This data set provides annual spatial patterns of cropland, natural pasture, and planted pasture land uses across Amazonia for the period 1940/1950-1995. Two series of 5-minute grid cell historical maps were generated starting from land use classification products for 1995. Annual data are the fraction of natural pasture, planted pasture, and cropland in each 5-min grid cell. The annual maps are provided in two NetCDF (.nc) format file at 5-minute resolution. The AMZ-C.nc file covers the Brazilian portion of Amazon and Tocantins Rivers basins, and is based on the 1995 land use classification of Cardille et al. (2002), generated through the fusion of remote sensing (AVHRR) and agricultural census data. The second file, AMZ-R.nc, covers the entire Legal Amazon region and adjacent areas and is based on the 1995 land use classification by Ramankutty et al. (2008). The land use classification was generated by the fusion of satellite imagery (MODIS and VEGETATION-SPOT) and data from the agricultural census. A historical land-use reconstruction algorithm was used to generate the annual spatial patterns (based on work from Ramunkutty and Foley, 1999).

The Town of Apex was incorporated in 1873. N.C.G.S. 160A-22 requires current city boundaries to be drawn at all times on a map. This statute also requires that all alterations to the boundaries (annexations) be indicated on the map. This shapefiles depicts all individual additions to the boundaries of the Town of Apex corporate limits. Additions to the boundary occur a maximum of twice a month as the Town Council approves annexation requests from property owners. Boundary locations are based on legal descriptions referenced in the approved annexation ordinances recorded with the Town, Wake County, and North Carolina Secretary of State. Older annexations may not match with more recent annexations due to datum changes and variations in survey accuracy.

Guilford County enjoys a rich history and a strong sense of pride in its past. The County is committed to protect the rich inheritance by recognizing and protecting sites that embody elements of culture, history, architectural story. The Guilford County Historic Preservation Commission has recognized individual sites through a standard voluntary process established by state law, known as Landmark sites. Once recognized, alterations to these designated Landmarks are monitored, and changes can be made upon receiving approval by the Commission. This story map is a virtual tour to all such Landmark properties in Guilford County, North Carolina.

In the face of sea level rise and as climate change conditions increase the frequency and intensity of tropical storms along the north-Atlantic Coast, coastal areas will become increasingly vulnerable to storm damage, and the decline of already-threatened species could be exacerbated. Predictions about response of coastal birds to effects of hurricanes will be essential for anticipating and countering environmental impacts. This project will assess coastal bird populations, behavior, and nesting in Hurricane Sandy-impacted North Carolina barrier islands. The project comprises three components: 1) ground-based and airborne lidar analyses to examine site specific selection criteria of coastal birds; 2) NWI classification habitat mapping of DOI lands to examine habitat change associated with Hurricane Sandy, particularly in relation to coastal bird habitat; and 3) a GIS-based synthesis of how patterns of coastal bird distribution and abundance and their habitats have been shaped by storms such as Hurricane Sandy, coastal development, population density, and shoreline management over the past century. We will trace historic changes to shorebird populations and habitats in coastal North Carolina over the past century. Using historic maps and contemporary imagery, the study will quantify changes in shorebird populations and their habitats resulting from periodic storms such as Hurricane Sandy in 2012, to development projects such as the Intracoastal Waterway early in the last century, as well as more recent urban development. We will synthesize existing data on the distribution and abundance of shorebirds in North Carolina and changes in habitats related to storms, coastal development, inlet modifications, and shoreline erosion to give us a better understanding of historic trends for shorebirds and their coastal habitats. Historic data on the distribution and abundance of shorebirds are available from a variety of sources and include bird species identification, location, activity, habitat, and band data. Habitat maps of federal lands in the study area will be created using National Wetlands Inventory mapping standards to assess storm impacts on available nesting habitat. Ground-based LIDAR and high-accuracy GPS data will be collected to develop methods to estimate shorebird nest elevation and microtopography to make predictions about nest site selection and success. Microtopography information collected from lidar data in the area immediately surrounding nest site locations will be used to analyze site specific nesting habitat selection criteria related to topography, substrate (coarseness of sand or cobble), and vegetation cover. The data will be used in future models to assess storm impacts on nest locations, predict long-term population impacts, and influence landscape-scale habitat management strategies that might lessen future impacts of hurricanes on coastal birds and lead to better restoration alternatives.

