66 datasets found
  1. a

    Maya Forest Map-Copy

    • hub.arcgis.com
    • spatialdiscovery-ucsb.opendata.arcgis.com
    • +2more
    Updated Nov 16, 2018
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    University of California, Santa Barbara (2018). Maya Forest Map-Copy [Dataset]. https://hub.arcgis.com/maps/72f658950d144b2b99bdd41a4bb0a7fc
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    Dataset updated
    Nov 16, 2018
    Dataset authored and provided by
    University of California, Santa Barbara
    Area covered
    Description

    The El Pilar Project has been conducting research at El Pilar, Belize and Guatemala since 1993, and was founded on a base of survey work that goes back to 1983. This unusual archaeological program recognizes the present environment as a part of the ancient Maya past. Our mission is the preservation and conservation of endangered resources through local and international education. Addressing tensions between culture and nature, we use the past as a reference to build a responsible future. Weaving together traditional knowledge and practice with scientific inquiry and interpretation, we promote a deeper awareness of heritage through local partnership.

    The University of California Santa Barbara (UCSB) Maya Forest GIS is an essential tool to organize and use the numerous geographic resources involved in our studies, and provide reliable datasets for the project.

  2. African Development Bank Project Report

    • sdg-template-cat-sdgs.opendata.arcgis.com
    • data.amerigeoss.org
    Updated Oct 5, 2015
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    Esri National Government (2015). African Development Bank Project Report [Dataset]. https://sdg-template-cat-sdgs.opendata.arcgis.com/datasets/esrifederal::african-development-bank-project-report
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    Dataset updated
    Oct 5, 2015
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri National Government
    Description

    To create this app:Make a map of the AfDB projects CSV file in the Training Materials group.Download the CSV file, click Map (at the top of the page), and drag and drop the file onto your mapFrom the layer menu on your Projects layer choose Change Symbols and show the projects using Unique Symbols and the Status of field.Make a second map of the AfDB projects shown using Unique Symbols and the Sector field.HINT: Create a copy of your first map using Save As... and modify the copy.Assemble your story map on the Esri Story Maps websiteGo to storymaps.arcgis.comAt the top of the site, click AppsFind the Story Map Tabbed app and click Build a Tabbed Story MapFollow the instructions in the app builder. Add the maps you made in previous steps and copy the text from this sample app to your app. Explore and experiment with the app configuration settings.=============OPTIONAL - Make a third map of the AFDB projects summarized by country and add it to your story map.Add the World Countries layer to your map (Add > Search for Layers)From the layer menu on your Projects layer choose Perform Analysis > Summarize Data > Aggregate Points and run the tool to summarize the projects in each country.HINT: UNCHECK "Keep areas with no points"Experiment with changing the symbols and settings on your new layer and remove other unnecessary layers.Save AS... a new map.At the top of the site, click My Content.Find your story map application item, open its Details page, and click Configure App.Use the builder to add your third map and a description to the app and save it.

  3. RPDP Nearby Projects

    • mapdirect-fdep.opendata.arcgis.com
    • geodata.dep.state.fl.us
    • +1more
    Updated Aug 15, 2022
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    Florida Department of Environmental Protection (2022). RPDP Nearby Projects [Dataset]. https://mapdirect-fdep.opendata.arcgis.com/datasets/rpdp-nearby-projects
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    Dataset updated
    Aug 15, 2022
    Dataset authored and provided by
    Florida Department of Environmental Protectionhttp://www.floridadep.gov/
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    This layer file has been created for data entry in Florida Department of Environmental Protection (DEP) Basin Management Action Plan (BMAP) Statewide Annual Report (STAR) via the Restoration Projects Data Portal (RPDP). The map is only intended for this purpose. This map should not be used for assessment purposes or for any other DEP department or division such as for permit or grant applications. This layer contains DRAFT project information (which may be incorrect) submitted for approval and verification determination by the Water Quality Restoration Program. It is intended only to assist the portal users reference existing nearby projects to; reduce duplication of entries, tie projects to existing projects in treatment trains; or encourage proper duplication when a project is shared by multiple entities.

  4. a

    maina rosemary ke universities-Copy

    • africageoportal.com
    Updated Feb 10, 2023
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    Africa GeoPortal (2023). maina rosemary ke universities-Copy [Dataset]. https://www.africageoportal.com/maps/f3281df76f0d4fe1901694e20b1581ce
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    Dataset updated
    Feb 10, 2023
    Dataset authored and provided by
    Africa GeoPortal
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    This map references the OpenStreetMap tile layer hosted by Esri. This tile layer presents a new vector basemap of OpenStreetMap (OSM) data created and hosted by Esri, now in beta release. Esri produced this vector tile basemap in ArcGIS Pro from a live replica of OSM data, hosted by Esri, that was rendered using OSM cartography. The vector tiles are updated every few weeks; refer to the OpenStreetMap tile layer for details on when it was last updated. When fully released, this vector basemap will be freely available for any user or developer to build into their web map or web mapping apps.OpenStreetMap (OSM) 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 and is excited to make this new vector basemap available available to the OSM, GIS, and Developer communities.

