34 datasets found
  1. Open-Source GIScience Online Course

    • ckan.americaview.org
    Updated Nov 2, 2021
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    ckan.americaview.org (2021). Open-Source GIScience Online Course [Dataset]. https://ckan.americaview.org/dataset/open-source-giscience-online-course
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    Dataset updated
    Nov 2, 2021
    Dataset provided by
    CKANhttps://ckan.org/
    License

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

    Description

    In this course, you will explore a variety of open-source technologies for working with geosptial data, performing spatial analysis, and undertaking general data science. The first component of the class focuses on the use of QGIS and associated technologies (GDAL, PROJ, GRASS, SAGA, and Orfeo Toolbox). The second component of the class introduces Python and associated open-source libraries and modules (NumPy, Pandas, Matplotlib, Seaborn, GeoPandas, Rasterio, WhiteboxTools, and Scikit-Learn) used by geospatial scientists and data scientists. We also provide an introduction to Structured Query Language (SQL) for performing table and spatial queries. This course is designed for individuals that have a background in GIS, such as working in the ArcGIS environment, but no prior experience using open-source software and/or coding. You will be asked to work through a series of lecture modules and videos broken into several topic areas, as outlined below. Fourteen assignments and the required data have been provided as hands-on opportunites to work with data and the discussed technologies and methods. If you have any questions or suggestions, feel free to contact us. We hope to continue to update and improve this course. This course was produced by West Virginia View (http://www.wvview.org/) with support from AmericaView (https://americaview.org/). This material is based upon work supported by the U.S. Geological Survey under Grant/Cooperative Agreement No. G18AP00077. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the opinions or policies of the U.S. Geological Survey. Mention of trade names or commercial products does not constitute their endorsement by the U.S. Geological Survey. After completing this course you will be able to: apply QGIS to visualize, query, and analyze vector and raster spatial data. use available resources to further expand your knowledge of open-source technologies. describe and use a variety of open data formats. code in Python at an intermediate-level. read, summarize, visualize, and analyze data using open Python libraries. create spatial predictive models using Python and associated libraries. use SQL to perform table and spatial queries at an intermediate-level.

  2. All Chapters Tutorial Data

    • hub.arcgis.com
    Updated Jun 14, 2020
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    Esri Tutorials (2020). All Chapters Tutorial Data [Dataset]. https://hub.arcgis.com/datasets/9f9984c3eadd420689cbeced693292b2
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    Dataset updated
    Jun 14, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri Tutorials
    Description

    Total file size: about 367M in zip format and about 600M after extracted. (To download: click the Download button at the upper right area of this page)Alternatively, you can download the data by chapters:- Go to https://go.esri.com/gtkwebgis4- Under Group Categories on the left, click each chapter, you will see the data file to download for that chapter.

  3. OpenStreetMap

    • esriindia.hub.arcgis.com
    • ethiopia.africageoportal.com
    • +33more
    Updated Nov 21, 2024
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    Esri India SAAS App (2024). OpenStreetMap [Dataset]. https://esriindia.hub.arcgis.com/maps/671a954016794bef88b76ac215ec5fef
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    Dataset updated
    Nov 21, 2024
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri India SAAS App
    License

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

    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

  4. Aerial Data and Processed Models of Port Arthur Coastal Neighborhood and...

    • osti.gov
    • search.dataone.org
    Updated Jan 1, 2024
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    Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) (United States) (2024). Aerial Data and Processed Models of Port Arthur Coastal Neighborhood and Pleasure Island Golf Course, June 2024 [Dataset]. http://doi.org/10.15485/2406464
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    Dataset updated
    Jan 1, 2024
    Dataset provided by
    United States Department of Energyhttp://energy.gov/
    Southeast Texas Urban Integrated Field Laboratory (SETx UIFL) – Equitable solutions for communities caught between floods and air pollution
    DOE:DE-SC0023216
    Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) (United States)
    Area covered
    Port Arthur
    Description

