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1 January 2006 Challenges of Integrating Geospatial Technologies Into Rangeland Research and Management
Keith T. Weber
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With the development and commercial availability of submeter spatial resolution satellite imagery, geospatial tools can better accommodate the needs of range professionals than ever before. However, with these new tools comes a new set of challenges. Range managers and range scientists must now 1) better understand and take advantage of the geotechnical tools at their disposal, 2) collect field observations/measurements in ways that act synergistically with these tools, and 3) utilize high-accuracy global positioning system (GPS) receivers. To produce reliable rangeland models it is important to collect field data that correspond with what the satellite “sees.” Further, it is frequently necessary to use high-resolution imagery, which subsequently necessitates the use of high-accuracy GPS receivers to ensure field data are recorded in the correct pixel and properly coregistered. This paper describes the results of research and experimentation that have led to the development of techniques to improve geospatial rangeland applications. For optimal classification accuracy, field data collected for use in remote sensing applications should estimate/measure ground cover using general vegetation community types and must never exceed 100%. Further, the field sample sites used for classification must be located using a GPS receiver with accuracy ≤ 50% of the size of satellite imagery pixels (e.g., if Landsat imagery is used—with 28.5-m pixels—the GPS receiver must be able to achieve ± 14 m accuracy with 95% confidence). Finally, a series of best practices are suggested to help range managers and range scientists better understand and implement geospatial technologies.

Keith T. Weber "Challenges of Integrating Geospatial Technologies Into Rangeland Research and Management," Rangeland Ecology and Management 59(1), 38-43, (1 January 2006).
Published: 1 January 2006

global positioning system
range science
remote sensing
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