  5. m

    Queensland geology and structural framework - GIS data July 2012

    • demo.dev.magda.io
    • researchdata.edu.au
    • +2more
    zip
    Updated Apr 13, 2022
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    Bioregional Assessment Program (2022). Queensland geology and structural framework - GIS data July 2012 [Dataset]. https://demo.dev.magda.io/dataset/ds-dga-32ede73f-85f8-4053-acf1-bf72265dd539
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    zipAvailable download formats
    Dataset updated
    Apr 13, 2022
    Dataset provided by
    Bioregional Assessment Program
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Area covered
    Queensland
    Description

    Abstract This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied. This dataset was sourced from the Queensland Department of Natural Resources and Mines in 2012. Information provided by the Department describes the dataset as follows: This data was originally provided on DVD and contains the converted shapefiles, layer files, raster images and project .mxd files used on the Queensland geology …Show full descriptionAbstract This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied. This dataset was sourced from the Queensland Department of Natural Resources and Mines in 2012. Information provided by the Department describes the dataset as follows: This data was originally provided on DVD and contains the converted shapefiles, layer files, raster images and project .mxd files used on the Queensland geology and structural framework map. The maps were done in ArcGIS 9.3.1 and the data stored in file geodatabases, topology created and validated. This provides greater data quality by performing topological validation on the feature's spatial relationships. For the purposes of the DVD, shapefiles were created from the file geodatabases and for MapInfo users MapInfo .tab and .wor files. The shapefiles on the DVD are a revision of the 1975 Queensland geology data, and are both are available for display, query and download on the department's online GIS application. The Queensland geology map is a digital representation of the distribution or extent of geological units within Queensland. In the GIS, polygons have a range of attributes including unit name, type of unit, age, lithological description, dominant rock type, and an abbreviated symbol for use in labelling the polygons. The lines in this dataset are a digital representation of the position of the boundaries of geological units and other linear features such as faults and folds. The lines are attributed with a description of the type of line represented. Approximately 2000 rock units were grouped into the 250 map units in this data set. The digital data was generalised and simplified from the Department's detailed geological data and was captured at 1:500 000 scale for output at 1:2 000 000 scale. In the ESRI version, a layer file is provided which presents the units in the colours and patterns used on the printed hard copy map. For Map Info users, a simplified colour palette is provided without patterns. However a georeferenced image of the hard copy map is included and can be displayed as a background in both Arc Map and Map Info. The geological framework of Queensland is classified by structural or tectonic unit (provinces and basins) in which the rocks formed. These are referred to as basins (or in some cases troughs and depressions) where the original form and structure are still apparent. Provinces (and subprovinces) are generally older basins that have been strongly tectonised and/or metamorphosed so that the original basin extent and form are no longer preserved. Note that intrusive and some related volcanic rocks that overlap these provinces and basins have not been included in this classification. The map was compiled using boundaries modified and generalised from the 1:2 000 000 Queensland Geology map (2012). Outlines of subsurface basins are also shown and these are based on data and published interpretations from petroleum exploration and geophysical surveys (seismic, gravity and magnetics). For the structural framework dataset, two versions are provided. In QLD_STRUCTURAL_FRAMEWORK, polygons are tagged with the name of the surface structural unit, and names of underlying units are imbedded in a text string in the HIERARCHY field. In QLD_STRUCTURAL_FRAMEWORK_MULTI_POLYS, the data is structured into a series of overlapping, multi-part polygons, one for each structural unit. Two layer files are provided with the ESRI data, one where units are symbolised by name. Because the dataset has been designed for units display in the order of superposition, this layer file assigns colours to the units that occur at the surface with concealed units being left uncoloured. Another layer file symbolises them by the orogen of which they are part. A similar set of palettes has been provided for Map Info. Dataset History Details on the source data can be found in the xml file associated with data layer. Data in this release *ESRI.shp and MapInfo .tab files of rock unit polygons and lines with associated layer attributes of Queensland geology *ESRI.shp and MapInfo .tab files of structural unit polygons and lines with associated layer attributes of structural framework *ArcMap .mxd and .lyr files and MapInfo .wor files containing symbology *Georeferenced Queensland geology map, gravity and magnetic images *Queensland geology map, structural framework and schematic diagram PDF files *Data supplied in geographical coordinates (latitude/longitude) based on Geocentric Datum of Australia - GDA94 Accessing the data Programs exist for the viewing and manipulation of the digital spatial data contained on this DVD. Accessing the digital datasets will require GIS software. The following GIS viewers can be downloaded from the internet. ESRI ArcExplorer can be found by a search of www.esriaustralia.com.au and MapInfo ProViewer by a search on www.pbinsight.com.au collectively ("the websites"). Metadata Metadata is contained in .htm files placed in the root folder of each vector data folder. For ArcMap users metadata for viewing in ArcCatalog is held in an .xml file with each shapefile within the ESRI Shapefile folders. Disclaimer The State of Queensland is not responsible for the privacy practices or the content of the websites and makes no statements, representations, or warranties about the content or accuracy or completeness of, any information or products contained on the websites. Despite our best efforts, the State of Queensland makes no warranties that the information or products available on the websites are free from infection by computer viruses or other contamination. The State of Queensland disclaims all responsibility and all liability (including without limitation, liability in negligence) for all expenses, losses, damages and costs you might incur as a result of accessing the websites or using the products available on the websites in any way, and for any reason. The State of Queensland has included the websites in this document as an information source only. The State of Queensland does not promote or endorse the websites or the programs contained on them in any way. WARNING: The Queensland Government and the Department of Natural Resources and Mines accept no liability for and give no undertakings, guarantees or warranties concerning the accuracy, completeness or fitness for the purposes of the information provided. The consumer must take all responsible steps to protect the data from unauthorised use, reproduction, distribution or publication by other parties. Please view the 'readme.html' and 'licence.html' file for further, more complete information Dataset Citation Geological Survey of Queensland (2012) Queensland geology and structural framework - GIS data July 2012. Bioregional Assessment Source Dataset. Viewed 07 December 2018, http://data.bioregionalassessments.gov.au/dataset/69da6301-04c1-4993-93c1-4673f3e22762.

