Bruce K. Wylie (USGS EROS)Neal J. Pastick (SGT at USGS EROS)20160601Alaska LandCarbon Wetland Distribution MapRaster Digital Data SetZhiliang ZhuA. David McGuire20160601Baseline and projected future carbon storage and greenhouse-gas fluxes in ecosystems of AlaskaPublication (Other)USGS Professional Paper1826http://dx.doi.org/10.3133/pp1826USGS Professional Paper 1826http://dx.doi.org/10.3133/pp1826This product was to provide regional estimates of specific wetland types (bog and fen) in Alaska, available wetland types mapped by the National Wetlands Inventory (NWI) program were re-classed into bog, fen, and other. NWI mapping of wetlands was only done for a portion of the area so a decision tree mapping algorithm was then developed to estimate bog, fen, and other across the state of Alaska using remote sensing and GIS spatial data sets as inputs.
He, Y., Genet, H., McGuire, A.D., Zhuang, Q., Wylie, B.K., and Zhang, Y., 2016, Terrestrial carbon modeling—Baseline and projections in lowland ecosystems of Alaska, chap. 7 in Zhu, Z., and McGuire, A.D., eds., Baseline and projected future carbon storage and greenhouse-gas fluxes in ecosystems of Alaska: U. S. Geological Survey Professional Paper 1826, p. 133-158, at http://dx.doi.org/10.3133/pp1826.Carbon flux and methane flux models need bog and fen wetland types to quantify wetland impacts on Alaska carbon fluxes. Bog and fen were the primary wetland types that the carbon flux model was applicable to. This bog and fen maps were used and presente in various chapters on the USGS Alaska LandCaron Report ( Zhu, Z. and McGuire, A.D., 2016).
Zhu, Zhiliang, and McGuire, A.D., eds., 2016, Baseline and projected future carbon storage and greenhouse-gas fluxes in ecosystems of Alaska: U.S. Geological Survey Professional Paper 1826, 196 p., http://dx.doi.org/10.3133/pp1826.20000101See Supplemental InfoNone planned-173.49206181-117.44762090571.34121551652.43074463NonewetlandsAlaskaBogFendecsion treeNWINoneAlaskaNone. Please see 'Distribution Info' for details.None. Users are advised to read the data set's metadata thoroughly to understand appropriate use and data limitations.U.S. Geological Survey, CLIMATE & LAND-USEBruce K Wyliemailing address47914 252Nd StreetSioux FallsSD57198605-594-6078wylie@usgs.govEnvironment as of Metadata Creation: Microsoft Windows 7 Version 6.1 (Build 7601) Service Pack 1; Esri ArcGIS 10.3.1 (Build 4959) Service Pack N/A (Build N/A)Independent witheld test accruacy: Overall accruacy 75%
Mapped as
bog fen other sum %
Ref. bog 52 3 64 119 43.7%
(NWI) fen 7 188 124 319 58.9%
other 42 18 532 592 89.9%
sum 101 209 720 1030
% 51.5% 90.0% 73.9% 75.0%
20-fold random Cross Validation accruacy: Overall accuracy 66.9%
Mapped as
bog fen other sum %
Ref bog 1385 60 1807 3252 42.6%
(NWI) fen 118 2077 1705 3900 53.3%
other 985 956 7901 9842 80.3%
sum 2488 3093 11413 16994
% 55.7% 67.2% 69.2% 66.9%Qualitative checks at Minto Flats, Alaska and Yukon Flats, Alaska.The goal was to only map wetland types of Bog and Fen because subsequent models which were to use this data were properly parameterized for these wetland types.Horizontal accuracy is epected to be less than 30m (the original mapping resolution). The 30 m bog and fen data calls were then sumarized to the 1 km scale.A formal accuracy assessment of the vertical positional information in the data set has either not been conducted, or is not applicable.Julie Michaelson, NWI Assistant Coordinator201401016Alaska National Wetland InventoryVector Digital Data Sethttps://www.fws.gov/alaska/fisheries/nwi/U.S Fish and Wildlif Service24000Digital and/or Hardcopy Resources1978010120140116publication dateAlaska NWIBog and fen categories assigned based on NDI codes and served as reference data for a decision tree mapping model.The NWI mapped area only (30 m resolution) covers a small percentage of Alaska, but represents coastal and north to south gradients along the road systems. NWI wetland codes were recoded into classes representing bog, fen, and other. Bogs should be seasonally flooded during spring melt. We suspected they were called saturated shrub scrub because of the dwarf shrubs and mosses. The NWI codes of SS4B, SS1E,and SS7B were used to define bogs. Fens should be seasonally flooded or more usually semi permanently flooded. We assumed this should be persistent emergent wetlands, or the NWI codes of EM1F and EM1E. Marine wetlands in NWI were not estimated so predictions were for freshwater bogs and fens only.
