@misc{10481/70379,
year = {2021},
url = {http://hdl.handle.net/10481/70379},
abstract = {Monitoring the structure parameters and damage to trees plays an important role in forest
management. Remote-sensing data collected by an unmanned aerial vehicle (UAV) provides valuable
resources to improve the efficiency of decision making. In this work, we propose an approach to
enhance algorithms for species classification and assessment of the vital status of forest stands by
using automated individual tree crowns delineation (ITCD). The approach can be potentially used for
inventory and identifying the health status of trees in regional-scale forest areas. The proposed ITCD
algorithm goes through three stages: preprocessing (contrast enhancement), crown segmentation
based on wavelet transformation and morphological operations, and boundaries detection. The performance of the ITCD algorithm was demonstrated for different test plots containing homogeneous
and complex structured forest stands. For typical scenes, the crown contouring accuracy is about
95%. The pixel-by-pixel classification is based on the ensemble supervised classification method
error correcting output codes with the Gaussian kernel support vector machine chosen as a binary
learner. We demonstrated that pixel-by-pixel species classification of multi-spectral images can be
performed with a total error of about 1%, which is significantly less than by processing RGB images.
The advantage of the proposed approach lies in the combined processing of multispectral and RGB
photo images.},
organization = {National Science Program “Environmental
Protection and Reduction of Risks of Adverse Events and Natural Disasters”, approved by the
Resolution of the Council of Ministers № 577/17.08.2018 and supported by the Ministry of Education
and Science (MES) of Bulgaria (Agreement № D01-363/17.12.2020)},
organization = {Russian Foundation for
Basic Research (RFBR) with projects no. 19-01-00215 and no. 20-07-00370},
organization = {Moscow Center for
Fundamental and Applied Mathematics (Agreement 075-15-2019-1624 with the Ministry of Education
and Science of the Russian Federation; MESRF)},
publisher = {MDPI},
keywords = {Remote sensing},
keywords = {Pattern recognition},
keywords = {Unmanned aerial vehicle},
keywords = {Aerial photo and multispectral images},
keywords = {Individual tree crowns delineation},
keywords = {Species classification},
keywords = {Vital status assessment},
title = {Individual Tree Crown Delineation for the Species Classification and Assessment of Vital Status of Forest Stands from UAV Images},
doi = {10.3390/drones5030077},
author = {Safonova, Anastasiia},
}