100+ datasets found
  1. India GIS Data

    • kaggle.com
    Updated Sep 11, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Neha Prabhavalkar (2020). India GIS Data [Dataset]. https://www.kaggle.com/nehaprabhavalkar/india-gis-data/discussion
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 11, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Neha Prabhavalkar
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    India
    Description

    Content

    This dataset contains various geospatial file formats of India such as shape files, project files, etc that are useful for geospatial analysis.

    Acknowledgements

    The files were collected from Igismap - https://www.igismap.com/

  2. u

    Data from: GIS shapefiles for India's parliamentary and assembly...

    • pub.uni-bielefeld.de
    Updated Jul 24, 2018
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Raphael Susewind (2018). GIS shapefiles for India's parliamentary and assembly constituencies including polling booth localities [Dataset]. https://pub.uni-bielefeld.de/record/2674065
    Explore at:
    Dataset updated
    Jul 24, 2018
    Authors
    Raphael Susewind
    Area covered
    India
    Description

    Efforts to spatially understand and map elections in India depend on geodata which have so far only been available from commercial sources. This dataset in contrast provides GIS shapefiles of Indian parliamentary and assembly constituency boundaries at the time of the 2014 general elections under an open license. These shapefiles were generated from raw polling booth point localities published by the Election Commission using a heatmap algorithm. While this automated approach reduces accuracy somewhat, and even though raw data accuracy varies by district, the shapefiles should generally be accurate enough for most visualization and analytical tasks.

  3. a

    India Admin Boundaries (Tiled) -V1

    • goa-state-gis-esriindia1.hub.arcgis.com
    • hub.arcgis.com
    Updated Oct 21, 2020
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    GIS Online (2020). India Admin Boundaries (Tiled) -V1 [Dataset]. https://goa-state-gis-esriindia1.hub.arcgis.com/datasets/india-admin-boundaries-tiled-v1
    Explore at:
    Dataset updated
    Oct 21, 2020
    Dataset authored and provided by
    GIS Online
    License

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

    Area covered
    Description

    This layer shows the administrative boundaries of India up to District level. The boundaries are optimized to support visualization in ArcGIS Online. The map contains following layers:Country State DistrictThis layer is provided by Survey of India. The Survey of India is the National Survey and Mapping agency of the country under the Department of Science and Technology, Govt. of India.

  4. Geospatial data for the Vegetation Mapping Inventory Project of Knife River...

    • catalog.data.gov
    • data.amerigeoss.org
    Updated Jun 5, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    National Park Service (2024). Geospatial data for the Vegetation Mapping Inventory Project of Knife River Indian Villages National Historic Site [Dataset]. https://catalog.data.gov/dataset/geospatial-data-for-the-vegetation-mapping-inventory-project-of-knife-river-indian-village
    Explore at:
    Dataset updated
    Jun 5, 2024
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Description

    The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. Vegetation map development for KNRI has somewhat different protocols than for other Parks. Normally photointerpretation is preceded by extensive field work which includes plot selection and vegetation sampling using detailed descriptions which are subsequently analyzed using ordination and other statistical techniques. The data are then summarized and association descriptions are assigned to each plot or, if the association is previously unrecognized, then a new association name is assigned. Subsequently, the plots locations are compared to its photographic signature and a photointerpretive key is developed. Given the very small size of KNRI and the extensive historical impact and alteration of the vegetation a simplified technique was used. NatureServe developed a list of potential vegetation types prior to any field work. This list was referenced during the field visit and modified after comparison of site characteristics and vegetation descriptions. Aerial photographs were viewed prior to the field visit and areas of like signature were differentiated. All vegetation and land-use information was then transferred to a GIS database using the latest grayscale USGS digital orthophoto quarter-quads as the base map and using a combination of on-screen digitizing and scanning techniques. Overall thematic map accuracy for the Park is considered 100% as all interpreted polygons received a filed visit for verification.

