IDWM vector datasets

These layers contain all of the MIT light grey basemap layers used for thematic mapping.

This is a subset of World Imagery (Firefly).This layer presents an alternative view of the World Imagery map designed to be used as a neutral imagery basemap, with de-saturated colors, that is useful for overlaying other brightly styled layers. This map is intended to support 'firefly cartography' and other cartographic designs that require a neutral background, with the spatial context and texture of imagery, to contrast with the foreground thematic layers that are designed to capture the users attention.Content meant to provide spatial context (the basemap) should recede in visual priority, helping to establish the thematic layers that they support (rather than compete with them). There are many ways to sufficiently mute your basemap, but for satellite imagery, de-saturation is a nice option. An image that is all or mostly black and white won’t compete as much with the brightly colored thematic data that it supports. With this map, the color of the imagery is mostly removed at the smallest global scales and then gradually re-introduced at the larger scales, where the full detail of the imagery is available.

This layer represents Land use polygons as determined by a combination of analytic techniques, mostly using Landsat 5 image mosaics . BTM 1 was done on a federal satellite image base that was only accurate to about 250m. The images were geo-corrected, not ortho-corrected, so there is distortion in areas of high relief. This is not a multipart feature

These layers contain all of the MIT light grey basemap layers used for thematic mapping.

This map features an alternative view of the World Imagery map designed to be used as a neutral imagery basemap, with de-saturated colors, that is useful for overlaying other brightly styled layers. This map is intended to support 'firefly cartography' and other cartographic designs that require a neutral background, with the spatial context and texture of imagery, to contrast with the foreground thematic layers that are designed to capture the users attention. The map also includes a reference layer.Content meant to provide spatial context (the basemap) should recede in visual priority, helping to establish the thematic layers that they support (rather than compete with them). There are many ways to sufficiently mute your basemap, but for satellite imagery, de-saturation is a nice option. An image that is all or mostly black and white won’t compete as much with the brightly colored thematic data that it supports. With this map, the color of the imagery is mostly removed at the smallest global scales and then gradually re-introduced at the larger scales, where the full detail of the imagery is available.

LAND_COVER_2006_USGS_IN is a grid (30-meter cell size) showing 2006 Land Cover data in Indiana. This grid is a subset of the National Land Cover Data (NLCD 2006) data set. There are 15 categories of land use shown in this data set when the associated layer file (LAND_COVER_2006_USGS_IN.LYR) is loaded. The following is excerpted from metadata provided by the USGS for the NLCD 2006: "The National Land Cover Database products are created through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of federal agencies (www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (EPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (FWS), the Bureau of Land Management (BLM) and the USDA Natural Resources Conservation Service (NRCS). Previously, NLCD consisted of three major data releases based on a 10-year cycle. These include a circa 1992 conterminous U.S. land cover dataset with one thematic layer (NLCD 1992), a circa 2001 50-state/Puerto Rico updated U.S. land cover database (NLCD 2001) with three layers including thematic land cover, percent imperviousness, and percent tree canopy, and a 1992/2001 Land Cover Change Retrofit Product. With these national data layers, there is often a 5-year time lag between the image capture date and product release. In some areas, the land cover can undergo significant change during production time, resulting in products that may be perpetually out of date. To address these issues, this circa 2006 NLCD land cover product (NLCD 2006) was conceived to meet user community needs for more frequent land cover monitoring (moving to a 5-year cycle) and to reduce the production time between image capture and product release. NLCD 2006 is designed to provide the user both updated land cover data and additional information that can be used to identify the pattern, nature, and magnitude of changes occurring between 2001 and 2006 for the conterminous United States at medium spatial resolution. For NLCD 2006, there are 3 primary data products: 1) NLCD 2006 Land Cover map; 2) NLCD 2001/2006 Change Pixels labeled with the 2006 land cover class; and 3) NLCD 2006 Percent Developed Imperviousness. Four additional data products were developed to provide supporting documentation and to provide information for land cover change analysis tasks: 4) NLCD 2001/2006 Percent Developed Imperviousness Change; 5) NLCD 2001/2006 Maximum Potential Change derived from the raw spectral change analysis; 6) NLCD 2001/2006 From-To Change pixels; and 7) NLCD 2006 Path/Row Index vector file showing the footprint of Landsat scene pairs used to derive 2001/2006 spectral change with change pair acquisition dates and scene identification numbers included in the attribute table. In addition to the 2006 data products listed in the paragraph above, two of the original release NLCD 2001 data products have been revised and reissued. Generation of NLCD 2006 data products helped to identify some update issues in the NLCD 2001 land cover and percent developed imperviousness data products. These issues were evaluated and corrected, necessitating a reissue of NLCD 2001 data products (NLCD 2001 Version 2.0) as part of the NLCD 2006 release. A majority of NLCD 2001 updates occur in coastal mapping zones where NLCD 2001 was published prior to the National Oceanic and Atmospheric Administration (NOAA) Coastal Change Analysis Program (C-CAP) 2001 land cover products. NOAA C-CAP 2001 land cover has now been seamlessly integrated with NLCD 2001 land cover for all coastal zones. NLCD 2001 percent developed imperviousness was also updated as part of this process. As part of the NLCD 2011 project, NLCD 2006 data products have been revised and reissued (2011 Edition) to provide full compatibility with all other NLCD 2011 Edition products. The 2014 amended version corrects for the over-elimination of small areas of the four developed classes. Land cover maps, derivatives and all associated documents are considered "provisional" until a formal accuracy assessment can be conducted. The NLCD 2006 is created on a path/row basis and mosaicked to create a seamless national product. Questions about the NLCD 2006 land cover product can be directed to the NLCD 2006 land cover mapping team at the USGS/EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov."

