Abstract
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
Highlights
In a large part of Córdoba Province, dryland wheat production is marginal, characterized by low average yields and high harvesting uncertainty [1]
Characteristic Phenology Behavior Method (CPBM) Following a decision tree approach, this procedure considers that wheat can be identified by exploiting the contrast between typical values of Normalized Difference Vegetation Index (NDVI) variation throughout the cycle with respect to the area not occupied by active vegetation
The planting area that the state office obtains by system surveys and field survey information, and the determinations of each computational procedure, were both expressed relative to the departmental area, so that the difference or residue between the two is a measure of the error
Summary
In a large part of Córdoba Province, dryland wheat production is marginal, characterized by low average yields and high harvesting uncertainty [1]. While wheat production faces poor agroclimatic conditions in Cordoba, because of lack of water availability and frost damage [2,3], the great increase of the soybean area in recent years has become the main threat to the sustainability of farming systems because of a negative carbon balance (organic matter) and lower soil water availability. The inclusion of wheat in crop rotations has been proved to be a necessary and advantageous practice for agriculture in the region. In order to estimate agricultural production in a region, it is necessary, on the one hand, to establish the area occupied by each crop and, on the other hand, to know the productivity achieved. Using of radiometric data produced by remote sensing of the Earth has been developed as a promising solution to overcome these limitations [5]
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