  5. Digital Geologic-GIS Map of the Pine Ridge Indian Reservation Area, South...

    • catalog.data.gov
    • s.cnmilf.com
    Updated Jun 4, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    National Park Service (2024). Digital Geologic-GIS Map of the Pine Ridge Indian Reservation Area, South Dakota (NPS, GRD, GRI, BADL, PRIR digital map) adapted from a U.S. Geological Survey Hydrologic Investigations Atlas map by Ellis and Adolphson (1971) [Dataset]. https://catalog.data.gov/dataset/digital-geologic-gis-map-of-the-pine-ridge-indian-reservation-area-south-dakota-nps-grd-gr
    Explore at:
    Dataset updated
    Jun 4, 2024
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Area covered
    South Dakota, Pine Ridge Reservation
    Description

    The Digital Geologic-GIS Map of the Pine Ridge Indian Reservation Area, South Dakota is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (prir_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (prir_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (prir_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (badl_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (badl_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (prir_geology_metadata_faq.pdf). Please read the badl_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri.htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). 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 section(s) of this metadata record (prir_geology_metadata.txt or prir_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:125,000 and United States National Map Accuracy Standards features are within (horizontally) 63.5 meters or 208.3 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

  6. a

    India: Smart Cities

    • hub.arcgis.com
    • up-state-observatory-esriindia1.hub.arcgis.com
    • +1more
    Updated Dec 20, 2019
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    GIS Online (2019). India: Smart Cities [Dataset]. https://hub.arcgis.com/maps/esriindia1::india-smart-cities/about
    Explore at:
    Dataset updated
    Dec 20, 2019
    Dataset authored and provided by
    GIS Online
    Area covered
    Description

    Smart City Mission is an initiative of Govt. of India. This layer provides boundary of 100 smart cities announced till fourth round. Source of information is http://smartcities.gov.in/content/innerpage/city-wise-projects-under-smart-cities-mission.phpPoint data has been extracted from OpenStreetMap. Please refer OSM website for more details on data contributors.

  7. a

    India: Land Cover 1992-2019

    • hub.arcgis.com
    • opendata.rcmrd.org
    • +1more
    Updated Mar 21, 2022
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    GIS Online (2022). India: Land Cover 1992-2019 [Dataset]. https://hub.arcgis.com/maps/9aeb44fb438645e8ae8387231f5c2815
    Explore at:
    Dataset updated
    Mar 21, 2022
    Dataset authored and provided by
    GIS Online
    Area covered
    Description

