The thematic land cover dataset was created in raster format by NOAA's Coastal Change Analysis Program (C-CAP). C-CAP has produced numerous standardized land cover products which are included in the National Land Cover Database. These products are used in numerous ways to assess urban growth, inventory wetlands, coastal intertidal areas, and adjacent uplands, and delineate wildlife habitat to monitor changes in these areas. This information helps in the understanding of the landscape's response to natural and human-caused changes.
MassGIS includes a layer file for use in ArcMap 10.4+ and ArcGIS Pro with each download. (Users will need to apply the symbology or reset the data source for each download.) The LYR uses the 'Unique values, many fields' option with COVERCODE and USEGENCODE and symbolizes all impervious polygons (COVERCODE = 2) based on their generalized use code; all non-impervious land cover polygons are symbolized by their land cover category. The idea behind this method is to use both cover and use codes to provide a truer picture of how land is being used: parcel use codes may indicate allowed or assessed, not actual use; land cover alone (especially impervious) does not indicate actual use.
MRLC hosts land cover and land condition data from various sources, including NLCD and Rangeland Condition Monitoring Assessment and Projection (RCMAP) time-series, Ecological Potential, and projections of future fractional rangeland components. Data are offered for download, as WMS services, and in applications.
The U.S. Geological Survey (USGS), in collaboration with the MRLC consortium and Bureau of Land Management (BLM), is pleased to announce the availability of a new generation of Rangeland, Condition, Monitoring, Assessment, and Projection (RCMAP) fractional component data spanning a 1985-2021 time-series. The new time-series includes yearly cover predictions for 9 components: shrub, sagebrush, non-sagebrush shrub, herbaceous, annual herbaceous, perennial herbaceous, litter, bare ground, and new to this version, tree cover. Trends statistics of the new time-series will be available by Jan 2023. Data are available for download and on the rangelands viewer. The new generation of data update previously released 1985-2020 RCMAP data and are not designed to be backwards compatible (1985-2020 cover predictions are different between versions). While users are encouraged to use the newest generation of data, the previous versions of the time-series data are archived.
The U.S. Geological Survey (USGS) has released a new generation of National Land Cover Database (NLCD) products named NLCD 2019 for the conterminous U.S. NLCD 2019 contains 34 different land cover products characterizing land cover and land cover change across 8 epochs from 2001-2019. Products include urban imperviousness and urban imperviousness change updated to match all landcover epochs; tree canopy and tree canopy change across 2 epochs from 2011-2016, with a 2019 and 2021 canopy suite set to be released in the next year; and RCMAP rangeland fractional component data including a 1985-2020 time-series, projections of future component cover through the 2080s, and Ecological Potential component cover. Data are available on this website either as prepackaged products or custom product areas can be interactively chosen using the viewer. NLCD 2019 represents the most comprehensive land cover database ever produced by the USGS and was specifically developed to meet the rapidly growing demand for land cover change data. NLCD is coordinated through the 10-member Multi Resolution Land Characteristics Consortium (MRLC), a two decades-long interagency federal government collaboration that has proved an exemplary model of cooperation among federal agencies to combine resources to provide digital land cover information for the Nation.
NLCD 2019 now offers land cover for years 2001, 2004, 2006, 2008, 2011, 2013, 2016, 2019, and impervious surface and impervious descriptor products now updated to match each date of land cover. These products update all previously released versions of landcover and impervious products for CONUS (NLCD 2001, NLCD 2006, NLCD 2011, NLCD 2016) and are not directly comparable to previous products. NLCD 2019 land cover and impervious surface product versions of previous dates must be downloaded for proper comparison. Also included with thelLand cover is the NLCD Land Cover Change Index. This index provides a simple and comprehensive way to visualize change from all 8 dates of land cover in a single layer. The change index was designed to assist NLCD users to understand complex land cover change with a single product. NLCD 2019 also offers an impervious surface descriptor product that identifies the type of each impervious surface pixel. This product identifies types of roads, wind tower sites, building locations, and energy production sites to allow deeper analysis of developed features.
TerrSet is an integrated constellation of applications for the monitoring and modeling of terrestrial systems, and offers innovative tools to intelligently address the main challenges of global growth: climate change, changes in land uses, ecosystem variations.