Random NWI pixel locations (18,024) were used to build data base of spatial inputs and NWI Classes at each point. These pixel locations (30 m resolution) were constrained to areas not already mapped as water. Only 789 of these were picked manually. Most of the points were simple random selections but some random pixel searches were focused only on only two the wetland types. This was done to insure that the training data for model development both represented the frequency of wetlands in the population to be mapped as well as to insure there were adequate numbers of rare classes to insure they were predicted and not lumped in to the more prevalent upland/other wetland class. Attributes from each of the potential input layers were extracted at each of these pixel locations and a database constructed. Randomly 1,030 pixel locations were selected and withheld as test. The test pixels were constrained to be more that 90m from a training pixel to mitigate spatial autocorrelation impacts. This resulted in a model development data base which consisted of the remaining 16,994 pixel locations.
A Decision tree (C5 see www.rulequest.com) was trained to predict bog, fen, and other classes using Landsat Weld data, DEM, slope, NLCD land cover, various vegetation and moisture spectral indices, soil texture (from M.T. Jorgeson), surface water map, compound terrain index, and a previous wetland map (Whitcomb et al. 2009). Decision tree approaches of boosting, winnowing, and constraining the minimum number of observation needed for a rule.
The final map (1 km resolution) used a moving window approach to summarize the percent of each km pixel which was classified as either a bog or a fen (percent wetland). The units range from 0 to 106 percent.20150202RasterGrid Cell185022281NAD 1983 Albers (ESRI Full Name: NAD_1983_Albers)55.065.0-154.050.00.00.0row and column1000.01000.0MeterD_North_American_1983GRS_19806378137.0298.257222101Attribute TableTable containing attribute information associated with the data set.Producer definedValuePercent area of each 1 km2 pixel which was classified as bog or fen wetlands at the 30m resolution. Values greater than 100 should be truncated to 100 percentProducer defined0106percent of area of 1 km2Wetlands important indicators and drivers of high latitude climate. Changing lake dynamics can impact albedo and thermal absorption and carbon emissions. High latitude wetlands can have high carbon stocks and are dynamic and variable. To support regional LandCarbon carbon flux and permafrost modeling and future projection efforts, wetland maps were needed for bog and fen wetlands.These wetland results were presented and applied in He et al. 2016 and applied in McGuire et a. 2016 and Pastick et al. accepted).
He, Y., Genet, H., McGuire, A.D., Zhuang, Q., Wylie, B.K., and Zhang, Y., 2016, Terrestrial carbon modeling—Baseline and projections in lowland ecosystems of Alaska, chap. 7 in Zhu, Z., and McGuire, A.D., eds., Baseline and projected future carbon storage and greenhouse-gas fluxes in ecosystems of Alaska: U. S. Geological Survey Professional Paper 1826, p. 133-158, at http://dx.doi.org/10.3133/pp1826.
McGuire, A.D., Genet, H., He, Y., Stackpoole, S., D'Amore, D.V., Rupp, T.S., Wylie, B.K., Zhou, X., and Zhu, Z., 2016, Alaska carbon balance, chap. 9 in Zhu, Z., and McGuire, A.D., eds., Baseline and projected future carbon storage and greenhouse-gas fluxes in ecosystems of Alaska: U. S. Geological Survey Professional Paper 1826, p. 189-196, at
http://dx.doi.org/10.3133/pp1826.
Pastick, N.J., Duffy, P., Genet, H., Rupp, T.S., Wylie, B.K., Johnson, K.D., Jorgenson, M.T., Bliss, N., McGuire, A.D., Jararov, E.E., and Knight, J.F., accepted, Historical and Projected Trends in Landscape Drivers Affecting Carbon Dynamics in Alaska, Ecological Applications.U.S. Geological Survey, CLIMATE & LAND-USEBruce K Wyliemailing address47914 252Nd StreetSioux FallsSD57198605-594-6078wylie@usgs.govDistributor assumes no liability for misuse of data.expected delivery will be at http://www.snap.uaf.edu/ but also anticipate availability at ScienceBase (https://www.sciencebase.gov/)20161222Bruce K WylieU.S. Geological Survey, CLIMATE & LAND-USEmailing address47914 252Nd StreetSioux FallsSD57198605-594-6078wylie@usgs.govFGDC Content Standard for Digital Geospatial MetadataFGDC-STD-001-1998