Professor California State Polytechnic University, Pomona
Disclosure: Disclosure information not submitted.
This presentation talks about the effect of altitude on the accuracy of unmanned aerial vehicles (UAV)-based remote sensing data in detecting plant nitrogen and water stresses. The main advantage of UAV-based remote sensing technique is the immediate availability of high-resolution data that can be used to determine the crop nitrogen and water stresses. The data can then be used for the optimization of water and nitrogen for crop production using site-specific management. However, to be useful for the end users, remote sensing data must provide the crop nitrogen and water stresses very accurately. One of the factors that affects the accuracy of remote sensing data is the altitude from which the data is collected. This presentation talks about the effect of altitude on the accuracy of remote sensing data when the sensor field of view is fixed. UAVs equipped with hyperspectral and multispectral sensors were used to collect the remote sensing data of lettuce and citrus plants from different altitudes at Cal Poly Pomona’s Spadra Farm. The remote sensing data was then used in the calculation of various vegetation indices including normalized difference vegetation index (NDVI), Green NDVI (GNDVI), modified NDVI (mND705), and Water Band Index (WBI). These indices were compared with the data obtained from proximal sensors that include Handheld Spectroradiometer, Water Potential Meter, and Chlorophyll Meter. Correlations between the vegetation indices for different altitudes, proximal sensor data, and leaf nitrogen and water contents will be shown.