  6. Wetland Types

    • catalog.data.gov
    • opendata.dc.gov
    • +3more
    Updated Feb 4, 2025
    + more versions
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    U.S. Fish and Wildlife Service (2025). Wetland Types [Dataset]. https://catalog.data.gov/dataset/wetland-types
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    Dataset updated
    Feb 4, 2025
    Dataset provided by
    U.S. Fish and Wildlife Servicehttp://www.fws.gov/
    Description

    This data set represents the extent, approximate location and type of wetlands and deepwater habitats in the United States and its Territories. These data delineate the areal extent of wetlands and surface waters as defined by Cowardin et al. (1979). The National Wetlands Inventory - Version 2, Surface Waters and Wetlands Inventory was derived by retaining the wetland and deepwater polygons that compose the NWI digital wetlands spatial data layer and reintroducing any linear wetland or surface water features that were orphaned from the original NWI hard copy maps by converting them to narrow polygonal features. Additionally, the data are supplemented with hydrography data, buffered to become polygonal features, as a secondary source for any single-line stream features not mapped by the NWI and to complete segmented connections. Wetland mapping conducted in WA, OR, CA, NV and ID after 2012 and most other projects mapped after 2015 were mapped to include all surface water features and are not derived data. The linear hydrography dataset used to derive Version 2 was the U.S. Geological Survey's National Hydrography Dataset (NHD). Specific information on the NHD version used to derive Version 2 and where Version 2 was mapped can be found in the 'comments' field of the Wetlands_Project_Metadata feature class. Certain wetland habitats are excluded from the National mapping program because of the limitations of aerial imagery as the primary data source used to detect wetlands. These habitats include seagrasses or submerged aquatic vegetation that are found in the intertidal and subtidal zones of estuaries and near shore coastal waters. Some deepwater reef communities (coral or tuberficid worm reefs) have also been excluded from the inventory. These habitats, because of their depth, go undetected by aerial imagery. By policy, the Service also excludes certain types of "farmed wetlands" as may be defined by the Food Security Act or that do not coincide with the Cowardin et al. definition. Contact the Service's Regional Wetland Coordinator for additional information on what types of farmed wetlands are included on wetland maps. This dataset should be used in conjunction with the Wetlands_Project_Metadata layer, which contains project specific wetlands mapping procedures and information on dates, scales and emulsion of imagery used to map the wetlands within specific project boundaries.

  7. ON47 Pine Creek Metallogenic GIS package 1:500 000 scale (version 1.2)

    • ecat.ga.gov.au
    • researchdata.edu.au
    • +1more
    Updated Jan 1, 1998
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    Commonwealth of Australia (Geoscience Australia) (1998). ON47 Pine Creek Metallogenic GIS package 1:500 000 scale (version 1.2) [Dataset]. https://ecat.ga.gov.au/geonetwork/srv/api/records/a05f7892-8cb5-7506-e044-00144fdd4fa6
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    www:link-1.0-http--linkAvailable download formats
    Dataset updated
    Jan 1, 1998
    Dataset provided by
    Geoscience Australiahttp://ga.gov.au/
    Area covered
    Description

    The Pine Creek GIS package has been prepared jointly by AGSO and the Northern Territory Survey for release in both digital and hard copy (atlas) formats. Based on the 1:500 000 geological map of the Pine Creek Geosyncline (2nd edition) published by BMR in 1984, the GIS has been supplemented where possible by recently acquired data from mapping in the Litchfield, Katherine, and South Alligator areas. The aim of this project was to bring together almost 45 years of regional mapping projects by both organisations by integrating existing hard copy geological maps and other relevant geoscientific data into a digital Metallogenic Geographic Information System (GIS).

  8. Geospatial data for the Vegetation Mapping Inventory Project of Saugus Iron...

    • catalog.data.gov
    • data.amerigeoss.org
    Updated Jun 5, 2024
    + more versions
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    National Park Service (2024). Geospatial data for the Vegetation Mapping Inventory Project of Saugus Iron Works National Historic Site [Dataset]. https://catalog.data.gov/dataset/geospatial-data-for-the-vegetation-mapping-inventory-project-of-saugus-iron-works-national
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    Dataset updated
    Jun 5, 2024
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Area covered
    Saugus
    Description

    The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. To produce a USNVC association-level vegetation map that satisfied the standards of the USGS/NPS Vegetation Mapping Program, the alliance-level vegetation map developed by Agius was edited and refined onscreen in ArcGIS 9.1. The Agius (2003b) vegetation map was not developed following the USGS/NPS Vegetation Mapping Program standards and therefore could not be used as the final vegetation classification map. Polygons that represented vegetation were readily attributed to existing associations in the U.S. National Vegetation Classification. Polygons that represented intensive land uses were attributed with names modified from the Anderson Level II categories.. Because Saugus Iron Works National Historic Park is a small park with only 21 polygons, the mapping did not rely entirely on aerial photograph interpretation, but also incorporated lines sketched onto a hard-copy map on site. Using ArcGIS 9.1, polygon boundaries were drawn onscreen based on the plot data and additional field observations. Each polygon was attributed with the name of an USNVC association or an Anderson Level II (modified) land use/land cover map class based on plot data, field observations, aerial photography signatures, and topographic maps. The shapefile was projected in Universal Transverse Mercator Zone 19 North, North American Datum 1983, meters, in ArcGIS 9.1.

  9. H

    Wetlands

    • opendata.hawaii.gov
    • geoportal.hawaii.gov
    • +2more
    Updated Dec 21, 2024
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    Office of Planning (2024). Wetlands [Dataset]. https://opendata.hawaii.gov/dataset/wetlands1
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    pdf, arcgis geoservices rest api, kml, zip, csv, geojson, html, ogc wfs, ogc wmsAvailable download formats
    Dataset updated
    Dec 21, 2024
    Dataset provided by
    U.S. Fish and Wildlife Service
    Authors
    Office of Planning
    Description

    [Metadata] Wetlands in the State of Hawaii. Source: USFWS, November 2024. (https://www.fws.gov/program/national-wetlands-inventory/data-download). This data set represents the extent, approximate location and type of wetlands and deepwater habitats in the State of Hawaii.