The VMap Level 0 database provides worldwide coverage of vector-based geospatial data which can be viewed at 1:1,000,000 scale. It consists of geographic, attribute, and textual data. The complete database is organized into 10 thematic layers. The top level thematic layers are: Boundaries, elevation, hydrography, industry, physiography, population, transportation, utilities and vegetation. In addition, there are various layers underneath each top level category.

This layer represents Land use polygons as determined by a combination of analytic techniques, mostly using Landsat 5 image mosaics . BTM 1 was done on a federal satellite image base that was only accurate to about 250m. The images were geo-corrected, not ortho-corrected, so there is distortion in areas of high relief. This is not a multipart feature

The datasets are in MID/MIF formats to be processed in QGIS with use of self-written open source software. The datasets are used to model single or multiple socio-economic scenarios of regional spatial development and to build graded suitability maps.

The datasets contain:

• the 10x10 km grid, topographic layers (navigable rivers, railways, paved roads, settlements, and river ports), and semantic description of each unit area of the Novosibirsk region;
• thematic maps (accessibility maps) on navigational rivers, paved roads, railways, river ports, and settlements.

These data products are preliminary burn severity assessments derived from data obtained from suitable imagery (including Landsat TM, Landsat ETM+, Landsat OLI, Sentinel 2A, and Sentinel 2B). The pre-fire and post-fire subsets included were used to create a differenced Normalized Burn Ratio (dNBR) image. The dNBR image attempts to portray the variation of burn severity within a fire. The severity ratings are influenced by the effects to the canopy. The severity rating is based upon a composite of the severity to the understory (grass, shrub layers), midstory trees and overstory trees. Because there is often a strong correlation between canopy consumption and soil effects, this algorithm works in many cases for Burned Area Emergency Response (BAER) teams whose objective is a soil burn severity assessment. It is not, however, appropriate in all ecosystems or fires. It is expected that BAER teams will adjust the thresholds to match field observations to produce a soil burn severity. This map layer is a thematic raster image of burn severity classes for all inventoried fires occurring in CONUS. Fires omitted from this mapped inventory are those where suitable satellite imagery was not available, or fires which were not discernable from available imagery.

description: These are polygon and raster data sets derived from 2002 Landsat Thematic Mapper Satellite Imagery that indicates areas of land and areas of water in Louisiana. The interface is for the entire state within a 10 mile buffer. There are 4 layers: a 3 acre filter layer, a 5 acre filter layer, a 25 acre filter layer, and a 1 acre filter raster layer.; abstract: These are polygon and raster data sets derived from 2002 Landsat Thematic Mapper Satellite Imagery that indicates areas of land and areas of water in Louisiana. The interface is for the entire state within a 10 mile buffer. There are 4 layers: a 3 acre filter layer, a 5 acre filter layer, a 25 acre filter layer, and a 1 acre filter raster layer.

Burn severity layers are thematic images depicting severity as unburned to low, low, moderate, high, and increased greenness (increased post-fire vegetation response). The layer may also have a sixth class representing a mask for clouds, shadows, large water bodies, or other features on the landscape that erroneously affect the severity classification. This data has been prepared as part of the Monitoring Trends in Burn Severity (MTBS) project. Due to the lack of comprehensive fire reporting information and quality Landsat imagery, burn severity for all targeted MTBS fires are not available. Additionally, the availability of burn severity data for fires occurring in the current and previous calendar year is variable since these data are currently in production and released on an intermittent basis by the MTBS project.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.