    Our Co-design team is from the University of Texas, working on a Department of Energy-funded project focused on the Beaumont-Port Arthur area. As part of this project, we will be developing climate-resilient design solutions for areas of the region. More on www.caee.utexas.edu.We captured aerial photos in the Port Arthur Coastal Neighborhood Community and the Golf Course on Pleasure Island, Texas, in June 2024.Aerial photos taken were through DroneDeploy autonomous flight, and models were processed through the DroneDeploy engine as well. All aerial photos are in .JPG format and contained in zipped files for each area.The processed data package includes 3D models, geospatial data, mappings, and point clouds. Please be aware that DTM, Elevation toolbox, Point cloud, and Orthomosaic use EPSG: 6588. And 3D Model uses EPSG: 3857.For using these data:- The Adobe Suite gives you great software to open .Tif files.- You can use LASUtility (Windows), ESRI ArcGIS Pro (Windows), or Blaze3D (Windows, Linux) to open a LAS file and view the data it contains.- Open an .OBJ file with a large number of free and commercial applications. Some examples include Microsoft 3D Builder, Apple Preview, Blender, and Autodesk.- You may use ArcGIS, Merkaartor, Blender (with the Google Earth Importer plug-in), Global Mapper, and Marble to open .KML files.- The .tfw world file is a text file used to georeference the GeoTIFF raster images, like the orthomosaic and the DSM. You need suitable software like ArcView to open a .TFW file.This dataset provides researchers with sufficient geometric data and the status quo of the land surface at the locations mentioned above. This dataset could streamline researchers' decision-making processes and enhance the design as well.

  5. 04.5 Using ArcGIS for Land Records Management

    • training-iowadot.opendata.arcgis.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • +1more
    Updated Feb 18, 2017
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    Iowa Department of Transportation (2017). 04.5 Using ArcGIS for Land Records Management [Dataset]. https://training-iowadot.opendata.arcgis.com/documents/b432b3b66e954db9bc4c855f0f678d2b
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    Dataset updated
    Feb 18, 2017
    Dataset authored and provided by
    Iowa Department of Transportationhttps://iowadot.gov/
    License

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

    Description

    This seminar discusses the five common business patterns of GIS implementation (asset management, planning and analyis, field mobility, operational awareness, and citizen engagement), and how to address these patterns with the ArcGIS system and free applications on the Resource Center.

  6. 07.0 Data QC with ArcGIS: Visual Review

    • training-iowadot.opendata.arcgis.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    Updated Feb 23, 2017
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    Iowa Department of Transportation (2017). 07.0 Data QC with ArcGIS: Visual Review [Dataset]. https://training-iowadot.opendata.arcgis.com/documents/c9450ca88b084800bdc6f82bc69ec27f
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    Dataset updated
    Feb 23, 2017
    Dataset authored and provided by
    Iowa Department of Transportationhttps://iowadot.gov/
    License

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

    Description

    How do you ensure your data is free of errors? While you may already leverage ArcGIS Data Reviewer for its automated validation capabilities, you might ocassionally encounter problems with certain challenging subsets of features. For example, think about a situation in which you expected an automated data check to return a certain error but it did not. You tried configuring the check over and over again, but did not figure out a method of automatically detecting the error.Visual review can help. Manually reviewing your data provides a way to find errors that are difficult to detect using automated methods, such as features that are missing, misplaced, miscoded, or redundant.The following graphic shows the topics that will be covered throughout the course. You will learn the associated workflows that take advantage of ArcGIS Data Reviewer functionality.After completing this course, you will be able to:Determine situations in which visual review is appropriate.Analyze a statistically significant sample.Create a QC grid and perform a systematic visual review.Indicate missing, misplaced, miscoded, or redundant features.Recognize how to find changes between versions.