    These data delineate the areal extent of wetlands and surface waters as defined by Cowardin et al. (1979). The National Wetlands Inventory - Version 2, Surface Waters and Wetlands Inventory was derived by retaining the wetland and deepwater polygons that compose the NWI digital wetlands spatial data layer and reintroducing any linear wetland or surface water features that were orphaned from the original NWI hard copy maps by converting them to narrow polygonal features. Additionally, the data are supplemented with hydrography data, buffered to become polygonal features, as a secondary source for any single-line stream features not mapped by the NWI and to complete segmented connections. Wetland mapping conducted in WA, OR, CA, NV and ID after 2012 and most other projects mapped after 2015 were mapped to include all surface water features and are not derived data. The linear hydrography dataset used to derive Version 2 was the U.S. Geological Survey's National Hydrography Dataset (NHD). Specific information on the NHD version used to derive Version 2 and where Version 2 was mapped can be found in the 'comments' field of the Wetlands_Project_Metadata feature class (downloadable from the USFWS website via the link shown above). Certain wetland habitats are excluded from the National mapping program because of the limitations of aerial imagery as the primary data source used to detect wetlands. These habitats include seagrasses or submerged aquatic vegetation that are found in the intertidal and subtidal zones of estuaries and near shore coastal waters. Some deepwater reef communities (coral or tuberficid worm reefs) have also been excluded from the inventory. These habitats, because of their depth, go undetected by aerial imagery. By policy, the Service also excludes certain types of "farmed wetlands" as may be defined by the Food Security Act or that do not coincide with the Cowardin et al. definition. Contact the Service's Regional Wetland Coordinator for additional information on what types of farmed wetlands are included on wetland maps. This dataset should be used in conjunction with the Wetlands_Project_Metadata layer (see link above), which contains project specific wetlands mapping procedures and information on dates, scales and emulsion of imagery used to map the wetlands within specific project boundaries.

    For additional information, please refer to metadata at https://files.hawaii.gov/dbedt/op/gis/data/wetlands.pdf or complete metadata at https://files.hawaii.gov/dbedt/op/gis/data/wetlands.html or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

  10. a

    Hiking Red Rock Canyon-Copy

    • africageoportal.com
    • hub.arcgis.com
    Updated Jan 21, 2021
    + more versions
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    Africa GeoPortal (2021). Hiking Red Rock Canyon-Copy [Dataset]. https://www.africageoportal.com/maps/64f4e42ce1b740f49882813e72158bce
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    Dataset updated
    Jan 21, 2021
    Dataset authored and provided by
    Africa GeoPortal
    Area covered
    Description

    This map shows the boundaries and visitor's center of the Red Rock Canyon National Conservation Area.This map is part of the project Hiking Red Rock Canyon on Learn ArcGIS.

  11. g

    National Subsoils Map, EPA

    • geohive.ie
    • ga.geohive.ie
    • +1more
    Updated Nov 22, 2022
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    geohive_curator (2022). National Subsoils Map, EPA [Dataset]. https://www.geohive.ie/maps/19e8bd6ec85a4ac199b0b7b6c0aaad93
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    Dataset updated
    Nov 22, 2022
    Dataset authored and provided by
    geohive_curator
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    For more information on this dataset please go to https://gis.epa.ie/geonetwork/srv/eng/catalog.search#/metadata/5f1999f0-37e4-4c14-acf8-3b42bfdae894The Teagasc Subsoils map classifies the subsoils of Ireland into 16 themes, using digital stereo photogrammetry supported by field work. Produced by Teagasc (Kinsealy), EPA and GSI.The dataset was created using a compilation of existing data, photogrammetric mapping, field studies. Soil survey maps, Quaternary maps and published and unpublished reports were complied and boundaries between sediment types are interpreted and mapped using photo-interpretation in a soft copy photogrammetric workstation with digital stereo-pairs of black and white photography acquired at a scale of 1:40,000. Fieldwork was carried out, around the flanks of large bogs delineate the exact boundary between peat and mineral soils but predominantly within the boundary zones of differencing subsoils. Areas mapped during the photogrammetric analysis were also checked during the fieldwork. Methods adopted during field mapping include reconnaissance mapping, auger sampling, trenching, digital photography and GPS data recording. Aerial photography datasets involved in mapping were acquired in 1995 while field data collected was collected during 1998-2005.The classification of subsoils is based on the classification used by the Geological Survey of Ireland Quaternary Section in mapping Quaternary sediment types.This classification has been altered only to ensure utility specific to the requirements of the EPA Soil and Subsoil Mapping Project. (Please refer to "Teagasc-EPA Soils and Subsoils Mapping Project - Final Report" for more information. Available for download at https://gis.epa.ie)

  12. e

    Southern California Outer Continental Shelf Rocky Substrate

    • knb.ecoinformatics.org
    • dataone.org
    • +1more
    Updated Jan 6, 2015
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    William McClintock; Brian Kinlan (2015). Southern California Outer Continental Shelf Rocky Substrate [Dataset]. http://doi.org/10.5063/AA/will.9.1
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    Dataset updated
    Jan 6, 2015
    Dataset provided by
    Knowledge Network for Biocomplexity
    Authors
    William McClintock; Brian Kinlan
    Time period covered
    Jan 1, 1987
    Area covered
    Description

    This dataset represents the state of knowledge about the distribution of rocky substrate for the Southern California continental shelf. The dataset is derived from a map series of seven adjacent but descrete maps illustrating seafloor sediment and rock.

    The purpose of this project was to create digital, GIS format versions of the Southern California continental shelf seafloor substrate maps originally produced by PS Associates of Cardiff, California for the Minerals Management Service in Reston, Verginia.

