Multiscale assessment of green leaf cover in a semi-arid rangeland with a small unmanned aerial vehicle

Abstract

Spatial variability in green leaf cover of a semi-arid rangeland was studied by comparing field measurements on 50 m crossed transects to aerial and satellite imagery. The normalized difference vegetation index was calculated for 2 cm resolution images collected with a multispectral digital camera mounted on a radio-controlled helicopter, as well as a 30 m resolution Landsat Thematic Mapper image. Variograms of green cover from these two sources show that the range of influence for spatial autocorrelation extended to a distance of approximately 200 m. Field transects that are much smaller than the extent of this spatial autocorrelation are more likely to fall within local deviations from the mean landscape condition. A sampling scheme that exceeds the spatial scale of these localized deviations is shown to reduce sample variance and require fewer sampling locations to reach a given level of measurement uncertainty. The time and cost of more spatially extensive sampling at each location may be less than deploying to a larger number of locations with smaller transects, and unmanned aerial vehicles may be a valuable tool in extending current field sampling strategies for quantifying the health of shrub-dominated rangelands.

Acknowledgements

This work was supported by the Desert Research Institute of the Nevada System of Higher Education, by USDA's Agricultural Research Service, and by the NRCS Conservation Effects Assessment Program (CEAP). We would like to give special thanks to Eric Knight for his extraordinary RCH piloting. Mention of specific products in the article does not reflect an endorsement of these products but is provided for full disclosure on how research was conducted.