolution snow depth mapping in the Arctic. Remote Sensing, 2017. V. 9. No. 11. # 1144. DOI: 10.3390/rs9111144.
  87. Clapuyt F., Vanacker V., van Oost K. Reproducibility of UAV-based earth topography reconstructions based on Structure-from-Motion algorithms. Geomorphology, 2016. V. 260. P. 4–15. DOI: 10.1016/j.geomorph.2015.05.011.
  88. Clarke K.C., Romero B.E. On the topology of topography: a review. Cartography and Geographic Information Science, 2017. V. 44. No. 3. P. 271–282. DOI: 10.1080/15230406.2016.1164625.
  89. Clubb F.J., Mudd S.M., Attal M., Milodowski D.T., Grieve S.W.D. The relationship between drainage density, erosion rate, and hilltop curvature: implications for sediment transport processes. Journal of Geophysical Research: Earth Surface, 2016. V. 121. No. 10. P. 1724–1745. DOI: 10.1002/2015JF003747.
  90. Clubb F.J., Mudd S.M., Milodowski D.T., Valters D.A., Slater L.J., Hurst M.D., Limaye A.B. Geomorphometric delineation of floodplains and terraces from objectively defined topographic thresholds. Earth Surface Dynamics, 2017. V. 5. P. 369–385. DOI: 10.5194/esurf-5-369-2017.
  91. Collin A., Hench J.L., Pastol Y., Planes S., Thiault L., Schmitt R.J, Holbrook S.J., Davies N., Troyer M. High resolution topobathymetry using a Pleiades-1 triplet: Moorea Island in 3D. Remote Sensing of Environment, 2018. V. 208. P. 109–119. DOI: 10.1016/j.rse. 2018.02.015.
  92. Colucci R.R., Boccali C., Žebre M., Guglielmin M. Rock glaciers, protalus ramparts and pronival ramparts in the south-eastern Alps. Geomorphology, 2016. V. 269. P. 112–121. DOI: 10.1016/j.geomorph.2016.06.039.
  93. Conway S.J., Balme M.R. A novel topographic parameterization scheme indicates that martian gullies display the signature of liquid water. Earth and Planetary Science Letters, 2016. V. 454. P. 36–45. DOI: 10.1016/j.epsl.2016.08.031.
  94. Copping J.P., Stewart B.D., McClean C.J., Hancock J., Rees R. Does bathymetry drive coastal whale shark (Rhincodon typus) aggregations? PeerJ, 2018. V. 6. # e4904. DOI: 10.7717/peerj.4904.
  95. Cucchiaro S., Cazorzi F., Marchi L., Crema S., Beinat A., Cavalli M. Multi-temporal analysis of the role of check dams in a debris-flow channel: linking structural and functional connectivity. Geomorphology, 2019. V. 345. # 106844. DOI: 10.1016/j.geomorph.2019.106844.
  96. Cucchiaro S., Maset E., Cavalli M., Crema S., Marchi L., Beinat A. How does coregistration affect geomorphic change estimates in multi-temporal surveys? GIScience and Remote Sensing, 2020. V. 57. No. 5. P. 611–632. DOI: 10.1080/15481603.2020.1763048.
  97. Cunha N.S., Magalhães M.R., Domingos T., Abreu M.M., Küpfer C. The land morphology approach to flood risk mapping: an application to portugal. Journal of Environmental Management, 2017. V. 193. P. 172–187. DOI: 10.1016/j.jenvman.2017.01.077.
  98. Cunha N.S., Magalhães M.R., Domingos T., Abreu M.M., Withing K. The land morphology concept and mapping method and its application to mainland portugal. Geoderma, 2018. V. 325. P. 72–89. DOI: 10.1016/j.geoderma.2018.03.
  99. Dąbski M., Zmarz A., Pabjanek P., Korczak-Abshire M., Karsznia I., Chwedorzewska K.J. UAV-based detection and spatial analyses of periglacial landforms on Demay Point (King George Island, South Shetland Islands, Antarctica). Geomorphology, 2017. V. 290. P. 29–38. DOI: 10.1016/j.geomorph.2017.03.033.
  100. Dai C., Durand M., Howat I.M., Altenau E.H., Pavelsky T.M. Estimating river surface elevation from ArcticDEM. Geophysical Research Letters, 2018. V. 45. No. 7. P. 3107–3114. DOI: 10.1002/2018GL077379.
  101. Dai C., Howat I.M. Measuring lava flows with ArcticDEM: application to the 2012–2013 eruption of Tolbachik, Kamchatka. Geophysical Research Letters, 2017. V. 44. No. 24. P. 12133–12140. DOI: 10.1002/2017GL075920.
  102. Dai C., Howat I.M., Freymueller J.T., Vijay S., Jia Y. Characterization of the 2008 phreatomagmatic eruption of okmok from ArcticDEM and InSAR: deposition, erosion, and deformation. Journal of Geophysical Research: Solid Earth, 2020. V. 125. No. 6. # e2019JB018977. DOI: 10.1029/2019JB018977.
  103. Dai W., Hu G., Huang N., Zhang P., Yang X., Tang G. A contour-directional detection for deriving terrace ridge from open source images and digital elevation models. IEEE Access, 2019a. V. 7. P. 129215–129224. DOI: 10.1109/ACCESS.2019.2940437.
  104. Dai W., Na J., Huang N., Hu G., Yang X., Tang G., Xiong L., Li F. Integrated edge detection and terrain analysis for agricultural terrace delineation from remote sensing images. International Journal of Geographical Information Science, 2020. V. 34. No. 3. P. 484–503. DOI: 10.1080/13658816.2019.1650363.
  105. Dai W., Yang X., Na J., Li J., Brus D., Xiong L., Tang G., Huang X. Effects of DEM resolution on the accuracy of gully maps in loess hilly areas. Catena, 2019b. V. 177. P. 114–125. DOI: 10.1016/j.catena.2019.02.010.
  106. Dall’Asta E., Forlani G., Roncella R., Santise M., Diotri F., Morra di Cella U. Unmanned aerial systems and DSM matching for rock glacier monitoring. ISPRS Journal of Photogrammetry and Remote Sensing, 2017. V. 127. P. 102–114. DOI: 10.1016/j.isprsjprs.2016.10.003.
  107. Danchenkov A., Belov N., Stont Z. Using the terrestrial laser scanning technique for aeolian sediment transport assessment in the coastal zone in seasonal scale. Estuarine, Coastal and Shelf Science, 2019. V. 223. P. 105–114. DOI: 10.1016/j.ecss.2019.04.044.
  108. De Michele C., Avanzi F., Passoni D., Barzaghi R., Pinto L., Dosso P., Ghezzi A., Gianatti R., Della Vedova G. Using a fixed-wing UAS to map snow depth distribution: an evaluation at peak accumulation. Cryosphere, 2016. V. 10. No. 2. P. 511–522. DOI: 10.5194/tc-10-511-2016.
  109. De Waele J., Fabbri S., Santagata T., Chiarini V., Columbu A., Pisani L. Geomorphological and speleogenetical observations using terrestrial laser scanning and 3D photogrammetry in a gypsum cave (Emilia Romagna, N. Italy). Geomorphology, 2018. V. 319. P. 47–61. DOI: 10.1016/j.geomorph.2018.07.012.
  110. Dehecq A., Millan R., Berthier E., Gourmelen N., Trouve E. Elevation changes inferred from TanDEM-X data over the Mont-Blanc area: impact of the X-band interferometric bias. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016. V. 9. No. 8. P. 3870–3882. DOI: 10.1109/JSTARS.2016.2581482.
  111. Dekavalla M., Argialas D. Evaluation of a spatially adaptive approach for land surface classification from digital elevation models. International Journal of Geographical Information Science, 2017. V. 31. No. 10. P. 1978–2000. DOI: 10.1080/13658816.2017.1344984.
  112. Dekavalla M., Argialas D. Object-based classification of global undersea topography and geomorphological features from the SRTM30_PLUS data. Geomorphology, 2017. V. 288. P. 66–82. DOI: 10.1016/j.geomorph.2017.03.026.
  113. Deng Y. New trends in digital terrain analysis: landform definition, representation, and classification. progress in physical geography, 2007. V. 31. No. 4. P. 405–419. DOI: 10.1177/0309133307081291.
  114. Dharumarajan S., Hegde R., Singh S.K. Spatial prediction of major soil properties using Random Forest techniques—a case study in semi-arid tropics of South India. Geoderma Regional, 2017. V. 10. P. 154–162. DOI: 10.1016/j.geodrs.2017.07.005.
  115. Dhingra R.D., Barnes J.W., Yanites B.J., Kirk R.L. Large catchment area recharges Titan’s Ontario Lacus. Icarus, 2018. V. 299. P. 331–338. DOI: 10.1016/j.icarus.2017.08.009.
  116. Dirscherl M., Rossi C. Geomorphometric analysis of the 2014–2015 Bárðarbunga volcanic eruption, Iceland. Remote Sensing of Environment, 2018. V. 204. P. 244–259. DOI: 10.1016/j.rse.2017.10.027.
  117. Dornik A., Drăguţ L., Urdea P. Classification of soil types using geographic object-based image analysis and random forests. Pedosphere, 2018. V. 28. No. 6. P. 913–925. DOI: 10.1016/S1002-0160(17)60377-1.
  118. Dos Reis A.A., Franklin S.E., de Mello J.M., Acerbi F.W. Jr. Volume estimation in a Eucalyptus plantation using multi-source remote sensing and digital terrain data: a case study in Minas Gerais State, Brazil. International Journal of Remote Sensing, 2019. V. 40. No. 7. P. 2683–2702. DOI: 10.1080/01431161.2018.1530808.
  119. Drăguţ L., Dornik A. Land-surface segmentation as a method to create strata for spatial sampling and its potential for digital soil mapping. International Journal of Geographical Information Science, 2016. V. 30. No. 7. P. 1359–1376. DOI: 10.1080/13658816.2015.1131828.
  120. Duan X., Li L., Zhu H., Shen Y. A high-fidelity multiresolution digital elevation model for Earth systems. Geoscientific Model Development, 2017. V. 10. No. 1. P. 239–253. DOI: 10.5194/gmd-10-239-2017.
  121. Duszyński F., Jancewicz K., Kasprzak M., Migoń P. The role of landslides in downslope transport of caprock-derived boulders in sedimentary tablelands, Stołowe Mts, SW Poland. Geomorphology, 2017. V. 295. P. 84–101. DOI: 10.1016/j.geomorph.2017.06.016.
  122. Elez J., Silva P.G., Huerta P., Perucha M.Á., Civis J., Roquero E., Rodríguez-Pascu M.A., Bardají T., Giner-Robles J.L., Martínez-Graña A. Quantitative paleotopography and paleogeography around the Gibraltar Arc (South Spain) during the Messinian Salinity Crisis. Geomorphology, 2016. V. 275. P. 26–45. DOI: 10.1016/j.geomorph.2016.09.023.
  123. Eltner A., Kaiser A., Castillo C., Rock G., Neugirg F., Abellán A. Image-based surface reconstruction in geomorphometry—merits, limits and developments. Earth Surface Dynamics, 2016. V. 4. No. 2. P. 359–389. DOI: 10.5194/esurf-4-359-2016.
  124. Ely J.C., Graham C., Barr I.D., Rea B.R., Spagnolo M., Evans J. Using UAV acquired photography and structure from motion techniques for studying glacier landforms: application to the glacial flutes at Isfallsglaciären. Earth Surface Processes and Landforms, 2017. V. 42. No. 6. P. 877–888. DOI: 10.1002/esp.4044.
  125. Evans D. Airborne laser scanning as a method for exploring long-term socioecological dynamics in Cambodia. Journal of Archaeological Science, 2016. V. 74. P. 164–175. DOI: 10.1016/j.jas.2016.05.009.
  126. Evans I.S. General geomorphometry, derivatives of altitude, and descriptive statistics. Spatial Analysis in Geomorphology. London: Methuen, 1972. P. 17–90. DOI: 10.4324/9780429273346-2.
  127. Ewertowski M.W., Tomczyk A.M., Evans D.J.A., Roberts D.H., Ewertowski W. Operational framework for rapid, very-high resolution mapping of glacial geomorphology using low-cost unmanned aerial vehicles and structure-from-motion approach. Remote Sensing, 2019. V. 11. No. 1. # 65. DOI: 10.3390/rs11010065.
  128. Fa W., Cai Y., Xiao Z., Tian W. Topographic roughness of the northern high latitudes of Mercury from MESSENGER Laser Altimeter data. Geophysical Research Letters, 2016. V. 43. No. 7. P. 3078–3087. DOI: 10.1002/2016GL068120.
  129. Fabbri S., Sauro F., Santagata T., Rossi G., de Waele J. High-resolution 3-D mapping using terrestrial laser scanning as a tool for geomorphological and speleogenetical studies in caves: an example from the Lessini mountains (North Italy). Geomorphology, 2017. V. 280. P. 16–29. DOI: 10.1016/j.geomorph.2016.12.001.
  130. Fan B., Tao W., Qin G., Hopkins I., Zhang Y., Wang Q., Lin H., Guo L. Soil micro-climate variation in relation to slope aspect, position, and curvature in a forested catchment. Agricultural and Forest Meteorology, 2020. V. 290. # 107999. DOI: 10.1016/j.agrformet. 2020.107999.
  131. Favalli M., Fornaciai A. Visualization and comparison of DEM-derived parameters: application to volcanic areas. Geomorphology, 2017. V. 290. P. 69–84. DOI: 10.1016/j.geomorph.2017.02.029.
  132. Feizizadeh B., Blaschke T., Tiede D., Moghaddam M.H.R. Evaluating fuzzy operators of an object-based image analysis for detecting landslides and their changes. Geomorphology, 2017. V. 293. Pt. A. P. 240–254. DOI: 10.1016/j.geomorph.2017.06.002.
  133. Fissore C., Dalzell B.J., Berhe A.A., Voegtle M., Evans M., Wu A. Influence of topography on soil organic carbon dynamics in a Southern California grassland. Catena, 2017. V. 149, 1. P. 140–149. DOI: 10.1016/j.catena.2016.09.016.
  134. Florinsky I.V. Combined analysis of digital terrain models and remotely sensed data in landscape investigations. Progress in Physical Geography, 1998. V. 22. No. 1. P. 33–60. DOI: 10.1177/030913339802200102.
  135. Florinsky I.V. Digital Terrain Analysis in Soil Science and Geology. 2nd ed. Amsterdam: Academic Press, 2016. 486 p.
  136. Florinsky I.V. An illustrated introduction to general geomorphometry. Progress in Physical Geography, 2017a. V. 41. No. 6. P. 723–752. DOI: 10.1177/0309133317733667.
  137. Florinsky I.V. Spheroidal equal angular DEMs: the specificity of morphometric treatment. Transactions in GIS, 2017b. V. 21. No. 6. P. 1115–1129. DOI: 10.1111/tgis.12269.
  138. Florinsky I.V. Geomorphometry on the surface of a triaxial ellipsoid: towards the solution of the problem. International Journal of Geographical Information Science, 2018. V. 32. No. 8. P. 1558–1571. DOI: 10.1080/13658816.2018.1461220.
  139. Florinsky I.V., Bliakharskii D.P. Detection of crevasses by geomorphometric treatment of data from unmanned aerial surveys. Remote Sensing Letters, 2019a. V. 10, 4. P. 323–332. DOI: 10.1080/2150704X.2018.1552809.
  140. Florinsky I.V., Bliakharskii D.P. The 2017 catastrophic subsidence in the Dålk Glacier, East Antarctica: unmanned aerial survey and terrain modelling. Remote Sensing Letters, 2019b. V. 10. No. 4. P. 333–342. DOI: 10.1080/2150704X.2018.1552810.
