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About the Author

Ilya A. Rylskiy

Lomonosov Moscow State University, Faculty of Geography,
Leninskie Gory, 1, 119991, Moscow, Russia,


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.


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


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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