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| Created: | Sep 09, 2019 at 3:41 p.m. | |
| Last updated: | Sep 09, 2019 at 4:29 p.m. | |
| Citation: | See how to cite this resource | |
| Content types: | Geographic Raster Content |
| Sharing Status: | Public |
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Abstract
This is a supplementary data for the study "Accounting for adaptive water supply management when quantifying climate and landcover change vulnerability" by D. E. Gorelick,, L. Lin, H.B. Zeff, Y. Kim, J. M. Vose, J. W. Coulston, D. N. Wear, L. E. Band, P. M. Reed, and G. W. Characklis, as one of the publications supported by Water Sustainability and Climate NSF awarded project (EAR-1360442). The study article is submitted to the Water Resources Research (WRR) journal.
In this supplementary data package, users will find some spatially distributed maps (raster data) that were used by the study. We attached six projection realizations for all the data below, indicated by the number after letter 'r' in the file names.
1) projected 30-m Leaf Area Index (LAI) maps, derived from forest canopy information, e.g., vegetation community and vegetation density, are maintained by United States Department of Agriculture (USDA) Forest Service. General model and data descriptions are available at (https://www.fia.fs.fed.us/library/maps/index.php) Due to server storage size limit and data confidential, we reduced the accuracy of the LAI values from decimal to integer. Note that these LAI values are for the forested landcover, excluding the urban canopy LAI in urban area and the pasture/lawn LAI.
2) projected 30-m Landuse-Landcover (LULC) maps, produced by statistical spatial models by Martin et al. (2017) and Wear (2013) forecasting future forest landcover and urban expansion based on the economic scenarios (CMIP 5 RCP 6; Suttles et al. 2018) and planning development by the Triangle J Council of Governments (TJCOG). The LULC classes are the same as NLCD classes (https://www.mrlc.gov/data/legends/national-land-cover-database-2011-nlcd2011-legend) except all the forest LULC classes are lumped together as class ID 40.
Subject Keywords
Coverage
Spatial
Content
Data Services
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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