EarthExplorerUse the USGS EarthExplorer (EE) to search, download, and order satellite images, aerial photographs, and cartographic products. In addition to data from the Landsat missions and a variety of other data providers, EE provides access to MODIS land data products from the NASA Terra and Aqua missions, and ASTER level-1B data products over the U.S. and Territories from the NASA ASTER mission. Registered users of EE have access to more features than guest users.Earth Explorer Distribution DownloadThe EarthExplorer user interface is an online search, discovery, and ordering tool developed by the United States Geological Survey (USGS). EarthExplorer supports the searching of satellite, aircraft, and other remote sensing inventories through interactive and textual-based query capabilities. Through the interface, users can identify search areas, datasets, and display metadata, browse and integrated visual services within the interface.The distributable version of EarthExplorer provides the basic software to provide this functionality. Users are responsible for verification of system recommendations for hosting the application on your own servers. By default, this version of our code is not hooked up to a data source so you will have to integrate the interface with your data. Integration options include service-based API's, databases, and anything else that stores data. To integrate with a data source simply replace the contents of the 'getDataset' and 'search' functions in the CWIC.php file.Distribution is being provided due to users requests for the codebase. The EarthExplorer source code is provided "As Is", without a warranty or support of any kind. The software is in the public domain; it is available to any government or private institution.The software code base is managed through the USGS Configuration Management Board. The software is managed through an automated configuration management tool that updates the code base when new major releases have been thoroughly reviewed and tested.Link: https://earthexplorer.usgs.gov/

This FREE extension enables discovering and using GIS resources available in a GEOSS Clearinghouse directly from ArcGIS Desktop and ArcGIS Explorer. The CS-W Client for ArcGIS can search many implementations of CS-W implementing CS-W 2.0.0, 2.0.1, 2.0.2 and a number of Application Profiles (OGCCORE, APISO, EBRIM). Providers can extend the CS-W Client by creating a profile of their CS-W service and including that in the CS-W client configuration. View the title, abstract, or footprints of search results or view and download the full metadata. Add referenced live map services (ArcGIS Server, ArcIMS, WMS) to an ArcMap document or ArcGIS Explorer globe. ArcGIS Desktop 9.3 is required to install the ArcMap component of the CS-W Clients for ArcGIS. The CS-W Clients for ArcGIS component for ArcGIS Explorer requires ArcGIS Explorer 380 or higher.

About the dataLand use land cover (LULC) maps are an increasingly important tool for decision-makers in many industry sectors and developing nations around the world. The information provided by these maps helps inform policy and land management decisions by better understanding and quantifying the impacts of earth processes and human activity.ArcGIS Living Atlas of the World provides a detailed, accurate, and timely LULC map of the world. The data is the result of a three-way collaboration among Esri, Impact Observatory, and Microsoft. For more information about the data, see Sentinel-2 10m Land Use/Land Cover Time Series.About the appOne of the foremost capabilities of this app is the dynamic change analysis. The app provides dynamic visual and statistical change by comparing annual slices of the Sentinel-2 10m Land Use/Land Cover data as you explore the map.Overview of capabilities:Visual change analysis with either 'Step Mode' or 'Swipe Mode'Dynamic statistical change analysis by year, map extent, and classFilter by selected land cover classRegional class statistics summarized by administrative boundariesImagery mode for visual investigation and validation of land coverSelect imagery renderings (e.g. SWIR to visualize forest burn scars)Data download for offline use

The ArcGIS Online US Geological Survey (USGS) topographic map collection now contains over 177,000 historical quadrangle maps dating from 1882 to 2006. The USGS Historical Topographic Map Explorer app brings these maps to life through an interface that guides users through the steps for exploring the map collection:

Finding the maps of interest is simple. Users can see a footprint of the map in the map view before they decide to add it to the display, and thumbnails of the maps are shown in pop-ups on the timeline. The timeline also helps users find maps because they can zoom and pan, and maps at select scales can be turned on or off by using the legend boxes to the left of the timeline. Once maps have been added to the display, users can reorder them by dragging them. Users can also download maps as zipped GeoTIFF images. Users can also share the current state of the app through a hyperlink or social media. This ArcWatch article guides you through each of these steps: https://www.esri.com/esri-news/arcwatch/1014/envisioning-the-past.

