Open AccessForest change detection based on sub-pixel tree cover estimates using Landsat-OLI and Sentinel 2 data
Author(s) -
T.S. Khovratovich,
С.А. Барталев,
А.В. Кашницкий,
И.В. Balashov,
Aleksandra Ivanova
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/507/1/012011
Subject(s) - remote sensing , logging , change detection , satellite , pixel , forest cover , environmental science , tree (set theory) , satellite imagery , computer science , forestry , geography , mathematics , artificial intelligence , engineering , ecology , mathematical analysis , biology , aerospace engineering
The paper presents a method of forest change detection and its application for clear-cutting and selective logging disturbances assessment. Based on optical remote sensing data it uses of satellite images and sub-pixel estimation of tree cover, performed by using linear spectral mixture model for estimation of forest area portion in each pixel. The paper describes the main steps of the change detection method and the influence of algorithm input settings on the results. The method was implemented as a satellite data processing tool and was tested on selected sites in Primorsky Krai and the Republic of Udmurtia regions. Forest change maps related to logging in year 2016 were developed over the test areas using the Landsat 8 and Sentinel-2 satellite data. The paper compares obtained change areas with official logging statistics and Global Forest Change project data in order to evaluate the method performance for clear-cutting and selective logging area detection.