Location: Range Management Research
Title: Application of high resolution images from unmanned aircraft systems for watershed and rangeland science Authors
|Vivoni, Enrique -|
|Anderson, Cody -|
|Pierini, Nicole -|
|Schreiner-Mcgraw, A -|
|Saripalli, S -|
|Laliberte, Andrea -|
Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: November 10, 2013
Publication Date: N/A
Interpretive Summary: Hydrologic studies on small watersheds in semiarid regions require significant and advanced ground based measurements along with high resolution remote sensing from unmanned aerial vehicles. A small watershed at the Jornada Experimental Range was intensively instrumented with an eddy covariance tower to measure fluxes, a COsmic-ray soil moisture observing system and several National Network sites including SCAN, NOAA-CRN, NSF NEON and LTER sites, all of which can be accessed in near real time. The unmanned aerial vehicle (UAV) Bat-3, was flown at 215 m to provide a spatial resolution of 6 cm. The Bat-3 imagery was used to construct a 1 m DEM, a digital mosaic of the entire basin, a detailed watershed boundary, and a high resolution drainage network. Combined UAV and ground-based measurement provide spatial characterizations of highly heterogeneous semiarid landscapes that can be used for both watershed and rangeland assessments. These assessments can be of great value for both federal and state agencies charged with land resources management.
Technical Abstract: UAS provide a new way to acquire hyperspatial data with a resolution of 6 cm that has not been available in the past. This hyperspatial data can be used to obtain detailed 1-m DEMs, mosaics of entire watersheds, detailed vegetation classification of bare soils and vegetation type, and input to models in watershed and rangeland science. Because of improved UAS guidance systems, UAS can be used to repetitively cover the same areas for change detection. UAS can provide frequent and affordable aerial coverage of study areas with high resolution data to fill in gaps in ground observation networks and between satellite overpasses.