This web map references the live tiled map service from the OpenStreetMap 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 such as free satellite imagery, and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap server: http://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 and ArcGIS Explorer Online. 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.

Temperature survey at 2 meters. This web map service (WMS) was published using ArcServer v. 10.1 and is compliant with OGC (Open Geospatial Consortium) version 1.30 specifications. This service provides dynamic, spatially referenced geographic information using data collected for the National Geothermal Data System (http://www.geothermaldata.org/). In addition to the WMS capabilities, this service was designed to be interoperable with both WFS (Web Feature Services) as well as KML (Keyhole Markup Language). The WFS capabilities allow the client to query, make additions and/or modifications to an existing dataset. WFS can be utilized through the interoperability extension in ArcCatalog. For more information on using the ArcGIS data interoperability extension visit http://www.esri.com/software/arcgis/extensions/datainteroperability /common-questions.html. A KML service allows the client to view an image of the data in three dimensions, using free software available for download on the internet such as ArcGIS Explorer or Google Earth. For more information on OGC specifications, visit http://www.opengeospatial.org/standards.

This web map service (WMS) was published using ArcServer v. 10.1 and is compliant with OGC (Open Geospatial Consortium) version 1.30 specifications. This service provides dynamic, spatially referenced geographic information using data collected for the National Geothermal Data System (http://www.geothermaldata.org/). In addition to the WMS capabilities, this service was designed to be interoperable with both WFS (Web Feature Services) as well as KML (Keyhole Markup Language). The WFS capabilities allow the client to query, make additions and/or modifications to an existing dataset. WFS can be utilized through the interoperability extension in ArcCatalog. For more information on using the ArcGIS data interoperability extension visit http://www.esri.com/software/arcgis/extensions/datainteroperability /common-questions.html. A KML service allows the client to view an image of the data in three dimensions, using free software available for download on the internet such as ArcGIS Explorer or Google Earth. For more information on OGC specifications, visit http://www.opengeospatial.org/standards.

The North Carolina Natural Heritage Program"s Managed Areas are primarily a collection of fee simple properties and easements where natural resource conservation is one of the primary management goals. It does include a number of properties and easements that are not primarily managed for conservation, but that are of conservation interest. This conservation interest ranges from properties and easements which support rare species and intact, high-quality natural communities to those that are open spaces in places where open space is scarce. Lands that are Dedicated Nature Preserves or Registered Heritage Areas are found in this data set.These data are the current equivalent of the Conservation Tax Credit Properties and Land Trust Conservation Properties data set.Some of the Managed Areas represented in this data set are on private land and are not open to the public. Written permission should be obtained from all appropriate landowners before visiting any of these sites.NOTE: This is a large dataset and compiling the download using the map may take some time or fail. The data is also available as an Esri shapefile in a ZIP download from the North Carolina Natural Heritage Program"s Data Explorer data download page (https://ncnhde.natureserve.org/content/data-download).

Use the American Viticultural Area (AVA) Map Explorer to view the boundaries of all established and proposed AVAs. The Map Explorer has information about each AVA, including its state and county, when it was established, what other AVAs it contains or is within, and a link to its codified official boundary description. You can even plot an address on the Map Explorer to see if that location is within an AVA. You can also download "shapefiles" for the various AVAs, which you can use with geographic information system (GIS) software.

