Estimation and mapping of wheat crop chlorophyll content using hyperion hyperspectral data

Abstract

The estimation of chlorophyll content is an essential biochemical parameter to track the main developmental stages and yield of cereals relevant for precision agriculture. Traditional techniques for chlorophyll content measurements are time consuming, expensive and laborious. Measurements at field level have proven to be a good alternative, but their use is limited due to extensive sampling designs and techniques. Several spectral chlorophyll indices have been developed to estimate chlorophyll content both at the leaf and canopy level using remote sensing data. A methodology of using spectral chlorophyll indices to estimate chlorophyll content from laboratory and satellite hyperspectral data was carried out in this study for wheat crops. The application of this technique under agricultural field conditions has been very limited and not rigorously validated for wheat crops. The main objective of this study is to validate the chlorophyll content estimation using spectral chlorophyll indices, and to examine the potential for chlorophyll content estimation using hyperspectral remote sensing data in the context of precision agriculture. (Abstract shortened by UMI.)