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Proceedings Paper

Characterization model for crop stress using hand-held radiometer data
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Paper Abstract

Remotely sensed reflectance from stressed and non-stressed crop vegetative cover can be predicted from two combinations of spectral bands as a ratio or as normalized vegetation indices. The most common spectral bands used lie in the red and infrared region (350-800 nm) and are dominated by the absorption of chlorophyll and other accessory pigments. In addition, reflectance in the middle infrared is dominated by absorption from liquid water contained in plant’s tissues. The objectives of the present work are: 1) to develop characterization model to evaluate the reflectance data from frequently irrigated and water stressed alfalfa, Sudan grass, and other crops such cotton as using a handheld radiometer and assess the spectral correlation with the ground-truth and; 2) The model will be better model to evaluate the stressed crops. The experiment was designed to collect reflectance data from cotton crops planted at the Blythe area, California. The fields are planted with cotton crops in different stages of maturity at Longitude of -114°32.79 and -114°32.80 and Latitude 33° 39.64. With a field spectrometer, the scan over each treatment was made at 1 hr intervals between 10:00 a.m. and 2:00 p.m. Pacific Day Time (PDT). Vegetative samples were taken from the two treatments (i.e. stressed and unstressed vegetation) during the initial sampling for purposes of conducting chemical analysis. Soil samples were collected to determine the amount of available soil moisture differences in the two treatments. The suggested model in the present paper is called the Model of Water Stress (MWS) where it include in it the statistical values and parameters, indicates that the stressed crops have values higher than unstressed crops in MWS scale. This means that the model is differentiating between the stressed and unstressed vegetation. Additional work will evaluate the reflectance peaks and their relationship to other parameters that were collected and are relevant to the applications of the model. The model will be tested against the AVIRIS data that were collected at the same time of the collection of ground-truth data.

Paper Details

Date Published: 23 January 2001
PDF: 17 pages
Proc. SPIE 4171, Remote Sensing for Agriculture, Ecosystems, and Hydrology II, (23 January 2001); doi: 10.1117/12.413959
Show Author Affiliations
Safwat H. Shakir Hanna, Prairie View A&M Univ. (United States)


Published in SPIE Proceedings Vol. 4171:
Remote Sensing for Agriculture, Ecosystems, and Hydrology II
Manfred Owe; Guido D'Urso; Eugenio Zilioli, Editor(s)

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