23 October 2006 Using ASTER image for soybean plant residue coverage estimation
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Proceedings Volume 6381, Optics for Natural Resources, Agriculture, and Foods; 638102 (2006) https://doi.org/10.1117/12.686268
Event: Optics East 2006, 2006, Boston, Massachusetts, United States
Abstract
Soil erosion and its related runoff is a serious problem in U.S. agriculture. USDA has classified 27% of U.S. agricultural land as being highly erodible. Because of the erosion, rivers, lakes, and water table are contaminated due to the agriculture chemicals such as nitrogen, phosphorus, and pesticides contained in the runoff water. This is a serious environmental problem nationwide. It is well recognized that residue coverage on the soil surface can reduce soil erosion. The objective of this paper was to explore the potential of using ASTER data for soybean plant residue cover estimation. In the spring of 2004, personnel from Natural Resource Conservation Service (NRCS) and Institute for Technology Development (ITD) did a traditional windshield survey in three Indiana Counties, Wabash, Huntington, and Grant. Fields with greater than 30% residue cover were classified as conservation tillage (no till); those with 16-30% residue cover as reduced tillage; and those with less than 15% residue cover as traditional tillage. ASTER data was collected over the study sites on April 14, 2004. Spectral information was extracted from the ASTER image for statistical analysis. Field values for various indices were calculated from the reflectance data. Residue coverage estimation from the survey was used as the ground truth for the field. Analysis was performed to determine the capability of ASTER data to identify crop residue coverage. The initial results indicated that ASTER imagery has moderate capability to identify residue coverage - or tillage practice within the soybean fields.
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Haibo Yao, Haibo Yao, David Lewis, David Lewis, Russell Kincaid, Russell Kincaid, } "Using ASTER image for soybean plant residue coverage estimation", Proc. SPIE 6381, Optics for Natural Resources, Agriculture, and Foods, 638102 (23 October 2006); doi: 10.1117/12.686268; https://doi.org/10.1117/12.686268
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