A digital version of multiple compiled geologic maps of the state of Nevada, displayed on multiple scales, and available as a WMS and WFS on the OneGeology portal (www.onegeology.org/portal) and through the NBMG GeoServer. Data compiled by the Nevada Bureau of Mines and Geology for OneGeology (http://www.onegeology.org/). Published using ArcServer v. 10.0 and is compliant with OGC (Open Geospatial Consortium) version 1.30 specifications and interoperable with GeoSciML v. 3.0. Visit http://www.opengeospatial.org/standards for more information on OGC specifications. In addition to WMS and WFS, the service was designed to be interoperable with KML (Keyhole Markup Language), which allows the client to view an image of the data in three dimensions, using free software available for download on the internet such as ArcGIS Explorer or Google Earth.

The Global Data Explorer (GDEx) tool allows users to browse and download ASTER GDEM data based on geographic areas of interest or predefined regions, including state, province, and county (for the United States). Data output from GDEx is available in GeoTIFF or ArcASCII format. GDEx is the result of collaboration between the LP DAAC and George Mason University's Center for Spatial Information Science and Systems.

Geoscience Australia is releasing its 2014 version of the Marine Seismic Surveys Shape and Kml files. These files have been updated to include recent openfile surveys. The spatial files have been created from a cleansed, updated collection of p190 navigation files. This navigation collection has grown from the checking of navigation submitted to the GA Repository under the Offshore Petroleum and Greenhouse Gas Storage Regulations, checking of the 2003 SNIP navigation files and the digitisation of old survey track maps as required. Soon the individual p190 files will be available for download through the new NOPIMS delivery system. The collection is based on P190 navigation files which follows the UKOOA standard. Extensive industry standard metadata associated with a seismic survey is preserved in the attribute tables of these datasets.

The shapefiles have been categorised into 3D exploration, 2D exploration and 2D investigative seismic files. All marine surveys undertaken by Geoscience Australia for exploration or investigative purposes have been included in the collection. Geoscience Australia (email - AusGeodata@ga.gov.au) appreciates being notified of any errors found in the navigation collection.

The data is available in both KML and Shape file formats.

The KML file can be viewed using a range of applications including Google Earth, NASA WorldWind, ESRI ArcGIS Explorer, Adobe PhotoShop, AutoCAD3D or any other earth browser (geobrowser) that accepts KML formatted data.

Alternatively the Shape files can be downloaded and viewed using any application that supports shape files.

Disclaimer: Geoscience Australia gives no warranty regarding the data downloads provided herein nor the data's accuracy, completeness, currency or suitability for any particular purpose. Geoscience Australia disclaims all other liability for all loss, damages, expense and costs incurred by any person as a result of relying on the information in the data downloads.

This service contains UDOT mile point measures and tenth mile point measures created from UDOT's ALRS. The data is scale dependent and is only visible at specific scales. Data in this service only appears along state routes. This information has a weekly refresh. Click on the point for link to RoadViewer Explorer and Streetview.To download this data please visit UDOT's Open Data Site.

About the dataLand use land cover (LULC) maps are an increasingly important tool for decision-makers in many industry sectors and developing nations around the world. The information provided by these maps helps inform policy and land management decisions by better understanding and quantifying the impacts of earth processes and human activity.ArcGIS Living Atlas of the World provides a detailed, accurate, and timely LULC map of the world. The data is the result of a three-way collaboration among Esri, Impact Observatory, and Microsoft. For more information about the data, see Sentinel-2 10m Land Use/Land Cover Time Series.About the appOne of the foremost capabilities of this app is the dynamic change analysis. The app provides dynamic visual and statistical change by comparing annual slices of the Sentinel-2 10m Land Use/Land Cover data as you explore the map.Overview of capabilities:Visual change analysis with either 'Step Mode' or 'Swipe Mode'Dynamic statistical change analysis by year, map extent, and classFilter by selected land cover classRegional class statistics summarized by administrative boundariesImagery mode for visual investigation and validation of land coverSelect imagery renderings (e.g. SWIR to visualize forest burn scars)Data download for offline use