  7. Land cover of United Republic of Tanzania - Globcover Regional (46 classes)

    • data.amerigeoss.org
    html, http, png, wms +1
    Updated Mar 14, 2023
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    Food and Agriculture Organization (2023). Land cover of United Republic of Tanzania - Globcover Regional (46 classes) [Dataset]. https://data.amerigeoss.org/dataset/adb0b581-b530-4a06-8a86-ed562ddc63b6
    Explore at:
    http, zip, html, png, wmsAvailable download formats
    Dataset updated
    Mar 14, 2023
    Dataset provided by
    Food and Agriculture Organizationhttp://fao.org/
    Description

    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 United Republic of Tanzania - Shape file format

    GLOBCOVER on the ESA Web site

    Global Land Cover Network - GLCN

  8. H

    Digital Elevation Models and GIS in Hydrology (M2)

    • hydroshare.org
    • beta.hydroshare.org
    • +1more
    zip
    Updated Jun 7, 2021
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    Irene Garousi-Nejad; Belize Lane (2021). Digital Elevation Models and GIS in Hydrology (M2) [Dataset]. http://doi.org/10.4211/hs.9c4a6e2090924d97955a197fea67fd72
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    zip(88.2 MB)Available download formats
    Dataset updated
    Jun 7, 2021
    Dataset provided by
    HydroShare
    Authors
    Irene Garousi-Nejad; Belize Lane
    License

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

    Area covered
    Description

    This resource contains data inputs and a Jupyter Notebook that is used to introduce Hydrologic Analysis using Terrain Analysis Using Digital Elevation Models (TauDEM) and Python. TauDEM is a free and open-source set of Digital Elevation Model (DEM) tools developed at Utah State University for the extraction and analysis of hydrologic information from topography. This resource is part of a HydroLearn Physical Hydrology learning module available at https://edx.hydrolearn.org/courses/course-v1:Utah_State_University+CEE6400+2019_Fall/about

    In this activity, the student learns how to (1) derive hydrologically useful information from Digital Elevation Models (DEMs); (2) describe the sequence of steps involved in mapping stream networks, catchments, and watersheds; and (3) compute an approximate water balance for a watershed-based on publicly available data.

    Please note that this exercise is designed for the Logan River watershed, which drains to USGS streamflow gauge 10109000 located just east of Logan, Utah. However, this Jupyter Notebook and the analysis can readily be applied to other locations of interest. If running the terrain analysis for other study sites, you need to prepare a DEM TIF file, an outlet shapefile for the area of interest, and the average annual streamflow and precipitation data. - There are several sources to obtain DEM data. In the U.S., the DEM data (with different spatial resolutions) can be obtained from the National Elevation Dataset available from the national map (http://viewer.nationalmap.gov/viewer/). Another DEM data source is the Shuttle Radar Topography Mission (https://www2.jpl.nasa.gov/srtm/), an international research effort that obtained digital elevation models on a near-global scale (search for Digital Elevation at https://www.usgs.gov/centers/eros/science/usgs-eros-archive-products-overview?qt-science_center_objects=0#qt-science_center_objects). - If not already available, you can generate the outlet shapefile by applying basic terrain analysis steps in geospatial information system models such as ArcGIS or QGIS. - You also need to obtain average annual streamflow and precipitation data for the watershed of interest to assess the annual water balance and calculate the runoff ratio in this exercise. In the U.S., the streamflow data can be obtained from the USGS NWIS website (https://waterdata.usgs.gov/nwis) and the precipitation from PRISM (https://prism.oregonstate.edu/normals/). Note that using other datasets may require preprocessing steps to make data ready to use for this exercise.

  9. Land cover of Egypt - Globcover Regional (46 classes)

    • data.amerigeoss.org
    html, http, png, wms +1
    Updated Mar 14, 2023
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    Food and Agriculture Organization (2023). Land cover of Egypt - Globcover Regional (46 classes) [Dataset]. https://data.amerigeoss.org/dataset/83e8e4c9-4011-489a-8b0d-aa3a9693ccce
    Explore at:
    zip, wms, html, png, httpAvailable download formats
    Dataset updated
    Mar 14, 2023
    Dataset provided by
    Food and Agriculture Organizationhttp://fao.org/
    License

    Attribution-NonCommercial-ShareAlike 3.0 (CC BY-NC-SA 3.0)https://creativecommons.org/licenses/by-nc-sa/3.0/
    License information was derived automatically

    Area covered
    Egypt
    Description

    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 Egypt - Shape file format

    GLOBCOVER on the ESA Web site

    Global Land Cover Network - GLCN

  10. d

    Real-time kinematic (RTK) Drone-collected Data and Processed Models of Port...

