A 6-in resolution 8-class land cover dataset derived from the 2017 Light Detection and Ranging (LiDAR) data capture. This dataset was developed as part of an updated urban tree canopy assessment and therefore represents a ''top-down" mapping perspective in which tree canopy overhanging features is assigned to the tree canopy class. The eight land cover classes mapped were: (1) Tree Canopy, (2) Grass\Shrubs, (3) Bare Soil, (4) Water, (5) Buildings, (6) Roads, (7) Other Impervious, and (8) Railroads. The primary sources used to derive this land cover layer were 2017 LiDAR (1-ft post spacing) and 2016 4-band orthoimagery (0.5-ft resolution). Object based image analysis was used to automate land-cover features using LiDAR point clouds and derivatives, orthoimagery, and vector GIS datasets -- City Boundary (2017, NYC DoITT) Buildings (2017, NYC DoITT) Hydrography (2014, NYC DoITT) LiDAR Hydro Breaklines (2017, NYC DoITT) Transportation Structures (2014, NYC DoITT) Roadbed (2014, NYC DoITT) Road Centerlines (2014, NYC DoITT) Railroads (2014, NYC DoITT) Green Roofs (date unknown, NYC Parks) Parking Lots (2014, NYC DoITT) Parks (2016, NYC Parks) Sidewalks (2014, NYC DoITT) Synthetic Turf (2018, NYC Parks) Wetlands (2014, NYC Parks) Shoreline (2014, NYC DoITT) Plazas (2014, NYC DoITT) Utility Poles (2014, ConEdison via NYCEM) Athletic Facilities (2017, NYC Parks)

For the purposes of classification, only vegetation > 8 ft were classed as Tree Canopy. Vegetation below 8 ft was classed as Grass/Shrub.

To learn more about this dataset, visit the interactive "Understanding the 2017 New York City LiDAR Capture" Story Map -- https://maps.nyc.gov/lidar/2017/ Please see the following link for additional documentation on this dataset -- https://github.com/CityOfNewYork/nyc-geo-metadata/blob/master/Metadata/Metadata_LandCover.md

This group of maps, which includes the CanMatrix and CanTopo collections, is now a legacy product that is no longer maintained. It may not meet current government standards. Natural Resources Canada's (NRCan) topographic raster maps provide a representation of the topographic phenomena of the Canadian landmass. Several editions of paper maps have been produced over time in order to offer improved products compared to their predecessors in terms of quality and the most up to date information possible. The georeferenced maps can be used in a Geographic Information System (GIS). In all cases, they accurately represent the topographical data available for the date indicated (validity date). The combination of CanMatrix and CanTopo data provides complete national coverage. • CanMatrix - Print Ready: Raster maps produced by scanning topographic maps at scales from 1:25 000 to 1:1 000 000. This product is not georeferenced. Validity dates: 1944 to 2005 (1980 on average). Available formats: PDF and TIFF • CanMatrix - Georeferenced: Raster maps produced by scanning topographic maps at scales of 1:50 000 and 1:250 000. These maps are georeferenced according to the 1983 North American Reference System (NAD 83). Validity dates: 1944 to 2005 (1980 on average). Available format: GeoTIFF • CanTopo: Digital raster maps produced mainly from the GeoBase initiative, NRCan digital topographic data, and other sources. Approximately 2,234 datasets (maps) at scale of 1:50 000, primarily covering northern Canada, are available. CanTopo datasets in GeoPDF and GeoTIFF format are georeferenced according to the 1983 North American Reference System (NAD 83). Validity dates: 1946 to 2012 (2007 on average). Available formats: PDF, GeoPDF, TIFF and GeoTIFF

Landscape change in Tuolumne Meadows, Yosemite National Park, California, was characterized using data derived from four lidar surveys: one airborne survey in 2006 and three terrestrial surveys in 2016, 2017, and 2018. These surveys were used to generate a better quantitative understanding of changes associated with fluvial processes along the reach of the Tuolumne River where it crosses Tuolumne Meadows. The dataset consist of five archive (*.zip) files. These are: raster_data_geotiff.zip tabular_data_csv.zip vector_data_extractionareas_stable_areas_streambanks.zip lidar_pointcloud_data_laz.zip photo_data_jpg.zip Metadata for all files is contained within each .zip archive

OS Open Raster stack of GB for use as base mapping from national scale through to street level data. The currency of the data is: GB Overview Maps - 12/2014 MiniScale - 01/2024 OS 250K Raster - 06/2024Vector Map District Raster - 05/2024Open Map Local Raster - 10/2024 The coverage of the map service is GB. The map projection is British National Grid. The service is appropriate for viewing down to a scale of approximately 1:2,500. For more information on OS Open Services see: https://osdatahub.os.uk/downloads/open Updated: 29/10/2024