  141. Florinsky I.V., Filippov S.V. Three-dimensional terrain modeling with multiple-source illumination. Transactions in GIS, 2019. V. 23. No. 5. P. 937–959. DOI: 10.1111/tgis.12546.
  142. Florinsky I.V., Filippov S.V. Three-dimensional geomorphometric modeling of the Arctic ocean submarine topography: a low-resolution desktop application. IEEE Journal of oceanic Engineering, 2021. V. 46. No. 1. P. 88–101. DOI: 10.1109/JOE.2020.2969283.
  143. Florinsky I.V., Kurkov V.M., Bliakharskii D.P. Geomorphometry from unmanned aerial surveys. Transactions in GIS, 2018a. V. 22. No. 1. P. 58–81. DOI: 10.1111/tgis.12296.
  144. Florinsky I.V., Pankratov A.N. A universal spectral analytical method for digital terrain modeling. International Journal of Geographical Information Science, 2016. V. 30. No. 12. P. 2506–2528. DOI: 10.1080/13658816.2016.1188932.
  145. Florinsky I.V., Skrypitsyna T.N., Luschikova O.S. Comparative accuracy of the AW3D30 DSM, ASTER GDEM, and SRTM1 DEM: a case study on the Zaoksky testing ground, Central European Russia. Remote Sensing Letters, 2018b. V. 9. No. 7. P. 706–714. DOI: 10.1080/2150704X.2018.1468098.
  146. Florinsky I.V., Skrypitsyna T.N., Trevisani S., Romaikin S.V. Statistical and visual quality assessment of nearly-global and continental digital elevation models of Trentino, Italy. Remote Sensing Letters, 2019. V. 10. No. 8. P. 726–735. DOI: 10.1080/2150704X.2019.1602790.
  147. Flynn T., Rozanov A., de Clercq W., Warr B., Clarke C. Semi-automatic disaggregation of a national resource inventory into a farm-scale soil depth class map. geoderma, 2019. V. 337. P. 1136–1145. DOI: 10.1016/j.geoderma.2018.11.003.
  148. Foroutan M., Marshall S.J., Menounos B. Automatic mapping and geomorphometry extraction technique for crevasses in geodetic mass-balance calculations at haig glacier, Canadian Rockies. Journal of Glaciology, 2019. V. 65. No. 254. P. 971–982. DOI: 10.1017/jog.2019.71.
  149. Franklin J. Predictive vegetation mapping: geographic modelling of biospatial patterns in relation to environmental gradients. Progress in Physical Geography, 1995. V. 19. No. 4. P. 474–499. DOI: 10.1177/030913339501900403.
  150. Franklin S.E. Interpretation and use of geomorphometry in remote sensing: a guide and review of integrated applications. International Journal of Remote Sensing, 2020. V. 41. No. 19. P. 7700–7733. DOI: 10.1080/01431161.2020.1792577.
  151. Freeland T., Heung B., Burley D.V., Clark G., Knudby A. Automated feature extraction for prospection and analysis of monumental earthworks from aerial LiDAR in the Kingdom of Tonga. Journal of Archaeological Science, 2016. V. 69. P. 64–74. DOI: 10.1016/j.jas.2016.04.011.
  152. Freitas H.R.A., Freitas C.D.C., Rosim S., Oliveira J.R.F. Drainage networks and watersheds delineation derived from TIN-based digital elevation models. Computers and Geosciences, 2016. V. 92. P. 21–37. DOI: 10.1016/j.cageo.2016.04.003.
  153. Fugazza D., Scaioni M., Corti M., d’Agata C., Azzoni R.S., Cernuschi M., Smiraglia C., Diolaiuti G.A. Combination of UAV and terrestrial photogrammetry to assess rapid glacier evolution and conditions of glacier hazards. Natural Hazards and Earth System Sciences, 2018. V. 18. No. 4, P. 1055–1071. DOI: 10.5194/nhess-18-1055-2018.
  154. Fuss C.E., Berg A.A., Lindsay J.B. DEM fusion using a modified k-means clustering algorithm. International Journal of Digital Earth, 2016. V. 9. No. 12. P. 1242–1255. DOI: 10.1080/17538947.2016.1208685.
  155. Gabrlik P., La Cour-Harbo A., Zalud L., Janata P. Calibration and accuracy assessment in a direct georeferencing system in UAS photogrammetry. International Journal of Remote Sensing, 2018. V. 39. No. 15/16. P. 4931–4959. DOI: 10.1080/01431161.2018.1434331.
  156. Gaffey C., Bhardwaj A. Applications of unmanned aerial vehicles in cryosphere: latest advances and prospects. Remote Sensing, 2020. V. 12. No. 6. # 948. DOI: 10.3390/rs12060948.
  157. Gallant J.C., Hutchinson M.F. A differential equation for specific catchment area. Water Resources Research, 2011. V. 47. No. 5. # W05535. DOI: 10.1029/2009WR008540.
  158. Gallay M., Hochmuth Z., Kaňuk J., Hofierka J. Geomorphometric analysis of cave ceiling channels mapped with 3D terrestrial laser scanning. Hydrology and Earth System Sciences, 2016. V. 20. No. 5. P. 1827–1849. DOI: 10.5194/hess-2016-74.
  159. Gallwey J., Eyre M., Tonkins T., Coggan J. Bringing lunar LiDAR back down to Earth: mapping our industrial heritage through deep transfer learning. Remote Sensing, 2019. V. 11. No. 17. # 1994. DOI: 10.3390/rs11171994.
  160. Gao Y., Wang W., Yao T., Lu N., Lu A. Hydrological network and classification of lakes on the Third Pole. Journal of Hydrology, 2018. V. 560. P. 582–594. DOI: 10.1016/j.jhydrol.2018.03.062.
  161. García-Romero L., Delgado-Fernández I., Hesp P.A., Hernández-Calvento L., Viera-Pérez M., Hernández-Cordero A.I., Cabrera-Gámez J., Domínguez-Brito A.C. Airflow dynamics, vegetation and aeolian erosive processes in a shadow zone leeward of a resort in an arid transgressive dune system. Aeolian Research, 2019. V. 38. P. 48–59. DOI: 10.1016/J.AEOLIA.2019.03.006.
  162. Garosi Y., Sheklabadi M., Besalatpour A.A., Pourghasemi H.R., Conoscenti C., van Oost K. Comparison of the different resolution and source of controlling factors for gully erosion susceptibility mapping. Geoderma, 2018. V. 330. P. 65–78. DOI: 10.1016/j.geoderma.2018.05.027.
  163. Garrison T.G., Houston S., Alcover Firpi O. Recentering the rural: lidar and articulated landscapes among the Maya. Journal of Anthropological Archaeology, 2019. V. 53. P. 133–146. DOI: 10.1016/j.jaa.2018.11.005.
  164. Garstki K. Virtual representation: the production of 3D digital artifacts. Journal of Archaeological Method and Theory, 2017. V. 24. No. 3. P. 726–750. DOI: 10.1007/s10816-016-9285-z.
  165. Gatter R., Cavalli M., Crema S., Bossi G. Modelling the dynamics of a large rock landslide in the Dolomites (eastern Italian Alps) using multi-temporal DEMs. PeerJ, 2018. V. 6. # e5903. DOI: 10.7717/peerj.5903.
  166. Gaucherel C., Frelat R., Salomon L., Rouy B., Pandey N., Cudennec C. Regional watershed characterization and classification with river network analyses. Earth Surface Processes and Landforms, 2017. V. 42. No. 13. P. 2068–2081. DOI: 10.1002/esp.4172.
  167. Gevaert C., Persello C., Nex F., Vosselman G. A deep learning approach to DTM extraction from imagery using rule-based training labels. ISPRS Journal of Photogrammetry and Remote Sensing, 2018. V. 142. P. 106–123. DOI: 10.1016/j.isprsjprs.2018.06.001.
  168. Gheyle W., Stichelbaut B., Saey T., Note N., van den Berghe H., van Eetvelde V., van Meirvenne M., Bourgeois J. Scratching the surface of war. Airborne laser scans of the great War conflict landscape in Flanders (Belgium). Applied Geography, 2018. V. 90. P. 55–68. DOI: 10.1016/j.apgeog.2017.11.011.
  169. Ghorbanzadeh O., Blaschke T., Gholamnia K., Meena S., Tiede D., Aryal J. Evaluation of different machine learning methods and deep-learning convolutional neural networks for landslide detection. Remote Sensing, 2019. V. 11. No. 2. # 196. DOI: 10.3390/rs11020196.
  170. Gibson M.J., Glasser N.F., Quincey D.J., Mayer C., Rowan A.V., Irvine-Fynn T.D. Temporal variations in supraglacial debris distribution on Baltoro Glacier, Karakoram between 2001 and 2012. Geomorphology, 2017. V. 295. P. 572–585. DOI: 10.1016/j.geomorph.2017.08.012.
  171. Gillings M., Hacıgüzeller P., Lock G. (eds.) Archaeological Spatial Analysis: A Methodological Guide. London: Routledge, 2020. 512 p. DOI: 10.4324/9781351243858.
  172. Gindraux S., Boesch R., Farinotti D. Accuracy assessment of digital surface models from unmanned aerial vehicles’ imagery on glaciers. Remote Sensing, 2017. V. 9. No. 2. # 186. DOI: 10.3390/rs9020186.
  173. Gomez C. Understanding volcanic geomorphology from derivatives and wavelet analysis: a case study at Miyakejima Volcano, Izu Islands, Japan. Journal of Volcanology and Geothermal Research, 2018. V. 354. P. 57–66. DOI: 10.1016/j.jvolgeores.2018.02.007.
  174. Gonzalez C., Rizzoli P. Landcover-dependent assessment of the relative height accuracy in TanDEM-X DEM products. IEEE Geoscience and Remote Sensing Letters, 2018. V. 15. No. 12. P. 1892–1896. DOI: 10.1109/LGRS.2018.2864774.
  175. González-García J., Gómez-Espinosa A., Cuan-Urquizo E., García-Valdovinos L.G., Salgado-Jiménez T., Cabello J.A.E. Autonomous underwater vehicles: localization, navigation, and communication for collaborative missions. Applied Sciences, 2020. V. 10. No. 4. # 1256. DOI: 10.3390/app10041256.
  176. González-Moradas M.d.R., Viveen W. Evaluation of ASTER GDEM2, SRTMv3.0, ALOS AW3D30 and TanDEM-X DEMs for the peruvian Andes against highly accurate GNSS ground control points and geomorphological-hydrological metrics. Remote Sensing of Environment, 2020. V. 237. # 111509. DOI: 10.1016/j.rse.2019.111509.
  177. Gorini M.A.V., Mota G.L.A. Dealing with double vagueness in DEM morphometric analysis. International Journal of Geographical Information Science, 2016. V. 30. No. 8. P. 1644–1666. DOI: 10.1080/13658816.2016.1150484.
  178. Goudge T.A., Milliken R.E., Head J.W., Mustard J.F., Fassett C.I. Sedimentological evidence for a deltaic origin of the western fan deposit in Jezero crater, Mars and implications for future exploration. Earth and Planetary Science Letters, 2017. V. 458. P. 357–365. DOI: 10.1016/J.EPSL.2016.10.056.
  179. Grieve S.W.D., Mudd S.M., Hurst M.D., Milodowski D.T. A nondimensional framework for exploring the relief structure of landscapes. Earth Surface Dynamics, 2016. V. 4. No. 2. P. 309–325. DOI: 10.5194/esurf-4-309-2016.
  180. Grimm K., Tahmasebi Nasab M., Chu X. TWI computations and topographic analysis of depression-dominated surfaces. Water, 2018. V. 10. No. 5. # 663. DOI: 10.3390/w10050663.
  181. Grohmann C.H. Evaluation of TanDEM-X DEMs on selected Brazilian sites: comparison with SRTM, ASTER GDEM and ALOS AW3D30. Remote Sensing of Environment, 2018. V. 212. P. 121–133. DOI: 10.1016/j.rse.2018.04.043.
  182. Grohmann C.H., Garcia G.P.B., Affonso A.A., Albuquerque R.W. Dune migration and volume change from airborne LiDAR, terrestrial LiDAR and Structure from Motion–Multi View Stereo. Computers and Geosciences, 2020. V. 143. # 104569. DOI: 10.1016/j.cageo.2020.104569.
  183. Groom J., Bertin S., Friedrich H. Evaluation of DEM size and grid spacing for fluvial patch-scale roughness parameterisation. Geomorphology, 2018. V. 320. P. 98–110. DOI: 10.1016/J.GEOMORPH.2018.08.017.
  184. Gruber F.E., Baruck J., Geitner C. Algorithms vs. surveyors: a comparison of automated landform delineations and surveyed topographic positions from soil mapping in an Alpine environment. Geoderma, 2017. V. 308. P. 9–25. DOI: 10.1016/j.geoderma.2017.08.017.
  185. Guida D., Cuomo A., Palmieri V. Using object-based geomorphometry for hydrogeomorphological analysis in a Mediterranean research catchment. Hydrology and Earth System Sciences, 2016. V. 20. No. 9. P. 3493–3509. DOI: 10.5194/hess-20-3493-2016.
  186. Guirado E., Alcaraz-Segura D., Rigol-Sánchez J.P., Gisbert J., Martínez-Moreno F.J., Galindo-Zaldívar J., González-Castillo L., Cabello J. Remote-sensing-derived fractures and shrub patterns to identify groundwater dependence. Ecohydrology, 2018. V. 11. No. 6. # e1933. DOI: 10.1002/eco.1933.
  187. Guisado-Pintado E., Jackson D.W.T., Rogers D. 3D mapping efficacy of a drone and terrestrial laser scanner over a temperate beach-dune zone. Geomorphology, 2019. V. 328. P. 157–172. DOI: 10.1016/j.geomorph.2018.12.013.
  188. Guo Y., Liu Y., Oerlemans A., Lao S., Wu S., Lew M.S. Deep learning for visual understanding: a review. Neurocomputing, 2016. V. 187. P. 27–48. DOI: 10.1016/j.neucom.2015.09.116.
  189. Guo Z., Adhikari K., Chellasamy M., Greve M.B., Owens P.R., Greve M.H. Selection of terrain attributes and its scale dependency on soil organic carbon prediction. geoderma, 2019. V. 340. P. 303–312. DOI: 10.1016/j.geoderma.2019.01.023.
  190. Guevara M., Arroyo C., Brunsell N., Cruz C.O., Domke G., Equihua J., Etchevers J., Hayes D., Hengl T., Ibelles A., Johnson K., de Jong B., Libohova Z., Llamas R., Nave L., Ornelas J.L., Paz F., Ressl R., Schwartz A., Victoria A., Wills S., Vargas R. Soil organic carbon across Mexico and the conterminous United States (1991–2010). Global Biogeochemical Cycles, 2020. V. 34. No. 3. # e2019GB006219. DOI: 10.1029/2019GB006219.
  191. Guevara M., Vargas R. Downscaling satellite soil moisture using geomorphometry and machine learning. PLoS ONE, 2019. V. 14. No. 9. # e0219639. DOI: 10.1371/journal.pone.0219639.
  192. Guyot A., Hubert-Moy L., Lorho T. Detecting neolithic burial mounds from liDAR-derived elevation data using a multi-scale approach and machine learning techniques. Remote Sensing, 2018. V. 10. No. 2. # 225. DOI: 10.3390/rs10020225.