    • dataone.org
    • osti.gov
    Updated Oct 26, 2024
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    Paul Buschow; Linchao Luo; William Mobley; Suzanne Pierce (2024). Real-time kinematic (RTK) Drone-collected Data and Processed Models of Port Arthur Coastal Neighborhood and Pleasure Island Golf Course, June 2024 [Dataset]. http://doi.org/10.15485/2447557
    Explore at:
    Dataset updated
    Oct 26, 2024
    Dataset provided by
    ESS-DIVE
    Authors
    Paul Buschow; Linchao Luo; William Mobley; Suzanne Pierce
    Time period covered
    Jun 17, 2024 - Jun 20, 2024
    Area covered
    Description

    The Southeast Texas Urban Integrated field lab’s Co-design team captured aerial photos in the Port Arthur Coastal Neighborhood Community and the Golf Course on Pleasure Island, Texas, in June 2024. Aerial photos taken were through autonomous flight, and models were processed through the DroneDeploy engine. All aerial photos are in .JPG format and contained in zipped files for each area. The processed data package includes 3D models, geospatial data, mappings, and point clouds. Please be aware that DTM, Elevation toolbox, Point Cloud, and Orthomosaic use EPSG: 6588. And 3D Model uses EPSG: 3857. For using these data: - The Adobe Suite gives you great software to open .Tif files. - You can use LASUtility (Windows), ESRI ArcGIS Pro (Windows), or Blaze3D (Windows, Linux) to open a LAS file and view the data it contains. - Open an .OBJ file with a large number of free and commercial applications. Some examples include Microsoft 3D Builder, Apple Preview, Blender, and Autodesk. - You may use ArcGIS, Merkaartor, Blender (with the Google Earth Importer plug-in), Global Mapper, and Marble to open .KML files. - The .tfw world file is a text file used to georeference the GeoTIFF raster images, like the orthomosaic and the DSM. You need suitable software like ArcView to open a .TFW file. This dataset provides researchers with sufficient geometric data and the status quo of the land surface at the locations mentioned above. This dataset will support researchers' decision-making processes under uncertainties.

  11. Land cover of Seychelles - Globcover Regional (46 classes)

    • data.amerigeoss.org
    html, http, png, wms +1
    Updated Mar 14, 2023
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    Food and Agriculture Organization (2023). Land cover of Seychelles - Globcover Regional (46 classes) [Dataset]. https://data.amerigeoss.org/dataset/e86cfe98-9a50-4b96-a65a-b0a9bc789e73
    Explore at:
    html, wms, zip, png, httpAvailable download formats
    Dataset updated
    Mar 14, 2023
    Dataset provided by
    Food and Agriculture Organizationhttp://fao.org/
    License

    Attribution-NonCommercial-ShareAlike 3.0 (CC BY-NC-SA 3.0)https://creativecommons.org/licenses/by-nc-sa/3.0/
    License information was derived automatically

    Area covered
    Seychelles
    Description

    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

  12. Training: 3. GIS Concepts, Applications, and Software

    • sudan-uneplive.hub.arcgis.com
    Updated Jun 25, 2020
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    UN Environment, Early Warning &Data Analytics (2020). Training: 3. GIS Concepts, Applications, and Software [Dataset]. https://sudan-uneplive.hub.arcgis.com/documents/642a61631daf44e0b91991fbd774e3e8
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    Dataset updated
    Jun 25, 2020
    Dataset provided by
    United Nations Environment Programmehttp://www.unep.org/
    Authors
    UN Environment, Early Warning &Data Analytics
    Description

    This is a full-day training, developed by UNEP CMB, to introduce participants to the basics of GIS, how to import points from Excel to a GIS, and how to make maps with QGIS, MapX and Tableau. It prioritizes the use of free and open software.

