Hyperion Studies Of Crop Stress In Mexico

Satellite-based measurements of crop stress could provide much needed information for cropland management, especially in developing countries where other precision agriculture technologies are too expensive (Pierce and Nowak 1999; Robert 2002). For example, detection of areas that are nitrogen deficient or water stressed could guide fertilizer and water management decisions for all farmers within the swath of the satellite. Several approaches have been proposed to quantify canopy nutrient or water content based on spectral reflectance, most of which involve combinations of reflectance in the form of vegetation indices. While these indices are designed to maximize sensitivity to leaf chemistry, variations in other aspects of plant canopies may significantly impact remotely sensed reflectance. These confounding factors include variations in canopy structural properties (e.g., leaf area index, leaf angle distribution) as well as the extent of canopy cover, which determines the amount of exposed bare soil within a single pixel. In order to assess the utility of spectral indices for monitoring crop stress, it is therefore not only necessary to establish relationships at the leaf level, but also to test the relative importance of variations in other canopy attributes at the spatial scale of the remote sensing measurement. In this context, the relative importance of a given attribute will depend on (1) the sensitivity of the reflectance index to variation in the attribute and (2) the degree to which the attribute varies spatially and temporally.