    This layer is a time series of the annual ESA CCI (Climate Change Initiative) land cover maps of the world. ESA has produced land cover maps for the years since 1992. These are available at the European Space Agency Climate Change Initiative website.Time Extent: 1992-2019Cell Size: 300 meterSource Type: ThematicPixel Type: 8 Bit UnsignedData Projection: GCS WGS84Mosaic Projection: Web Mercator Auxiliary SphereExtent: GlobalSource: ESA Climate Change InitiativeUpdate Cycle: AnnualWhat can you do with this layer?This layer may be added to ArcGIS Online maps and applications and shown in a time series to watch a "time lapse" view of land cover change since 1992 for any part of the world. The same behavior exists when the layer is added to ArcGIS Pro.In addition to displaying all layers in a series, this layer may be queried so that only one year is displayed in a map. This layer can be used in analysis. For example, the layer may be added to ArcGIS Pro with a query set to display just one year. Then, an area count of land cover types may be produced for a feature dataset using the zonal statistics tool. Statistics may be compared with the statistics from other years to show a trend.To sum up area by land cover using this service, or any other analysis, be sure to use an equal area projection, such as Albers or Equal Earth.Different Classifications Available to MapFive processing templates are included in this layer. The processing templates may be used to display a smaller set of land cover classes.Cartographic Renderer (Default Template)Displays all ESA CCI land cover classes.*Forested lands TemplateThe forested lands template shows only forested lands (classes 50-90).Urban Lands TemplateThe urban lands template shows only urban areas (class 190).Converted Lands TemplateThe converted lands template shows only urban lands and lands converted to agriculture (classes 10-40 and 190).Simplified RendererDisplays the map in ten simple classes which match the ten simplified classes used in 2050 Land Cover projections from Clark University.Any of these variables can be displayed or analyzed by selecting their processing template. In ArcGIS Online, select the Image Display Options on the layer. Then pull down the list of variables from the Renderer options. Click Apply and Close. In ArcGIS Pro, go into the Layer Properties. Select Processing Templates from the left hand menu. From the Processing Template pull down menu, select the variable to display.Using TimeBy default, the map will display as a time series animation, one year per frame. A time slider will appear when you add this layer to your map. To see the most current data, move the time slider until you see the most current year.In addition to displaying the past quarter century of land cover maps as an animation, this time series can also display just one year of data by use of a definition query. For a step by step example using ArcGIS Pro on how to display just one year of this layer, as well as to compare one year to another, see the blog called Calculating Impervious Surface Change.Hierarchical ClassificationLand cover types are defined using the land cover classification (LCCS) developed by the United Nations, FAO. It is designed to be as compatible as possible with other products, namely GLCC2000, GlobCover 2005 and 2009.This is a heirarchical classification system. For example, class 60 means "closed to open" canopy broadleaved deciduous tree cover. But in some places a more specific type of broadleaved deciduous tree cover may be available. In that case, a more specific code 61 or 62 may be used which specifies "open" (61) or "closed" (62) cover.Land Cover ProcessingTo provide consistency over time, these maps are produced from baseline land cover maps, and are revised for changes each year depending on the best available satellite data from each period in time. These revisions were made from AVHRR 1km time series from 1992 to 1999, SPOT-VGT time series between 1999 and 2013, and PROBA-V data for years 2013, 2014 and 2015. When MERIS FR or PROBA-V time series are available, changes detected at 1 km are re-mapped at 300 m. The last step consists in back- and up-dating the 10-year baseline LC map to produce the 24 annual LC maps from 1992 to 2015.Source dataThe datasets behind this layer were extracted from NetCDF files and TIFF files produced by ESA. Years 1992-2015 were acquired from ESA CCI LC version 2.0.7 in TIFF format, and years 2016-2018 were acquired from version 2.1.1 in NetCDF format. These are downloadable from ESA with an account, after agreeing to their terms of use. https://maps.elie.ucl.ac.be/CCI/viewer/download.phpCitationESA. Land Cover CCI Product User Guide Version 2. Tech. Rep. (2017). Available at: maps.elie.ucl.ac.be/CCI/viewer/download/ESACCI-LC-Ph2-PUGv2_2.0.pdfMore technical documentation on the source datasets is available here:https://cds.climate.copernicus.eu/cdsapp#!/dataset/satellite-land-cover?tab=doc*Index of all classes in this layer:10 Cropland, rainfed11 Herbaceous cover12 Tree or shrub cover20 Cropland, irrigated or post-flooding30 Mosaic cropland (>50%) / natural vegetation (tree, shrub, herbaceous cover) (<50%)40 Mosaic natural vegetation (tree, shrub, herbaceous cover) (>50%) / cropland (<50%)50 Tree cover, broadleaved, evergreen, closed to open (>15%)60 Tree cover, broadleaved, deciduous, closed to open (>15%)61 Tree cover, broadleaved, deciduous, closed (>40%)62 Tree cover, broadleaved, deciduous, open (15-40%)70 Tree cover, needleleaved, evergreen, closed to open (>15%)71 Tree cover, needleleaved, evergreen, closed (>40%)72 Tree cover, needleleaved, evergreen, open (15-40%)80 Tree cover, needleleaved, deciduous, closed to open (>15%)81 Tree cover, needleleaved, deciduous, closed (>40%)82 Tree cover, needleleaved, deciduous, open (15-40%)90 Tree cover, mixed leaf type (broadleaved and needleleaved)100 Mosaic tree and shrub (>50%) / herbaceous cover (<50%)110 Mosaic herbaceous cover (>50%) / tree and shrub (<50%)120 Shrubland121 Shrubland evergreen122 Shrubland deciduous130 Grassland140 Lichens and mosses150 Sparse vegetation (tree, shrub, herbaceous cover) (<15%)151 Sparse tree (<15%)152 Sparse shrub (<15%)153 Sparse herbaceous cover (<15%)160 Tree cover, flooded, fresh or brakish water170 Tree cover, flooded, saline water180 Shrub or herbaceous cover, flooded, fresh/saline/brakish water190 Urban areas200 Bare areas201 Consolidated bare areas202 Unconsolidated bare areas210 Water bodies