  13. o

    10m Annual Land Use Land Cover (9-class)

    • registry.opendata.aws
    • collections.sentinel-hub.com
    Updated Jul 6, 2023
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    Impact Observatory (2023). 10m Annual Land Use Land Cover (9-class) [Dataset]. https://registry.opendata.aws/io-lulc/
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    Dataset updated
    Jul 6, 2023
    Dataset provided by
    <a href="https://www.impactobservatory.com/">Impact Observatory</a>
    License

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

    Description

    This dataset, produced by Impact Observatory, Microsoft, and Esri, displays a global map of land use and land cover (LULC) derived from ESA Sentinel-2 imagery at 10 meter resolution for the years 2017 - 2023. Each map is a composite of LULC predictions for 9 classes throughout the year in order to generate a representative snapshot of each year. This dataset was generated by Impact Observatory, which used billions of human-labeled pixels (curated by the National Geographic Society) to train a deep learning model for land classification. Each global map was produced by applying this model to the Sentinel-2 annual scene collections from the Mircosoft Planetary Computer. Each of the maps has an assessed average accuracy of over 75%. These maps have been improved from Impact Observatory’s previous release and provide a relative reduction in the amount of anomalous change between classes, particularly between “Bare” and any of the vegetative classes “Trees,” “Crops,” “Flooded Vegetation,” and “Rangeland”. This updated time series of annual global maps is also re-aligned to match the ESA UTM tiling grid for Sentinel-2 imagery. Data can be accessed directly from the Registry of Open Data on AWS, from the STAC 1.0.0 endpoint, or from the IO Store for a specific Area of Interest (AOI).

  14. Land cover of Cameroon - Globcover Regional (46 classes)

    • data.amerigeoss.org
    html, http, png, wms +1
    Updated Mar 14, 2023
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    Food and Agriculture Organization (2023). Land cover of Cameroon - Globcover Regional (46 classes) [Dataset]. https://data.amerigeoss.org/dataset/235d6f0d-b6c7-41d3-a09b-a741dee3f555
    Explore at:
    html, http, wms, png, zipAvailable download formats
    Dataset updated
    Mar 14, 2023
    Dataset provided by
    Food and Agriculture Organizationhttp://fao.org/
    License

    Attribution-NonCommercial-ShareAlike 3.0 (CC BY-NC-SA 3.0)https://creativecommons.org/licenses/by-nc-sa/3.0/
    License information was derived automatically

    Area covered
    Cameroon
    Description

    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 Cameroon - Shape file format

    GLOBCOVER on the ESA Web site

    Global Land Cover Network - GLCN

  15. Land cover of Mozambique - Globcover Regional (46 classes)

    • data.amerigeoss.org
    html, http, png, wms +1
    Updated Mar 14, 2023
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    Food and Agriculture Organization (2023). Land cover of Mozambique - Globcover Regional (46 classes) [Dataset]. https://data.amerigeoss.org/dataset/e58eada2-046a-4277-a812-5c11762ed902
    Explore at:
    png, wms, http, html, zipAvailable download formats
    Dataset updated
    Mar 14, 2023
    Dataset provided by
    Food and Agriculture Organizationhttp://fao.org/
    License

    Attribution-NonCommercial-ShareAlike 3.0 (CC BY-NC-SA 3.0)https://creativecommons.org/licenses/by-nc-sa/3.0/
    License information was derived automatically

    Area covered
    Mozambique
    Description

    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 Mozambique - Shape file format

    GLOBCOVER on the ESA Web site

    Global Land Cover Network - GLCN

  16. Land cover of Viet Nam - Globcover (22 classes)

    • data.amerigeoss.org
    html, http, png, zip
    Updated Mar 14, 2023
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    Food and Agriculture Organization (2023). Land cover of Viet Nam - Globcover (22 classes) [Dataset]. https://data.amerigeoss.org/dataset/838ae47f-1318-41f1-a3cd-bb36b80f3b42
    Explore at:
    html, png, http, zipAvailable download formats
    Dataset updated
    Mar 14, 2023
    Dataset provided by
    Food and Agriculture Organizationhttp://fao.org/
    License

