@proceedings {51327,
	title = {Using high temporal resolution satellite data to assess shrub control effectiveness},
	volume = {General Technical Report INT-GTR-338},
	year = {1996},
	month = {May 23-25, 1995},
	pages = {88-94},
	publisher = {USDA Forest Service, Intermountain Research Station, Gen. Tech. Rep. INT-GTR-338},
	address = {Las Cruces, NM},
	abstract = {<p class="rtejustify">Mapping vegetation through remotely sensed images involves various considerations, processes and techniques. Increasing availability of remotely sensed images due to the rapid advancement of remote sensing technology expands the horizon of our choices of imagery sources. Various sources of imagery are known for their differences in spectral, spatial, radioactive and temporal characteristics and thus are suitable for different purposes of vegetation mapping. Generally, it needs to develop a vegetation classification at first for classifying and mapping vegetation cover from remote sensed images either at a community level or species level. Then, correlations of the vegetation types (communities or species) within this classification system with discernible spectral characteristics of remote sensed imagery have to be identified. These spectral classes of the imagery are finally translated into the vegetation types in the image interpretation process, which is also called image processing. This paper presents an overview of how to use remote sensing imagery to classify and map vegetation cover.</p>
},
	keywords = {image classification, image processing, remote sensing sensors, vegetation mapping},
	doi = {doi.org/10.1093/jpe/rtm005},
	url = {/files/bibliography/478.pdf},
	author = {M.D. Eve and Peters, A.J.},
	editor = {J.R. Barrow and McArthur, E. Durant and R. E. Sosebee and R. J. Tausch}
}