  193. Hayes A.G., Birch S.P.D., Dietrich W.E., Howard A.D., Kirk R.L., Poggiali V., Mastrogiuseppe M., Michaelides R.J., Corlies P.M., Moore J.M., Malaska M.J., Mitchell K.L., Lorenz R.D., Wood C.A. Topographic constraints on the evolution and connectivity of Titan’s lacustrine basins. Geophysical Research Letters, 2017. V. 44. No. 23. P. 11745–11753. DOI: 10.1002/2017GL075468.
  194. Heckmann T., Cavalli M., Cerdan O., Foerster S., Javaux M., Lode E., Smetanova A., Vericat D., Brardinoni F. Indices of sediment connectivity: opportunities, challenges and limitations. Earth-Science Reviews, 2018. V. 187. P. 77–108. DOI: 10.1016/j.earscirev.2018.08.004.
  195. Hendrickx H., Vivero S., de Cock L., de Wit B., de Maeyer P., Lambiel C., Delaloye R., Nyssen J., Frankl A. The reproducibility of SfM algorithms to produce detailed digital surface models: the example of PhotoScan applied to a high-alpine rock glacier. Remote Sensing Letters, 2019. V. 10. No. 1. P. 11–20. DOI: 10.1080/2150704X.2018.1519641.
  196. Hengl T., Reuter H.I. (eds.) Geomorphometry: Concepts, Software, Applications. Amsterdam: Elsevier, 2009. 765 p.
  197. Hengl T., Leenaars J.G.B., Shepherd K.D., Walsh M.G., Heuvelink G.B.M., Mamo T., Tilahun H., Berkhout E., Cooper M., Fegraus E., Wheeler I., Kwabena N.A. Soil nutrient maps of Sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learning. Nutrient Cycling in Agroecosystems, 2017a. V. 109. No. 1. P. 77–102. DOI: 10.1007/s10705-017-9870-x.
  198. Hengl T., Mendes de Jesus J., Heuvelink G.B.M., Ruiperez Gonzalez M., Kilibarda M., Blagotić A., Wei S., Wright M.N., Geng X., Bauer-Marschallinger B., Guevara M.A., Varga R., MacMillan R.A., Batjes N.H., Leenaars J.G.B., Ribeiro E., Wheeler I., Mantel S., Kempen B. Soilgrids250m: global gridded soil information based on machine learning. PLoS ONE, 2017b. V. 12. No. 2. # e0169748. DOI: 10.1371/journal.pone.0169748.
  199. Hengl T., Miller M.A.E., Križan J., Shepherd K.D., Sila A., Kilibarda M., Antonijević O., Glušica L., Dobermann A., Haefele S.M., McGrath S.P., Acquah G.E., Collinson J., Parente L., Sheykhmousa M., Saito K., Johnson J.-M., Chamberlin J., Silatsa F.B.T., Yemefack M., Wendt J., MacMillan R.A., Wheeler I., Crouch J. African soil properties and nutrients mapped at 30 m spatial resolution using two-scale ensemble machine learning. Scientific Reports, 2021. V. 11. # 6130. DOI: 10.1038/s41598-021-85639-y.
  200. Hengl T., Nussbaum M., Wright M.N., Heuvelink G.B.M., Gräler B. Random forest as a generic framework for predictive modeling of spatial and spatio-temporal variables. PeerJ, 2018. V. 6. # e5518. DOI: 10.7717/peerj.5518.
  201. Hergarten S., Robl J., Stüwe K. Tectonic geomorphology at small catchment sizes—extensions of the stream-power approach and the χ method. Earth Surface Dynamics, 2016. V. 4. No. 2. P. 1–9. DOI: 10.5194/esurf-4-1-2016.
  202. Heung B., Ho H.C., Zhang J., Knudby A., Bulmer C.E., Schmidt M.G. An overview and comparison of machine-learning techniques for classification purposes in digital soil mapping. Geoderma, 2016. V. 265. P. 62–77. DOI: 10.1016/j.geoderma.2015.11.014.
  203. Hodúl M., Bird S., Knudby A., Chénier R. Satellite derived photogrammetric bathymetry. ISPRS Journal of Photogrammetry and Remote Sensing, 2018. V. 142. P. 268–277. DOI: 10.1016/j.isprsjprs.2018.06.015.
  204. Hofierka J., Gallay M., Bandura P., Šašak J. Identification of karst sinkholes in a forested karst landscape using airborne laser scanning data and water flow analysis. Geomorphology, 2018. V. 308. P. 265–277. DOI: 10.1016/j.geomorph.2018.02.004.
  205. Hofierka J., Gallay M., Onačillová K., Hofierka J. Jr. Physically-based land surface temperature modeling in urban areas using a 3-D city model and multispectral satellite data. Urban Climate, 2020. V. 31. # 100566. DOI: 10.1016/j.uclim.2019.100566.
  206. Hong H., Llia L., Tsangaratos P., Chen W., Xu C. A hybrid fuzzy weight of evidence method in landslide susceptibility analysis on the Wuyuan area, China. Geomorphology, 2017. V. 290. P. 1–16. DOI: 10.1016/j.geomorph.2017.04.002.
  207. Hooshyar M., Wang D., Kim S., Medeiros S.C., Hagen S.C. Valley and channel networks extraction based on local topographic curvature and k-means clustering of contours. Water Resources Research, 2016. V. 52. No. 10. P. 8081–8102. DOI: 10.1002/2015WR018479.
  208. Horáček M., Samec P., Minár J. The mapping of soil taxonomic units via fuzzy clustering—a case study from the outer Carpathians, Czechia. Geoderma, 2018. V. 326. P. 111–122. DOI: 10.1016/j.geoderma.2018.04.012.
  209. Horn B.K.P. Hill shading and the reflectance map. Proceedings of the IEEE, 1981. V. 69. No. 1. P. 14–47. DOI: 10.1109/PROC.1981.11918.
  210. Horn C., Ivarsson O., Lindhé C., Potter R., Green A., Ling J. Artificial intelligence, 3D documentation, and rock art—approaching and reflecting on the automation of identification and classification of rock art images. Journal of Archaeological Method and Theory, 2021. V. 28. DOI: 10.1007/s10816-021-09518-6.
  211. Houser C., Bishop M., Wernette P. Multi-scale topographic anisotropy patterns on a barrier island. Geomorphology, 2017. V. 297. P. 153–158. DOI: 10.1016/j.geomorph.2017.09.026.
  212. Howat I.M., Porter C., Smith B.E., Noh M.-J., Morin P. The reference elevation model of Antarctica. Cryosphere, 2019. V. 13. No. 2. P. 665–674. DOI: 10.5194/tc-13-665-2019.
  213. Hu G., Dai W., Li S., Xiong L., Tang G. A vector operation to extract second-order terrain derivatives from digital elevation models. Remote Sensing, 2020. V. 12. No. 19. # 3134. DOI: 10.3390/rs12193134.
  214. Hu G., Dai W., Li S., Xiong L., Tang G., Strobl J. Quantification of terrain plan concavity and convexity using aspect vectors from digital elevation models. Geomorphology, 2021. V. 375. # 107553. DOI: 10.1016/j.geomorph.2020.107553.
  215. Hu Q., Zhou Y., Wang S., Wang F. Machine learning and fractal theory models for landslide susceptibility mapping: case study from the Jinsha River Basin. Geomorphology, 2020. V. 351. # 106975. DOI: 10.1016/j.geomorph.2019.106975.
  216. Huang H., Chen X., Wang X., Wang X., Liu L. A depression-based index to represent topographic control in urban pluvial flooding. Water, 2019. V. 11. No. 10. # 2115. DOI: 10.3390/w11102115.
  217. Huang P.-C., Lee K.T. Distinctions of geomorphological properties caused by different flow-direction predictions from digital elevation models. International Journal of Geographical Information Science, 2016. V. 30. No. 2. P. 168–185. DOI: 10.1080/13658816.2015.1079913.
  218. Hurskainen P., Adhikari H., Siljander M., Pellikka P., Hemp A. Auxiliary datasets improve accuracy of object-based land use/landcover classification in heterogeneous savanna landscapes. Remote Sensing of Environment, 2019. V. 233. # 111354. DOI: 10.1016/j.rse.2019.111354.
  219. Ibanez D.M., Almeida-Filho R., Miranda F.P. Analysis of SRTM data as an aid to hydrocarbon exploration in a frontier area of the Amazonas Sedimentary Basin, northern Brazil. Marine and petroleum geology, 2016. V. 73. P. 528–538. DOI: 10.1016/j.marpetgeo.2016.03.024.
  220. Idrees M.O., Pradhan B. A decade of modern cave surveying with terrestrial laser scanning: a review of sensors, method and application development. International Journal of Speleology, 2016. V. 45. No. 1. P. 71–88. DOI: 10.5038/1827-806X.45.1.1923.
  221. Inomata T., Triadan D., Pinzón F., Burham M., Ranchos J.L., Aoyama K., Haraguchi T. Archaeological application of airborne LiDAR to examine social changes in the Ceibal region of the Maya Lowlands. PLoS ONE, 2018. V. 13. No. 2. # e0191619. DOI: 10.1371/journal.pone.0191619.
  222. Iwahashi J., Kamiy I., Matsuoka M., Yamazaki D. Global terrain classification using 280m DEMs: segmentation, clustering and reclassification. Progress in Earth and Planetary Science, 2018. V. 5. # 1. DOI: 10.1186/s40645-017-0157-2.
  223. Jacobs L., Dewitte O., Poesen J., Sekajugo J., Nobile A., Rossi M., Thiery W., Kervyn M. Field-based landslide susceptibility assessment in a data-scarce environment: the populated areas of the Rwenzori Mountains. Natural Hazards and Earth System Sciences, 2018. V. 18. P. 105–124. DOI: 10.5194/nhess-18-105-2018.
  224. Jacobs L., Kervyn M., Reichenbach P., Rossi M., Marchesini I., Alvioli M., Dewitte O. Regional susceptibility assessments with heterogeneous landslide information: slope unit- vs. pixel-based approach. Geomorphology, 2020. V. 356. # 107084. DOI: 10.1016/j.geomorph.2020.107084.
  225. Jain A.O., Thaker T., Chaurasia A., Patel P., Singh A.K. Vertical accuracy evaluation of SRTM-GL1, GDEM-V2, AW3D30 and CartoDEM-V3.1 of 30-m resolution with dual frequency GNSS for lower Tapi Basin India. Geocarto International, 2018. V. 33. No. 11. P. 1237–1256. DOI: 10.1080/10106049.2017.1343392.
  226. Jakobsson M., Mayer L.A., Bringensparr C., Castro C.F., Mohammad R., Johnson P., Ketter T., Accettella D., Amblas D., An L., Arndt J.E., Canals M., Casamor J.L., Chauché N., Coakley B., Danielson S., Demarte M., Dickson M.-L., Dorschel B., Dowdeswell J.A., Dreutter S., Fremand A.C., Gallant D., Hall J.K., Hehemann L., Hodnesdal H., Hong J., Ivaldi R., Kane E., Klaucke I., Krawczyk D.W., Kristoffersen Y., Kuipers B.R., Millan R., Masetti G., Morlighem M., Noormets R., Prescott M.M., Rebesco M., Rignot E., Semiletov I., Tate A.J., Travaglini P., Velicogna I., Weatherall P., Weinrebe W., Willis J.K., Wood M., Zarayskaya Y., Zhang T., Zimmermann M., Zinglersen K.B. The International Bathymetric Chart of the Arctic Ocean version 4.0. Scientific Data, 2020. V. 7. No. 176. # 14. DOI: 10.1038/s41597-020-0520-9.
  227. James M.R., Robson S., d’Oleire-Oltmanns S., Niethammer U. Optimising UAV topographic surveys processed with structure-from-motion: ground control quality, quantity and bundle adjustment. Geomorphology, 2017. V. 280. P. 51–66. DOI: 10.1016/j.geomorph.2016.11.021.
  228. Jancewicz K., Migoń P., Kasprzak M. Connectivity patterns in contrasting types of tableland sandstone relief revealed by Topographic Wetness Index. Science of the Total Environment, 2019. V. 656. P. 1046–1062. DOI: 10.1016/j.scitotenv.2018.11.467.
  229. Jenčo M., Fulajtár E., Bobáľová H., Matečný I., Saksa M., Kožuch M., Gallay M., Kaňuk J., Píš V., Oršulová V. Mapping soil degradation on arable land with aerial photography and erosion models, case study from Danube Lowland, Slovakia. Remote Sensing, 2020. V. 12. No. 24. # 4047. DOI: 10.3390/rs12244047.
  230. Jenny B. Terrain generalization with line integral convolution. Cartography and Geographic Information Science, 2020. V. 48. No. 1. P. 78–92. DOI: 10.1080/15230406.2020.1833762.
  231. Jenny B., Heitzler M., Singh D., Farmakis-Serebryakova M., Liu J.C., Hurni L. Cartographic relief shading with neural networks. IEEE Transactions on Visualization and Computer Graphics, 2020. V. 27. No. 2. P. 1225–1235. DOI: 10.1109/TVCg.2020.3030456.
  232. Karachevtseva I.P., Kozlova N.A., Kokhanov A.A., Zubarev A.E., Nadezhdina I.E., Patratiy V.D., Konopikhin A.A., Basilevsky A.T., Abdrakhimov A.M., Oberst J., Haase I., Jolliff B.L., Plescia J.B., Robinson M.S. Cartography of the Luna-21 landing site and Lunokhod-2 traverse area based on Lunar Reconnaissance Orbiter Camera images and surface archive TV-panoramas. Icarus, 2017. V. 283. P. 104–121. DOI: 10.1016/j.icarus.2016.05.021.
  233. Karátson D., Yepes J., Favalli M., Rodríguez-Peces M.J., Fornaciai A. Reconstructing eroded paleovolcanoes on Gran Canaria, Canary Islands, using advanced geomorphometry. Geomorphology, 2016. V. 253. P. 123–134. DOI: 10.1016/j.geomorph.2015.10.004.
  234. Kasprak A., Bransky N.D., Sankey J.B., Caster J., Sankey T.T. The effects of topographic surveying technique and data resolution on the detection and interpretation of geomorphic change. Geomorphology, 2019. V. 333. P. 1–15. DOI: 10.1016/J.GEOMORPH.2019.02.020.
  235. Kasprak A., Caster J., Bangen S.G., Sankey J.B. Geomorphic process from topographic form: automating the interpretation of repeat survey data in river valleys. Earth Surface Processes and Landforms, 2017. V. 42. No. 12. P. 1872–1883. DOI: 10.1002/esp.4143.
  236. Kasvi E., Salmela J., Lotsari E., Kumpula T., Lane S.N. Comparison of remote sensing based approaches for mapping bathymetry of shallow, clear water rivers. Geomorphology, 2019. V. 333. P. 180–197. DOI: 10.1016/j.geomorph.2019.02.017.
  237. Kennelly P.J., Patterson T., Jenny B., Huffman D.P., Marston B.E., Bell S., Tait A.M. Elevation models for reproducible evaluation of terrain representation. Cartography and Geographic Information Science, 2021. V. 48. No. 1. P. 63–77. DOI: 10.1080/15230406.2020.1830856.
  238. Keylock C.J., Singh A., Passalacqua P., Foufoula-Georgiou E. Evaluating landscape complexity and the contribution of non-locality to geomorphometry. Journal of Geophysical Research: Earth Surface, 2021. V. 126. No. 4. # e2020JF005765. DOI: 10.1029/2020JF005765.
  239. Khosravi K., Pham B.T., Chapi K., Shirzadi A., Shahabi H., Revhaug I., Prakash I., Tien Bui D. A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at haraz watershed, northern Iran. Science of the Total Environment, 2018. V. 627. P. 744–755. DOI: 10.1016/j.scitotenv.2018.01.266.