    The original data was presented in hard copy format and depicted areas of "rock outcrop, hard-ground, or less than 1 meter of sediment overlaying." Areas identified as "rock" on the hard copy map were designated as "rock" in this dataset. In areas where no rock was identified, we designated this as "sediment". Note that this is liberal interpretation of the original map data. A more conservative and accurate interpretation involved using "no data" maps which indicated the areas in which no information on substrate type was gathered. Please see the "no_data" dataset that is part of this series.

    Original map title: Isopach map of the post-Wisconsin sediment thickness data sources. California Outer Continental Shelf Archeaological Resource Study from Morro Bay to the Mexican Border. Prepared by P.S. Associates, Contract number 14-12-0001-30272, May 1, 1987. Map scale was 1:125,000. Used maps 1A, 2A, 3A, 4A, 5A.

  13. a

    OpenStreetMap-Copy of Moscow

    • uscssi.hub.arcgis.com
    Updated Mar 7, 2022
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    Spatial Sciences Institute (2022). OpenStreetMap-Copy of Moscow [Dataset]. https://uscssi.hub.arcgis.com/maps/USCSSI::openstreetmap-copy-of-moscow
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    Dataset updated
    Mar 7, 2022
    Dataset authored and provided by
    Spatial Sciences Institute
    License

    Attribution-ShareAlike 2.0 (CC BY-SA 2.0)https://creativecommons.org/licenses/by-sa/2.0/
    License information was derived automatically

    Area covered
    Description

    This web map references the live tiled map service from the OpenStreetMap (OSM) project. OpenStreetMap (OSM) 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 server: https://www.OpenStreetMap.org. See that website for additional information about OpenStreetMap. It is made available as a basemap for GIS work in ESRI products under a Creative Commons Attribution-ShareAlike license. Tip: This service is one of the basemaps used in the ArcGIS.com map viewer. Simply click one of those links to launch the interactive application of your choice, and then choose Open Street Map from the Basemap control to start using this service. You'll also find this service in the Basemap gallery in ArcGIS Explorer Desktop and ArcGIS Desktop 10. Tip: Here are some well known locations as they appear in this web map, accessed by launching the web map with a URL that contains location parameters: Athens, Cairo, Jakarta, Moscow, Mumbai, Nairobi, Paris, Rio De Janeiro, Shanghai

  14. d

    Toronto Land Use Spatial Data - parcel-level - (2019-2021)

    • search.dataone.org
    • borealisdata.ca
    Updated Dec 28, 2023
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    Fortin, Marcel (2023). Toronto Land Use Spatial Data - parcel-level - (2019-2021) [Dataset]. http://doi.org/10.5683/SP3/1VMJAG
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    Dataset updated
    Dec 28, 2023
    Dataset provided by
    Borealis
    Authors
    Fortin, Marcel
    Area covered
    Toronto
    Description

    Please note that this dataset is not an official City of Toronto land use dataset. It was created for personal and academic use using City of Toronto Land Use Maps (2019) found on the City of Toronto Official Plan website at https://www.toronto.ca/city-government/planning-development/official-plan-guidelines/official-plan/official-plan-maps-copy, along with the City of Toronto parcel fabric (Property Boundaries) found at https://open.toronto.ca/dataset/property-boundaries/ and Statistics Canada Census Dissemination Blocks level boundary files (2016). The property boundaries used were dated November 11, 2021. Further detail about the City of Toronto's Official Plan, consolidation of the information presented in its online form, and considerations for its interpretation can be found at https://www.toronto.ca/city-government/planning-development/official-plan-guidelines/official-plan/ Data Creation Documentation and Procedures Software Used The spatial vector data were created using ArcGIS Pro 2.9.0 in December 2021. PDF File Conversions Using Adobe Acrobat Pro DC software, the following downloaded PDF map images were converted to TIF format. 9028-cp-official-plan-Map-14_LandUse_AODA.pdf 9042-cp-official-plan-Map-22_LandUse_AODA.pdf 9070-cp-official-plan-Map-20_LandUse_AODA.pdf 908a-cp-official-plan-Map-13_LandUse_AODA.pdf 978e-cp-official-plan-Map-17_LandUse_AODA.pdf 97cc-cp-official-plan-Map-15_LandUse_AODA.pdf 97d4-cp-official-plan-Map-23_LandUse_AODA.pdf 97f2-cp-official-plan-Map-19_LandUse_AODA.pdf 97fe-cp-official-plan-Map-18_LandUse_AODA.pdf 9811-cp-official-plan-Map-16_LandUse_AODA.pdf 982d-cp-official-plan-Map-21_LandUse_AODA.pdf Georeferencing and Reprojecting Data Files The original projection of the PDF maps is unknown but were most likely published using MTM Zone 10 EPSG 2019 as per many of the City of Toronto's many datasets. They could also have possibly been published in UTM Zone 17 EPSG 26917 The TIF images were georeferenced in ArcGIS Pro using this projection with very good results. The images were matched against the City of Toronto's Centreline dataset found here The resulting TIF files and their supporting spatial files include: TOLandUseMap13.tfwx TOLandUseMap13.tif TOLandUseMap13.tif.aux.xml TOLandUseMap13.tif.ovr TOLandUseMap14.tfwx TOLandUseMap14.tif TOLandUseMap14.tif.aux.xml TOLandUseMap14.tif.ovr TOLandUseMap15.tfwx TOLandUseMap15.tif TOLandUseMap15.tif.aux.xml TOLandUseMap15.tif.ovr TOLandUseMap16.tfwx TOLandUseMap16.tif TOLandUseMap16.tif.aux.xml TOLandUseMap16.tif.ovr TOLandUseMap17.tfwx TOLandUseMap17.tif TOLandUseMap17.tif.aux.xml TOLandUseMap17.tif.ovr TOLandUseMap18.tfwx TOLandUseMap18.tif TOLandUseMap18.tif.aux.xml TOLandUseMap18.tif.ovr TOLandUseMap19.tif TOLandUseMap19.tif.aux.xml TOLandUseMap19.tif.ovr TOLandUseMap20.tfwx TOLandUseMap20.tif TOLandUseMap20.tif.aux.xml TOLandUseMap20.tif.ovr TOLandUseMap21.tfwx TOLandUseMap21.tif TOLandUseMap21.tif.aux.xml TOLandUseMap21.tif.ovr TOLandUseMap22.tfwx TOLandUseMap22.tif TOLandUseMap22.tif.aux.xml TOLandUseMap22.tif.ovr TOLandUseMap23.tfwx TOLandUseMap23.tif TOLandUseMap23.tif.aux.xml TOLandUseMap23.tif.ov Ground control points were saved for all georeferenced images. The files are the following: map13.txt map14.txt map15.txt map16.txt map17.txt map18.txt map19.txt map21.txt map22.txt map23.txt The City of Toronto's Property Boundaries shapefile, "property_bnds_gcc_wgs84.zip" were unzipped and also reprojected to EPSG 26917 (UTM Zone 17) into a new shapefile, "Property_Boundaries_UTM.shp" Mosaicing Images Once georeferenced, all images were then mosaiced into one image file, "LandUseMosaic20211220v01", within the project-generated Geodatabase, "Landuse.gdb" and exported TIF, "LandUseMosaic20211220.tif" Reclassifying Images Because the original images were of low quality and the conversion to TIF made the image colours even more inconsistent, a method was required to reclassify the images so that different land use classes could be identified. Using Deep learning Objects, the images were re-classified into useful consistent colours. Deep Learning Objects and Training The resulting mosaic was then prepared for reclassification using the Label Objects for Deep Learning tool in ArcGIS Pro. A training sample, "LandUseTrainingSamples20211220", was created in the geodatabase for all land use types as follows: Neighbourhoods Insitutional Natural Areas Core Employment Areas Mixed Use Areas Apartment Neighbourhoods Parks Roads Utility Corridors Other Open Spaces General Employment Areas Regeneration Areas Lettering (not a land use type, but an image colour (black), used to label streets). By identifying the letters, it then made the reclassification and vectorization results easier to clean up of unnecessary clutter caused by the labels of streets. Reclassification Once the... Visit https://dataone.org/datasets/sha256%3A3e3f055bf6281f979484f847d0ed5eeb96143a369592149328c370fe5776742b for complete metadata about this dataset.

