Digital photogrammetric surface models generated from low flying remotely piloted aircraft provide a wealth of data that can be used to interpret surface features at centimeter to sub-centimeter spatial resolutions.� Digital terrain models at this high spatial resolution when applied to the study of vegetation communities can provide detailed information of vegetation structure, height, cover, and density that heretofore could only be acquired using expensive and time-consuming field surveys.� Further, unlike field surveys, these data, coupled with matching color ortho-imagery, provide a highly detailed, permanent record of vegetation community conditions that can be revisited and re-analyzed in the future.� This ability to re-analyze original data and extract additional or improved information as statistical and spatial analysis techniques mature promises to revolutionize the monitoring of natural landscapes.� This study shows that high resolution, natural-color imagery collected with a remotely piloted aircraft and processed to extract a topographic point-cloud is very effective at estimating individual shrub height and cover as well as producing a high quality spatial database consisting of an ortho-image coupled with a detailed photogrammetric point-cloud.� The combination of these two datasets provides an excellent tool for characterizing shrub communities at a level of detail that will allow land managers to effectively assess canopy cover, height, structure, and potentially help characterize erosional features such as gully development and pedestaling.
Oral presentation and poster titles, abstracts, and authors from the Society for Range Management (SRM) Annual Meetings and Tradeshows, from 2013 forward.