@article {49958,
	title = {Image processing and classification procedures for analysis of sub-decimeter imagery acquired with an unmanned aircraft over arid rangelands},
	journal = {GIScience \& Remote Sensing},
	volume = {48},
	year = {2011},
	pages = {4-23},
	chapter = {4-23},
	abstract = {Unmanned aerial systems (UAS) have great potential as a platform for acquiring very high resolution aerial imagery for vegetation mapping. However, image processing and classification techniques require adaptation to images obtained with low-cost digital cameras. We developed and evaluated an image processing workflow that included the integration of resolution-appropriate field sampling, feature selection, and object-based image analysis for the purpose of classifying rangeland vegetation from a five-centimeter-resolution UAS image mosaic. Classification tree analysis was used to determine the optimal spectral, spatial, and contextual features. Segmentation and classification rule sets were developed on a test plot and were applied to the remaining study area, resulting in an overall classification accuracy of 78\% at the species level and 81\% at the structure-group level. The image processing approach provides a roadmap for deriving quality vegetation classification products from UAS imagery with very high spatial, but low spectral resolution.},
	doi = {10.2747/1548-1603.48.1.4},
	url = {/files/bibliography/11-001.pdf},
	author = {Andrea S. Laliberte and A. Rango}
}
