|LALIBERTE, ANDREA - New Mexico State University|
|Herrick, Jeffrey - Jeff|
|WINTERS, CRAIG - New Mexico State University|
|STEELE, CAITI - New Mexico State University|
Submitted to: Journal of Applied Remote Sensing (JARS)
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/11/2009
Publication Date: 8/13/2009
Citation: Rango, A., Laliberte, A., Herrick, J.E., Winters, C., Havstad, K.M., Steele, C., Browning, D.M. 2009. Unmanned aerial vehicle-based remote sensing for rangeland assessment, monitoring, and management. Journal of Applied Remote Sensing (JARS). 3(1):033542.
Interpretive Summary: Rangeland makes up the majority of the earth’s surface, and point measurements are not sufficient for rangeland assessment, monitoring, and management. Because of the remote locations of most rangeland, remote sensing is ideal for monitoring, but high resolution sensing on the order of 10 cm is required. Satellite and most aircraft imaging is insufficient to provide the necessary monitoring resolution. We have developed our own Unmanned Aerial Vehicle (UAV) system that provides the necessary resolution and capability to go back for follow-up imaging to allow change detection. We can also mosaick individual images to produced coverage over large rangeland areas. Vegetation differences can be assessed, and an application for determining rangeland health is possible. Potential users include rangeland scientists from the NRCS and BLM as well as scientists from state and local agencies.
Technical Abstract: Rangeland comprises as much as 70% of the Earth’s land surface area. Much of this vast space is in very remote areas that are expensive and often impossible to access on the ground. Unmanned Aerial Vehicles (UAVs) have great potential for rangeland management. UAVs have several advantages over satellites and piloted aircraft: they can be deployed quickly and repeatedly; they are less costly and safer than piloted aircraft; they are flexible in terms of flying height and timing of missions; and they can obtain imagery at sub-decimeter resolution. This hyperspatial imagery allows for quantification of plant cover, composition, and structure at multiple spatial scales. Our experiments have shown that this capability, from an off-the-shelf mini-UAV, is directly applicable to operational agency needs for measuring and monitoring. For use by operational agencies to carry out their mandated responsibilities, various requirements must be met: an affordable and reliable platform; a capability for autonomous, low altitude flights; takeoff and landing in small areas surrounded by rugged terrain; and an easily applied data analysis methodology. A number of image processing and orthorectification challenges have been or are currently being addressed, but the potential to depict the land surface commensurate with field data perspectives across broader spatial extents is unrivaled.