  240. Kim Y.J., Nam B.H., Youn H. Sinkhole detection and characterization using LiDAR-derived DEM with logistic regression. Remote Sensing, 2019. V. 11. No. 13. # 1592. DOI: 10.3390/rs11131592.
  241. Kizyakov A., Khomutov A., Zimin M., Khairullin R., Babkina E., Dvornikov Y., Leibman M. Microrelief associated with gas emission craters: remote-sensing and field-based study. Remote Sensing, 2018. V. 10. No. 5. # 677. DOI: 10.3390/rs10050677.
  242. Kizyakov A., Zimin M., Sonyushkin A., Dvornikov Y., Khomutov A., Leibman M. Comparison of gas emission crater geomorphodynamics on Yamal and Gydan Peninsulas (Russia), based on repeat very-high-resolution stereopairs. Remote Sensing, 2017. V. 9. No. 10. # 1023. DOI: 10.3390/rs9101023.
  243. Knitter D., Braun R., Clare L., Nykamp M., Schütt B. Göbekli Tepe: a brief description of the environmental development in the surroundings of the UNESCO World Heritage Site. Land, 2019. V. 8. No. 4. # 72. DOI: 10.3390/land8040072.
  244. Koriche S.A., Rientjes T.H.M. Application of satellite products and hydrological modelling for flood early warning. Physics and Chemistry of the Earth, Parts A/B/C, 2016. V. 93. P. 12–23. DOI: 10.1016/j.pce.2016.03.007.
  245. Korzeniowska K., Pfeifer N., Landtwing S. Mapping gullies, dunes, lava fields, and landslides via surface roughness. Geomorphology, 2018. V. 301. P. 53–67. DOI: 10.1016/ j.geomorph.2017.10.011.
  246. Kraaijenbrink P.D.A, Meijer S.W., Shea J.M., Pellicciotti F., De Jong S.M., Immerzeel W.W. Seasonal surface velocities of a Himalayan glacier derived by automated correlation of unmanned aerial vehicle imagery. Annals of Glaciology, 2016a. V. 57. No. 71. P. 103–113. DOI: 10.3189/2016AOG71A072.
  247. Kraaijenbrink P.D.A., Shea J.M., Litt M., Steiner J.F., Treichler D., Koch I., Immerzeel W.W. Mapping surface temperatures on a debris-covered glacier with an unmanned aerial vehicle. Frontiers in Earth Science, 2018. V. 6. # 64. DOI: 10.3389/feart.2018.00064.
  248. Kraaijenbrink P.D.A., Shea J.M., Pellicciotti F., de Jong S.M., Immerzeel W.W. Object-based analysis of unmanned aerial vehicle imagery to map and characterise surface features on a debris-covered glacier. Remote Sensing of Environment, 2016b. V. 186. P. 581–595. DOI: 10.1016/j.rse.2016.09.013.
  249. Łajczak A., Zarychta R., Wałek G. Changes in the topography of Krakow city centre, Poland, during the last millennium. Journal of Maps, 2021. V. 17. DOI: 10.1080/17445647.2020.1823253.
  250. Lane B.A., Pasternack G.B., Dahlke H.E., Sandoval-Solis S. The role of topographic variability in river channel classification. Progress in Physical Geography, 2017. V. 41. No. 5. P. 570–600. DOI: 10.1177/0309133317718133.
  251. Lavagnino A.C., Bastos A.C., Amado Filho G.M., de Moraes F.C., Araujo L.S., de Moura R.L. Geomorphometric seabed classification and potential megahabitat distribution in the Amazon continental margin. Frontiers in Marine Science, 2020. V. 7. # 190. DOI: 10.3389/fmars.2020.00190.
  252. Lecours V., Dolan M.F.J., Micallef A., Lucieer V.L. A review of marine geomorphometry, the quantitative study of the seafloor. Hydrology and Earth System Sciences, 2016a. V. 20. No. 8. P. 3207–3244. DOI: 10.5194/hess-20-3207-2016.
  253. Lecours V., Brown C.J., Devillers R., Lucieer V.L., Edinger E.N. Comparing selections of environmental variables for ecological studies: a focus on terrain attributes. PLoS ONE, 2016b. V. 11. No. 12. # e0167128. DOI: 10.1371/journal.pone.0167128.
  254. Lecours V., Devillers R., Edinger E.N., Brown C.J., Lucieer V.L. Influence of artefacts in marine digital terrain models on habitat maps and species distribution models: a multiscale assessment. Remote Sensing in Ecology and Conservation, 2017a. V. 3. No. 4. P. 232–246. DOI: 10.1016/j.envsoft.2016.11.027.
  255. Lecours V., Devillers R., Lucieer V.L., Brown C.J. Artefacts in marine digital terrain models: a multiscale analysis of their impact on the derivation of terrain attributes. IEEE Transactions on Geoscience and Remote Sensing, 2017b. V. 55. No. 9. P. 5391–5406. DOI: 10.1109/TGRS.2017.2707303.
  256. Lecours V., Devillers R., Simms A.E., Lucieer V.L., Brown C.J. Towards a framework for terrain attribute selection in environmental studies. Environmental Modelling and Software, 2017c. V. 89. P. 19–30. DOI: 10.1016/j.envsoft.2016.11.027.
  257. Legleiter C.J., Harrison L.R. Remote sensing of river bathymetry: evaluating a range of sensors, platforms, and algorithms on the Upper Sacramento River, California, USA. Water Resources Research, 2019. V. 55, 3. P. 2142–2169. DOI: 10.1029/2018WR0 23586.
  258. Lei S., Chen H., Bian Z., Liu Z. Evaluation of integrating topographic wetness index with backscattering coefficient of TerraSAR-X image for soil moisture estimation in a mountainous region. Ecological Indicators, 2016. V. 61. No. 2. P. 624–633. DOI: 10.1016/j.ecolind.2015.10.013.
  259. Leitão J.P., Moy de Vitry M., Scheidegger A., Rieckermann J. Assessing the quality of digital elevation models obtained from mini unmanned aerial vehicles for overland flow modelling in urban areas. Hydrology and Earth System Sciences, 2016. V. 20. No. 4. P. 1637–1653. DOI: 10.5194/hess-20-1637-2016.
  260. Li H., Zhao J. Evaluation of the newly released worldwide AW3D30 DEM over typical landforms of China using two global DEMs and ICESat/GLAS data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018. V. 11. No. 11. P. 4430–4440. DOI: 10.1109/JSTARS.2018.2874361.
  261. Li S., Xiong L., Tang G., Strobl J. Deep learning-based approach for landform classification from integrated data sources of digital elevation model and imagery. Geomorphology, 2020. V. 354. # 107045. DOI: 10.1016/j.geomorph.2020.107045.
  262. Li Y., Li Y., Lu X., Harbor J. Geomorphometric controls on mountain glacier changes since the little Ice Age in the Eastern Tien Shan, Central Asia. Annals of the American Association of Geographers, 2017. V. 107. No. 2. P. 284–298. DOI: 10.1080/24694452.2016.1248552.
  263. Li Z., Zhu Q., Gold C. Digital Terrain Modeling: principles and Methodology. New york: CRC Press, 2005. 323 p.
  264. Liang J., Shen S., Gong J., Liu J., Zhang J. Embedding user-generated content into oblique airborne photogrammetry-based 3D city model. International Journal of Geographical Information Science, 2017. V. 31. No. 1. P. 1–16. DOI: 10.1080/13658816.2016.1180389.
  265. Libohova Z., Winzeler H.E., Lee B., Schoeneberger P.J., Datta J., Owens P.R. Geomorphons: landform and property predictions in a glacial moraine in Indiana landscapes. Catena, 2016. V. 142. P. 66–76. DOI: 10.1016/j.catena.2016.01.002.
  266. Lin Y., Prentice S.E., Tran T., Bingham N.L., King J.Y., Chadwick O.A. Modeling deep soil properties on California grassland hillslopes using LiDAR digital elevation models. Geoderma Regional, 2016. V. 7. P. 67–75. DOI: 10.1016/J.GEODRS.2016.01.005.
  267. Lindsay J.B. Efficient hybrid breaching-filling sink removal methods for flow path enforcement in digital elevation models. Hydrological Processes, 2016a. V. 30. No. 6. P. 846–857. DOI: 10.1002/hyp.10648.
  268. Lindsay J.B. The practice of DEM stream burning revisited. Earth Surface Processes and Landforms, 2016b. V. 41. No. 5. P. 658–668. DOI: 10.1002/esp.3888.
  269. Lindsay J.B. Whitebox GAT: a case study in geomorphometric analysis. Computers and Geosciences, 2016c. V. 95. P. 75–84. DOI: 10.1016/j.cageo.2016.07.003.
  270. Liu K., Ding H., Tang G., Song C., Liu Y., Jiang L., Zhao B., Gao Y., Ma R. Large-scale mapping of gully-affected areas: an approach integrating google Earth images and terrain skeleton information. Geomorphology, 2018. V. 314. P. 13–26. DOI: 10.1016/j.geomorph.2018.04.011.
  271. Liu K., Song C., Ke L., Jiang L., Ma R. Automatic watershed delineation in the Tibetan endorheic basin: a lake-oriented approach based on digital elevation models. Geomorphology, 2020a. V. 358. # 107127. DOI: 10.1016/j.geomorph.2020.107127.
  272. Liu K., Song C., Ke L., Jiang L., Pan Y., Ma R. Global open-access DEM performances in Earth’s most rugged region High Mountain Asia: a multi-level assessment. Geomorphology, 2019. V. 338. P. 16–26. DOI: 10.1016/j.geomorph.2019.04.012.
  273. Liu K., Song C., Wang J., Ke L., Zhu Y., Zhu J., Ma R., Luo Z. Remote sensing-based modeling of the bathymetry and water storage for channel-type reservoirs worldwide. Water Resources Research, 2020b. V. 56. No. 11. # e2020WR027147. DOI: 10.1029/2020WR027147.
  274. Liu Y., Gong W., Hu X., Gong J. Forest type identification with random forest using Sentinel-1A, Sentinel 2A, multi-temporal Landsat-8 and DEM data. Remote Sensing, 2018. V. 10. No. 6. # 946. DOI: 10.3390/rs10060946.
  275. Loro M., Arce R.M., Ortega E. Identification of optimal landforms to reduce impacts on the landscape using LiDAR for hosting a new highway. Environmental Impact Assessment Review, 2017. V. 66. P. 99–114. DOI: 10.1016/j.eiar.2017.06.006.
  276. Loye A., Jaboyedoff M., Theule J.I., Liébault F. Headwater sediment dynamics in a debris flow catchment constrained by high-resolution topographic surveys. Earth Surface Dynamics, 2016. V. 4. No. 2. P. 489–513. DOI: 10.5194/esurf-4-489-2016.
  277. Lu S., Liu B., Hu Y., Fu S., Cao Q., Shi Y., Huang T. Soil erosion topographic factor (LS): accuracy calculated from different data sources. Catena, 2020. V. 187. # 104334. DOI: 10.1016/j.catena.2019.104334.
  278. Lu X., Yang K., Lu Y., Gleason C.J., Smith L.C., Li M. Small Arctic rivers mapped from Sentinel-2 satellite imagery and ArcticDEM. Journal of Hydrology, 2020. V. 584. # 124689. DOI: 10.1016/j.jhydrol.2020.124689.
  279. Luo L., Wang X., Guo H., Lasaponara R., Zong X., Masini N., Wang G., Shi P., Khatteli H., Chen F., Tariq S., Shao J., Bachagha N., Yang R., Yao Y. Airborne and spaceborne remote sensing for archaeological and cultural heritage applications: a review of the century (1907–2017). Remote Sensing of Environment, 2019. V. 232. # 111280. DOI: 10.1016/j.rse.2019.111280.
  280. Luo W., Jasiewicz J., Stepinski T., Wang J., Xu C., Cang X. Spatial association between dissection density and environmental factors over the entire conterminous United States. Geophysical Research Letters, 2016. V. 43. No. 2. P. 692–700. DOI: 10.1002/2015GL066941.
  281. Luo W., Liu C.-C. Innovative landslide susceptibility mapping supported by geomorphon and geographical detector methods. Landslides, 2018. V. 15. No. 3. P. 465–474. DOI: 10.1007/s10346-017-0893-9.
  282. Luo W., Xu X., Liu W., Liu M., Li Z., Peng T., Xu C., Zhang Y., Zhang R. UAV based soil moisture remote sensing in a karst mountainous catchment. Catena, 2019. V. 174. P. 478–489. DOI: 10.1016/j.catena.2018.11.017.
  283. Lv G., Xiong L., Chen M., Tang G., Sheng Y., Liu X., Song Z., Lu Y., Yu Z., Zhang K., Wang M. Chinese progress in geomorphometry. Journal of Geographical Sciences, 2017. V. 27. No. 11. P. 1389–1412. DOI: 10.1007/s11442-017-1442-0.
  284. Ma L., Liu Y., Zhang X., Ye Y., Yin G., Johnson B.A. Deep learning in remote sensing applications: a meta-analysis and review. ISPRS Journal of Photogrammetry and Remote Sensing, 2019. V. 152. P. 166–177. DOI: 10.1016/j.isprsjprs.2019.04.015.
  285. Mallalieu J., Carrivick J., Quincey D., Smith M., James W. An integrated Structure-from-Motion and time-lapse technique for quantifying ice-margin dynamics. Journal of Glaciology, 2017. V. 63. No. 242. P. 937–949. DOI: 10.1017/jog.2017.48.
  286. Mallet F., Marc V., Douvinet J., Rossello P., Joly D., Ruy S. Assessing soil water content variation in a small mountainous catchment over different time scales and land covers using geographical variables. Journal of Hydrology, 2020. V. 591. # 125593. DOI: 10.1016/j.jhydrol.2020.125593.
  287. Malone B.P., Jha S.K., Minasny B., McBratney A.B. Comparing regression-based digital soil mapping and multiple-point geostatistics for the spatial extrapolation of soil data. geoderma, 2016. V. 262. P. 243–253. DOI: 10.1016/j.geoderma.2015.08.037.
  288. Malone B.P., Sty  Q., Minasny B., McBratney A.B. Digital soil mapping of soil carbon at the farm scale: a spatial downscaling approach in consideration of measured and uncertain data. Geoderma, 2017. V. 290. P. 91–99. DOI: 10.1016/j.geoderma.2016.12.008.
  289. Marchese F., Bracchi V.A., Lisi G., Basso D., Corselli C., Savini A. Assessing fine-scale distribution and volume of Mediterranean algal reefs through terrain analysis of multi-beam bathymetric data. A case study in the Southern Adriatic continental shelf. Water, 2020. V. 12. No. 1. # 157. DOI: 10.3390/w12010157.
  290. Marchi L., Comiti F., Crema S., Cavalli M. Channel control works and sediment connectivity in the European Alps. Science of the Total Environment, 2019. V. 668. P. 389–399. DOI: 10.1016/j.scitotenv.2019.02.416.
  291. Marques K., Demattê J., Miller B.A., Lepsch I. Geomorphometric segmentation of complex slope elements for detailed digital soil mapping in Southeast Brazil. Geoderma Regional, 2018. V. 14. # e00175. DOI: 10.1016/j.geodrs.2018.e00175.
  292. Martini L., Picco L., Iroumé A., Cavalli M. Sediment connectivity changes in an Andean catchment affected by volcanic eruption. Science of the Total Environment, 2019. V. 692. P. 1209–1222. DOI: 10.1016/j.scitotenv.2019.07.303.