    Attribution-NonCommercial-ShareAlike 3.0 (CC BY-NC-SA 3.0)https://creativecommons.org/licenses/by-nc-sa/3.0/
    License information was derived automatically

    Area covered
    Vietnam
    Description

    This land cover data set is derived from the original raster based Globcover global archive. It has been post-processed to generate a vector version at national extent with the LCCS regional legend (22 classes worldwide). The 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) -Perimeter (m) -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 table (.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 global archive, Globcover. Globcover database 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 (24 classes globally); final processing to assure full compatibility with the GLCN software Advanced Database Gateway (ADG).

    Online resources:

    Download Land cover of Viet Nam - Shape file format

    GLOBCOVER on the ESA Web site

    Global Land Cover Network - GLCN

  17. Land cover of Burkina Faso - Globcover Regional (46 classes)

    • data.amerigeoss.org
    html, http, png, wms +1
    Updated Mar 14, 2023
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    Food and Agriculture Organization (2023). Land cover of Burkina Faso - Globcover Regional (46 classes) [Dataset]. https://data.amerigeoss.org/dataset/groups/d5acf3e9-5f60-4338-8a7d-4dfe36acb7d0
    Explore at:
    zip, png, html, wms, httpAvailable download formats
    Dataset updated
    Mar 14, 2023
    Dataset provided by
    Food and Agriculture Organizationhttp://fao.org/
    License

    Attribution-NonCommercial-ShareAlike 3.0 (CC BY-NC-SA 3.0)https://creativecommons.org/licenses/by-nc-sa/3.0/
    License information was derived automatically

    Area covered
    Burkina Faso
    Description

    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 Burkina Faso - Shape file format

    GLOBCOVER on the ESA Web site

    Global Land Cover Network - GLCN

  18. Land cover of Bolivia - Globcover (22 classes)

    • data.amerigeoss.org
    html, http, png, zip
    Updated Mar 14, 2023
    + more versions
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    Food and Agriculture Organization (2023). Land cover of Bolivia - Globcover (22 classes) [Dataset]. https://data.amerigeoss.org/dataset/e3cd1134-b99f-4436-aa59-c540d7237bcf
    Explore at:
    http, png, html, zipAvailable download formats
    Dataset updated
    Mar 14, 2023
    Dataset provided by
    Food and Agriculture Organizationhttp://fao.org/
    License

    Attribution-NonCommercial-ShareAlike 3.0 (CC BY-NC-SA 3.0)https://creativecommons.org/licenses/by-nc-sa/3.0/
    License information was derived automatically

    Area covered
    Bolivia
    Description

    This land cover data set is derived from the original raster based Globcover global archive. It has been post-processed to generate a vector version at national extent with the LCCS regional legend (22 classes worldwide). The 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) -Perimeter (m) -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 table (.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 global archive, Globcover. Globcover database 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 (24 classes globally); final processing to assure full compatibility with the GLCN software Advanced Database Gateway (ADG).

    Online resources:

    Download Land cover of Bolivia - Shape file format

    GLOBCOVER on the ESA Web site

    Global Land Cover Network - GLCN

  19. Land cover of Democratic Republic of the Congo - Globcover (22 classes)

    • data.amerigeoss.org
    html, http, png, zip
    Updated Mar 14, 2023
    + more versions
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    Food and Agriculture Organization (2023). Land cover of Democratic Republic of the Congo - Globcover (22 classes) [Dataset]. https://data.amerigeoss.org/dataset/cf4fa415-bba2-4f0a-9007-c08c17fbbddf
    Explore at:
    html, png, zip, httpAvailable download formats
    Dataset updated
    Mar 14, 2023
    Dataset provided by
    Food and Agriculture Organizationhttp://fao.org/
    License