The Cooperative Land Cover Map is a project to develop an improved statewide land cover map from existing sources and expert review of aerial photography. The project is directly tied to a goal of Florida's State Wildlife Action Plan (SWAP) to represent Florida's diverse habitats in a spatially-explicit manner. The Cooperative Land Cover Map integrates 3 primary data types: 1) 6 million acres are derived from local or site-specific data sources, primarily on existing conservation lands. Most of these sources have a ground-truth or local knowledge component. We collected land cover and vegetation data from 37 existing sources. Each dataset was evaluated for consistency and quality and assigned a confidence category that determined how it was integrated into the final land cover map. 2) 1.4 million acres are derived from areas that FNAI ecologists reviewed with high resolution aerial photography. These areas were reviewed because other data indicated some potential for the presence of a focal community: scrub, scrubby flatwoods, sandhill, dry prairie, pine rockland, rockland hammock, upland pine or mesic flatwoods. 3) 3.2 million acres are represented by Florida Land Use Land Cover data from the FL Department of Environmental Protection and Water Management Districts (FLUCCS). The Cooperative Land Cover Map integrates data from the following years: NWFWMD: 2006 - 07 SRWMD: 2005 - 08 SJRWMD: 2004 SFWMD: 2004 SWFWMD: 2008 All data were crosswalked into the Florida Land Cover Classification System. This project was funded by a grant from FWC/Florida's Wildlife Legacy Initiative (Project 08009) to Florida Natural Areas Inventory. The current dataset is provided in 10m raster grid format.Changes from Version 1.1 to Version 2.3:CLC v2.3 includes updated Florida Land Use Land Cover for four water management districts as described above: NWFWMD, SJRWMD, SFWMD, SWFWMDCLC v2.3 incorporates major revisions to natural coastal land cover and natural communities potentially affected by sea level rise. These revisions were undertaken by FNAI as part of two projects: Re-evaluating Florida's Ecological Conservation Priorities in the Face of Sea Level Rise (funded by the Yale Mapping Framework for Biodiversity Conservation and Climate Adaptation) and Predicting and Mitigating the Effects of Sea-Level Rise and Land Use Changes on Imperiled Species and Natural communities in Florida (funded by an FWC State Wildlife Grant and The Kresge Foundation). FNAI also opportunistically revised natural communities as needed in the course of species habitat mapping work funded by the Florida Department of Environmental Protection. CLC v2.3 also includes several new site specific data sources: New or revised FNAI natural community maps for 13 conservation lands and 9 Florida Forever proposals; new Florida Park Service maps for 10 parks; Sarasota County Preserves Habitat Maps (with FNAI review); Sarasota County HCP Florida Scrub-Jay Habitat (with FNAI Review); Southwest Florida Scrub Working Group scrub polygons. Several corrections to the crosswalk of FLUCCS to FLCS were made, including review and reclassification of interior sand beaches that were originally crosswalked to beach dune, and reclassification of upland hardwood forest south of Lake Okeechobee to mesic hammock. Representation of state waters was expanded to include the NOAA Submerged Lands Act data for Florida.Changes from Version 2.3 to 3.0: All land classes underwent revisions to correct boundaries, mislabeled classes, and hard edges between classes. Vector data was compared against high resolution Digital Ortho Quarter Quads (DOQQ) and Google Earth imagery. Individual land cover classes were converted to .KML format for use in Google Earth. Errors identified through visual review were manually corrected. Statewide medium resolution (spatial resolution of 10 m) SPOT 5 images were available for remote sensing classification with the following spectral bands: near infrared, red, green and short wave infrared. The acquisition dates of SPOT images ranged between October, 2005 and October, 2010. Remote sensing classification was performed in Idrisi Taiga and ERDAS Imagine. Supervised and unsupervised classifications of each SPOT image were performed with the corrected polygon data as a guide. Further visual inspections of classified areas were conducted for consistency, errors, and edge matching between image footprints. CLC v3.0 now includes state wide Florida NAVTEQ transportation data. CLC v3.0 incorporates extensive revisions to scrub, scrubby flatwoods, mesic flatwoods, and upland pine classes. An additional class, scrub mangrove – 5252, was added to the crosswalk. Mangrove swamp was reviewed and reclassified to include areas of scrub mangrove. CLC v3.0 also includes additional revisions to sand beach, riverine sand bar, and beach dune previously misclassified as high intensity urban or extractive. CLC v3.0 excludes the Dry Tortugas and does not include some of the small