This layer displays a global map of land use/land cover (LULC) derived from ESA Sentinel-2 imagery at 10m resolution. Each year is generated with Impact Observatory’s deep learning AI land classification model, trained using billions of human-labeled image pixels from the National Geographic Society. The global maps are produced by applying this model to the Sentinel-2 Level-2A image collection on Microsoft’s Planetary Computer, processing over 400,000 Earth observations per year.The algorithm generates LULC predictions for nine classes, described in detail below. The year 2017 has a land cover class assigned for every pixel, but its class is based upon fewer images than the other years. The years 2018-2024 are based upon a more complete set of imagery. For this reason, the year 2017 may have less accurate land cover class assignments than the years 2018-2024. Key Properties Variable mapped: Land use/land cover in 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024Source Data Coordinate System: Universal Transverse Mercator (UTM) WGS84Service Coordinate System: Web Mercator Auxiliary Sphere WGS84 (EPSG:3857)Extent: GlobalSource imagery: Sentinel-2 L2ACell Size: 10-metersType: ThematicAttribution: Esri, Impact ObservatoryAnalysis: Optimized for analysisClass Definitions: ValueNameDescription1WaterAreas where water was predominantly present throughout the year; may not cover areas with sporadic or ephemeral water; contains little to no sparse vegetation, no rock outcrop nor built up features like docks; examples: rivers, ponds, lakes, oceans, flooded salt plains.2TreesAny significant clustering of tall (~15 feet or higher) dense vegetation, typically with a closed or dense canopy; examples: wooded vegetation, clusters of dense tall vegetation within savannas, plantations, swamp or mangroves (dense/tall vegetation with ephemeral water or canopy too thick to detect water underneath).4Flooded vegetationAreas of any type of vegetation with obvious intermixing of water throughout a majority of the year; seasonally flooded area that is a mix of grass/shrub/trees/bare ground; examples: flooded mangroves, emergent vegetation, rice paddies and other heavily irrigated and inundated agriculture.5CropsHuman planted/plotted cereals, grasses, and crops not at tree height; examples: corn, wheat, soy, fallow plots of structured land.7Built AreaHuman made structures; major road and rail networks; large homogenous impervious surfaces including parking structures, office buildings and residential housing; examples: houses, dense villages / towns / cities, paved roads, asphalt.8Bare groundAreas of rock or soil with very sparse to no vegetation for the entire year; large areas of sand and deserts with no to little vegetation; examples: exposed rock or soil, desert and sand dunes, dry salt flats/pans, dried lake beds, mines.9Snow/IceLarge homogenous areas of permanent snow or ice, typically only in mountain areas or highest latitudes; examples: glaciers, permanent snowpack, snow fields.10CloudsNo land cover information due to persistent cloud cover.11RangelandOpen areas covered in homogenous grasses with little to no taller vegetation; wild cereals and grasses with no obvious human plotting (i.e., not a plotted field); examples: natural meadows and fields with sparse to no tree cover, open savanna with few to no trees, parks/golf courses/lawns, pastures. Mix of small clusters of plants or single plants dispersed on a landscape that shows exposed soil or rock; scrub-filled clearings within dense forests that are clearly not taller than trees; examples: moderate to sparse cover of bushes, shrubs and tufts of grass, savannas with very sparse grasses, trees or other plants.NOTE: Land use focus does not provide the spatial detail of a land cover map. As such, for the built area classification, yards, parks, and groves will appear as built area rather than trees or rangeland classes.Usage Information and Best PracticesProcessing TemplatesThis layer includes a number of preconfigured processing templates (raster function templates) to provide on-the-fly data rendering and class isolation for visualization and analysis. Each processing template includes labels and descriptions to characterize the intended usage. This may include for visualization, for analysis, or for both visualization and analysis. VisualizationThe default rendering on this layer displays all classes.There are a number of on-the-fly renderings/processing templates designed specifically for data visualization.By default, the most recent year is displayed. To discover and isolate specific years for visualization in Map Viewer, try using the Image Collection Explorer. AnalysisIn order to leverage the optimization for analysis, the capability must be enabled by your ArcGIS organization administrator. More information on enabling this feature can be found in the ‘Regional data hosting’ section of this help doc.Optimized for analysis means this layer does not have size constraints for analysis and it is recommended for multisource analysis with other layers optimized for analysis. See this group for a complete list of imagery layers optimized for analysis.Prior to running analysis, users should always provide some form of data selection with either a layer filter (e.g. for a specific date range, cloud cover percent, mission, etc.) or by selecting specific images. To discover and isolate specific images for analysis in Map Viewer, try using the Image Collection Explorer.Zonal Statistics is a common tool used for understanding the composition of a specified area by reporting the total estimates for each of the classes. GeneralIf you are new to Sentinel-2 LULC, the Sentinel-2 Land Cover Explorer provides a good introductory user experience for working with this imagery layer. For more information, see this Quick Start Guide.Global land use/land cover maps provide information on conservation planning, food security, and hydrologic modeling, among other things. This dataset can be used to visualize land use/land cover anywhere on Earth. Classification ProcessThese maps include Version 003 of the global Sentinel-2 land use/land cover data product. It is produced by a deep learning model trained using over five billion hand-labeled Sentinel-2 pixels, sampled from over 20,000 sites distributed across all major biomes of the world.The underlying deep learning model uses 6-bands of Sentinel-2 L2A surface reflectance data: visible blue, green, red, near infrared, and two shortwave infrared bands. To create the final map, the model is run on multiple dates of imagery throughout the year, and the outputs are composited into a final representative map for each year.The input Sentinel-2 L2A data was accessed via Microsoft’s Planetary Computer and scaled using Microsoft Azure Batch. CitationKarra, Kontgis, et al. “Global land use/land cover with Sentinel-2 and deep learning.” IGARSS 2021-2021 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2021.AcknowledgementsTraining data for this project makes use of the National Geographic Society Dynamic World training dataset, produced for the Dynamic World Project by National Geographic Society in partnership with Google and the World Resources Institute.