    Attribution-NonCommercial-ShareAlike 3.0 (CC BY-NC-SA 3.0)https://creativecommons.org/licenses/by-nc-sa/3.0/
    License information was derived automatically

    Area covered
    Democratic Republic of the Congo
    Description

    This land cover data set is derived from the original raster based Globcover global archive. It has been post-processed to generate a vector version at national extent with the LCCS regional legend (22 classes worldwide). The 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) -Perimeter (m) -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 table (.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 global archive, Globcover. Globcover database 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 0.2 skim (20 ha) (custom AML scripts launched inside ArcGis-arcinfo 9.3); application of the FAO/UNEP Land Cover Classification System (LCCS) legend (24 classes globally); final processing to assure full compatibility with the GLCN software Advanced Database Gateway (ADG).

    Online resources:

    Land cover of Democratic Republic of the Congo - Shape file format

    GLOBCOVER on the ESA Web site

    Global Land Cover Network - GLCN

  20. Land cover of Zambia - Globcover Regional (46 classes)

    • data.amerigeoss.org
    html, png, wms, zip
    Updated Mar 14, 2023
    + more versions
    Share
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    Food and Agriculture Organization (2023). Land cover of Zambia - Globcover Regional (46 classes) [Dataset]. https://data.amerigeoss.org/he/dataset/ddad78a7-64e5-47c5-9091-4c07480a8ff3
    Explore at:
    wms, html, png, zipAvailable download formats
    Dataset updated
    Mar 14, 2023
    Dataset provided by
    Food and Agriculture Organizationhttp://fao.org/
    License

    Attribution-NonCommercial-ShareAlike 3.0 (CC BY-NC-SA 3.0)https://creativecommons.org/licenses/by-nc-sa/3.0/
    License information was derived automatically

    Area covered
    Zambia
    Description

    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 Zambia 46 classes - Shape file format

    GLOBCOVER on the ESA Web site

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Link copied
Close
Cite
ckan.americaview.org (2021). Open-Source GIScience Online Course [Dataset]. https://ckan.americaview.org/dataset/open-source-giscience-online-course
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Open-Source GIScience Online Course

Explore at:
Dataset updated
Nov 2, 2021
Dataset provided by
CKANhttps://ckan.org/
License

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

Description

In this course, you will explore a variety of open-source technologies for working with geosptial data, performing spatial analysis, and undertaking general data science. The first component of the class focuses on the use of QGIS and associated technologies (GDAL, PROJ, GRASS, SAGA, and Orfeo Toolbox). The second component of the class introduces Python and associated open-source libraries and modules (NumPy, Pandas, Matplotlib, Seaborn, GeoPandas, Rasterio, WhiteboxTools, and Scikit-Learn) used by geospatial scientists and data scientists. We also provide an introduction to Structured Query Language (SQL) for performing table and spatial queries. This course is designed for individuals that have a background in GIS, such as working in the ArcGIS environment, but no prior experience using open-source software and/or coding. You will be asked to work through a series of lecture modules and videos broken into several topic areas, as outlined below. Fourteen assignments and the required data have been provided as hands-on opportunites to work with data and the discussed technologies and methods. If you have any questions or suggestions, feel free to contact us. We hope to continue to update and improve this course. This course was produced by West Virginia View (http://www.wvview.org/) with support from AmericaView (https://americaview.org/). This material is based upon work supported by the U.S. Geological Survey under Grant/Cooperative Agreement No. G18AP00077. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the opinions or policies of the U.S. Geological Survey. Mention of trade names or commercial products does not constitute their endorsement by the U.S. Geological Survey. After completing this course you will be able to: apply QGIS to visualize, query, and analyze vector and raster spatial data. use available resources to further expand your knowledge of open-source technologies. describe and use a variety of open data formats. code in Python at an intermediate-level. read, summarize, visualize, and analyze data using open Python libraries. create spatial predictive models using Python and associated libraries. use SQL to perform table and spatial queries at an intermediate-level.

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