keys between Key West and Marquesas.Changes from Version 3.0 to Version 3.1: CLC v3.1 includes several new site specific data sources: Revised FNAI natural community maps for 31 WMAs, and 6 Florida Forever areas or proposals. This data was either extracted from v2.3, or from more recent mapping efforts. Domains have been removed from the attribute table, and a class name field has been added for SITE and STATE level classes. The Dry Tortugas have been reincorporated. The geographic extent has been revised for the Coastal Upland and Dry Prairie classes. Rural Open and the Extractive classes underwent a more thorough reviewChanges from Version 3.1 to Version 3.2:CLC v3.2 includes several new site specific data sources: Revised FNAI natural community maps for 43 Florida Park Service lands, and 9 Florida Forever areas or proposals. This data is from 2014 - 2016 mapping efforts. SITE level class review: Wet Coniferous plantation (2450) from v2.3 has been included in v3.2. Non-Vegetated Wetland (2300), Urban Open Land (18211), Cropland/Pasture (18331), and High Pine and Scrub (1200) have undergone thorough review and reclassification where appropriate. Other classification errors were opportunistically corrected as found or as reported by users to landcovermap@myfwc.com. Changes from Version 3.2.5 to Version 3.3: The CLC v3.3 includes several new site specific data sources: Revised FNAI natural community maps for 14 FWC managed or co-managed lands, including 7 WMA and 7 WEA, 1 State Forest, 3 Hillsboro County managed areas, and 1 Florida Forever proposal. This data is from the 2017 – 2018 mapping efforts. Select sites and classes were included from the 2016 – 2017 NWFWMD (FLUCCS) dataset. M.C. Davis Conservation areas, 18331x agricultural classes underwent a thorough review and reclassification where appropriate. Prairie Mesic Hammock (1122) was reclassified to Prairie Hydric Hammock (22322) in the Everglades. All SITE level Tree Plantations (18333) were reclassified to Coniferous Plantations (183332). The addition of FWC Oyster Bar (5230) features. Other classification errors were opportunistically corrected as found or as reported by users to landcovermap@myfwc.com, including classification corrections to sites in T.M. Goodwin and Ocala National Forest. CLC v3.3 utilizes the updated The Florida Land Cover Classification System (2018), altering the following class names and numbers: Irrigated Row Crops (1833111), Wet Coniferous Plantations (1833321) (formerly 2450), Major Springs (4131) (formerly 3118). Mixed Hardwood-Coniferous Swamps (2240) (formerly Other Wetland Forested Mixed).Changes from Version 3.4 to Version 3.5: The CLC v3.5 includes several new site specific data sources: Revised FNAI natural community maps for 16 managed areas, and 10 Florida Forever Board of Trustees Projects (FFBOT) sites. This data is from the 2019 – 2020 mapping efforts. Other classification errors were opportunistically corrected as found or as reported by users to landcovermap@myfwc.com. This version of the CLC is also the first to include land identified as Salt Flats (5241).Changes from Version 3.5 to 3.6: The CLC v3.6 includes several new site specific data sources: Revised FNAI natural community maps for 11 managed areas, and 24 Florida Forever Board of Trustees Projects (FFBOT) sites. This data is from the 2018 – 2022 mapping efforts. Other classification errors were opportunistically corrected as found or as reported by users to landcovermap@myfwc.com. Changes from Version 3.6 to 3.7: The CLC 3.7 includes several new site specific data sources: Revised FNAI natural community maps for 5 managed areas (2022-2023). Revised Palm Beach County Natural Areas data for Pine Glades Natural Area (2023). Other classification errors were opportunistically corrected as found or as reported by users to landcovermap@myfwc.com. In this version a few SITE level classifications are reclassified for the STATE level classification system. Mesic Flatwoods and Scrubby Flatwoods are classified as Dry Flatwoods at the STATE level. Upland Glade is classified as Barren, Sinkhole, and Outcrop Communities at the STATE level. Lastly Upland Pine is classified as High Pine and Scrub at the STATE level.Changes from Version 3.7 to 4.0: CLC 4.0 represents a major update to CLC performed cooperatively by FWC and FNAI via a State Wildlife Grant to address changes on the landscape such as conversion to development and to integrate other recent high quality land cover sources. CLC v4.0 includes FWC's comprehensive delineation of solar farms, FLUCCS updates based on aerial photos from 2017-2022, ground-truthed mapping from FNAI and Florida Park Service, a statewide update of Intensive Development from Google Dynamic World land cover as of 2024, and additional FNAI review and revisions of target classes including sand beach and beach dune. A complete description of updates is available in the Cooperative Land Cover version 4.0 report, available from FNAI