This map is designed to be used as a base map by GIS professionals to overlay other thematic layers such as demographics or land cover. The base map features shaded relief imagery, bathymetry, and coastal water features designed to provide a neutral background for other data layers. The map was compiled from a variety of sources from several data providers, including the U.S. Geological Survey, NOAA, and Esri. The base map currently provides coverage for the world down to a scale of ~1:1m and coverage for the continental United States and Hawaii to a scale of ~1:70k. For more information on this map, including our terms of use, visit us online at http://goto.arcgisonline.com/maps/World_Terrain_Base

The National Land Cover Database products are created through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of federal agencies (www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (EPA), the U.S. Department of Agriculture - Forest Service (USDA-FS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM) and the USDA Natural Resources Conservation Service (NRCS). Previously, NLCD consisted of three major data releases based on a 10-year cycle. These include a circa 1992 conterminous U.S. land cover dataset with one thematic layer (NLCD 1992), a circa 2001 50-state/Puerto Rico updated U.S. land cover database (NLCD 2001 2011 Edition) with three layers including thematic land cover, percent imperviousness, and percent tree canopy, and a 1992/2001 Land Cover Change Retrofit Product. With these national data layers, there is often a 5-year time lag between the image capture date and product release. In some areas, the land cover can undergo significant change during production time, resulting in products that may be perpetually out of date. To address these issues, this circa 2006 NLCD land cover product (NLCD 2006 2011 Edition) was conceived to meet user community needs for more frequent land cover monitoring (moving to a 5-year cycle) and to reduce the production time between image capture and product release. NLCD 2006 (2011 edition) is designed to provide the user both updated land cover data and additional information that can be used to identify the pattern, nature, and magnitude of changes occurring between 2001 (2011 Edition) and 2006 (2011 Edition) for the conterminous United States at medium spatial resolution. For NLCD 2006 (2011 Edition), there are 4 primary data products: 1) NLCD 2006 Land Cover (2011 Edition); 2) NLCD 2001/2006 Land Cover Change Pixels (2011 Edition) labeled with the 2006 land cover class; 3) NLCD 2006 Percent Developed Imperviousness (2011 Edition), and 4) NLCD 2001/2006 Percent Developed Imperviousness Change (2011 Edition). In addition, ancillary metadata includes the NLCD 2006 Path/Row Index vector file showing the footprint of Landsat scene pairs used to derive 2001/2006 spectral change with change pair acquisition dates included in the attribute table. As part of the NLCD 2011 project, NLCD 2001 data products have been revised and reissued (2011 Edition) to provide full compatibility with all other NLCD 2011 Edition products. The 2014 amended version corrects for the over-elimination of small areas of the four developed classes. Land cover maps, derivatives and all associated documents are considered "provisional" until a formal accuracy assessment can be conducted. The NLCD 2006 is created on a path/row basis and mosaicked to create a seamless national product. Questions about the NLCD 2006 land cover product can be directed to the NLCD 2006 land cover mapping team at the USGS/EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.

These layers contain all of the MIT light grey basemap layers used for thematic mapping.

The establishment of a BES Multi-User Geodatabase (BES-MUG) allows for the storage, management, and distribution of geospatial data associated with the Baltimore Ecosystem Study. At present, BES data is distributed over the internet via the BES website. While having geospatial data available for download is a vast improvement over having the data housed at individual research institutions, it still suffers from some limitations. BES-MUG overcomes these limitations; improving the quality of the geospatial data available to BES researches, thereby leading to more informed decision-making. BES-MUG builds on Environmental Systems Research Institute's (ESRI) ArcGIS and ArcSDE technology. ESRI was selected because its geospatial software offers robust capabilities. ArcGIS is implemented agency-wide within the USDA and is the predominant geospatial software package used by collaborating institutions. Commercially available enterprise database packages (DB2, Oracle, SQL) provide an efficient means to store, manage, and share large datasets. However, standard database capabilities are limited with respect to geographic datasets because they lack the ability to deal with complex spatial relationships. By using ESRI's ArcSDE (Spatial Database Engine) in conjunction with database software, geospatial data can be handled much more effectively through the implementation of the Geodatabase model. Through ArcSDE and the Geodatabase model the database's capabilities are expanded, allowing for multiuser editing, intelligent feature types, and the establishment of rules and relationships. ArcSDE also allows users to connect to the database using ArcGIS software without being burdened by the intricacies of the database itself. For an example of how BES-MUG will help improve the quality and timeless of BES geospatial data consider a census block group layer that is in need of updating. Rather than the researcher downloading the dataset, editing it, and resubmitting to through ORS, access rules will allow the authorized user to edit the dataset over the network. Established rules will ensure that the attribute and topological integrity is maintained, so that key fields are not left blank and that the block group boundaries stay within tract boundaries. Metadata will automatically be updated showing who edited the dataset and when they did in the event any questions arise. Currently, a functioning prototype Multi-User Database has been developed for BES at the University of Vermont Spatial Analysis Lab, using Arc SDE and IBM's DB2 Enterprise Database as a back end architecture. This database, which is currently only accessible to those on the UVM campus network, will shortly be migrated to a Linux server where it will be accessible for database connections over the Internet. Passwords can then be handed out to all interested researchers on the project, who will be able to make a database connection through the Geographic Information Systems software interface on their desktop computer. This database will include a very large number of thematic layers. Those layers are currently divided into biophysical, socio-economic and imagery categories. Biophysical includes data on topography, soils, forest cover, habitat areas, hydrology and toxics. Socio-economics includes political and administrative boundaries, transportation and infrastructure networks, property data, census data, household survey data, parks, protected areas, land use/land cover, zoning, public health and historic land use change. Imagery includes a variety of aerial and satellite imagery. See the readme: http://96.56.36.108/geodatabase_SAL/readme.txt See the file listing: http://96.56.36.108/geodatabase_SAL/diroutput.txt

