Remote Sensing for Precision Agriculture

Research applications of remote sensing in precision agriculture are numerous, and include techniques for detecting water stress, nitrogen stress, weed infestations, fungal disease, and insect damage. Significant advances have been made in identifying key wavelengths and spectral indices at which these stresses influence the reflectance or fluorescence properties of plant pigments and crop canopy architecture. However, little research has been conducted on detecting locations affected by crop stress and simultaneously distinguishing between different types of crop stress. A basic problem is that remote sensing does not typically respond directly to water, nutrient, weed, insect, or disease stresses, rather it responds indirectly to the changes in chlorophyll or crop canopy architecture caused by these crop stresses. For this reason, remote sensing has not yet been widely adopted by farmers for routine use in precision agriculture. The main reasons include the difficulty in interpreting spectral signatures, the slow processing time for data, the high expense, and the need to collect confirmatory data from ground surveys to diagnose causative factors for anomalous spectral reflectance data. Clearly, there is a significant scope for improving the interpretation and utility of remote sensing data for precision agriculture.