  293. Masini N., Gizzi F.T., Biscione M., Fundone V., Sedile M., Sileo M., Pecci A., Lacovara B., Lasaponara R. Medieval archaeology under the canopy with LiDAR. The (re)discovery of a medieval fortified settlement in Southern Italy. Remote Sensing, 2018. V. 10. No. 10. # 1598. DOI: 10.3390/rs10101598.
  294. Mather A.E., Fyfe R.M., Clason C.C., Stokes M., Mills S., Barrows T.T. Automated mapping of relict patterned ground: an approach to evaluate morphologically subdued landforms using unmanned-aerial-vehicle and structure-from-motion technologies. Progress in Physical Geography, 2019. V. 43. No. 2. P. 174–192. DOI: 10.1177/0309133318788966.
  295. Maxwell A.E., Sharma M., Kite J.S., Donaldson K.A., Thompson J.A., Bell M.L., Maynard S.M. Slope failure prediction using random forest machine learning and LiDAR in an eroded folded mountain belt. Remote Sensing, 2020. V. 12. No. 3. # 486. DOI: 10.3390/rs12030486.
  296. Maxwell A.E., Warner T.A. Is high spatial resolution DEM data necessary for mapping palustrine wetlands? International Journal of Remote Sensing, 2019. V. 40. No. 1. P. 118–137. DOI: 10.1080/01431161.2018.1506184.
  297. McBratney A.B., Minasny B., Stockmann U. (eds.) Pedometrics. Cham: Springer, 2018. 720 p. DOI: 10.1007/978-3-319-63439-5.
  298. Meddens A.J.H., Vierling L.A., Eitel J.U.H., Jennewein J.S., White J.C., Wulder M.A. Developing 5 m resolution canopy height and digital terrain models from WorldView and ArcticDEM data. Remote Sensing of Environment, 2018. V. 218. P. 174–188. DOI: 10.1016/j.rse.2018.09.010.
  299. Medvedev A., Telnova N., Alekseenko N., Koshkarev A., Kuznetchenko P., Asmaryan S., Narykov A. UAV-derived data application for environmental monitoring of the coastal area of Lake Sevan, Armenia with a changing water level. Remote Sensing, 2020. V. 12. No. 22. # 3821. DOI: 10.3390/rs12223821.
  300. Meles M.B., Younger S.E., Jackson C.R., Du E., Drover D. Wetness index based on landscape position and topography (WILT): modifying TWI to reflect landscape position. Journal of Environmental Management, 2020. V. 255. # 109863. DOI: 10.1016/j.jenvman.2019.109863.
  301. Menna F., Agrafiotis P., Georgopoulos A. State of the art and applications in archaeological underwater 3D recording and mapping. Journal of Cultural Heritage, 2018. V. 33. P. 231–248. DOI: 10.1016/j.culher.2018.02.017.
  302. Mertes J.R., Gulley J.D., Benn D.I., Thompson S.S., Nicholson L.I. Using structure-from-motion to create glacier DEMs and orthoimagery from historical terrestrial and oblique aerial imagery. Earth Surface Processes and Landforms, 2017. V. 42. No. 14. P. 2350–2364. DOI: 10.1002/esp.4188.
  303. Middleton M., Heikkonen J., Nevalainen P., Hyvönen E., Sutinen R. Machine learning-based mapping of micro-topographic earthquake-induced paleo-pulju moraines and liquefaction spreads from a digital elevation model acquired through laser scanning. Geomorphology, 2020. V. 358. # 107099. DOI: 10.1016/j.geomorph.2020.107099.
  304. Midgley N.G., Tonkin T.N., Graham D.J., Cook S.J. Evolution of high-Arctic glacial landforms during deglaciation. Geomorphology, 2018. V. 311. P. 63–75. DOI: 10.1016/j.geomorph.2018.03.027.
  305. Migoń P., Jancewicz K., Różycka M., Duszyński F., Kasprzak M. Large-scale slope remodelling by landslides—geomorphic diversity and geological controls, Kamienne Mts., Central Europe. Geomorphology, 2017. V. 289. P. 134–151. DOI: 10.1016/j.geomorph.2016.09.037.
  306. Migoń P., Kasprzak M. Pathways of geomorphic evolution of sandstone escarpments in the Góry Stołowe tableland (SW Poland)—insights from LiDAR-based high-resolution DEM. Geomorphology, 2016. V. 260. P. 51–63. DOI: 10.1016/j.geomorph.2015.08.022.
  307. Mills S.C., Le Brocq A.M., Winter K., Smith M., Hillier J., Ardakova E., Boston C.M., Sugden D., Woodward J. Testing and application of a model for snow redistribution (Snow_Blow) in the Ellsworth Mountains, Antarctica. Journal of Glaciology, 2019. V. 65. No. 254. P. 957–970. DOI: 10.1017/jog.2019.70.
  308. Minár J., Evans I.S., Jenčo M. A comprehensive system of definitions of land surface (topographic) curvatures, with implications for their application in geoscience modelling and prediction. Earth-Science Reviews, 2020. V. 211. # 103414. DOI: 10.1016/j.earscirev.2020.103414.
  309. Minár J., Krcho J., Evans I.S. Geomorphometry: quantitative land-surface analysis. Reference Module in Earth Systems and Environmental Sciences. Amsterdam: Elsevier, 2016. DOI: 10.1016/B978-0-12-409548-9.10260-X.
  310. Minasny B., McBratney A.B. Digital soil mapping: a brief history and some lessons. Geoderma, 2016. V. 264. Pt. B. P. 301–311. DOI: 10.1016/j.geoderma.2015.07.017.
  311. Misiuk B., Lecours V., Bell T. A multiscale approach to mapping seabed sediments. PLoS ONE, 2018. V. 13. No. 2. # e0193647. DOI: 10.1371/journal.pone.0193647.
  312. Mithan H.T., Hales T.C., Cleall P.J. Supervised classification of landforms in Arctic mountains. Permafrost and Periglac Processes, 2019. V. 30. No. 3. P. 131–145. DOI: 10.1002/ppp.2015.
  313. Mitusov A.V., Burian L., Khrisanov V.R. Distribution of local landforms at head and end points of gullies on different grid spacing. Catena, 2017. V. 159. P. 159–170. DOI: 10.1016/j.catena.2017.08.010.
  314. Mohamed M.A. Classification of landforms for digital soil mapping in urban areas using LiDAR data derived terrain attributes: a case study from Berlin, Germany. Land, 2020. V. 9. No. 9. # 319. DOI: 10.3390/land9090319.
  315. Mölg N., Bolch T. Structure-from-motion using historical aerial images to analyse changes in glacier surface elevation. Remote Sensing, 2017. V. 9. No. 10. # 1021. DOI: 10.3390/rs9101021.
  316. Mondal A., Khare D., Kundu S., Mukherjee S., Mukhopadhyay A., Mondal S. Uncertainty of soil erosion modelling using open source high resolution and aggregated DEMs. Geoscience Frontiers, 2017. V. 8. No. 3. P. 425–436. DOI: 10.1016/j.gsf.2016.03.004.
  317. Moon S., Perron J.T., Martel S.J., Holbrook W.S., St. Clair J. A model of three-dimensional topographic stresses with implications for bed-rock fractures, surface processes, and landscape evolution. Journal of Geophysical Research: Earth Surface, 2017. V. 122. No. 4, 823–846. DOI: 10.1002/2016JF004155.
  318. Moore I.D., Grayson R.B., Ladson A.R. Digital terrain modelling: a review of hydrological, geomorphological and biological applications. Hydrological Processes, 1991. V. 5. No. 1. P. 3–30. DOI: 10.1002/hyp.3360050103.
  319. Moreno-Gómez M., Liedl R., Stefan C., Moreno-Gómez M., Liedl R., Stefan C. A new GIS-based model for karst dolines mapping using LiDAR; application of a multidepth threshold approach in the yucatan Karst, Mexico. Remote Sensing, 2019. V. 11. No. 10. # 1147. DOI: 10.3390/rs11101147.
  320. Morlighem M., Williams C.N., Rignot E., An L., Arndt J.E., Bamber J.L., Catania G., Chauché N., Dowdeswell J.A., Dorschel B., Fenty I., Hogan K., Howat I., Hubbard A., Jakobsson M., Jordan T.M., Kjeldsen K.K., Millan R., Mayer L., Mouginot J., Noël B.P.Y., O’Cofaigh C., Palmer S., Rysgaard S., Seroussi H., Siegert M.J., Slabon P., Straneo F., van den Broeke M.R., Weinrebe W., Wood M., Zinglersen K.B. BedMachine v3: complete bed topography and ocean bathymetry mapping of greenland from multibeam echo sounding combined with mass conservation. Geophysical Research Letters, 2017. V. 44. P. 11051–11061. DOI: 10.1002/2017GL074954.
  321. Moudrý V., Lecours V., Gdulová K., Gábor L., Moudrá L., Kropáček J., Wild J. On the use of global DEMs in ecological modelling and the accuracy of new bare-earth DEMs. Ecological Modelling, 2018. V. 383. P. 3–9. DOI: 10.1016/j.ecolmodel.2018.05.006.
  322. Mulder V.L., Lacoste M., Richer-de-Forges A.C., Arrouays D. GlobalSoilMap France: high-resolution spatial modelling the soils of France up to two meter depth. Science of the Total Environment, 2016a. V. 573. P. 1352–1369. DOI: 10.1016/j.scitotenv.2016.07.066.
  323. Mulder V.L., Lacoste M., Richer-de-Forges A.C., Martin M.P., Arrouays D. National versus global modelling the 3D distribution of soil organic carbon in mainland France. Geoderma, 2016b. V. 263. P. 16–34. DOI: 10.1016/j.geoderma.2015.08.035.
  324. Müller R.D., Qin X., Sandwell D.T., Dutkiewicz A., Williams S.E., Flament N., Maus S., Seton M. The gplates portal: cloud-based interactive 3D visualization of global geophysical and geological data in a web browser. PLoS ONE, 2016. V. 11. No. 3. # e0150883, DOI: 10.1371/journal.pone.0150883.
  325. Muthusamy M., Rivas Casado M., Butler D., Leinster P. Understanding the effects of digital elevation model resolution in urban fluvial flood modelling. Journal of Hydrology, 2021. V. 596. # 126088. DOI: 10.1016/j.jhydrol.2021.126088.
  326. Nachappa T.G., Kienberger S., Meena S.R., Hölbling D., Blaschke T. Comparison and validation of per-pixel and object-based approaches for landslide susceptibility mapping. geomatics, Natural hazards and Risk, 2020. V. 11. No. 1. P. 572–600. DOI: 10.1080/19475705.2020.1736190.
  327. Nagy-Reis M.B., Estevo C.A., Setz E.Z.F., Ribeiro M.C., Chiarello A.G., Nichols J.D. Relative importance of anthropogenic landscape characteristics for Neotropical frugivores at multiple scales. Animal Conservation, 2017a. V. 20. No. 6. P. 520–531. DOI: 10.1111/acv.12346.
  328. Nagy-Reis M.B., Nichols J.D., Chiarello A.G., Ribeiro M.C., Setz E.Z.F. Landscape use and co-occurrence patterns of neotropical spotted cats. PLoS ONE, 2017b. V. 12. No. 1. # e0168441. DOI: 10.1371/journal.pone.0168441.
  329. Nevalainen P., Middleton M., Sutinen R., Heikkonen J., Pahikkala T. Detecting terrain stoniness from airborne laser scanning data. Remote Sensing, 2016. V. 8. No. 9. # 720. DOI: 10.3390/rs8090720.
  330. Newman D.R., Lindsay J.B., Cockburn J.M.H. Evaluating metrics of local topographic position for multiscale geomorphometric analysis. Geomorphology, 2018. V. 312. P. 40–50. DOI: 10.1016/j.geomorph.2018.04.003.
  331. Nicoll T., Brierley G. Within-catchment variability in landscape connectivity measures in the garang catchment, upper yellow River. Geomorphology, 2017. V. 277. P. 197–209. DOI: 10.1016/j.geomorph.2016.03.014.
  332. Nicu I.C., Asăndulesei A. GIS-based evaluation of diagnostic areas in landslide susceptibility analysis of Bahluieţ River Basin (Moldavian Plateau, NE Romania): are Neolithic sites in danger? Geomorphology, 2018. V. 314. P. 27–41. DOI: 10.1016/j.geomorph.2018.04.010.
  333. Niculiţă M. Automatic landslide length and width estimation based on the geometric processing of the bounding box and the geomorphometric analysis of DEMs. Natural Hazards and Earth System Sciences, 2016. V. 16. No. 8. P. 2021–2030. DOI: 10.5194/nhess-16-2021-2016.
  334. Niculiţă M. Geomorphometric methods for burial mound recognition and extraction from high-resolution LiDAR DEMs. Sensors, 2020. V. 20. No. 4. # 1192. DOI: 10.3390/s20041192.
  335. Niculiţă M., Mărgărint M.C., Cristea A.I. Using archaeological and geomorphological evidence for the establishment of a relative chronology and evolution pattern for holocene landslides. PLoS ONE, 2019. V. 14. No. 12. # e0227335. DOI: 10.1371/journal.pone.0227335.
  336. Noriega-Londoño S., Restrepo-Moreno S.A., Vinasco C., Bermúdez M.A., Min K. Thermochronologic and geomorphometric constraints on the Cenozoic landscape evolution of the Northern Andes: Northwestern Central Cordillera, Colombia. Geomorphology, 2020. V. 351. # 106890. DOI: 10.1016/j.geomorph.2019.106890.
  337. Novaczek E., Devillers R., Edinger E. Generating higher resolution regional seafloor maps from crowd-sourced bathymetry. PLoS ONE, 2019. V. 14. No. 6. # e0216792. DOI: 10.1371/journal.pone.0216792.
  338. Nussbaum M., Spiess K., Baltensweiler A., Grob U., Keller A., Greiner L., Schaepman M.E., Papritz A. Evaluation of digital soil mapping approaches with large sets of environmental covariates. Soil, 2018. V. 4. No. 1. P. 1–22. DOI: 10.5194/soil-4-1-2018.
  339. O’Loughlin F.E., Paiv R.C.D., Durand M., Alsdorf D.E., Bates P.D. A multi-sensor approach towards a global vegetation corrected SRTM DEM product. Remote Sensing of Environment, 2016. V. 182. P. 49–59. DOI: 10.1016/j.rse.2016.04.018.
  340. O’Neil G.L., Goodall J.L., Watson L.T. Evaluating the potential for site-specific modification of LiDAR DEM derivatives to improve environmental planning-scale wetland identification using Random Forest classification. Journal of Hydrology, 2018. V. 559. P. 192–208. DOI: 10.1016/j.jhydrol.2018.02.009.
  341. O’Neil G.L., Saby L., Band L.E., Goodall J.L. Effects of LiDAR DEM smoothing and conditioning techniques on a topography-based wetland identification model. Water Resources Research, 2019. V. 55. No. 5. P. 4343–4363. DOI: 10.1029/2019WR024784.
  342. O’Reilly D., Evans D., Shewan L. Airborne LiDAR prospection at lovea, an Iron Age moated settlement in central Cambodia. Antiquity, 2017. V. 91. No. 358. P. 947–965. DOI: 10.15184/aqy.2017.69.
  343. Orti M.V., Negussie K., Corral-Pazos-de-Provens E., Höfle B., Bubenzer O. Comparison of three algorithms for the evaluation of TanDEM-X data for gully detection in Krumhuk Farm (Namibia). Remote Sensing, 2019. V. 11. No. 11. # 1327. DOI: 10.3390/rs11111327.
  344. Owono F.M., Ntamak-Nida M.-J., Dauteuil O., Guillocheau F., Njom B. Morphology and long-term landscape evolution of the South African plateau in South Namibia. Catena, 2016. V. 142. P. 47–65. DOI: 10.1016/j.catena.2016.02.012.