  8. I

    India Geospatial Analytics Market Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated Jan 10, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Data Insights Market (2025). India Geospatial Analytics Market Report [Dataset]. https://www.datainsightsmarket.com/reports/india-geospatial-analytics-market-12588
    Explore at:
    doc, ppt, pdfAvailable download formats
    Dataset updated
    Jan 10, 2025
    Dataset authored and provided by
    Data Insights Market
    License

    https://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    India
    Variables measured
    Market Size
    Description

    The size of the India Geospatial Analytics market was valued at USD XXX Million in 2023 and is projected to reach USD XXX Million by 2032, with an expected CAGR of 14.82% during the forecast period.Geospatial analytics in the India market uses GIS and other technologies to analyze spatial data and provide valuable insights. Actually, geospatial analytics is a practice, which involves gathering, processing, and interpreting data on locations and their attributes that go with them. This includes geographic coordinates, images, or sensor readings. It helps business and governments make informed decisions regarding resource management, urban planning, transportation, environment monitoring, and disaster response. Increasing government initiatives, growth in private sector adoption, and the advancements of AI and machine learning are making the Indian market more and more driven forward. Recent developments include: January 2023: Eris India, a company providing Geographic Information System (GIS) software and solutions, announced that the company is developing a policy map to offer data to help states and policymakers in decision-making. The Policy Maps have been designed to provide meaningful insights into various government functions., July 2022: Google announced a new partnership in India with local authorities and organizations in order to provide customized features for the diverse needs of the people in the country. Also, Google is building helpful maps that provide more visual and accurate navigation.. Key drivers for this market are: Increasing Demand of Location Based Service, Growing Availability of Spatial Data. Potential restraints include: High Initial Cost in Implementing Geospatial Analytics Solutions. Notable trends are: Increasing Demand of Location Based Service.

  9. d

    Compilation of Geospatial Data (GIS) for the Mineral Industries and Related...

    • catalog.data.gov
    • data.usgs.gov
    Updated Jul 6, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    U.S. Geological Survey (2024). Compilation of Geospatial Data (GIS) for the Mineral Industries and Related Infrastructure of Select Countries in Southwest Asia [Dataset]. https://catalog.data.gov/dataset/compilation-of-geospatial-data-gis-for-the-mineral-industries-and-related-infrastructure-o-6058f
    Explore at:
    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Description

    The U.S. Geological Survey (USGS) has compiled a geodatabase containing mineral-related geospatial data for 10 countries of interest in Southwest Asia (area of study): Afghanistan, Cambodia, Laos, India, Indonesia, Iran, Nepal, North Korea, Pakistan, and Thailand. The data can be used in analyses of the extractive fuel and nonfuel mineral industries and related economic and physical infrastructure integral for the successful operation of the mineral industries within the area of study as well as the movement of mineral products across domestic and global markets. This geodatabase reflects the USGS ongoing commitment to its mission of understanding the nature and distribution of global mineral commodity supply chains by updating and publishing the georeferenced locations of mineral commodity production and processing facilities, mineral exploration and development sites, and mineral commodity exporting ports for the countries in the area of study. The geodatabase contains data feature classes from USGS, foreign governmental, and open-source sources as follows: (1) mineral production and processing facilities, (2) mineral exploration and development sites, (3) mineral occurrence sites and deposits, (4) undiscovered mineral resource tracts for copper, phosphate, and potash, (5) coal occurrence areas, (6) electric power generating facilities, (7) electric power transmission lines, (8) liquefied natural gas terminals, (9) undiscovered, technically recoverable conventional and continuous hydrocarbon resources (by USGS geologic province), (10) cumulative production and recoverable conventional resources (by oil- and gas-producing nation), and (11) major mineral exporting maritime ports.