In the face of sea level rise and as climate change conditions increase the frequency and intensity of tropical storms along the north-Atlantic Coast, coastal areas will become increasingly vulnerable to storm damage, and the decline of already-threatened species could be exacerbated. Predictions about response of coastal birds to effects of hurricanes will be essential for anticipating and countering environmental impacts. This project will assess coastal bird populations, behavior, and nesting in Hurricane Sandy-impacted North Carolina barrier islands. The project comprises three components: 1) ground-based and airborne lidar analyses to examine site specific selection criteria of coastal birds; 2) NWI classification habitat mapping of DOI lands to examine habitat change associated with Hurricane Sandy, particularly in relation to coastal bird habitat; and 3) a GIS-based synthesis of how patterns of coastal bird distribution and abundance and their habitats have been shaped by storms such as Hurricane Sandy, coastal development, population density, and shoreline management over the past century. We will trace historic changes to shorebird populations and habitats in coastal North Carolina over the past century. Using historic maps and contemporary imagery, the study will quantify changes in shorebird populations and their habitats resulting from periodic storms such as Hurricane Sandy in 2012, to development projects such as the Intracoastal Waterway early in the last century, as well as more recent urban development. We will synthesize existing data on the distribution and abundance of shorebirds in North Carolina and changes in habitats related to storms, coastal development, inlet modifications, and shoreline erosion to give us a better understanding of historic trends for shorebirds and their coastal habitats. Historic data on the distribution and abundance of shorebirds are available from a variety of sources and include bird species identification, location, activity, habitat, and band data. Habitat maps of federal lands in the study area will be created using National Wetlands Inventory mapping standards to assess storm impacts on available nesting habitat. Ground-based LIDAR and high-accuracy GPS data will be collected to develop methods to estimate shorebird nest elevation and microtopography to make predictions about nest site selection and success. Microtopography information collected from lidar data in the area immediately surrounding nest site locations will be used to analyze site specific nesting habitat selection criteria related to topography, substrate (coarseness of sand or cobble), and vegetation cover. The data will be used in future models to assess storm impacts on nest locations, predict long-term population impacts, and influence landscape-scale habitat management strategies that might lessen future impacts of hurricanes on coastal birds and lead to better restoration alternatives.

Geospatial inventory of Historic Properties in Mecklenburg County, NC.

This dataset consists of a netCDF file with a number of layers at half-degree global resolution. Each layer is a binary map representing whether each gridcell is included (1 if yes, 0 if no) in one or more input datasets used in the ISIMIP3 Agriculture (GGCMI phase 3) model runs. Individual-dataset masks:

has_soil indicates inclusion in the ISIMIP3 soil input dataset (Volkholz & Müller, 2020) (ignoring "gravel," which has some missing cells).

has_cropcals indicates inclusion in the Jägermeyr et al. (publication in prep.) crop calendar dataset (ignoring second-season rice, which is not grown in all gridcells).

has_lu indicates inclusion in all 15 area maps in the historical land use area dataset prepared for ISIMIP3 (landuse-totals_histsoc_annual_1850_2014.nc).

has_crops indicates inclusion in all 15 area maps in the historical 15-crop dataset prepared for ISIMIP3 (landuse-15crops_histsoc_annual_1850_2014.nc). Note that there are two gridcells that are missing from this

has_fertilizer indicates inclusion in every fertilizer_application_histsoc*.nc file in the fertilizer and manure dataset prepared by Heinke et al. (2021) for GGCMI3.

has_all is a composite mask indicating inclusion in all of the above.

Also included are a figure showing the masks and the MATLAB script used to generate the data and figure.

These data were collected to reconstruct spatially explicit land use/land cover change trajectories that were temporally consistent and at very high accuracies for a selection of watersheds in Macon County, NC: Cartoogechaye, Coweeta, Skeenah and Watauga. Buildings (points) and roads (lines) were digitized from historic maps and aerial photographs and aligned where necessary for temporal consistency. Land cover was simultaneously classified across all years for each 25x25m pixel (1/16 ha) in order to maximize temporal consistency.

This map was created for a Story Map titled "Historic summer heat in the U.S."Much of the U.S. is statistically likely to experience their hottest day of the year between mid-July and mid-August. In honor of that sweltering milestone, we've created these maps of the hottest summer temperature on record for thousands of U.S. locations.The map contains two hosted tile layers: Hottest maximum temperature ("daytime high") recorded at a given station between June 21 and September 22 during its entire history; and the week of the summer when a station's record was set. The third layer is a hosted feature layer of the point data from CICS-NC providing pop-up information.These maps are based on NOAA's Global Historical Climatology Network -Daily data. The length of station histories varies, but all stations have, at minimum, data for the period 1981-2010 (the current U.S. Climate Normals period). All have been subjected to a common suite of quality assurance reviews. For stations that are still operating, the analysis covers observations through summer 2016. Analysis provided by Jared Rennie, Cooperative Institute for Climate and Satellites - North Carolina.

Historic Buildings, including Landmark Buildings.

Fish community collection sites are typically located at bridge crossings or other public access points on second, third, and fourth order streams where backpack electrofishing methods can be safely and efficiently applied. Historic NCIBI stations and ratings throughout NC are indicated on the map, representing a site's most recent fish community survey from the early 1990’s through 2022.Last Data Update: 04/26/23