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Proceedings Paper

Spatial validation of cotton simulation model in relation to soils and multispectral imagery
Author(s): Javed Iqbal; Frank D. Whisler; John J. Read; John A. Thomasson; Ishtiaq Ali; Johnie N. Jenkins; Dorgelis Villarroel
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Paper Abstract

Field studies were conducted in 1998 and 1999 in Livingston Field at Perthshire Farm, Bolivar County which is located in west-central Mississippi along the Mississippi River. It is a 162 ha field and has a 2-m elevation range. The dominant soil series of the field are Commerce silt loam, Robinsonville fine sandy loam and Souva silty clay loam. The objectives of the study were to (1) compare GOSSYM simulated yield with actual yield, (2) study spatial and temporal pattern of cotton crop across two growing seasons using multispectral imagery, 3) predict field based lint yield from remote sensed data, and determine age of the crop most suitable for aerial image acquisition in predicting yield and/or discriminating differences in cotton growth. Two transects were selected for GOSSYM study, each containing twelve sites. A 1-m length of single row plot was established at each profile. Plant mapping was done five times in 1998 and seven times in 1999 growing seasons. GOSSYM simulation runs were made for each profile and compared with actual crop parameters using root mean square error (RMSE). Results based on averaging common soil mapping units indicate that GOSSYM accuracy in predicting yield varied from 0.45 bales acre-1 to 0.61 bales acre-1. To monitor and estimate the biophysical condition of the cotton crop, airborne multispectral images were acquired on 10 dates in 1998 and 17 dates in 1999 from April to September. In both years site-specific yield and normalized difference vegetation index (NDVI) were significantly (p < 0.0001) correlated in July. Changes in NDVI in 1999 across sampling dates for the different sites showed the least distinctiveness due to somewhat wetter weather conditions, as compared to drier weather in 1998. Crop growing in or near the drainage areas were low in NDVI and lint yield. Multispectral images acquired between ~ 300 - 600 growing degree days above 60°C (GDD60) may be useful decision tools for replanting certain areas of the field, especially in dry weather conditions when variability in crop growth pattern is enhanced due to spatial variability in soil texture, which influences the capacity of a soil to hold moisture and to release it to plants for growth. Results suggest that 2-3 multispectral images acquired between 800 and 1500 GDD60 can be used to monitor crop health and predict yield in a normal weather condition.

Paper Details

Date Published: 22 December 2003
PDF: 8 pages
Proc. SPIE 5153, Ecosystems' Dynamics, Agricultural Remote Sensing and Modeling, and Site-Specific Agriculture, (22 December 2003);
Show Author Affiliations
Javed Iqbal, Mississippi State Univ. (United States)
Frank D. Whisler, Mississippi State Univ. (United States)
John J. Read, USDA Agricultural Research Service (United States)
John A. Thomasson, Mississippi State Univ. (United States)
Ishtiaq Ali, Univ. of Southern Mississippi (United States)
Johnie N. Jenkins, USDA Agricultural Research Service (United States)
Dorgelis Villarroel, Mississippi State Univ. (United States)

Published in SPIE Proceedings Vol. 5153:
Ecosystems' Dynamics, Agricultural Remote Sensing and Modeling, and Site-Specific Agriculture
Wei Gao; David R. Shaw, Editor(s)

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