Analysis of MODIS imagery for detection of clear cuts in the boreal forest in north-west Russia

Abstract

This study examines the feasibility of using MODIS images (MOD02 products) for the detection and monitoring of forest clear cuts in the boreal forest in north-west Russia. The proposed approach combines three change detection methods, including Change Vector Analysis, Textural Analysis using the coefficient of variation, and Constrained Energy Minimization analysis. For each individual method a series of thresholds was tested in order to obtain an optimal identification of clear cuts. A clear cut detection was only accepted if the change was detected by each individual method. All input parameters needed were derived from a set of reference clear cuts, mapped from 30 m resolution Landsat ETM+ imagery and used also for accuracy assessment. Change assessment was tested with MODIS images of two and of three acquisition dates. Referring to two test sites (Karelia, Komi) the detection omission and commission errors, assessed within a 3×3 pixels moving kernel, were at 23% and 8%, and at 21% and 17%, respectively. In terms of detectable clear cut size, a detection accuracy of about 90% can be expected for clear cuts in the size category above 15 ha, which contains the majority of cuts in the region. MODIS therefore provides good capabilities for large scale monitoring of major clear cut activities in the boreal forests of north-western Russia.