EVALUATION OF MEDIUM-RESOLUTION SATELLITE IMAGES FOR LAND USE MONITORING USING SPECTRAL MIXTURE ANALYSIS

摘要

Keeping up-to-date land cover information and tracking changes are important tasks carried out by various national and international agencies and institutions. Satellite images are an attractive data source for these purposes as they cover large areas and are recorded on a regular basis. Continuos updating of complete data bases using high resolution data is usually prohibitively expensive, especially when done on a continental or even only national level. This paper examines the use of medium spatial resolution satellite data for basic monitoring purposes. NOAA-AVHRR, SPOT Vegetation and Resource-01 MSU-SK images, covering parts of the Netherlands, are transformed using a linear unmixing algorithm in order to derive proportions of spectrally defined land cover types. The results are compared with an existing land use data base (LGN-3) in order to evaluate how suitable the different sensors are for unmixing purposes.