  10. a

    India: Ocean Base

    • hub.arcgis.com
    • sdgs.amerigeoss.org
    • +2more
    Updated Mar 24, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    GIS Online (2022). India: Ocean Base [Dataset]. https://hub.arcgis.com/maps/f9356a98369043e9979549522ed37fc8
    Explore at:
    Dataset updated
    Mar 24, 2022
    Dataset authored and provided by
    GIS Online
    Area covered
    Description

    The map is designed to be used as a basemap by marine GIS professionals and as a reference map by anyone interested in ocean data. The basemap focuses on bathymetry. It also includes inland waters and roads, overlaid on land cover and shaded relief imagery.The Ocean Base map currently provides coverage for the world down to a scale of ~1:577k; coverage down to ~1:72k in United States coastal areas and various other areas; and coverage down to ~1:9k in limited regional areas.The World Ocean Reference is designed to be drawn on top of this map and provides selected city labels throughout the world. This web map lets you view the World Ocean Base with the Reference service drawn on top. Article in the Fall 2011 ArcUser about this basemap: "A Foundation for Ocean GIS".The map was compiled from a variety of best available sources from several data providers, including General Bathymetric Chart of the Oceans GEBCO_08 Grid version 20100927 and IHO-IOC GEBCO Gazetteer of Undersea Feature Names August 2010 version (https://www.gebco.net), National Oceanic and Atmospheric Administration (NOAA) and National Geographic for the oceans; and Garmin, HERE, and Esri for topographic content. You can contribute your bathymetric data to this service and have it served by Esri for the benefit of the Ocean GIS community. For details on the users who contributed bathymetric data for this map via the Community Maps Program, view the list of Contributors for the Ocean Basemap. The basemap was designed and developed by Esri. The GEBCO_08 Grid is largely based on a database of ship-track soundings with interpolation between soundings guided by satellite-derived gravity data. In some areas, data from existing grids are included. The GEBCO_08 Grid does not contain detailed information in shallower water areas, information concerning the generation of the grid can be found on GEBCO's website: https://www.gebco.net/data_and_products/gridded_bathymetry_data/. The GEBCO_08 Grid is accompanied by a Source Identifier (SID) Grid which indicates which cells in the GEBCO_08 Grid are based on soundings or existing grids and which have been interpolated. The latest version of both grids and accompanying documentation is available to download, on behalf of GEBCO, from the British Oceanographic Data Centre (BODC) https://www.bodc.ac.uk/data/online_delivery/gebco/.The names of the IHO (International Hydrographic Organization), IOC (intergovernmental Oceanographic Commission), GEBCO (General Bathymetric Chart of the Oceans), NERC (Natural Environment Research Council) or BODC (British Oceanographic Data Centre) may not be used in any way to imply, directly or otherwise, endorsement or support of either the Licensee or their mapping system.Tip: Here are some famous oceanic locations as they appear this map. Each URL launches this map at a particular location via parameters specified in the URL: Challenger Deep, Galapagos Islands, Hawaiian Islands, Maldive Islands, Mariana Trench, Tahiti, Queen Charlotte Sound, Notre Dame Bay, Labrador Trough, New York Bight, Massachusetts Bay, Mississippi Sound

