World Continents represents the boundaries for the continents of the world. It provides a basemap layer of the continents, delivering a straightforward method of selecting a small multicountry area for display or study.This layer is best viewed out beyond a scale of 1:3,000,000. The original source was extracted from the ArcWorld Supplement database in 2001 and updated as country boundaries coincident to regional boundaries change. To download the data for this layer as a layer package for use in ArcGIS desktop applications, refer to World Continents.

Complete Topographic dataset in shapefile format. Consume this dataset if you wish to download the entire Topographic dataset at once.

Shapefiles for each conttinent, subset of publicly available shapefile from ESRI.

This city boundary shapefile was extracted from Esri Data and Maps for ArcGIS 2014 - U.S. Populated Place Areas. This shapefile can be joined to 500 Cities city-level Data (GIS Friendly Format) in a geographic information system (GIS) to make city-level maps.

This shapefile provides a worldwide geographic division by merging the World Continents division proposed by Esri Data and Maps (2024) to the Global Oceans and Seas version 1 division proposed by the Flanders Marine Institute (2021). Though divisions of continents and oceans/seas are available, the combination of both in a single shapefile is scarce.

The Continents and Oceans/Seas shapefile was carefully processed to remove overlaps between the inputs, and to fill gaps (i.e., areas with no information) by spatially joining these gaps to neighbour polygons. In total, the original world continents input divides land areas into 8 categories (Africa, Antarctica, Asia, Australia, Europe, North America, Oceania, and South America), while the original oceans/seas input divides the oceans/seas into 10 categories (Arctic Ocean, Baltic Sea, Indian Ocean, Mediterranean Region, North Atlantic Ocean, North Pacific Ocean, South Atlantic Ocean, South China and Easter Archipelagic Seas, South Pacific Ocean, and Southern Ocean). Therefore, the resulting world geographic division has 18 possible categories.

References

Esri Data and Maps (2024). World Continents. Available online at https://hub.arcgis.com/datasets/esri::world-continents/about. Accessed on 05 March 2024.

Flanders Marine Institute (2021). Global Oceans and Seas, version 1. Available online at https://www.marineregions.org/. https://doi.org/10.14284/542. Accessed on 04 March 2024.

Draft of the Geographies of the Watershed Improvement Program (WIP) Capacity Assessments for reference only. (This is a draft for resolution refinements of the watershed boundaries.) If you wish to be contacted when the final file is posted contact john.tangenberg @ sierranevada.ca.gov or use the dynamic service found at in your map document as it will automatically update. https://snc.maps.arcgis.com/home/item.html?id=6843fd5e35cf42e4a5c0c4fa548b1df8A WIP Capacity Assessment Geography is an aggregation of WIP watersheds More info on the WIP Watersheds can be found here:https://snc.maps.arcgis.com/home/item.html?id=f38517016ee54e7998ecade01f1a17eb

The Digital (Detailed) Geomorphology Map of Cape Lookout National Seashore, North Carolina is composed of GIS data layers complete with ArcMap 9.2 layer (.LYR) files, two ancillary GIS tables, a Windows Help File with ancillary map text, figures and tables, a FGDC metadata record and a 9.2 ArcMap (.MXD) Document that displays the digital map in 9.2 ArcGIS. The data were completed as a component of the Geologic Resource Evaluation (GRE) program, a National Park Service (NPS) Inventory and Monitoring (I&M) funded program that is administered by the NPS Geologic Resources Division (GRD). Source geologic maps and data used to complete this GRE digital dataset were provided by the following: East Carolina University (ECU). As the source ECU maps were only site studies this map doesn't provided comeplete coverage of Cape Lookout National Seashore, only selected areas. Detailed information concerning the sources used and their contribution the GRE product are listed in the Source Citation sections(s) of this metadata record (calg_metadata.txt; available at http://nrdata.nps.gov/calo/nrdata/geology/gis/calg_metadata.xml). All GIS and ancillary tables were produced as per the NPS GRE Geology-GIS Geodatabase Data Model v. 2.0. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as a 9.2 personal geodatabase (calg_geology.mdb), and as shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 18. That data is within the area of interest of Cape Lookout National Seashore.

Download high-quality, up-to-date Iran shapefile boundaries (SHP, projection system SRID 4326). Our Iran Shapefile Database offers comprehensive boundary data for spatial analysis, including administrative areas and geographic boundaries. This dataset contains accurate and up-to-date information on all administrative divisions, zip codes, cities, and geographic boundaries, making it an invaluable resource for various applications such as geographic analysis, map and visualization, reporting and business intelligence (BI), master data management, logistics and supply chain management, and sales and marketing. Our location data packages are available in various formats, including Shapefile, GeoJSON, KML, ASC, DAT, CSV, and GML, optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more. Companies choose our location databases for their enterprise-grade service, reduction in integration time and cost by 30%, and weekly updates to ensure the highest quality.