The data involved in this paper is from https://www.planet.com/explorer/. The resolution is 3m, and there are 3 main bands, RGB. Since the platform can only download a certain amount of data after applying for an account in the form of education, and at the same time the data is only retained for one month, we chose 8 major cities for the study, 2 images per city. we also provide detailed information on the data visualization and classification results that we have tested and retained in a PPT file called paper, we also provide detailed information on the data visualization and classification results of our tests in a PPT file called paper-result, which can be easily reviewed by reviewers. At the same time, reviewers can also download the data to verify the applicability of the results based on the coordinates of the data sources provided in this paper.The algorithms consist of three main types, one is based on traditional algorithms including object-based and pixel-based, in which we tested the generalization ability of four classifiers, including Random Forest, Support Vector Machine, Maximum Likelihood, and K-mean, in the form of classification in this different way. In addition, we tested two of the more mainstream deep learning classification algorithms, U-net and deeplabV3, both of which can be found and applied in the ArcGIS pro software. The traditional algorithms can be found by checking https://pro.arcgis.com/en/pro-app/latest/help/analysis/image-analyst/the-image-classification-wizard.htm to find the running process, while the related parameter settings and Sample selection rules can be found in detail in the article. Deep learning algorithms can be found at https://pro.arcgis.com/en/pro-app/latest/help/analysis/deep-learning/deep-learning-in-arcgis-pro.htm, and the related parameter settings and sample selection rules can be found in detail in the article. Finally, the big model is based on the SAM model, in which the running process of SAM is from https://github.com/facebookresearch/segment-anything, and you can also use the official Meta segmentation official website to provide a web-based segmentation platform for testing https:// segment-anything.com/. However, the official website has restrictions on the format of the data and the scope of processing.

U.S. States and Canada Provinces represents the states of the United States and the provinces of Canada.