  11. I

    India Geospatial Analytics Market Report

    • marketreportanalytics.com
    doc, pdf, ppt
    Updated Apr 24, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Market Report Analytics (2025). India Geospatial Analytics Market Report [Dataset]. https://www.marketreportanalytics.com/reports/india-geospatial-analytics-market-89133
    Explore at:
    doc, ppt, pdfAvailable download formats
    Dataset updated
    Apr 24, 2025
    Dataset authored and provided by
    Market Report Analytics
    License

    https://www.marketreportanalytics.com/privacy-policyhttps://www.marketreportanalytics.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    India
    Variables measured
    Market Size
    Description

    The India Geospatial Analytics Market is experiencing robust growth, projected to reach $1.38 billion in 2025 and exhibiting a Compound Annual Growth Rate (CAGR) of 14.82% from 2025 to 2033. This expansion is fueled by several key drivers. Firstly, increasing government initiatives promoting digitalization and infrastructure development create significant demand for geospatial data and analytics across sectors like agriculture, utilities, and defense. Secondly, the rising adoption of advanced technologies such as AI, Machine Learning, and IoT enhances the capabilities of geospatial analytics, leading to more accurate insights and improved decision-making. Furthermore, the growing need for efficient resource management, precise urban planning, and enhanced disaster response mechanisms further propel market growth. Segmentation reveals strong contributions from surface analysis and network analysis within the 'By Type' category, while the 'By End-user Vertical' segment is dominated by Agriculture, Utility & Communication, and Defense & Intelligence sectors, reflecting their significant reliance on location-based intelligence. However, challenges exist. Data security and privacy concerns, particularly with sensitive location data, pose a restraint. The high cost of implementation and the requirement for specialized expertise also hinder wider adoption. Despite these challenges, the market's positive trajectory is anticipated to continue, driven by increasing data availability, improved technological capabilities, and growing awareness of the value of geospatial insights across various industries. The competitive landscape includes both global giants like Google and Esri, as well as domestic players like Esri India and Matrix Geo Solutions, indicating a dynamic market with opportunities for both established companies and emerging businesses. The forecast period of 2025-2033 promises further significant expansion, making the India Geospatial Analytics Market an attractive investment opportunity. Recent developments include: January 2023: Eris India, a company providing Geographic Information System (GIS) software and solutions, announced that the company is developing a policy map to offer data to help states and policymakers in decision-making. The Policy Maps have been designed to provide meaningful insights into various government functions., July 2022: Google announced a new partnership in India with local authorities and organizations in order to provide customized features for the diverse needs of the people in the country. Also, Google is building helpful maps that provide more visual and accurate navigation.. Key drivers for this market are: Increasing Demand of Location Based Service, Growing Availability of Spatial Data. Potential restraints include: Increasing Demand of Location Based Service, Growing Availability of Spatial Data. Notable trends are: Increasing Demand of Location Based Service.

  12. e

    India - Population density - Dataset - ENERGYDATA.INFO

    • energydata.info
    Updated Apr 3, 2018
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2018). India - Population density - Dataset - ENERGYDATA.INFO [Dataset]. https://energydata.info/dataset/india--population-density-2015
    Explore at:
    Dataset updated
    Apr 3, 2018
    License

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

    Area covered
    India
    Description

    Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata. DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted. REGION: Africa SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available. India data available from WorldPop here.

  13. Z

    GIS and Pollution Data: Designating Regional Airsheds for Air Quality...

    • data.niaid.nih.gov
    Updated Jul 13, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Guttikunda, Sarath (2024). GIS and Pollution Data: Designating Regional Airsheds for Air Quality Management in India [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_11332106
    Explore at:
    Dataset updated
    Jul 13, 2024
    Dataset authored and provided by
    Guttikunda, Sarath
    License

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

    Area covered
    India
    Description

    Full journal article published hereDesignating Airsheds in India for Urban and Regional Air Quality Managementhttps://doi.org/10.3390/air2030015

    [Summary presentation download]

    Datasets used for proposing India's 15 regional airsheds for air quality management are the following

    PM2.5 DatasetsRaw data source: https://sites.wustl.edu/acag/datasets/surface-pm2-5