This file contains European countries in a shapefile format that can be used in python, R or matlab. The file has been created by Drin Marmullaku based on GADM version 4.1 (https://gadm.org/) and distributed according to their license (https://gadm.org/license.html).

Please cite as: Sevdari, Kristian; Marmullaku, Drin (2023). Shapefile of European countries. Technical University of Denmark. Dataset. https://doi.org/10.11583/DTU.23686383 This dataset is distributed under a CCBY-NC-SA 4.0 license

Using the data to create maps for publishing of academic research articles is allowed. Thus you can use the maps you made with GADM data for figures in articles published by PLoS, Springer Nature, Elsevier, MDPI, etc. You are allowed (but not required) to publish these articles (and the maps they contain) under an open license such as CC-BY as is the case with PLoS journals and may be the case with other open access articles. Data for the following countries is covered by a a different license Austria: Creative Commons Attribution-ShareAlike 2.0 (source: Government of Austria)

In order to use the standard color legend for Romanian soil type maps in the ESRI ArcMap-10 electronic format, a dataset consisting a shapefile set (.dbf, .shp, .shx, .sbn, and .sbx files), four different .lyr files, and three different .style files have been prepared (ESRI, 2016). The shapefile set is not a “real” georeferenced layer/coverage; it is designed only to handle all the instants of soil types from the standard legend. This legend contains 67 standard items: 63 proper colors (different color hues, each of them having, generally, 2 - 4 degrees of lightness and/or chroma, four shades of grey, and white color), and four hatching patterns on white background (ESRI, 2016). The “color difference DE*ab” between any two legend colors, calculated with the color perceptually-uniform model CIELAB , is greater than 10 units, thus ensuring acceptably-distinguishable colors in the legend. The 67 standard items are assigned to 60 main soils existing in Romania, four main nonsoils, and three special cases of unsurveyed land. The soils are specified in terms of the current Romanian system of soil taxonomy, SRTS-2012+, and of the international soil classification system WRB-2014. The four different .lyr files presented here are: legend_soilcode_srts_wrb.lyr, legend_soilcode_wrb.lyr, legend_colourcode_srts_wrb.lyr, and legend_colourcode_wrb.lyr. The first two of them are built using as value field the ‘Soil_codes’ field, and as labels (explanation texts) the ‘Soil_name’ field (storing the soil types according to SRTS/WRB classification), respectively, the ‘WRB’ field (the soil type according to WRB classification), while the last two .lyr files are built using as value field the ‘colour_code’ field (storing the color codes) and as labels the soil name in SRTS and WRB, respectively, in WRB classification. In order to exemplify how the legend is displayed, two .jpg files are also presented: legend_soil_srts_wrb.jpg and legend_colour_wrb.jpg. The first displays the legend (symbols and labels) according to the SRTS classification order, the second according to the WRB classification. The three different .style files presented here are: soil_symbols.style, wrb_codes.style, and colour_codes.style. They use as name the soil acronym in SRTS classification, soil acronym in WRB classification, and, respectively, the color code.

Distribution map of Atlas cedar (Cedrus atlantica)These maps were produced by combining numerous and heterogeneous data collected from atlas monographs providing complete species distribution maps, from national to regional atlases, occurrence geo-databases, scientific and grey literature.The maps were created using ESRI shapefiles (*.shp, *.shx, *.dbf, *.prj files) archived in the ZIP file. Species range is mapped with polygon features (name suffix "plg"), which define continuous areas of occupancy of the species, and with point features (name suffix "pnt"), which identify more fragmented and isolated populations. If synanthropic occurrences are reported outside the species natural range, additional point and/or polygon shapefiles are also present (suffix "syn").Polygon borders delimiting species ranges are generalized across the mainland and sea boundaries. This offers the possibility to mask sea areas or to clip and extract the terrestrial range parts using GIS data layers of the users' choice. An additional version of polygon ranges are clipped with a coastline (name suffix "clip"), which have been derived from Natural Earth dataset "Admin 0 - Countries" 1:50M version 4.1.0 (https://www.naturalearthdata.com)Please cite as:Caudullo, G., Welk, E., San-Miguel-Ayanz, J., 2017. Chorological maps for the main European woody species. Data in Brief 12, 662-666. DOI: doi.org/10.1016/j.dib.2017.05.007Additional information and used references are on 'supplementary materials' document:https://doi.org/10.6084/m9.figshare.5091901Chorological maps are part of the "European Atlas of Forest Tree Species" project:https://w3id.org/mtv/FISE-Comm/v01

