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Determining the area occupied by a crop is a prerequisite for estimating agricultural production in a region, and such information at present can be generated from satellite remote sensing systems. This study uses multitemporal NDVI images of SPOT-VEGETATION with a 1 km spatial resolution to estimate the wheat area in Cordoba Province, Argentina, and to assess 2 generic digital classification procedures based on crop phenological behavior. The Characteristic Phenology Behavior Method (CPBM) uses the contrast each year between typical values of NDVI variation in the wheat crop season and those of the area not occupied by active vegetation; while the other procedure, the Reference Curve Method (RCM), assesses the correspondence in each pixel between the observed sequence of NDVI from seeding to physiological maturity, compared with 4 curves of reference. The CPBM 2 procedure, which uses the amplitude of NDVI between sowing and heading (ampsh), produces estimates that correlate better with the observed record, with approximately 70% (P s the state reports at about 5%. On the other hand, RCM using Curve 1 explains 50% (P sh in the model with the minimum NDVI during physiological maturity stage (minpm) produced a deterioration of estimation, with R2 reduced to 0.37 (P 2 of 0.61 (P ed the linear relationship between observed and estimated with a slope that did not approach 1. RCM classification models reach a predictive performance similar to that shown in Rio Segundo, with R2 values close to 0.50 (P

Estimation of Wheat Area in C&#243;rdoba, Argentina, with Multitemporal NDVI Data of SPOT-Vegetation

Estimation of Wheat Area in Córdoba, Argentina, with Multitemporal NDVI Data of SPOT-Vegetation