@article {49840,
	title = {Vegetation index differencing for broad-scale assessment of productivity under prolonged drought and sequential high rainfall conditions},
	journal = {Remote Sensing},
	volume = {5},
	year = {2013},
	month = {01/2013},
	pages = {327-341},
	chapter = {327},
	abstract = {<p class="rtejustify">Spatially-explicit depictions of plant productivity over large areas are critical to monitoring landscapes in highly heterogeneous arid ecosystems. Applying radiometric change detection techniques we sought to determine whether: (1) differences between pre- and post-growing season spectral vegetation index values effectively identify areas of significant change in vegetation; and (2) areas of significant change coincide with altered ecological states. We differenced NDVI values, standardized difference values to Z-scores to identify areas of significant increase and decrease in NDVI, and examined the ecological states associated with these areas. The vegetation index differencing method and translation of growing season NDVI to Z-scores permit examination of change over large areas and can be applied by non-experts. This method identified areas with potential for vegetation/ecological state transition and serves to guide field reconnaissance efforts that may ultimately inform land management decisions for millions of acres of federal lands.\&nbsp;</p>
},
	keywords = {change detection; rangeland monitoring; Landsat; ecological state mapping; state-and-transition models; phenology},
	doi = {10.3390/rs5010327 },
	url = {/files/bibliography/13-001.pdf},
	author = {Dawn M. Browning and Caitriana Steele}
}