  15. a

    KS Contacts

    • archive-gis-data-ksdot.hub.arcgis.com
    • archivehub.kansasgis.org
    Updated Sep 25, 2020
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    The University of Kansas (2020). KS Contacts [Dataset]. https://archive-gis-data-ksdot.hub.arcgis.com/datasets/KU::ks-contacts
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    Dataset updated
    Sep 25, 2020
    Dataset authored and provided by
    The University of Kansas
    Area covered
    Description

    This is a data download for Statewide Geology. For an interactive map to view Statewide Geology, please visit Surficial Geology of Kansas. First published in 1937 and last revised in 1991, the state geologic map is updated periodically to incorporate new geologic information and up-to-date rock classifications. This new 2008 data revision includes a shift in the boundary between the Pennsylvanian and Permian bedrock, which was recently redefined by the geologic community. The data for the 1991 map was digitized from an original paper copy publication of Map M-1, "Geologic Map of Kansas," (1964), which incorporated a 1:500,000-scale USGS base map. The goal of that project was to capture, in GIS format, the spatial and attribute information portrayed on the 1964 map. This data is from the Kansas Geological Survey - Cartographic Services and its predecessors.

  16. d

    2011 Protected Open Space Mapping Set

    • catalog.data.gov
    • geodata.ct.gov
    • +3more
    Updated Feb 12, 2025
    + more versions
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    Department of Energy & Environmental Protection (2025). 2011 Protected Open Space Mapping Set [Dataset]. https://catalog.data.gov/dataset/2011-protected-open-space-mapping-set-0be8c
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    Dataset updated
    Feb 12, 2025
    Dataset provided by
    Department of Energy & Environmental Protection
    Description