This dataset consists of a 25m resolution raster version of the Land Cover Map 2000 for Great Britain. Each 25m pixel represents a 25m area of land cover target class, broadly representing Broad Habitats (see below). The dataset is part of a series of data products produced by the Centre for Ecology & Hydrology known as LCM2000. LCM2000 is a parcel-based thematic classification of satellite image data covering the entire United Kingdom. The map updates and upgrades the Land Cover Map of Great Britain (LCMGB) 1990. Like the earlier 1990 products, LCM2000 is derived from a computer classification of satellite scenes obtained mainly from Landsat, IRS and SPOT sensors and also incorporates information derived from other ancillary datasets. LCM2000 was classified using a nomenclature corresponding to the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompasses the entire range of UK habitats. In addition, it recorded further detail where possible. The series of LCM2000 products includes vector and raster formats, with a number of different versions containing varying levels of detail and at different spatial resolutions.

Summary of Methods for Developing Ecological Units in Southern California

Allan Hollander and Emma Underwood, University of California Davis.

1) Compiling GIS layers. These data were compiled from a variety of sources and resolutions (Table 1) for the southern California study area (see Methods_figure_1.png for the study area). The original resolution of these raster layers ran from 10 meters to 270 meters, and resampling was conducted so all analyses were performed at a 30 meter raster resolution. We decided not to include vegetation in the data stack as the aim was to capture biophysical characteristics and vegetation will reflect current landscape history and land use patterns (e.g. fire history, type conversion from shrubland, or agricultural use). Lakes and reservoirs were omitted from the subsequent analysis. Data compiled:

a) Soil suborders. This was a discretely-classified raster layer with 22 soil suborder classes included in the southern California region. This was derived ...

We summarized annual remote sensing land cover classifications from the U.S. Geological Survey Land Cover Monitoring, Assessment, and Projection (LCMAP) annual time series to characterize forest change across the conterminous United States (CONUS) for the years 1985-2020. The raster output includes a map where each pixel is given an integer value based on the number of years in which it was classified as forest across the annual LCMAP time series. Values of 36 indicate the pixel was classified as forest across all years while a value of 0 indicates forests (tree cover) was never detected during the time series.

The product represents a new design of the State Map at a scale of 1:5,000 in raster form, whose advantages are recency and colour processing. The map contains planimetry based on cadastral map, altimetry adopted from the altimetry part of ZABAGED and map lettering based on database of geographic names Geonames and abbreviations of feature type signification coming up from attributes of selected ZABAGED features. The cartographic visualisation is solved automatically without manual works of a cartographer. This new design of the SM 5 is repeatedly generated once a year on the part of the Czech territory where the vector form of cadastral map is available. Therefore, part of export units (map sheets of SM 5) has not a full coverage (price of such export unit is then proportionally reduced).

DOWNLOAD RASTER IMAGERYRS-FRIS Version 5.4 is a remote-sensing based forest inventory for WA DNR State Trust lands. Predictions are derived from three-dimensional photogrammetric point cloud data (DAP), field measurements, and statistical models. RS-FRIS 5.4 was constructed using remote sensing data collected in 2021 and 2022, and incorporates depletions for selected completed harvest types through 2025-08-31.

The product represents a new design of the State Map at a scale of 1:5,000 in raster form, whose advantages are recency and colour processing. The map contains planimetry based on cadastral map, altimetry adopted from the altimetry part of ZABAGED and map lettering based on database of geographic names Geonames and abbreviations of feature type signification coming up from attributes of selected ZABAGED features. The cartographic visualisation is solved automatically without manual works of a cartographer. This new design of the SM 5 is repeatedly generated once a year on the part of the Czech territory where the vector form of cadastral map is available. Therefore, part of export units (map sheets of SM 5) has not a full coverage (price of such export unit is then proportionally reduced).

Colour and greyscale OS raster mapping for UK

1:1,000,000 raster map of Northern Ireland with place names. A raster map is a static image displayed on screen which is suitable as background mapping. 1:1 000,000 Raster is smallest scale OSNI raster product giving an excellent overview of Northern Ireland. Published here for OpenData. By download or use of this dataset you agree to abide by the Open Government Data Licence.Please Note for Open Data NI Users: Esri Rest API is not Broken, it will not open on its own in a Web Browser but can be copied and used in Desktop and Webmaps

This set of raster maps at 1:50 000 scale shows base mapping with settlements, roads, townland names and boundaries.

