An approach for assessing boreal forest conditions based on combined use of satellite SAR and multi-spectral data

Abstract

The degree and spatial distribution of boreal forest ecosystem degradation in Russia are not well known. The objective of this study is to develop an interpretation basis for analysis of satellite remote sensing data using a set of indicators characterizing the ecological situation and the degree of industrial pollution. European Remote Sensing Satellite (ERS) Synthetic Aperture Radar (SAR) and Landsat Multi-Spectral Scanner (MSS) data are used in combination for this purpose, along with an exceptionally extensive in situ data set of ground measurements of spectral radiance of pine biocenose components, and the results of moss chemistry and bio-indicator studies from the ecologically stressed St Petersburg region. It is shown that ERS SAR images provide an assessment of forested area distribution and forest type classification. The main factors of variability in parameters such as Normalized Difference Vegetation Index (NDVI) that are most strongly related to in situ indicators reflecting the state of the forest are identified. A supervised classification of forest degradation was performed on the basis of the NDVI values from the Landsat images. The results obtained make it possible to specify the areas at a local level and perform regional assessments. The potential for multi-temporal ERS SAR and multi-spectral sensor observations to trace the dynamics of changes in forest ecosystems is evaluated.