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Thermal and Color Near-Infrared Spectral Remotely Sensed Scanners to Detect In-Field Soybean and Corn Water Stress Variability
Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.orgCitation: Paper number 033127, 2003 ASAE Annual Meeting . (doi: 10.13031/2013.14067) @2003
Authors: Reinaldo L. Gomide, Lei Tian, Francisco A. de Carvalho Pinto
Keywords: Hyperspectral image, crop canopy reflectance and temperature, crop water stress signature, spatial variability
Remotely sensed scanners in the near and thermal-infrared spectral portions have potential for assessing in-field variability of crop water stress. The objectives of this work are: to study the feasibility of using two scanners for soybean and corn water stress variability detection; to establish temporally and spatially consistent, quantitative relationships between remotely sensed measurements and crop water stress levels by calibrating and correcting for atmospheric interference, illumination intensity, and solar and viewing angles; to develop a soil background correction algorithm during the early crops season when the crops are not completely covering the soil surface. A high resolution digital multispectral camera, with a large-format progressive scan 3-CCD sensors, is being equipment mounted and used to acquire color infrared (CIR) images for detecting in-field crop water stress spatial variability in the Red, Green, Blue, and Near infrared bands. Images patterns acquired is being processed and classified into groups using an unsupervised learning (clustering) method. These clustered images are being geo-referenced and the data are being directly integrated into a geographic information system (GIS) package. An infrared thermometer scanner is being used with the camera to measure the crop canopy temperature remotely in the thermal-infrared band. The amount of energy reflected from the plants in the visible and near infrared (NIR) portion of the spectrum is being measured and correlated to crop water stress, light use efficiency, canopy density, chlorophyll content, and yield. The reflectance data measured are being used in the generation of the normalized difference vegetation index (NDVI). The Crop Water Stress Index (CWSI) method (Jackson et al., 1982) will be used to quantify crop water stress. Water differentiation will be produced by means of a continuous gradient of water applied from a line source sprinkling system, which will be installed in the center of the plots. Samples and measurements will be taken weekly with each scanner/sensor to track the growth of the crops and the images and signatures of water stresses.(Download PDF) (Export to EndNotes)