  345. Pacheco-Ruiz R., Adams J., Pedrotti F. 4D modelling of low visibility underwater archaeological excavations using multi-source photogrammetry in the Bulgarian Black Sea. Journal of Archaeological Science, 2018. V. 100. P. 120–129. DOI: 10.1016/j.jas.2018. 10.005.
  346. Padarian J., Minasny B., McBratney A.B. Using deep learning for digital soil mapping. Soil, 2019. V. 5. No. 1. P. 79–89. DOI: 10.5194/soil-5-79-2019.
  347. Pánek T., Břežný M., Kapustová V., Lenart J., Chalupa V. Large landslides and deep-seated gravitational slope deformations in the Czech Flysch Carpathians: new LiDAR-based inventory. Geomorphology, 2019. V. 346. # 106852. DOI: 10.1016/j.geomorph.2019.106852.
  348. Papageorgaki I., Nalbantis I. Classification of drainage basins based on readily available information. Water Resources Management, 2016. V. 30. No. 15. P. 5559–5574. DOI: 10.1007/s11269-016-1410-y.
  349. Papworth H., Ford A., Welham K., Thackray D. Assessing 3D metric data of digital surface models for extracting archaeological data from archive stereo-aerial photographs. Journal of Archaeological Science, 2016. V. 72. P. 85–104. DOI: 10.1016/j.jas.2016.05.005.
  350. Patton N.R., Ellerton D., Shulmeister J. High-resolution remapping of the coastal dune fields of south East Queensland, Australia: a morphometric approach. Journal of Maps, 2019. V. 15. No. 2. P. 578–589. DOI: 10.1080/17445647.2019.1642246.
  351. Patton N.R., Lohse K.A., Godsey S.E., Crosby B.T., Seyfried M.S. Predicting soil thickness on soil mantled hillslopes. Nature Communications, 2018. V. 9. # 3329. DOI: 10.1038/s41467-018-05743-y.
  352. Peckham S.D., Stoica M., Jafarov E., Endalamaw A., Bolton W.R. Reproducible, component-based modeling with TopoFlow, a spatial hydrologic modeling toolkit. Earth and Space Science, 2017. V. 4. No. 6. P. 377–394. DOI: 10.1002/2016ea000237.
  353. Pedersen G.B.M. Semi-automatic classification of glaciovolcanic landforms: an object-based mapping approach based on geomorphometry. Journal of Volcanology and Geothermal Research, 2016. V. 311. P. 29–40. DOI: 10.1016/j.jvolgeores.2015.12.015.
  354. Pedersen G.B.M., Grosse P., Gudmundsson M.T. Morphometry of glaciovolcanic edifices from Iceland: types and evolution. Geomorphology, 2020. V. 370. # 107334. DOI: 10.1016/j.geomorph.2020.107334.
  355. Pejović M., Nikolić M., Heuvelink G.B.M., Hengl T., Kilibarda M., Bajat B. Sparse regression interaction models for spatial prediction of soil properties in 3D. Computers and geosciences, 2018. V. 118. P. 1–13. DOI: 10.1016/j.cageo.2018.05.008.
  356. Penížek V., Zádorová T., Kodešová R., Vaněk A. Influence of elevation data resolution on spatial prediction of colluvial soils in a luvisol region. PLoS ONE, 2016. V. 11. No. 11. # e0165699. DOI: 10.1371/journal.pone.0165699.
  357. Petrasova A., Harmon B., Petras V., Tabrizian P., Mitasova H. Tangible Modeling with Open Source GIS. 2nd ed. Cham: Springer, 2018. 202 p. DOI: 10.1007/978-3-319-89303-7.
  358. Piccini C., Marchetti A., Rivieccio R., Napoli R. Multinomial logistic regression with soil diagnostic features and land surface parameters for soil mapping of latium (Central Italy). Geoderma, 2019. V. 352. P. 385–394. DOI: 10.1016/j.geoderma.2018.09.037.
  359. Piermattei L., Carturan L., de Blasi F., Tarolli P., Dalla Fontana G., Vettore A., Pfeifer N. Suitability of ground-based SfM-MVS for monitoring glacial and periglacial processes. Earth Surface Dynamics, 2016. V. 4. No. 2. P. 425–443. DOI: 10.5194/esurf-4-425-2016.
  360. Pijl A., Bailly J.-S., Feurer D., El Maaoui M.A., Boussema M.R., Tarolli P. TERRA: Terrain Extraction from elevation Rasters through Repetitive Anisotropic filtering. International Journal of Applied Earth Observation and Geoinformation, 2020. V. 84. # 101977. DOI: 10.1016/J.JAG.2019.101977.
  361. Pike R.J. Geomorphometry—diversity in quantitative surface analysis. Progress in Physical Geography, 2000. V. 24. No. 1. P. 1–20. DOI: 10.1177/030913330002400101.
  362. Pike R.J. Digital terrain modeling and industrial surface metrology: converging realms. Professional Geographer, 2001. V. 53. No. 2. P. 263–274. DOI: 10.1111/0033-0124.00284.
  363. Podgórski J., Kinnard C., Pętlicki M., Urrutia R. Performance assessment of TanDEM-X DEM for mountain glacier elevation change detection. Remote Sensing, 2019. V. 11. No. 2. # 187. DOI: 10.3390/rs11020187.
  364. Polidori L., El Hage M. Digital elevation model quality assessment methods: a critical review. Remote Sensing, 2020. V. 12. No. 21. # 3522. DOI: 10.3390/rs12213522.
  365. Popa C.N., Knitter D. From environment to landscape. Reconstructing environment perception using numerical data. Journal of Archaeological Method and Theory, 2016. V. 23. No. 4. P. 1285–1306. DOI: 10.1007/s10816-015-9264-9.
  366. Porter C., Morin P., Howat I., Noh M.-J., Bates B., Peterman K., Keesey S., Schlenk M., Gardiner J., Tomko K., Willis M., Kelleher C., Cloutier M., Husby E., Foga S., Nakamura H., Platson M., Wethington M. Jr., Williamson C., Bauer G., Enos J., Arnold G., Kramer W., Becker P., Doshi A., D’Souza C., Cummens P., Laurier F., Bojesen M. ArcticDEM. Harvard Dataverse, 2018. DOI: 10.7910/DVN/OHHUKH.
  367. Pourtaghi Z.S., Pourghasemi H.R., Aretano R., Semeraro T. Investigation of general indicators influencing on forest fire and its susceptibility modelling using different data mining techniques. Ecological Indicators, 2016. V. 64. P. 72–84. DOI: 10.1016/j.ecolind.2015.12.030.
  368. Puliti S., Hauglin M., Breidenbach J., Montesano P., Neigh C.S.R., Rahlf J., Solberg S., Klingenberg T.F., Astrup R. Modelling above-ground biomass stock over Norway using national forest inventory data with ArcticDEM and Sentinel-2 data. Remote Sensing of Environment, 2020. V. 236. # 111501. DOI: 10.1016/j.rse.2019.111501.
  369. Purinton B., Bookhagen B. Validation of digital elevation models (DEMs) and comparison of geomorphic metrics on the southern Central Andean Plateau. Earth Surface Dynamics, 2017. V. 5. No. 2. P. 211–237. DOI: 10.5194/esurf-5-211-2017.
  370. Qin C.-Z., Wu X.-W., Jiang J.-C., Zhu A-X. Case-based formalization and reasoning method for knowledge in digital terrain analysis: application to extracting drainage networks. Hydrology and Earth System Sciences, 2016. V. 20. No. 8. P. 3379–3392. DOI: 10.5194/hess-20-3379-2016.
  371. Qin C.-Z., Ai B.-B., Zhu A-X., Liu J.-Z. An efficient method for applying a differential equation to deriving the spatial distribution of specific catchment area from gridded digital elevation models. Computers and geosciences, 2017. V. 100. P. 94–102. DOI: 10.1016/j.cageo.2016.12.009.
  372. Qin L., Xu W., Tian Y., Chen B., Wang S. A river channel extraction method for urban environments based on terrain transition lines. Water Resources Research, 2018. V. 54. No. 7. P. 4887–4900. DOI: 10.1029/2018WR023095.
  373. Queen C.W., Nelson F.E., Gunn G.E., Nyland K.E. A characteristic periglacial landform: automated recognition and delineation of cryoplanation terraces in eastern Beringia. Permafrost and Periglacial Processes, 2021. V. 32, No. 1. P. 46–35. DOI: 10.1002/ppp.2083.
  374. Ragettli S., Bolch T., Pellicciotti F. Heterogeneous glacier thinning patterns over the last 40 years in Langtang Himal, Nepal. Cryosphere, 2016. V. 10. No. 5. P. 2075–2097. DOI: 10.5194/tc-10-2075-2016.
  375. Rahmati O., Ghorbanzadeh O., Teimurian T., Mohammadi F., Tiefenbacher J.P., Falah F., Pirasteh S., Ngo P.-T.T., Tien Bui D. Spatial modeling of snow avalanche using machine learning models and geo-environmental factors: comparison of effectiveness in two mountain regions. Remote Sensing, 2019. V. 11. No. 24. # 2995. DOI: 10.3390/rs11242995.
  376. Rahmati O., Pourghasemi H.R., Melesse A.M. Application of GIS-based data driven random forest and maximum entropy models for groundwater potential mapping: a case study at Mehran Region, Iran. Catena, 2016. V. 137. P. 360–372. DOI: 10.1016/j.catena.2015.10.010.
  377. Ramcharan A., Hengl T., T Nauman., Brungard C., Waltman S., Wills S., Thompson J. Soil property and class maps of the conterminous United States at 100-meter spatial resolution. Soil Science Society of America Journal, 2018. V. 82. No. 1. P. 186–201. DOI: 10.2136/sssaj2017.04.0122.
  378. Ren Z., Zielke O., Yu J. Active tectonics in 4D high-resolution. Journal of Structural Geology, 2018. V. 117. P. 264–271. DOI: 10.1016/j.jsg.2018.09.015.
  379. Richards-Rissetto H. What can GIS + 3D mean for landscape archaeology? Journal of Archaeological Science, 2017. V. 84. P. 10–21. DOI: 10.1016/j.jas.2017.05.005.
  380. Riza S., Sekine M., Kanno A., Yamamoto K., Imai T., Higuchi T. Modeling soil landscapes and soil textures using hyperscale terrain attributes. Geoderma, 2021. V. 402. # 115177. DOI: 10.1016/j.geoderma.2021.115177.
  381. Rizzoli P., Martone M., Gonzalez C., Wecklich C., Borla Tridon D., Bräutigam B., Bachmann M., Schulze D., Fritz T., Huber M., Wessel B., Krieger G., Zink M., Moreira A. Generation and performance assessment of the global TanDEM-X digital elevation model. ISPRS Journal of Photogrammetry and Remote Sensing, 2017. V. 132. P. 119–139. DOI: 10.1016/j.isprsjprs.2017.08.008.
  382. Robbins S.J., Watters W.A., Chappelow J.E., Bray V.J., Daubar I.J., Craddock R.A., Beyer R.A., Landis M.E., Ostrach L.R., Tornabene L., Riggs J.D., Weaver B.P. Measuring impact crater depth throughout the Solar system. Meteoritics and Planetary Science, 2017. V. 53. No. 4. P. 583–637. DOI: 10.1111/maps.12956.
  383. Romero B.E., Clarke K.C. Exploring uncertainties in terrain feature extraction across multi-scale, multi-feature, and multi-method approaches for variable terrain. Cartography and Geographic Information Science, 2018. V. 45. No. 5. P. 381–399. DOI: 10.1080/15230406.2017.1335235.
  384. Rossini M., Di Mauro B., Garzonio R., Baccolo G., Cavallini G., Mattavelli M., De Amicis M., Colombo R. Rapid melting dynamics of an alpine glacier with repeated UAV photogrammetry. Geomorphology, 2018. V. 304. P. 159–172. DOI: 10.1016/j.geomorph.2017.12.039.
  385. Rotnicka J., Dłużewski M., Dąbski M., Rodzewicz M., Włodarski W., Zmarz A. Accuracy of the UAV-based DEM of beach–foredune topography in relation to selected morphometric variables, land cover, and multitemporal sediment budget. Estuaries and Coasts, 2020. V. 43. No. 8. P. 1939–1955. DOI: 10.1007/s12237-020-00752-x.
  386. Roudier P., Malone B.P., Hedley C.B., Minasny B., McBratney A.B. Comparison of regression methods for spatial downscaling of soil organic carbon stocks maps. Computers and Electronics in Agriculture, 2017. V. 142. Pt. A. P. 91–100. DOI: 10.1016/j.compag. 2017.08.021.
  387. Różycka M., Jancewicz K., Migoń P., Szymanowski M. Tectonic versus rock-controlled mountain fronts—geomorphometric and geostatistical approach (Sowie Mts., Central Europe). Geomorphology, 2021. V. 373. # 107485. DOI: 10.1016/j.geomorph.2020.107485.
  388. Runyon K.D., Bridges N.T., Ayoub F., Newman C.E., Quade J.J. An integrated model for dune morphology and sand fluxes on Mars. Earth and Planetary Science Letters, 2017. V. 457. P. 204–212. DOI: 10.1016/J.EPSL.2016.09.054.
  389. Sam L., Bhardwaj A., Kumar R., Buchroithner M.F., Martín-Torres F.J. Heterogeneity in topographic control on velocities of Western Himalayan glaciers. Scientific Reports, 2018. V. 8. # 12843. DOI: 10.1038/s41598-018-31310-y.
  390. Samsonov T., Koshel S., Walther D., Jenny B. Automated placement of supplementary contour lines. International Journal of Geographical Information Science, 2019. V. 33. No. 10. P. 2072–2093. DOI: 10.1080/13658816.2019.1610965.
  391. Sărăşan A., Józsa E., Ardelean A.C., Drăguţ L. Sensitivity of geomorphons to mapping specific landforms from a digital elevation model: a case study of drumlins. Area, 2019. V. 51. No. 2. P. 257–267. DOI: 10.1111/area.12451.
  392. Sarmento E.C., Giasson E., Webster E.J., Flores C.A., Hasenack H. Regional disaggregating conventional soil maps with limited descriptive data: a knowledge-based approach in Serra Gaúcha, Brazil. Geoderma Regional, 2017. V. 8. P. 12–23. DOI: 10.1016/j.geodrs.2016.12.004.
  393. Šašak J., Gallay M., Kaňuk J., Hofierka J., Minár J. Combined use of terrestrial laser scanning and UAV photogrammetry in mapping alpine terrain. Remote Sensing, 2019. V. 11. No. 18. # 2154. DOI: 10.3390/rs11182154.
  394. Scholten T., Goebes P., Kühn P., Seitz S., Assmann T., Bauhus J., Bruelheide H., Buscot F., Erfmeier A., Fischer M., Härdtle W., He J.-S., Ma K., Niklaus P.A., Scherer-Lorenzen M., Schmid B., Shi X., Song Z., von Oheimb G., Wirth C., Wubet T., Schmidt K. On the combined effect of soil fertility and topography on tree growth in subtropical forest ecosystems—a study from SE China. Journal of Plant Ecology, 2017. V. 10. No. 1. P. 111–127. DOI: 10.1093/jpe/rtw065.
  395. Schumann G.J.-P., Bates P.D. The need for a high-accuracy, open-access global DEM. Frontiers in Earth Science, 2018. V. 6. # 225. DOI: 10.3389/feart.2018.00225.