    See full Data Guide here. This layer includes polygon features that depict protected open space for towns of the Protected Open Space Mapping (POSM) project, which is administered by the Connecticut Department of Energy and Environmental Protection, Land Acquisition and Management. Only parcels that meet the criteria of protected open space as defined in the POSM project are in this layer. Protected open space is defined as: (1) Land or interest in land acquired for the permanent protection of natural features of the state's landscape or essential habitat for endangered or threatened species; or (2) Land or an interest in land acquired to permanently support and sustain non-facility-based outdoor recreation, forestry and fishery activities, or other wildlife or natural resource conservation or preservation activities. Includes protected open space data for the towns of Andover, Ansonia, Ashford, Avon, Beacon Falls, Canaan, Clinton, Berlin, Bethany, Bethel, Bethlehem, Bloomfield, Bridgewater, Bolton, Brookfield, Brooklyn, Canterbury, Canton, Chaplin, Cheshire, Colchester, Colebrook, Columbia, Cornwall, Coventry, Cromwell, Danbury, Derby, East Granby, East Haddam, East Hampton, East Hartford, East Windsor, Eastford, Ellington, Enfield, Essex, Farmington, Franklin, Glastonbury, Goshen, Granby, Griswold, Groton, Guilford, Haddam, Hampton, Hartford, Hebron, Kent, Killingworth, Lebanon, Ledyard, Lisbon, Litchfield, Madison, Manchester, Mansfield, Marlborough, Meriden, Middlebury, Middlefield, Middletown, Monroe, Montville, Morris, New Britain, New Canaan, New Fairfield, New Milford, New Hartford, Newington, Newtown, Norfolk, North, Norwich, Preston, Ridgefield, Shelton, Stonington, Oxford, Plainfield, Plainville, Pomfret, Portland, Prospect, Putnam, Redding, Rocky Hill, Roxbury, Salem, Salisbury, Scotland, Seymour, Sharon, Sherman, Simsbury, Somers, South Windsor, Southbury, Southington, Sprague, Sterling, Suffield, Thomaston, Thompson, Tolland, Torrington, Union, Vernon, Wallingford, Windham, Warren, Washington, Waterbury, Watertown, West Hartford, Westbrook, Weston, Wethersfield, Willington, Wilton, Windsor, Windsor Locks, Wolcott, Woodbridge, Woodbury, and Woodstock. Additional towns are added to this list as they are completed. The layer is based on information from various sources collected and compiled during the period from March 2005 through the present. These sources include but are not limited to municipal Assessor's records (the Assessor's database, hard copy maps and deeds) and existing digital parcel data. The layer represents conditions as of the date of research at each city or town hall. The Protected Open Space layer includes the parcel shape (geometry), a project-specific parcel ID based on the Town and Town Assessor's lot numbering system, and system-defined (automatically generated) fields. The Protected Open Space layer has an accompanying table containing more detailed information about each feature (parcel). This table is called Protected Open Space Dat, and can be joined to Protected Open Space in ArcMap using the parcel ID (PAR_ID) field. Detailed information in the Protected Open Space Data attribute table includes the Assessor's Map, Block and Lot numbers (the Assessor's parcel identification numbering system), the official name of the parcel (such as the park or forest name if it has one), address and owner information, the deed volume and page numbers, survey information, open space type, the unique parcel ID number (Par_ID), comments collected by researchers during city/town hall visits, and acreage. This layer does not include parcels that do not meet the definition of open space as defined above. Features are stored as polygons that represent the best available locational information, and are "best fit" to the land base available for each. The Connecticut Department of Environmental Protection's (CTDEP) Permanently Protected Open Space Phase Mapping Project Phase 1 (Protected Open Space Phase1) layer

  17. g

    Geospatial data for the Vegetation Mapping Inventory Project of Wupatki...

    • gimi9.com
    Updated Jul 31, 2019
    + more versions
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    (2019). Geospatial data for the Vegetation Mapping Inventory Project of Wupatki National Monument | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_geospatial-data-for-the-vegetation-mapping-inventory-project-of-wupatki-national-monument
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    Dataset updated
    Jul 31, 2019
    Description

    The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. Final WUPA map classes used for interpreting the aerial photographs were derived (1) from plant associations and alliances described by CPRS, (2) from the Anderson (1976) Level II land use classification system, (3) from land cover classes, and (4) from unique stands specific to WUPA. A draft hard copy vegetation map at the 1:12,000 scale was printed and checked against the interpreted aerial photographs. As a final internal accuracy check, RSGIG applied photointerpretation observations and classification relevés over the vegetation map to determine if the polygon labels matched the field data. Map validation occurred prior to the accuracy assessment. Because of the difficulties in interpreting the vegetation directly from the aerial photographs, we eventually mapped and/or validated much of the project area in the field. Metadata are required for all spatial data produced by the federal government. RSGIG used SIMMS™ software to create the three FGDC-compliant metadata files attached to the spatial databases and to this report. The metadata files explain the vegetation coverage and ancillary coverages created by RSGIG, the plot data coverage created by CPRS, and the accuracy assessment data created by CPRS.

  18. GISCorps COVID-19 Testing Locations in the United States Symbolized by Test...

    • opendata.rcmrd.org
    • geo.btaa.org
    • +4more
    Updated May 5, 2020
    + more versions
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    URISA's GISCorps (2020). GISCorps COVID-19 Testing Locations in the United States Symbolized by Test Type [Dataset]. https://opendata.rcmrd.org/datasets/d7d10caf1cec43e0985cc90fbbcf91cb
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    Dataset updated
    May 5, 2020
    Dataset provided by
    GISCorpshttp://www.giscorps.org/
    Authors
    URISA's GISCorps
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Pacific Ocean, North Pacific Ocean
    Description

    Announcement: Project Ended on October 15, 2021After over 18 months of collaboration between hundreds of GISCorps volunteers, Esri's Disaster Response Program, Coders Against COVID, HERE Technologies, dozens of government agencies, and hundreds of testing providers, GISCorps has decided to end our COVID-19 Testing and Vaccination Sites Data Creation Project as of October 15th, 2021. Our data will remain available for use by researchers and analysts, but it should not be considered a reliable source of current testing and vaccination site location information after October 15th. We are grateful for the support we have received by so many throughout the life of this monumental undertaking. Read more about this effort https://covid-19-giscorps.hub.arcgis.com/pages/contribute-covid-19-testing-sites-data.Item details page: https://giscorps.maps.arcgis.com/home/item.html?id=d7d10caf1cec43e0985cc90fbbcf91cbThis view is the original COVID-19 Testing Locations in the United States - public dataset. A backup copy also exists: https://giscorps.maps.arcgis.com/home/item.html?id=11fe8f374c344549815a716c8472832f. The parent hosted feature service is the same. This version is symbolized by type of test (molecular, antibody, antigen, or combinations thereof).This feature layer view contains information about COVID-19 screening and testing locations. It is made available to the public using the GISCorps COVID-19 Testing Site Locator app (https://giscorps.maps.arcgis.com/apps/webappviewer/index.html?id=2ec47819f57c40598a4eaf45bf9e0d16) and on findcovidtesting.com. All information was sourced from public information shared by health departments, local governments, and healthcare providers. The data are aggregated by GISCorps volunteers in collaboration with volunteers from Coders Against COVID and should not be considered complete or authoritative. Please contact testing sites or your local health department directly for official information and testing requirements.The objective of this application is to aggregate and facilitate the public communications of local governments, health departments, and healthcare providers with regard to testing site locations. GISCorps does not share any screening or testing site location information not previously made public or provided to us by one of those entities.Data dictionary document: https://docs.google.com/document/d/1HlFmtsT3GzibixPR_QJiGqGOuia9r-exN3i5UK8c6h4/edit?usp=sharingArcade code for popups: https://docs.google.com/document/d/1PDOq-CxUX9fuC2v3N8muuuxN5mLMinWdf7fiwUt1lOM/edit?usp=sharing

  19. d

    Data from: Species occurrence data from the Range-Wide Bull Trout eDNA...