🇮🇹 이탈리아 English Please note: for a correct view and use of this dataset it is advisable to consult it at original page on the Arezzo Portal. At the same address there are also, for the enabled datasets, additional access formats, the preview of the visualization via API call, the consultation of the fields in DCAT-AP IT format, the possibility to express an evaluation and comment on the dataset itself. All resource formats available for this dataset can be downloaded as ZIP packages: inside the package sarà available the resource in the chosen format, complete with all the information on the metadata and the license associated with it. The conceptual model illustrated in the PDF file attached to the metadata sheet refers to the main classes adopted for the representation of the thematic layers in the QGIS project prepared for the realization of the cartographic elaboration referred to in the title of the sheet. The model was created as a diagram of the classes according to the UML language, adopting a reduced set of specifications. The classes represented in the diagram generally have a name coinciding with that of the corresponding dataset of the physical model. In the conceptual model, “classes” that are actually descriptive of layers representing particular thematic sub-sets of another class can also be illustrated by means of specific queries (Provided Feature Filter) and particular categorical representations. For the main classes are highlighted in special labels, with description enclosed by braces {}, the constraints (constraints) defined between the instances of the class and with the instances of the related classes. Additional natural language annotations have been added, including the name of the corresponding QGIS layer, a brief description of the class, and the data source. The colors assigned to the classes illustrated in the UML model are representative of the Spatialite geodatabases in which the corresponding datasets are stored: a descriptive legend of the various reference geodatabases has been reported in the UML model.

Important Note: This item is in mature support as of December 2024. See blog for more information.This 3D scene layer presents OpenStreetMap (OSM) trees data hosted by Esri. Esri created buildings and trees scene layers from the OSM Daylight map distribution, which is supported by Facebook and others. The Daylight map distribution has been sunsetted and data updates supporting this layer are no longer available. You can visit openstreetmap.maps.arcgis.com to explore a collection of maps, scenes, and layers featuring OpenStreetMap data in ArcGIS. You can review the 3D Scene Layers Documentation to learn more about how the building and tree features in OSM are modeled and rendered in the 3D scene layers, and see tagging recommendations to get the best results.OpenStreetMap is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap site: www.OpenStreetMap.org. Esri is a supporter of the OSM project.Note: This layer is supported in Scene Viewer and ArcGIS Pro 3.0 or higher.

These data products are preliminary burn severity assessments derived from data obtained from suitable imagery (including Landsat TM, Landsat ETM+, Landsat OLI, Sentinel 2A, and Sentinel 2B). The pre-fire and post-fire subsets included were used to create a differenced Normalized Burn Ratio (dNBR) image. The dNBR image attempts to portray the variation of burn severity within a fire. The severity ratings are influenced by the effects to the canopy. The severity rating is based upon a composite of the severity to the understory (grass, shrub layers), midstory trees and overstory trees. Because there is often a strong correlation between canopy consumption and soil effects, this algorithm works in many cases for Burned Area Emergency Response (BAER) teams whose objective is a soil burn severity assessment. It is not, however, appropriate in all ecosystems or fires. It is expected that BAER teams will adjust the thresholds to match field observations to produce a soil burn severity. This map layer is a thematic raster image of burn severity classes for all inventoried fires occurring in CONUS during calendar year 2023. Fires omitted from this mapped inventory are those where suitable satellite imagery was not available, or fires which were not discernable from available imagery.