A series of maps at 1:10 000 scale showing base mapping for Northern Ireland. These raster maps can be used with other maps or information to enhance the mapping. Midscale Raster for Northern Ireland can be used as a general background to give context at local and regional level and as a base to overlay data. Includes water bodies, rivers, main roads, town names and townlands.

The product represents a new design of the State Map at a scale of 1:5,000 in raster form, whose advantages are recency and colour processing. The map contains planimetry based on cadastral map, altimetry adopted from the altimetry part of ZABAGED and map lettering based on database of geographic names Geonames and abbreviations of feature type signification coming up from attributes of selected ZABAGED features. The cartographic visualisation is solved automatically without manual works of a cartographer. This new design of the SM 5 is repeatedly generated once a year on the part of the Czech territory where the vector form of cadastral map is available. Therefore, part of export units (map sheets of SM 5) has not a full coverage (price of such export unit is then proportionally reduced).

The product represents a new design of the State Map at a scale of 1:5,000 in raster form, whose advantages are recency and colour processing. The map contains planimetry based on cadastral map, altimetry adopted from the altimetry part of ZABAGED and map lettering based on database of geographic names Geonames and abbreviations of feature type signification coming up from attributes of selected ZABAGED features. The cartographic visualisation is solved automatically without manual works of a cartographer. This new design of the SM 5 is repeatedly generated once a year on the part of the Czech territory where the vector form of cadastral map is available. Therefore, part of export units (map sheets of SM 5) has not a full coverage (price of such export unit is then proportionally reduced).

The purpose of this acquisition was to provide LiDAR data for portions of the Kaibab National Forest and Grand Canyon National Park on the Kaibab Plateau, in support of ongoing studies of Northern Goshawk demographics. 3Di West, through its subcontractor Watershed Sciences Incorporated (WSI), acquired LiDAR data for over 450,000 acres in the summer of 2012.

Note that raster products are not all at the same spatial resolution:

This dataset consists of a 25m resolution raster version of the Land Cover Map 2007 for Great Britain. Each 25m pixel represents a 25m area of land cover target class, broadly representing Broad Habitats (see below). The dataset is part of a series of data products produced by the Centre for Ecology & Hydrology known as LCM2007. LCM2007 is a parcel-based thematic classification of satellite image data covering the entire United Kingdom. The map updates and upgrades the Land Cover Map of Great Britain (LCMGB) 1990 and LCM2000. Like the earlier 1990 and 2000 products, LCM2007 is derived from a computer classification of satellite scenes obtained mainly from Landsat, IRS and SPOT sensors and also incorporates information derived from other ancillary datasets. LCM2007 was classified using a nomenclature corresponding to the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompasses the entire range of UK habitats. In addition, it recorded further detail where possible. The series of LCM2007 products includes vector and raster formats, with a number of different versions containing varying levels of detail and at different spatial resolutions.

Land cover maps are the basic data layer required for understanding and modeling ecological patterns and processes. The Circumpolar Arctic Vegetation Map (CAVM), produced in 2003, has been widely used as a base map for studies in the arctic tundra biome. However, the relatively coarse resolution and vector format of the map were not compatible with many other data sets. We present a new version of the CAVM, building on the strengths of the original map, while providing a finer spatial resolution, raster format, and improved mapping. The Raster CAVM uses the legend, extent and projection of the original CAVM. The legend has 16 vegetation types, glacier, saline water, freshwater, and non-arctic land. The Raster CAVM divides the original rock-water-vegetation complex map unit that mapped the Canadian Shield into two map units, one with lichen-dominated vegetation and one with shrub-dominated vegetation. In contrast to the original hand-drawn CAVM, the raster map is based on unsupervised classifications of seventeen geographic/floristic sub-sections of the Arctic, using AVHRR and MODIS data (reflectance data and NDVI) and elevation data. The units resulting from the classification were modeled to the CAVM types using a wide variety of ancillary data. The map was reviewed by experts familiar with their particular region, including of the original authors of the CAVM from the U.S., Canada, Greenland (Denmark), Iceland, Norway (including Svalbard) and Russia.

Detailed information about the methods can be found in the publication to which this dataset is a supplement.

Citation

In order to use these data, you must cite this data set with the following citation:

Raynolds, Martha; Walker, Donald (2019), “Raster Circumpolar Arctic Vegetation Map”, Mendeley Data, v1 https://dx.doi.org/10.17632/c4xj5rv6kv.1