Studies have shown that the overall accuracy of the Global Land Survey (GLS) static forest cover is 91% with forest cover change at >88%. Echoing the accuracy of this paper, Central Park and the outer islands are clearly visible. The lack of forested areas on Fire island is consistent and logical. Things are looking good.
Studies have shown interannual variability with 40% of pixels showing the change in class one or more times in the 10-year span. Because of its coarseness, it misses the mark on Central Park and Fire Island. But Moderate Resolution Imaging Spectroradiometer (MODIS) captures the islands quite well.
The SLR-XA is an overlay of three hazards and does not account for interactive nature of these hazards as would be expected by natural processes. As with the individual exposure models, the SLR-XA maps hazard exposure on the present landscape. The modeling does not account for future (unknown) land use changes, including any adaptation measures. The SLR-XA also does not include impacts from less frequent high wave events (e.g., a 1-in-10 year event), storm surge, or tsunami. In addition, mapping errors may be found in some areas due to clipping (subsetting) of the original map layers using a shoreline (Special Management Area) boundary and possible modeling errors in the Annual High Wave Flooding model at reef and harbor channels (Figure 5). See descriptions of the individual Sea Level Rise Exposure models below for more information.
Assumptions and Limitations: Annual high wave flood modeling covered wave-exposed coasts with low-lying development on Maui, Oʻahu, and Kauaʻi. Annual high wave flooding was not available for the islands of Hawaiʻi, Molokaʻi, and Lānaʻi, nor for some harbors or other back-bay areas throughout all the islands. Additional studies would be needed to add the annual high wave flooding for those areas. The maximum annually recurring wave parameters (significant wave height, period, direction) were statistically determined using historical wave climate records and do not include potential changes in future wave climate, the effects of storm surge, or less-frequent high wave events (e.g., a 1-in-10 year wave event). In some locations, the extent of flooding modeled was limited by the extent of the 1-meter DEM.
Studies of historical shoreline change using aerial photographs and survey maps show that 70% of beaches on Kauaʻi, Oʻahu, and Maui are eroding (receding landward) (Fletcher et al. 2012). Beaches exist in a delicate balance between existing water levels, wave energy, and sand supply.
The combined SLR-XA from the 2017 Report was not updated with the updated 2020 erosion models. As a result, users may notice some mismatch between the coastal erosion projections and the SLR-XA in areas where the landward extent of the SLR-XA is defined by the coastal erosion hazard line. The addition of the new shoreline generally has a more pronounced influence on study areas with high seasonal or inter-annual variability in shoreline position. The coastal erosion exposure model is depicted as lines in the Viewer. The data are also available for download as polygons (exposure areas) below. In addition to changes in the landward extent of the erosion exposure areas, the seaward edge of updated erosion exposure polygons does not match up with the SLR-XA or the previous (2017) erosion exposure polygons. This is because the seaward edge of the 2017 data is defined by a Special Management Area shoreline boundary, whereas the seaward edge of the updated 2020 data is defined by the location of a vegetation line.
Assumptions and Limitations: Historical records of severe wave events used to model the 1%CFZ-3.2 do not consider potential changes in tropical cyclone or wave activity related to climate change. Also, riverine (rainfall) flooding is not included in the modeling. Historical data used to model the 1%CFZ-3.2 were based on the current Flood Insurance Study (FIS) for each island conducted by the FEMA NFIP. The FISs use historic severe wave events from hurricanes, tsunamis, and other significant events to develop the FIRMs.
National Wetlands Inventory (NWI) data can be accessed in several ways depending on your needs. To display and query wetlands data in your software application please use our Web Map Services. This will ensure you have the latest data and reduce data management overhead. If you need to conduct GIS analysis please reference the information below to download the data by watershed or by state. For downloads larger than a state, please contact the Wetlands Team to request a custom download.
Please note that NWI data is continuously being improved and new data is added on a biannual basis. Those updates are reflected on the Wetlands Mapper and in the data downloads in October and May of each year. To ensure that you have the most up to date information, please refer to the published date in the metadata, the location of new data on the Projects Mapper and download new data regularly. 2b1af7f3a8