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1 January 2013 Comparing Two Ground-Cover Measurement Methodologies for Semiarid Rangelands
Keith T. Weber, Fang Chen, D. Terrance Booth, Mansoor Raza, Kindra Serr, Bhushan Gokhale
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Abstract

The limited field of view (FOV) associated with single-resolution very-large-scale aerial (VLSA) imagery requires users to balance FOV and resolution needs. This balance varies by the specific questions being asked of the data. Here, we tested a FOV-resolution question by comparing ground cover measured in the field with the use of point-intercept transects with similar data measured from 50-mm-per-pixel (mmpp) VLSA imagery of the same locations. Particular care was given to spatial control of ground and aerial sample points from which observations were made, yet percent cover estimates were very different between methods. An error budget was used to calculate error of location and error of quantification. These results indicated location error (43.5%) played a substantial role with significant quantification error (21.6%) also present. We conclude that 1) although the georectification accuracy achieved in this project was actually quite good, the level of accuracy required to match ground and aerial sample points represents an unrealistic expectation with currently available positioning technologies, 2) 50-mmpp VLSA imagery is not adequate for accurate species identification or cover assessments of plant functional groups, and 3) the balance between resolution and FOV needs is best addressed by using multiple cameras to acquire nested imagery at multiple VLSA resolutions simultaneously. We recommend ground cover be measured from 1-mmpp imagery and that the imagery be nested in lower-resolution, larger FOV images simultaneously acquired.

Keith T. Weber, Fang Chen, D. Terrance Booth, Mansoor Raza, Kindra Serr, and Bhushan Gokhale "Comparing Two Ground-Cover Measurement Methodologies for Semiarid Rangelands," Rangeland Ecology and Management 66(1), 82-87, (1 January 2013). https://doi.org/10.2111/REM-D-11-00135.1
Received: 2 August 2011; Accepted: 1 July 2012; Published: 1 January 2013
KEYWORDS
aerial imagery
GIS
remote sensing
VLSA
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