REMOTE SENSING TOOLS FOR ANALYSIS OF VEGETATION CONDITION IN EXTENSIVELY USED AGRICULTURAL AREAS A. Jarocinska, B. Zagajewski Dept. of Geoinformatics and Remote Sensing, Faculty of Geography and Regional Studies, University of Warsaw, Krakowskie Przedmiescie 30, 00-927 Warszawa, Poland – a.jarocinska@student.uw.edu.pl, bogdan@uw.edu.pl KEY WORDS: Hyperspectral imagery, DAIS 7915, fAPAR, LAI, SAVI, NDVI, plant condition, mountains ABSTRACT: Remote sensing tools can be used to vegetation monitoring. It is possible to analyze plant physiology and biometrical properties using electromagnetic spectrum. In this study was developed the method of plant monitoring using vegetation indices. The test area is the Bystrzanka catchment in the Polish Low Beskid Mountains. This terrain is specified as natural and seminatural environment. Two kinds of data were used: vegetation indices (NDVI, SAVI, LAI and fAPAR) derived from ground measurements and calculated from hyperspectral DAIS 7915 images. Algorithm consists of few stages:  Collecting field data (NDVI, SAVI, LAI and fAPAR)  Creating images of vegetation indices (SAVI, LAI and fAPAR) from hyperspectral images using ATCOR software and NDVI basing on ENVI environment  Creating database with values of vegetation indices from images and ground measurements  Statistical analysis  Transformation of images to create maps of spatial distribution of vegetation indices  NDVI, SAVI, LAI and fAPAR maps validation  Creating map of plant condition using values of SAVI, LAI and fAPAR Some result can be outlined. Firstly, the remote sensing techniques allow analyzing spatial condition of plants. Secondly, different vegetation indices can be used for automated and objective plant monitoring, they can measure plant condition, quantity of biomass and pigments. Apart from that, high values of four analyzed vegetation indices showed good condition of plants of the Bystrzanka catchment. High values of NDVI indicated high chlorophyll content, and good plant condition. Values of LAI and SAVI showed that almost all of the area is covered by plants, but the canopy was not dense. Very high values of fAPAR meant that most of the visible light was used to product biomass and plants were in very good condition. INTRODUCTION Remote sensing data can be used for vegetation monitoring. It is possible to analyze biometrical properties of plants in different wavelengths of electromagnetic spectrum. It can be also used to modelling and simulation of biophysical processes. Hyperspectral data can be applied to the interpretation of vegetation, land cover and forecast of biomass crops and also for analyzing plant condition.