description: Seattle Parks and Recreation GIS Map Layer Shapefile - Basketball Court Point Shape File - This Seattle Parks and Recreation ARCGIS park feature map layer was exported from SPU ARCGIS and converted to a shapefile then manually uploaded to data.seattle.gov via Socrata. OR Web Services - Live "read only" data connection ESRI web services URL: http://gisrevprxy.seattle.gov/arcgis/rest/services/DPR_EXT/ParksExternalWebsite/MapServer/4; abstract: Seattle Parks and Recreation GIS Map Layer Shapefile - Basketball Court Point Shape File - This Seattle Parks and Recreation ARCGIS park feature map layer was exported from SPU ARCGIS and converted to a shapefile then manually uploaded to data.seattle.gov via Socrata. OR Web Services - Live "read only" data connection ESRI web services URL: http://gisrevprxy.seattle.gov/arcgis/rest/services/DPR_EXT/ParksExternalWebsite/MapServer/4

World Countries provides a detailed basemap layer for the country boundaries of the world. This layer has been designed to be used as a basemap and includes fields for official names and country codes, along with fields for continent and display. Particularly useful are the fields LAND_TYPE and LAND_RANK that separate polygons based on their size. These fields are helpful for rendering at different scales by providing the ability to turn off small islands that may clutter small-scale views. The data is sourced from Garmin International, Inc. with additional content from the U.S. Central Intelligence Agency (The World Factbook), and International Organization for Standardization (ISO). This layer was published in October 2024 and is updated every 12-18 months or as significant changes occur.

On shallow rocky reefs in northeastern Aotearoa, New Zealand, urchin barrens are recognised as indicators of the ecosystem effects of overfishing reef predators. Yet, information on their extent and variability is lacking. We use aerial imagery to map the urchin barrens and kelp forests on reefs (<30 m depth) across seven locations, including within two long-established marine reserves and a marine protected area that allows recreational fishing. Urchin barrens were present in all locations and were restricted to reefs <10-16 m deep. This archive contains ArcGIS shapefiles and layer files for all of the maps used in this study. The study area extends from Cape Reinga in the far north of the North Island to Tawharanui in the Hauraki Gulf near Auckland. Regional scale base maps of the prominent marine habitats were included along with the seven fine-scale maps where the kelp forests and urchin barrens were mapped., The GIS shapefiles produced in this study were hand-drawn over layers of low-level aerial photography taken in specific conditions, which maximised the visible depth observable to create polygons to depict the habitat boundaries of the shallow reef. Of particular interest was the mapping of urchin barrens. Ground truthing surveys creating point data and underwater imagery were also brought into the GIS project to assist in drawing the reef habitat polygons. Arc layer files contain a common symbology across the seven study maps to aid the interpretation of the mapping. Further information on the methodology used in the mapping can be found in two published papers and four technical reports corresponding to the maps. The Readme file details where technical reports and published reports can be downloaded from the internet., , # GIS data of urchin barren mapping in Northeastern New Zealand

GIS mapping resources supporting the research article: Kerr, V.C. Grace R.V. (deceased), and Shears N.T., 2004. Estimating the extent of urchin barrens and kelp forest loss in northeastern Aotearoa, New Zealand. Kerr and Associates, Whangarei, New Zealand.

Description of the data and file structure

Four folders in this archive contain ArcGIS shapefiles with the extension (.shp). The shapefiles can be uploaded to ArcGIS or any ArcGIS-compatible software to view and access the files' spatial data and habitat attributes. It is essential to retain the associated files in each folder as these are system files required by ArcGIS to open and use the shapefiles. Each shapefile has six associated files with extensions: .avi, .CPG, .dbf, .prf, .sbn, and .sbx. In this archive are maps based on polygons drawn to depict habitat boundaries of biological and physical habitats in the shallow coastal areas of Northeastern New Zealan...

New political and administrative boundaries Shapefile of Nepal. Downloaded and republished from the Survey Department website.