    • catalog.data.gov
    • agdatacommons.nal.usda.gov
    • +7more
    Updated Jun 21, 2023
    + more versions
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    U.S. Forest Service (2023). Species occurrence data from the Range-Wide Bull Trout eDNA Project [Dataset]. https://catalog.data.gov/dataset/species-occurrence-data-from-the-range-wide-bull-trout-edna-project-6332e
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    Dataset updated
    Jun 21, 2023
    Dataset provided by
    U.S. Forest Service
    Description

    These data include 2015 - 2018 eDNA field sample points indicating lab results for presence or absence of bull trout. Sample sites are spaced at a 1 kilometer interval throughout the historical range of bull trout. eDNA stream samples are collected and species presence/absence is determined by analyses at the National Genomics Center. Results are recorded in the feature attribute table of the eDNA sample site shapefile. One point feature in the shapefile was generated for each 1 kilometer sample point in the bull trout eDNA feature class. Where multiple samples were collected at a single eDNA sample site, replicate point features will occur at a single location in the shapefile. The bull trout is an ESA-listed species with a historical range that encompasses many waters across the Northwest. Though once abundant, bull trout have declined in many locations and are at risk from a changing climate, nonnative species, and habitat degradation. Informed conservation planning relies on sound and precise information about the distribution of bull trout in thousands of streams, but gathering this information is a daunting and expensive task. To overcome this problem, we coupled 1) predictions from the range-wide, spatially precise Climate Shield model on the location of natal habitats of bull trout with 2) a sampling template for every 8-digit hydrologic unit in the historical range of bull trout, based on the probability of detecting bull trout presence using environmental DNA (eDNA) sampling (McKelvey et al. 2016). The template consists of a master set of geospatially referenced sampling locations at 1-kilometer intervals within each cold-water habitat. We also identified sampling locations at this same interval based on the U.S. Fish and Wildlife Service's (USFWS) designation of critical spawning and rearing habitat. Based on field tests of eDNA detection probabilities conducted by the National Genomics Center for Wildlife and Fish Conservation, this sampling approach will reliably determine the presence of populations of bull trout, as well as provide insights on non-spawning habitats used by adult and subadult fish. The completed bull trout eDNA survey results are available through an interactive ArcGIS Online Map. The map provides the ability to zoom in and look at an area of interest, as well as to create queries or select an area to download points as a shapefile.

  20. d

    Southern California Cobble / Other Shores

    • search.dataone.org
    • knb.ecoinformatics.org
    Updated Jan 6, 2015
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    William McClintock; Brian Kinlan (2015). Southern California Cobble / Other Shores [Dataset]. http://doi.org/10.5063/AA/will.7.1
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    Dataset updated
    Jan 6, 2015
    Dataset provided by
    Knowledge Network for Biocomplexity
    Authors
    William McClintock; Brian Kinlan
    Time period covered
    Jan 1, 1974
    Area covered
    Description

    This dataset represents the state of knowledge about the distribution of shores classified as "cobble" or "other" along the Southern California coastline as of 1974. The complete data series is comprised of three overlapping polyline themes. The other two themes represent "rocky" and "sandy" shores.

    The purpose of this project was to create digital, GIS format versions of the Southern California coastline hardcopy maps produced by the U.S. Department of the Interior, Bureau of Land Management, Pacific Continental Shelf Office, Los Angeles, prepared by William E. Grant (Manager) and printed by the U.S. Government Printing Office in 1974.

    The original data was presented in hard copy format and, according to a disclosure on the map itself, the "visual graphic has been carefully prepared from existing sources. However, the Beareau of Land Management, U.S.D.I. does not guarantee the accuracy to the extent of responsibility or liability for reliance thereon. This is a special visual graphic overprint and is not to be used for navigational purposes." These non digital data were presented at a scale of 1:500,000. For the current project, these data were scanned, georeferenced (GCS_NAD83) and traced in ArcMap 8.3 software to produce polyline representations of the shoreline types. Data covers the shorelines from the US/Mexico border, north to California's Point Conception, including San Miguel, Santa Rosa, Santa Cruz, San Nicholas, Santa Catalina and San Clemente Islands.

    Data digitized from Channel Islands Area Map created by the US Department of the Interior Beurea of Land Management, Pacific Continental Shelf Office, 1974. University of California Santa Barbara library call number: 9507, .N2446, 1974, .US, graphic #10.

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University of California, Santa Barbara (2018). Maya Forest Map-Copy [Dataset]. https://hub.arcgis.com/maps/72f658950d144b2b99bdd41a4bb0a7fc

Maya Forest Map-Copy

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Dataset updated
Nov 16, 2018
Dataset authored and provided by
University of California, Santa Barbara
Area covered
Description

The El Pilar Project has been conducting research at El Pilar, Belize and Guatemala since 1993, and was founded on a base of survey work that goes back to 1983. This unusual archaeological program recognizes the present environment as a part of the ancient Maya past. Our mission is the preservation and conservation of endangered resources through local and international education. Addressing tensions between culture and nature, we use the past as a reference to build a responsible future. Weaving together traditional knowledge and practice with scientific inquiry and interpretation, we promote a deeper awareness of heritage through local partnership.

The University of California Santa Barbara (UCSB) Maya Forest GIS is an essential tool to organize and use the numerous geographic resources involved in our studies, and provide reliable datasets for the project.

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