  396. Seier G., Kellerer-Pirklbauer A., Wecht M., Hirschmann S., Kaufmann V., Lieb G.K., Sulzer W. UAS-based change detection of the glacial and proglacial transition zone at pasterze glacier, Austria. Remote Sensing, 2017. V. 9. No. 6. # 549. DOI: 10.3390/rs9060549.
  397. Sevara C., Verhoeven G., Doneus M., Draganits E. Surfaces from the visual past: recovering high-resolution terrain data from historic aerial imagery for multitemporal landscape analysis. Journal of Archaeological Method and Theory, 2018. V. 25. No. 2. P. 611–642. DOI: 10.1007/s10816-017-9348-9.
  398. Shary P.A. Land surface in gravity points classification by a complete system of curvatures. Mathematical Geology, 1995. V. 27. No. 3. P. 373–390. DOI: 10.1007/BF 02084608.
  399. Shary P.A., Sharaya L.S., Mitusov A.V. Fundamental quantitative methods of land surface analysis. Geoderma, 2002. V. 107. No. 1/2. P. 1–32. DOI: 10.1016/S0016-7061(01)00136-7.
  400. Shary P.A., Sharaya L.S., Mitusov A.V. Predictive modeling of slope deposits and comparisons of two small areas in Northern Germany. Geomorphology, 2017. V. 290. P. 222–235. DOI: 10.1016/j.geomorph.2017.04.018.
  401. Shen Q., Wang Y., Wang X., Liu X., Zhang X., Zhang S. Comparing interpolation methods to predict soil total phosphorus in the Mollisol area of Northeast China. Catena, 2019. V. 174. P. 59–72. DOI: 10.1016/j.catena.2018.10.052.
  402. Shi W., Deng S., Xu W. Extraction of multi-scale landslide morphological features based on local Gi* using airborne LiDAR-derived DEM. Geomorphology, 2018. V. 303. P. 229–242. DOI: 10.1016/j.geomorph.2017.12.005.
  403. Shi Y., Katzschner L., Ng E. Modelling the fine-scale spatiotemporal pattern of urban heat island effect using land use regression approach in a megacity. Science of the Total Environment, 2018. V. 618. P. 891–904. DOI: 10.1016/j.scitotenv.2017.08.252.
  404. Shi Y., Lau K.K.-L., Ng E. Incorporating wind availability into land use regression modelling of air quality in mountainous high-density urban environment. Environmental Research, 2017. V. 157. P. 17–29. DOI: 10.1016/j.envres.2017.05.007.
  405. Silva O.L., Bezerra F.H.R., Maia R.P., Cazarin C.L. Karst landforms revealed at various scales using LiDAR and UAV in semi-arid Brazil: consideration on karstification processes and methodological constraints. Geomorphology, 2017. V. 295. P. 611–630. DOI: 10.1016/J.GEOMORPH.2017.07.025.
  406. Silva S.H.G., de Menezes M.D., Owens P.R., Curi N. Retrieving pedologist’s mental model from existing soil map and comparing data mining tools for refining a larger area map under similar environmental conditions in Southeastern Brazil. Geoderma, 2016. V. 267. P. 65–77. DOI: 10.1016/j.geoderma.2015.12.025.
  407. Singh K.K., Frazier A.E. A meta-analysis and review of unmanned aircraft system (UAS) imagery for terrestrial applications. International Journal of Remote Sensing, 2018. V. 39. No. 15/16. P. 5078–5098. DOI: 10.1080/01431161.2017.1420941.
  408. Sîrbu F., Drăguţ L., Oguchi T., Hayakawa Y., Micu M. Scaling land-surface variables for landslide detection. Progress in Earth and Planetary Science, 2019. V. 6. # 44. DOI: 10.1186/s40645-019-0290-1.
  409. Skrypitsyna T.N., Florinsky I.V., Beloborodov D.E., Gaydalenok O.V. Mud volcanism at the Taman peninsula: multiscale analysis of remote sensing and morphometric data. Remote Sensing, 2020. V. 12. No. 22. # 3763. DOI: 10.3390/rs12223763.
  410. Smith M.W., Carrivick J.L., Quincey D.J. Structure from motion photogrammetry in physical geography. Progress in Physical Geography, 2016. V. 40. No. 2. P. 247–275. DOI: 10.1177/0309133315615805.
  411. Sofia G. Combining geomorphometry, feature extraction techniques and earth-surface processes research: the way forward. Geomorphology, 2020. V. 355. # 107055. DOI: 10.1016/j.geomorph.2020.107055.
  412. Song X.-D., Brus D.J., Liu F., Li D.-C., Zhao Y.-G., Yang J.-L., Zhang G.-L. Mapping soil organic carbon content by geographically weighted regression: a case study in the heihe River Basin, China. Geoderma, 2016. V. 261. P. 11–22. DOI: 10.1016/j.geoderma.2015.06.024.
  413. Sowers D.C., Masetti G., Mayer L.A., Johnson P., Gardner J.V., Armstrong A.A. Standardized geomorphic classification of seafloor within the United States Atlantic canyons and continental margin. Frontiers in Marine Science, 2020. V. 7. No. 9. DOI: 10.3389/fmars.2020.00009.
  414. Strobl P. The new Copernicus digital elevation model. GSICS Quarterly, 2020. V. 14. No. 1. P. 17–18. DOI: 10.25923/enp8-6w06.
  415. Stumpf F., Schmidt K., Goebes P., Behrens T., Schönbrodt-Stittc S., Wadouxd A., Wei X., Scholten T. Uncertainty-guided sampling to improve digital soil maps. Catena, 2017. V. 153. P. 30–38. DOI: 10.1016/j.catena.2017.01.033.
  416. Sun X.-L., Wang H.-L., Zhao Y.-G., Zhang C., Zhang G.-L. Digital soil mapping based on wavelet decomposed components of environmental covariates. Geoderma, 2017. V. 303. P. 118–132. DOI: 10.1016/j.geoderma.2017.05.017.
  417. Szymanowski M., Jancewicz K., Różycka M., Migoń P. Geomorphometry-based detection of enhanced erosional signal in polygenetic medium-altitude mountain relief and its tectonic interpretation, the Sudetes (Central Europe). Geomorphology, 2019. V. 341. P. 115–129. DOI: 10.1016/j.geomorph.2019.05.022.
  418. Tabrizian P., Baran P.K., van Berkel D., Mitasova H., Meentemeyer R. Modeling restorative potential of urban environments by coupling viewscape analysis of lidar data with experiments in immersive virtual environments. Landscape and Urban planning, 2020. V. 195. # 103704. DOI: 10.1016/j.landurbplan.2019.103704.
  419. Tadono T., Nagai H., Ishida H., Oda F., Naito S., Minakawa K., Iwamoto H. Generation of the 30 m-mesh global digital surface model by ALOS PRISM. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016. V. 41. Pt. B4. P. 157–162. DOI: 10.5194/isprsarchives-XlI-B4-157-2016.
  420. Tanyas H., Rossi M., Alvioli M., van Westena C.J., Marchesini I. A global slope unit-based method for the near real-time prediction of earthquake-induced landslides. Geomorphology, 2019. V. 327. P. 126–146. DOI: 10.1016/j.geomorph.2018.10.022.
  421. Tapete D., Banks V., Jones L., Kirkham M., Garton D. Contextualising archaeological models with geological, airborne and terrestrial LiDAR data: the Ice Age landscape in Farndon Fields, Nottinghamshire, UK. Journal of Archaeological Science, 2017. V. 81. P. 31–48. DOI: 10.1016/j.jas.2017.03.007.
  422. Tarolli P., Sofia G. Human topographic signatures and derived geomorphic processes across landscapes. Geomorphology, 2016. V. 255. P. 140–161. DOI: 10.1016/j.geomorph.2015.12.007.
  423. Tarolli P., Cao W., Sofia G., Evans D., Ellis E.C. From features to fingerprints: a general diagnostic framework for anthropogenic geomorphology. Progress in Physical geography, 2019. V. 43. No. 1. P. 95–128. DOI: 10.1177/0309133318825284.
  424. Tarolli P., Cavalli M., Masin R. High-resolution morphologic characterization of conservation agriculture. Catena, 2019. V. 172. P. 846–856. DOI: 10.1016/j.catena.2018.08.026.
  425. Tesch P., Reece R.S., Pope M.C., Markello J.R. Quantification of architectural variability and controls in an Upper oligocene to lower Miocene carbonate ramp, Browse Basin, Australia. Marine and Petroleum Geology, 2018. V. 91. P. 432–454. DOI: 10.1016/j.marpetgeo.2018.01.022.
  426. Theodoratos N., Seybold H., Kirchner J.W. Scaling and similarity of a stream-power incision and linear diffusion landscape evolution model. Earth Surface Dynamics, 2018. V. 6. No. 3. P. 79–808. DOI: 10.5194/esurf-6-779-2018.
  427. Thistlewood H.M.A., Gill P., Beers E.H., Shearer P.W., Walsh D.B., Rozema B.M., Acheampong S., Castagnoli S., Yee W.L., Smytheman P., Whitener A.B. Spatial analysis of seasonal dynamics and overwintering of Drosophila suzukii (Diptera: Drosophilidae) in the Okanagan–Columbia Basin, 2010–2014. Environmental Entomology, 2018. V. 47. No. 2. P. 221–232. DOI: 10.1093/ee/nvx178.
  428. Thompson S., Benn D., Mertes J., Luckman A. Stagnation and mass loss on a himalayan debris-covered glacier: processes, patterns and rates. Journal of Glaciology, 2016. V. 62. No. 233. P. 467–485. DOI: 10.1017/jog.2016.37.
  429. Thornton J.M., Mariethoz G., Brunner P. A 3D geological model of a structurally complex Alpine region as a basis for interdisciplinary research. Scientific Data, 2018. V. 5. # 180238. DOI: 10.1038/sdata.2018.238.
  430. Tien Bui D., Shirzadi A., Shahabi H., Chapi K., Omidavr E., Pham B.T., Asl D.T., Khaledian H., Pradhan B., Panahi M., Ahmad B.B., Rahmani H., Gróf G., Lee S. A novel ensemble artificial intelligence approach for gully erosion mapping in a semi-arid watershed (Iran). Sensors, 2019. V. 19. No. 11. # 2444. DOI: 10.3390/s19112444.
  431. Tomczyk A.M., Ewertowski M.W. Surface morphological types and spatial distribution of fan-shaped landforms in the periglacial high-Arctic environment of Central Spitsbergen, Svalbard. Journal of Maps, 2017. V. 13. No. 2. P. 239–251. DOI: 10.1080/17445647.2017.1294543.
  432. Tong R., Purser A., Guinan J., Unnithan V., Yu J., Zhang C. Quantifying relationships between abundances of cold-water coral Lophelia pertusa and terrain features: a case study on the Norwegian margin. Continental Shelf Research, 2016. V. 116. P. 13–26. DOI: 10.1016/j.csr.2016.01.012.
  433. Tonkin T.N., Midgley N.G., Cook S.J., Graham D.J. Ice-cored moraine degradation mapped and quantified using an unmanned aerial vehicle: a case study from a polythermal glacier in Svalbard. Geomorphology, 2016. V. 258. P. 1–10. DOI: 10.1016/j.geomorph.2015.12.019.
  434. Toso C., Madricardo F., Molinaroli E., Fogarin S., Kruss A., Petrizzo A., Pizzeghello N.M., Sinapi L., Trincardi F. Tidal inlet seafloor changes induced by recently built hard structures. PLoS ONE, 2019. V. 14. No. 10. # e0223240. DOI: 10.1371/journal.pone.0223240.
  435. Toth C., Jóźków G. Remote sensing platforms and sensors: a survey. ISPRS Journal of Photogrammetry and Remote Sensing, 2016. V. 115. P. 22–36. DOI: 10.1016/j.isprsjprs.2015.10.004.
  436. Tozer B., Sandwell D.T., Smith W.H.F., Olson C., Beale J.R., Wessel P. Global bathymetry and topography at 15 arc seconds: SRTM15+. Earth and Space Science, 2019. V. 6. No. 10. P. 1847–1864. DOI: 10.1029/2019EA000658.
  437. Trevisani S., Cavalli M. Topography-based flow-directional roughness: potential and challenges. Earth Surface Dynamics, 2016. V. 4. No. 2. P. 343–358. DOI: 10.5194/esurf-4-343-2016.
  438. Vajedian S., Motagh M. Extracting sinkhole features from time-series of TerraSAR-X/TanDEM-X data. ISPRS Journal of Photogrammetry and Remote Sensing, 2019. V. 150. P. 274–284. DOI: 10.1016/j.isprsjprs.2019.02.016.
  439. Valentine A.P., Kalnins L.M. An introduction to learning algorithms and potential applications in geomorphometry and Earth surface dynamics. Earth Surface Dynamics, 2016. V. 4. P. 445–460. DOI: 10.5194/esurf-4-445-2016.
  440. Valeriano M.M., Rossetti D.F. Regionalization of local geomorphometric derivations for geological mapping in the sedimentary domain of central Amazônia. Computers and Geosciences, 2017. V. 100. P. 46–56. DOI: 10.1016/j.cageo.2016.12.002.
  441. Van der Sluijs J., Kokelj S.V., Fraser R.H., Tunnicliffe J., Lacelle D. Permafrost terrain dynamics and infrastructure impacts revealed by UAV photogrammetry and thermal imaging. Remote Sensing, 2018. V. 10. No. 11. # 1734. DOI: 10.3390/rs10111734.
  442. Van Nieuwenhuizen N., Lindsay J.B., DeVries B. Automated mapping of transportation embankments in fine-resolution LiDAR DEMs. Remote Sensing, 2021. V. 13. No. 7. # 1308. DOI: 10.3390/rs13071308.
  443. Vassilaki D.I., Stamos A.A. TanDEM-X DEM: comparative performance review employing LIDAR data and DSMs. ISPRS Journal of Photogrammetry and Remote Sensing, 2020. V. 160. P. 33–50. DOI: 10.1016/j.isprsjprs.2019.11.015.
  444. Vaz D.A., Silvestro S., Sarmento P.T.K., Cardinale M. Migrating meter-scale bedforms on Martian dark dunes: are terrestrial aeolian ripples good analogs? Aeolian Research, 2017. V. 26. P. 101–116. DOI: 10.1016/j.aeolia.2016.08.003.
  445. Veitinger J., Purves R.S., Sovilla B. Potential slab avalanche release area identification from estimated winter terrain: a multi-scale, fuzzy logic approach. Natural Hazards and Earth System Sciences, 2016. V. 16. No. 10. P. 2211–2225. DOI: 10.5194/nhess-16-2211-2016.
  446. Vermeulen D., van Niekerk A. Machine learning performance for predicting soil salinity using different combinations of geomorphometric covariates. Geoderma, 2017. V. 299. P. 1–12. DOI: 10.1016/j.geoderma.2017.03.013.
  447. Villaça C.V.N., Crósta A.P., Grohmann C.H. Morphometric analysis of Pluto’s impact craters. Remote Sensing, 2021. V. 13. No. 3. # 377. DOI: 10.3390/rs13030377.
  448. Viloria J.A., Viloria-Botello A., Pineda M.C., Valera A. Digital modelling of landscape and soil in a mountainous region: a neuro-fuzzy approach. Geomorphology, 2016. V. 253. P. 199–207. DOI: 10.1016/J.GEOMORPH.2015.10.007.
  449. Wagnon P., Shea J.M., Immerzeel W.W., Kraaijenbrink P., Shrestha D., Soruco A., Arnaud Y., Brun F., Berthier E., Sherpa S.F. Reduced melt on debris-covered glaciers: investigations from Changri Nup Glacier, Nepal. Cryosphere, 2016. V. 10. No. 4. P. 1845–1858. DOI: 10.5194/tc-10-1845-2016.
