Remote sensing applications in precision farming for the Mississippi delta

被引:0
|
作者
Shaw, DR [1 ]
Hill, CL [1 ]
机构
[1] Mississippi State Univ, Remote Sensing Technol Ctr, Mississippi State, MS USA
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中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
Mississippi State University has established a Remote Sensing Technologies Center (RSTC) in the areas of agriculture, forestry and wildlife, and transportation. The unique characteristics of Mississippi's natural resource and economic development, along with the presence and commitment of Mississippi State University, the NASA Stennis Space Center's Commercial Remote Sensing Program (CRSP), and the Mississippi Space Commerce initiative make the State of Mississippi an excellent laboratory for developing applications of remote sensing. The research focus areas named above will be underpinned by the cross-cutting areas of computational modeling and workforce development. The RSTC complements a larger effort by NASA's CRSP to enhance U.S. economic competitiveness, reduce operational cost, and enhance NASA's own Earth Science Program through the development of aerial and satellite remote sensing technologies. As a result of a commitment to basic research in developing the understanding of phenomenology within a broad range of disciplined areas, MSU has developed a highly characterized field laboratory analysis capability. Within the agricultural focus area, projects are addressing diverse issues such as soil characterization, site-specific applications of fertilizers based on crop reflectance, characterization of weed populations through unique reflectance patterns, targeted insecticide applications based on remote sensing images of crop growth, cotton defoliation and growth regulation based on aerial images, early detection of crop stress caused by plant pathogens and other causal agents, and economic assessments of remote sensing technologies for precision agriculture. All of these projects are geared heavily toward extensive ground control verification and validation activities. Early results are particularly promising in targeted, site-specific applications of insecticides in cotton based on relative crop vigor, as determined by Normalized Differential Vegetative Indices(NDVI). By "smart" insect scouting based on these images, insecticide applications were reduced by as much as 40%. Similarly, early findings indicate that several of the most troublesome weeds of row crops in the southeastern U.S, can be delineated using hyperspectral data.
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页码:202 / 207
页数:6
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