NOAA-AVHRR NDVI DECOMPOSITION AND SUBPIXEL CLASSIFICATION USING LINEAR MIXING IN THE ARGENTINEAN PAMPA

Crop Normalized Difference Vegetation Index (NDVI) time profiles and c rop acreage estimates were derived from the application of linear mixt ure modelling to Advanced Very High Resolution Radiometer (AVHRR) data over a test area in the southern part of the Pampa region, Argentina. Bands 1 and 2 from seven AVHRR scenes (June to January 1991) were com bined to produce fraction images of winter crops, summer crops and pas tures. A Landsat Thematic Mapper (TM) scene of the region was classifi ed and superimposed to the AVHRR Local Area Coverage (LAG) data by mea ns of a correlation technique. Each class signature was extracted by r egressing the AVHRR response on the cover types proportions, estimated from Landsat-TM data, over sets of calibration windows. The crop NDVI profiles were hence derived from the class signatures in bands 1 and 2. These profiles appeared consistent with the cover types, but variab ility depending on the set of windows was noted. The assessment of the class signatures was indirectly accomplished through the subpixel cla ssifications of the AVHRR data, performed using the different sets of class spectra. Although some discrepancies between AVHRR and Landsat-T M estimates were observed at the individual window level, the classifi cation results compared quite well on a regional scale with Landsat-TM estimates: crop acreage was estimated to an overall accuracy ranging from 89 to 95 per cent according to the spectra used in the classifica tion. Definitely, the proposed methodology should permit a better expl oitation of the temporal resolution of AVHRR data in both the areas of yield prediction and vegetation classification. Furthermore, the oper ational application of such a methodology for crop monitoring will und oubtedly be facilitated with the coming sensor systems such as the Mod erate-Resolution Imaging Spectroradiometer (MODIS), the SPOT Vegetatio n Monitoring Instrument or the 'Satelite Argentino Cientifico' (SAC-C) .