Estimating Moisture Conditions From AVHRR Data

In cloud free areas the NOAA Advanced Very High Resolution Radiometer acquires data which relate to agricultural conditions. The visible and near infrared channels respond to the spectral signature of vegetation, providing information on the extent and vigor of crop cover, the thermal infrared (temperature) data are indicative of surface moisture condi-tions, as the cooling effect of evapotranspiration is readily apparent in the AVHRR data. Previous studies of Carlson and Boland,' Price,2 and Rosema et al.,3 have developed the formalism for reducing satellite thermal infrared data to quantitative estimates of surface moisture conditions. The results are generally reasonable, but have not been tested by comparison with surface observations. This problem of verification is chiefly one of spatial scale, e.g., the 1100 m scale of AVHRR data falls at the geometric mean of the scale of weather observations (100's of kilometers) and that of typical experimental ground truth (10's of meters). Yet precipitation and soil moisture at the scale of AVHRR are dominant variables affecting agricultural productivity. Data sets collected through the Statistical Reporting Service of the USDA represent an initial effort to permit tests the utility of AVHRR data for soil moisture and crop yield assessment. The physical and statistical formulations are discussed for dealing with these complex data sets, and the framework of a hypothetical operational system is addressed. The observing system of choice combines daily AVHRR passes with the infrequent but high spatial resolution data from Landsat or SPOT sensors.