  450. Vincent S., Lemercier B., Berthier L., Walter C. Spatial disaggregation of complex soil map units at the regional scale based on soil-landscape relationships. Geoderma, 2018. V. 311. P. 130–142. DOI: 10.1016/j.geoderma.2016.06.006.
  451. Waagen J. New technology and archaeological practice. Improving the primary archaeological recording process in excavation by means of UAS photogrammetry. Journal of Archaeological Science, 2019. V. 101. P. 11–20. DOI: 10.1016/j.jas.2018.10.011.
  452. Wadoux A.M.J.-C. Using deep learning for multivariate mapping of soil with quantified uncertainty. Geoderma, 2019. V. 351. P. 59–70. DOI: 10.1016/j.geoderma.2019.05.012.
  453. Wadoux A.M.J.-C., Brus D.J., Heuvelink G.B.M. Accounting for non-stationary variance in geostatistical mapping of soil properties. Geoderma, 2018. V. 324. P. 138–147. DOI: 10.1016/j.geoderma.2018.03.010.
  454. Wadoux A.M.J.-C., Padarian J., Minasny B. Multi-source data integration for soil mapping using deep learning. Soil, 2019. V. 5. No. 1. P. 107–119. DOI: 10.5194/soil-5-107-2019.
  455. Walker S.J., Wilkinson S.N., van Dijk A.I.J.M., Hairsine P.B. A multi-resolution method to map and identify locations of future gully and channel incision. Geomorphology, 2020. V. 358. # 107115. DOI: 10.1016/j.geomorph.2020.107115.
  456. Wang J., Cheng W., Zhou C., Zheng X. Automatic mapping of lunar landforms using DEM-derived geomorphometric parameters. Journal of Geographical Sciences, 2017. V. 27. No. 11. P. 1413–1427. DOI: 10.1007/s11442-017-1443-z.
  457. Wang J., Kreslavsky M.A., Liu J., Head J.W., Zhang K., Kolenkina M.M., Zhang L. Quantitative characterization of impact crater materials on the Moon: changes in topographic roughness and thermophysical properties with age. Journal of Geophysical Research: Planets, 2020. V. 125. No. 10. # e2019JE006091. DOI: 10.1029/2019JE006091.
  458. Wang S., Hu Q., Wang F., Ai M., Zhong R. A microtopographic feature analysis-based LiDAR data processing approach for the identification of Chu tombs. Remote Sensing, 2017. V. 9. No. 9. # 880. DOI: 10.3390/rs9090880.
  459. Watson C.S., Quincey D.J., Smith M., Carrivick J., Rowan A.V., James M. Quantifying ice cliff evolution with multi-temporal point clouds on the debris-covered Khumbu glacier, Nepal. Journal of Glaciology, 2017. V. 63. No. 241. P. 823–837. DOI: 10.1017/jog.2017.47.
  460. Wei H., Zhou G., Fu S. Efficient priority-Flood depression filling in raster digital elevation models. International Journal of Digital Earth, 2018. V. 12. No. 4. P. 415–427. DOI: 10.1080/17538947.2018.1429503.
  461. Westoby M.J., Dunning S.A., Woodward J., Hein A.S., Marrero S.M., Winter K., Sugden D.E. Interannual surface evolution of an Antarctic blue-ice moraine using multi-temporal DEMs. Earth Surface Dynamics, 2016. V. 4. No. 2. P. 515–529. DOI: 10.5194/esurf-4-515-2016.
  462. Wiekenkamp I., Huisman J.A., Bogena H.R., Lin H.S., Vereecken H. Spatial and temporal occurrence of preferential flow in a forested headwater catchment. Journal of Hydrology, 2016. V. 534. P. 139–149. DOI: 10.1016/j.jhydrol.2015.12.050.
  463. Wigmore O., Mark B. Monitoring tropical debris-covered glacier dynamics from high-resolution unmanned aerial vehicle photogrammetry, Cordillera Blanca, Peru. Cryosphere, 2017. V. 11. No. 6. P. 2463–2480. DOI: 10.5194/tc-11-2463-2017.
  464. Wilson J.P. Digital terrain modeling. Geomorphology, 2012. V. 137. No. 1. P. 107–121. DOI: j.geomorph.2011.03.012.
  465. Wilson J.P. Environmental Applications of Digital Terrain Modeling. Chichester: Wiley-Blackwell, 2018. 360 p.
  466. Wilson J.P., Gallant J.C. (eds.) Terrain Analysis: principles and Applications. New York: Wiley, 2000. 479 p.
  467. Wing O.E.J., Bates P.D., Neal J.C., Sampson C.C., Smith A.M., Quinn N., Shustikova I., Domeneghetti A., Gilles D.W., Goska R., Krajewski W.F. A new automated method for improved flood defense representation in large-scale hydraulic models. Water Resources Research, 2019. V. 55. P. 11007–11034. DOI: 2019WR025957.
  468. Wölfl A.-C., Snaith H., Amirebrahimi S., Devey C.W., Dorschel B., Ferrini V., Huvenne V.A.I., Jakobsson M., Jencks J., Johnston G., Lamarche G., Mayer L., Millar D., Pedersen T.H., Picard K., Reitz A., Schmitt T., Visbeck M., Weatherall P., Wigley R. Seafloor mapping—the challenge of a truly global ocean bathymetry. Frontiers in Marine Science, 2019. V. 6. # 283. DOI: 10.3389/fmars.2019.00283.
  469. Woodrow K., Lindsay J.B., Berg A.A. Evaluating DEM conditioning techniques, elevation source data, and grid resolution for field-scale hydrological parameter extraction. Journal of Hydrology, 2016. V. 540. P. 1022–1029. DOI: 10.1016/j.jhydrol.2016.07.018.
  470. Wu Q., Chen Y., Wilson J.P., Liu X., Li H. An effective parallelization algorithm for DEM generalization based on CUDA. Environmental Modelling and Software, 2019. V. 114. P. 64–74. DOI: 10.1016/j.envsoft.2019.01.002.
  471. Wu Q., Deng C., Chen Z. Automated delineation of karst sinkholes from LiDAR-derived digital elevation models. Geomorphology, 2016. V. 266. P. 1–10. DOI: 10.1016/j.geomorph.2016.05.006.
  472. Xiang J., Li S., Xiao K., Chen J., Sofia G., Tarolli P. Quantitative analysis of anthropogenic morphologies based on multitemporal high-resolution topography. Remote Sensing, 2019. V. 11. No. 12. # 1493. DOI: 10.3390/rs11121493.
  473. Xiang T.-Z., Xia G.-S., Zhang L. Mini-unmanned aerial vehicle-based remote sensing: techniques, applications, and prospects. IEEE Geoscience and Remote Sensing Magazine, 2019. V. 7. No. 3. P. 29–63. DOI: 0.1109/MGRS.2019.2918840.
  474. Xiong L.-Y., Jiang R.-Q., Lu Q.-H., Yang B.-S., Li F.-Y., Tang G.-A. Improved priority-Flood method for depression filling by redundant calculation optimization in local microrelief areas. Transactions in GIS, 2019. V. 23. No. 2. P. 259–274. DOI: 10.1111/tgis.12516.
  475. Xiong L.-Y., Tang G.-A., Strobl J., Zhu A-X. Paleotopographic controls on loess deposition in the loess plateau of China. Earth Surface Processes and Landforms, 2016. V. 41. No. 9. P. 1155–1168. DOI: 10.1002/esp.3883.
  476. Xiong L.-Y., Tang G.-A., Zhu A.-X., Qian Y.-Q. A peak-cluster assessment method for the identification of upland planation surfaces. International Journal of Geographical Information Science, 2017. V. 31. No. 2. P. 387–404. DOI: 10.1080/13658816.2016.1205193.
  477. Xu H., van der Steeg S., Sullivan J., Shelley D., Cely J.E., Viparelli E., Lakshmi V., Torres R. Intermittent channel systems of a low-relief, low-gradient floodplain: comparison of automatic extraction methods. Water Resources Research, 2020. V. 56. No. 9. # e2020WR027603. DOI: 10.1029/2020WR027603.
  478. Xue Y., Jing Z., Kang S., He X., Li C. Combining UAV and landsat data to assess glacier changes on the central Tibetan plateau. Journal of Glaciology, 2021. V. 67. DOI: 10.1017/jog.2021.37.
  479. Yamafune K., Torres R., Castro F. Multi-image photogrammetry to record and reconstruct underwater shipwreck sites. Journal of Archaeological Method and Theory, 2017. V. 24. No. 3. P. 703–725. DOI: 10.1007/s10816-016-9283-1.
  480. Yamazaki D., Ikeshima D., Tawatari R., Yamaguchi T., O’Loughlin F., Neal J.C., Sampson C.C., Kanae S., Bates P.D. A high-accuracy map of global terrain elevations. Geophysical Research Letters, 2017. V. 44. No. 11. P. 5844–5853. DOI: 10.1002/2017GL072874.
  481. Yang X., Tang G., Meng X., Xiong L. Classification of karst Fenglin and Fengcong landform units based on spatial relations of terrain feature points from DEMs. Remote Sensing, 2019. V. 11, 16. # 1950. DOI: 10.3390/rs11161950.
  482. Yao H., Qin R., Chen X. Unmanned aerial vehicle for remote sensing applications—a review. Remote Sensing, 2019. V. 11. No. 12. # 1443. DOI: 10.3390/rs11121443.
  483. Yeomans C.M., Middleton M., Shail R.K., Grebby S., Lusty P.A.J. Integrated object-based image analysis for semi-automated geological lineament detection in southwest England. Computers and Geosciences, 2019. V. 123. P. 137–148. DOI: 10.1016/j.cageo.2018.11.005.
  484. Yue L., Shen H., Zhang L., Zheng X., Zhang F., Yuan Q. High-quality seamless DEM generation blending SRTM-1, ASTER GDEM v2 and ICESat/GLAS observations. ISPRS Journal of Photogrammetry and Remote Sensing, 2017. V. 123. P. 20–34. DOI: 10.1016/j.isprsjprs.2016.11.002.
  485. Zabihi M., Mirchooli F., Motevalli A., Darvishan A.K., Pourghasemi H.R., Zakeri M.A., Sadighi F. Spatial modelling of gully erosion in Mazandaran province, northern Iran. Catena, 2018. V. 161. P. 1–13. DOI: 10.1016/j.catena.2017.10.010.
  486. Žabota B., Repe B., Kobal M. Influence of digital elevation model resolution on rockfall modelling. Geomorphology, 2019. V. 328. P. 183–195. DOI: 10.1016/j.geomorph.2018.12.029.
  487. Zhai R., Lu K., Pan W., Dai S. GPU-based real-time terrain rendering: design and implementation. Neurocomputing, 2016. V. 171. P. 1–8. DOI: 10.1016/j.neucom.2014.08.108.
  488. Zhang F., Zhou Q., Li Q., Wu G., Liu J. An enhanced approach for surface flow routing over drainage-constrained triangulated irregular networks. Transactions in GIS, 2018. V. 22. No. 1. P. 43–57. DOI: 10.1111/tgis.12294.
  489. Zhang H., Yao Z., Yang Q., Li S., Baartman J.E.M., Gai L., Yao M., Yang X., Ritsema C.J., Geissen V. An integrated algorithm to evaluate flow direction and flow accumulation in flat regions of hydrologically corrected DEMs. Catena, 2017. V. 151. P. 174–181. DOI: 10.1016/j.catena.2016.12.009.
  490. Zhang H., Zhang P., Prush V., Zheng D., Zheng W., Wang W., Liu C., Ren Z. Tectonic geomorphology of the Qilian Shan in the northeastern Tibetan plateau: insights into the plateau formation processes. Tectonophysics, 2017. V. 706–707. P. 103–115. DOI: 10.1016/j.tecto.2017.04.016.
  491. Zhang L., Zhang L., Du B. Deep learning for remote sensing data: a technical tutorial on the state of the art. IEEE geoscience and Remote Sensing Magazine, 2016. V. 4. No. 2. P. 22–40. DOI: 10.1109/MgRS.2016.2540798.
  492. Zhang S., Foerster S., Medeiros P., Araújo J.C., Motagh M., Waske B. Bathymetric survey of water reservoirs in north-eastern Brazil based on TanDEM-X satellite data. Science of the Total Environment, 2016. V. 571. P. 575–593. DOI: 10.1016/j.scitotenv.2016.07.024.
  493. Zhao D., Wu Z., Zhou J., Zhang K., Luo X., Wang M., Liu Y., Zhu C. From 10 m to 11000 m, automatic processing multi-beam bathymetric data based on pgo method. IEEE Access, 2021. V. 9. P. 14516–14527. DOI: 10.1109/ACCESS.2021.3051909.
  494. Zhong C., Liu Y., Gao P., Chen W., Li H., Hou Y., Nuremanguli T., Ma H. Landslide mapping with remote sensing: challenges and opportunities. International Journal of Remote Sensing, 2020. V. 41. No. 4. P. 1555–1581. DOI: 10.1080/01431161.2019.1672904.
  495. Zhou G., Liu X., Fu S., Sun Z. Parallel identification and filling of depressions in raster digital elevation models. International Journal of Geographical Information Science, 2017. V. 31. No. 6. P. 1061–1078. DOI: 10.1080/13658816.2016.1262954.
  496. Zhou G., Sun Z., Fu S. An efficient variant of the priority-Flood algorithm for filling depressions in raster digital elevation models. Computers and Geosciences, 2016. V. 90. Pt. A. P. 87–96. DOI: 10.1016/j.cageo.2016.02.021.
  497. Zhou X., Li W., Arundel S.T. A spatio-contextual probabilistic model for extracting linear features in hilly terrains from high-resolution DEM data. International Journal of Geographical Information Science, 2019. V. 33. No. 4. P. 666–686. DOI: 10.1080/13658816.2018.1554814.
  498. Zhou Y., Li Z., Li J. Slight glacier mass loss in the Karakoram region during the 1970s to 2000 revealed by Kh-9 images and SRTM DEM. Journal of Glaciology, 2017. V. 63. # 238. P. 331–342. DOI: 10.1017/jog.2016.142.
  499. Zumpano V., Pisano L., Parise M. An integrated framework to identify and analyze karst sinkholes. Geomorphology, 2019. V. 332. P. 213–225. DOI: 10.1016/j.geomorph.2019.02.013.
  500. Zwolak K., Wigley R., Bohan A., Zarayskaya Y., Bazhenova E., Dorshow W., Sumiyoshi M., Sattiabaruth S., Roperez J., Procto A., Wallace C., Sade H., Ketter T., Simpson B., Tinmouth N., Falconer R., Ryzhov I., Abou-Mahmoud M.E. The autonomous underwater vehicle integrated with the unmanned surface vessel mapping the Southern Ionian Sea. The winning technology solution of the Shell ocean Discovery XPRIZE. Remote Sensing, 2020. V. 12. No. 8. # 1344. DOI: 10.3390/rs12081344.

Для цитирования: Флоринский И.В. Геоморфометрия сегодня ИнтерКарто. ИнтерГИС. Геоинформационное обеспечение устойчивого развития территорий: Материалы Междунар. конф. M: Географический факультет МГУ, 2021. Т. 27. Ч. 2. С. 394–448. DOI: 10.35595/2414-9179-2021-2-27-394-448

For citation: Florinsky I.V. Geomorphometry today InterCarto. InterGIS. GI support of sustainable development of territories: Proceedings of the International conference. Moscow: MSU, Faculty of Geography, 2021. V. 27. Part 2. P. 394–448. DOI: 10.35595/2414-9179-2021-2-27-394-448 (In Russian)