APPROACHES TO THE DETERMINATION OF TAXATION INDICATORS OF FORESTS USING AEROSPACE IMAGES AND LIDAR DATA

http://doi.org/10.24057/2414-9179-2018-2-24-216-240

View or download the article (Rus)

About the Author

Ilya A. Rylskiy

Lomonosov Moscow State University, Faculty of Geography,
Leninskie Gory, 1, 119991, Moscow, Russia,
E-mail: rilskiy@mail.ru

Abstract

The article is dedicated to overview the approaches for solving basic problems of defining taxation parameters and forest inventorying using remote sensing methods without massive terrestrial surveying. Authors suggest using remote sensing data (high resolution space images), digital multispectral airborne data, LIDAR data (using manned vehicles) in a combination that allows to avoid weak point of each method.

Satellite images were used for depiction of forest type and taxation classes of trees. Satellite image processing (orthorectification) has been implemented using airborne data: the LIDAR data has been used to produce DEM for orthocorrection, aerial images with measured center coordinates and orientation angles were used for collection of ground control points for georeferencing.

Terrestrial researches described in the article include physical measurements of trees (as etalons values) and their parameters made on very small areas. These measurements are used as control values when proving results of remote sensing data processing, or for defining equations between parameters that can be measured using remote sensing data (tree height, diameter of canopy) and parameters that can not (log diameter, biomass, etc.). Basic and specific data processing technologies are briefly described, some practical recommendations are included. Based upon vast area of surveying and data processing, authors prove the ability to solve basic taxation problems and tasks using less efforts with better precision and higher speed.

Keywords

Remote sensing, forest inventory, forest monitoring, LIDAR, airborne laser scanning, digital aerial imagery, space images, image processing, GIS, geoinformatics.

References

  1. Chen Q. Airborne lidar data processing and information extraction. Photogrammetric Engineering & Remote Sensing. 2007. V. 73, No 2. P. 109–112.
  2. Danilin I.M., Favorskaya M.N. Using LIDAR for modelling forest structure and DEM. Lesnaya taksacia I lesoustroystvo. 2011. No 1–2. P. 40–47 (in Russian).
  3. Dvoriashin M.V., Skudin V.M., Korez M.A. Aerospace methods of monitoring for forested areas. Krasnoyarsk: Litera-Print, 2011. 152 p. (in Russian).
  4. Holmgren A., Persson  . Identifying species of individual trees using airborne laser scanner. Remote Sensing of Environment. 2004. V. 90, No 4. P. 415–423.
  5. Kaplunov V.Y. Contingency of tree distribution by log and canopy diameters. Lesovedenie. 2001. No 3. P. 63–69 (in Russian).
  6. Kapralov E.G., Koshkarev A.V., Tikunov V.S. Osnovy geoinformatiki. М.: Akademia, 2004. 480 p. (in Russian).
  7. Korpela I. Mapping of understory lichens with airborne discrete-return LiDAR data. Remote Sensing of Environment. 2008. V. 112, No 10. P. 3891–3897.
  8. Malevannaya M.S., Rylskiy I.A. Terrestrial laser scanning methods – new approaches to information provision of geographic researches. Geodezia I cartographia. М., 2014. V. 5, No 4. P. 23–34 (in Russian).
  9. Medvedev E.M., Danilin I.M., Melnikov S.R. Laser scanning of land and forests. M.: Geokosmos, 2007. 229 p. (in Russian).
  10. Rylskiy I.A. Laser scanning and satellite imagery—competition or partnership. Geomatika. М., 2016. No 1. P. 15–18 (in Russian).
  11. Soille P. Morphological Image Analysis: Principles and Applications. 2nd edition, SpringerVerlag, Berlin, Germany, 2003.
  12. Sukhih V.I. Aerospace methods in forest industry and landscape installation. Yoshkar-Ola: Izdatelstvo MarGTU, 2005. 392 p. (in Russian).
  13. Tikunov V.S., Kapralov E.G., Kravtzova V.I., Lurie I.K., Iliasov A.K., Rylskiy I.A. Informatics in geography, ecology and environmental management. М.: Akademia, 2013. 572 p. (in Russian).
  14. Tikunov V.S., Rylskiy I.A. Perspectives of using airborne laser scanning systems for forest mapping. Izvestia Irkutskogo gosudarstvennogo universiteta. Seria Nauki o zemle. 2016. V. 15, No 2073–3402. P. 104–113 (in Russian).
  15. Varygin K.A., Danilin I.M., Rylskiy I.A. Inventarization and forest monitoring using LIDAR, aerospace imagery and global navigation systems. Materialy 3 Mejdunarodnoy prakticheskoy conferencii po lesoustroystvu. Novosibirsk, 2012. P. 56 (in Russian).

For citation: Rylskiy I.A. APPROACHES TO THE DETERMINATION OF TAXATION INDICATORS OF FORESTS USING AEROSPACE IMAGES AND LIDAR DATA Proceedings of the International conference “InterCarto. InterGIS”. 2018;24(2):216–240 http://doi.org/10.24057/2414-9179-2018-2-24-216-240