Investigations of spectral separability of small grains, early season wheat detection, and multicrop inventory planning

Abstract

The author has identified the following significant results. LANDSAT data from seven 5 by 6 segments having crop type information were analyzed to determine the potential for spectral separation of spring wheat from other small grains as an alternative to the primary LACIE procedure for estimating spring wheat acreage. Within segment field-center, classification accuracies for spring wheat vs. barley tended to be best in mid-July when crop color changes were in progress. When correlations were made for differences in atmospheric haze, data from several segments could be aggregated, and results that approached within segment accuracies were obtained for selected dates. LACIE field measurement spectral reflectance data provided information on both wheat development patterns and the importance of various agronomic factors on wheat reflectance, the most important being availability of soil moisture. To investigate early season detection for winter wheat, reflectance of developing wheat patterns was simulated through reflectance modeling and was analyzed along with field measured reflectance from a Kansas site. The green component development of the wheat field was analyzed as a function of data throughout the season. A selected threshold was not crossed by all fields until mid-April. These reflectance data were shown to be consistent actual LANDSAT data.