Hierarchical object-based classification of ultra-high-resolution digital mapping camera (DMC) imagery for rangeland monitoring and assessment

Ultra high resolution digital aerial photography has great potential to complement or replace ground measurements of vegetation cover for rangeland monitoring and assessment. We investigated object-based image analysis (OBIA) techniques for classifying vegetation in southwestern U.S. arid rangelands with 4 cm resolution digital aerial photography. We obtained high r-square values for image- and ground-based measures of percent cover (r-square values: 0.82-0.92). OBIA enabled us to automate the classification process and demonstrated potential for quantifying fine-scale land cover attributes with ultra high resolution imagery. This approach exhibits promise for nationwide application for monitoring grazing lands.