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ARS Home » Plains Area » Las Cruces, New Mexico » Range Management Research » Research » Publications at this Location » Publication #239324
Title: Acquisition, orthorectification, and object-based classification of unmanned aerial vehicle (UAV) imagery for rangeland monitoring

Author
item LALIBERTE, ANDRES - New Mexico State University
item Herrick, Jeffrey - Jeff
item Rango, Albert
item WINTERS, CRAIG - New Mexico State University

Submitted to: Photogrammetric Engineering and Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/24/2009
Publication Date: 6/1/2010
Citation: Laliberte, A.S., Herrick, J.E., Rango, A., Winters, C. 2010. Acquisition, orthorectification, and object-based classification of unmanned aerial vehicle (UAV) imagery for rangeland monitoring. Photogrammetric Engineering and Remote Sensing. 76:661-672.

Interpretive Summary: Unmanned aerial vehicles (UAVs) are well suited for rangeland remote sensing applications due to the remoteness and low population density of rangelands. The requirement to monitor and assess millions of acres of rangelands is a task not feasibile with ground monitoring techniques alone. We examined the potential of using a small UAV for rangeland inventory, assessment and monitoring. Imagery with 8-cm resolution was acquired over 290 ha in southwestern Idaho. We developed a semi-automated orthorectification procedure suitable for handling large numbers of small-footprint UAV images. The orthorectified image mosaics had a geometric accuracy ranging from 1.5 m to 2 m. Object-based hierarchical image analysis was used to classify imagery of plots measured concurrently on the ground using standard rangeland monitoring procedures. Correlations between image- and ground-based estimates of percent cover resulted in r-squared values ranging from 0.86 to 0.98. Time estimates indicated a greater efficiency for the image-based method compared to ground measurements. Overall classification accuracies for the image mosaics were in the 83-88% range. While current limitations of operating UAVs in the National Airspace are imposed by the Federal Aviation Administration (FAA), the results of this study show that UAVs can be used successfully to obtain imagery for rangeland monitoring, and that the remote sensing approach can either complement or even replace some ground-based measurements.

Technical Abstract: In this paper, we examine the potential of using a small unmanned aerial vehicle (UAV) for rangeland inventory, assessment and monitoring. Imagery with 8-cm resolution was acquired over 290 ha in southwestern Idaho. We developed a semi-automated orthorectification procedure suitable for handling large numbers of small-footprint UAV images. The orthorectified image mosaics had a geometric accuracy ranging from 1.5 m to 2 m. Object-based hierarchical image analysis was used to classify imagery of plots measured concurrently on the ground using standard rangeland monitoring procedures. Correlations between image- and ground-based estimates of percent cover resulted in r-squared values ranging from 0.86 to 0.98. Time estimates indicated a greater efficiency for the image-based method compared to ground measurements. Overall classification accuracies for the image mosaics were in the 83-88% range. Even under the current limitations of operating a UAV in the National Airspace, the results of this study show that UAVs can be used successfully to obtain imagery for rangeland monitoring, and that the remote sensing approach can either complement or replace some ground-based measurements. Details of the UAV mission, image processing and analysis, and accuracy assessment are discussed.