Metadata https://oe.oregonexplorer.info/metadata/bnd_us_states.htm

Download https://oregonexplorer.info/ExternalContent/SpatialDataForDownload/bnd_us_states.zip

The ArcGIS Online USGS Topographic Maps image service contains over 181,000 historical topographic quadrangle maps (quads) dating from 1879 to 2006. These maps are part of the USGS Historical Topographic Map Collection (HTMC) which includes all the historical quads that had been printed since the USGS topographic mapping program was initiated in 1879. Previously available only as printed lithographic copies, the historical maps were scanned “as is” to create high-resolution images that capture the content and condition of each map sheet. All maps were georeferenced, and map metadata was captured as part of the process.

For the Esri collection, the scanned maps were published as this ArcGIS Online image service which can be viewed on the web and allows users to download individual scanned images. Esri’s collection contains historical quads (excluding orthophotos) dating from 1879 to 2006 with scales ranging from 1:10,000 to 1:250,000. The scanned maps can be used in ArcGIS Pro, ArcGIS Online, and ArcGIS Enterprise. They can also be downloaded as georeferenced TIFs for use in these and other applications.

We make it easy for you to explore and download these maps, or quickly create an ArcGIS Online map, using our Historical Topo Map Explorer app. The app provides a visual interface to search and explore the historical maps by geographic extent, publication year, and map scale. And you can overlay the historical maps on a satellite image or 3D hillshade and add labels for current geographic features.

This link provides information and additional metadata related to the NASA Socioeconomic Data and Applications Center (SEDAC) Global Volcano Hazard Frequency and Distribution dataset. A direct download is available at https://sedac.ciesin.columbia.edu/downloads/data/ndh/ndh-volcano-hazard-frequency-distribution/gdvol.zip (note: Earthdata Login required for download: https://urs.earthdata.nasa.gov/)Background on Hazard Explorer Tool:The Hazard Explorer Tool is a web mapping application available in FEMA's Preparedness Toolkit that allows exercise planners to identify hazards that exist in their community, where their population is most vulnerable, and where their critical infrastructure/key resources are at risk.The Hazard Explorer Tool was developed under the National Exercise Program, which serves as the principal mechanism for examining the preparedness and readiness of the United States across the entire homeland security and management exercise. Communities design, coordinate, conduct, and evaluate exercises across the US as a part of their preparedness efforts.The Map Journal serves as a tool to help you identify and evaluate potential exercise scenario locations, hazard exposure, and other risk-related factors to support exercise planning. In this tool, you will identify:Which hazards exist near your location;Where your population is most vulnerable; andWhat infrastructure and resources would be most impacted in your selected scenario location.The final output of this tool is a basic PDF map of your selected scenario location, as well as links to data sources that you can share with your GIS staff to conduct more in-depth analysis for use in planning and conducting your exercise.For more information on the Hazard Explorer Tool, please visit: https://preptoolkit.fema.gov/web/hazard-explorer/hazard-explorer-tool

The ArcGIS system provides access to both imagery and tools for visualizing and analyzing imagery. Imagery collections from the ArcGIS Living Atlas of the World can be viewed through apps such as the Landsat Explorer app, ArcGIS Online Map Viewer, and ArcGIS Pro, while the Spatial Analyst extension and ArcGIS Image Analyst for ArcGIS Pro, more commonly know as the Image Analyst extension, provide raster functions, classification and change detection tools, and other advanced image interpretation and analysis tools. The tutorials in the Working with Imagery in ArcGIS learning path will introduce you to exploring and selecting imagery in ArcGIS web applications, applying indices and raster functions to imagery in ArcGIS Pro, and performing image classification and change detection in ArcGIS Pro.This ArcGIS Pro project package contains data for Tutorial 3, Performing Image Classification in ArcGIS Pro, and Tutorial 4, Performing Change Detection in ArcGIS Pro, of the learning path. Click Download to download the .ppkx file or click Open in ArcGIS Pro then open the pitemx file to download and open the package.Software Used: ArcGIS Pro 2.8. Project package may be opened in 3.x versions.File Size: 170mbDate Created: November 7, 2022Last Tested: December 5, 2024