Download high-quality, up-to-date Ghana shapefile boundaries (SHP, projection system SRID 4326). Our Ghana Shapefile Database offers comprehensive boundary data for spatial analysis, including administrative areas and geographic boundaries. This dataset contains accurate and up-to-date information on all administrative divisions, zip codes, cities, and geographic boundaries, making it an invaluable resource for various applications such as geographic analysis, map and visualization, reporting and business intelligence (BI), master data management, logistics and supply chain management, and sales and marketing. Our location data packages are available in various formats, including Shapefile, GeoJSON, KML, ASC, DAT, CSV, and GML, optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more. Companies choose our location databases for their enterprise-grade service, reduction in integration time and cost by 30%, and weekly updates to ensure the highest quality.

This world cities layer presents the locations of many cities of the world, both major cities and many provincial capitals.Population estimates are provided for those cities listed in open source data from the United Nations and US Census.

The Digital Geologic and Volcanic Hazards Map for Crater Lake National Park and Vicinity, Oregon is composed of GIS data layers complete with ArcMap 9.3 layer (.LYR) files, two ancillary GIS tables, a Map PDF document with ancillary map text, figures and tables, a FGDC metadata record and a 9.3 ArcMap (.MXD) Document that displays the digital map in 9.3 ArcGIS. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) funded program that is administered by the NPS Geologic Resources Division (GRD). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation sections(s) of this metadata record (clhz_metadata.txt; available at http://nrdata.nps.gov/crla/nrdata/geology/gis/clhz_metadata.xml). All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.1. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as a 9.3 personal geodatabase (clhz_geology.mdb), and as shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 10N. That data is within the area of interest of Crater Lake National Park.

Download high-quality, up-to-date Mexico shapefile boundaries (SHP, projection system SRID 4326). Our Mexico Shapefile Database offers comprehensive boundary data for spatial analysis, including administrative areas and geographic boundaries. This dataset contains accurate and up-to-date information on all administrative divisions, zip codes, cities, and geographic boundaries, making it an invaluable resource for various applications such as geographic analysis, map and visualization, reporting and business intelligence (BI), master data management, logistics and supply chain management, and sales and marketing. Our location data packages are available in various formats, including Shapefile, GeoJSON, KML, ASC, DAT, CSV, and GML, optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more. Companies choose our location databases for their enterprise-grade service, reduction in integration time and cost by 30%, and weekly updates to ensure the highest quality.

This land cover data set is derived from the original raster based Globcover regional (Africa) archive. It has been post-processed to generate a vector version at national extent with the LCCS regional legend (46 classes). This database can be analyzed in the GLCN software Advanced Database Gateway (ADG), which provides a user-friendly interface and advanced functionalities to breakdown the LCCS classes in their classifiers for further aggregations and analysis.

The data set is intended for free public access.

The shape file's attributes contain the following fields: -Area (sqm) -ID -Gridcode (Globcover cell value) -LCCCode (unique LCCS code)

You can download a zip archive containing: -the shape file (.shp) -the ArcGis layer file with global legend (.lyr) -the ArcView 3 legend file (.avl) -the LCCS legend tables (.xls)

Supplemental Information:

This land cover product is a vector version (ESRI shape) of the Globcover archive that was published in 2008 as result of an initiative launched in 2004 by the European Space Agency (ESA). Globcover is currently the most recent (2005) and resoluted (300 m) datasets on land cover globally. Given the need of this valuable information for environmental studies, natural resources management and policy formulation, through activities of the Global Land Cover Network (GLCN) programme, the Globcover has been reprocessed to generate databases at national extent that can be analyzed through the Advanced Database Gateway software (ADG) by GLCN. ADG is a cross-cutting interrogation software that allows the easy and fast recombination of land cover polygons according to the individual end-user requirements. Aggregated land cover classes can be generated not only by name, but also using the set of existing classifiers. ADG uses land cover data with a Land Cover Classification System (LCCS) legend. The ADG software is available for download on the GLCN web site at http://www.glcn.org/sof_7_en.jsp

Contact points:

Metadata Contact: FAO-Data

Resource Contact: Antonio Martucci

Data lineage:

This land cover database is provided as ESRI shape file (vector format) and derives from reprocessing the raster based Globcover database (regional version). Globcover has undergone the following process: a) vectoralization at the national extent using ESRI ArcGis (arcinfo) 9.3; b) topological reconstruction (custom AML scripts launched inside ArcGis-arcinfo 9.3); c) simplification of areas according to a minimum mapping unit of 0.1 skim (10 ha) (custom AML scripts launched inside ArcGis-arcinfo 9.3); application of the FAO/UNEP Land Cover Classification System (LCCS) legend (46 classes); final processing to assure full compatibility with the GLCN software Advanced Database Gateway (ADG).

Online resources:

Download - Land cover of Seychelles - Shape file format

GLOBCOVER on the ESA Web site

Global Land Cover Network - GLCN