    Gridded 0.1 degree resolution source apportionment results from WUSTL's global model simulationsFile: india_data_pm25_wustl_source_cont_0p1deg.xlsxAggregated Source definitions used in this presentation

    1. DUST = Anthropogenic dust = AFCID

    2. WINDUST = Wind erosion (dust storms) = WDUST

    3. WASTE = Waste burning = WST

    4. RESI = All commercial and residential cooking, lighting, and heating = RCOC + RCOO + RCORbiofuel + RCORcoal + RCORother

    5. TRANS = All transport (excluding aviation) = ROAD + NRTR + SHP

    6. POWER = Energy generation = ENEcoal + ENEother

    7. INDUS = All industries and product use = INDcoal + INDother + SLV

    8. BIOB = Biomass burning, including forest fires and agricultural waste burning = GFEDoburn + GFEDagburn

    9. AGR = Agricultural activities (excluding agricultural waste burning) = AGR

    10. OTHER = All others = OTHER

    Gridded 0.1 degree resolution, reanalysis data from WUSTL's global model simulationsFile: india_data_pm25_wustl_reanalysis_0p1deg.xlsxTime period: 1998 to 2022, annual averages

    Gridded 0.1 degree achive for monthly averages from WUSTL's global model simulationsFile: Download-44MB

    Population DatasetsRaw data source: https://landscan.ornl.gov

    Gridded 0.1 degree resolution population density dataFile: india_data_population_2021_0p1deg.xlsx

    GIS databases used in this study

    ESRI shapefile of 0.1 x 0.1 degree mesh file for the Indian Subcontinent covering longitudes from 67E to 99E and latitudes from 7N to 39NFile: india_gis_grids-0.1x0.1deg.rar

    ESRI shapefile of India administrative level 2 data - 28 states and 8 union territories (as of December 2023)File: india_gis_states28+8_2023.rar

    ESRI shapefile of India administrative level 3 data - 755 districts (as of December 2023): district23 and states23 codes are re-designed for emissions and pollution mapping and data tracking purposesFile: India_gis_districts755_2023.rar (original source: https://projects.datameet.org/maps)

    ESRI shapefile of India's Agro-Climatic zonesFile: india_gis_agroclimatic_zones.rar (original source: https://karnataka.data.gov.in/resource/boundaries-agro-climatic-regions

    ESRI shapefile of India's meteorological sub-divisionsFile: india_gis_meteo_subdivisions.rar (original source: https://mausam.imd.gov.in)

  14. LandSHIFT simulation results for India (GIS ASCII Raster)

    • figshare.com
    zip
    Updated Jan 13, 2020
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Ruediger Schaldach (2020). LandSHIFT simulation results for India (GIS ASCII Raster) [Dataset]. http://doi.org/10.6084/m9.figshare.10049930.v2
    Explore at:
    zipAvailable download formats
    Dataset updated
    Jan 13, 2020
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Ruediger Schaldach
    License

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

    Area covered
    India
    Description

    This data collection includes land-use scenarios calculated with the LandSHIFT model for four scenarios as GIS-raster maps and Excel files used to calculate land-use change effects on biodiversity with the BII indicator.

  15. D

    Geographic Information System GIS Tools Market Report | Global Forecast From...

    • dataintelo.com
    csv, pdf, pptx
    Updated Sep 12, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Dataintelo (2024). Geographic Information System GIS Tools Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-geographic-information-system-gis-tools-market
    Explore at:
    pptx, pdf, csvAvailable download formats
    Dataset updated
    Sep 12, 2024
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Geographic Information System (GIS) Tools Market Outlook



    The global Geographic Information System (GIS) tools market size was valued at approximately USD 10.8 billion in 2023, and it is projected to reach USD 21.5 billion by 2032, growing at a compound annual growth rate (CAGR) of 7.9% from 2024 to 2032. The increasing demand for spatial data analytics and the rising adoption of GIS tools across various industries are significant growth factors propelling the market forward.



    One of the primary growth factors for the GIS tools market is the surging demand for spatial data analytics. Spatial data plays a critical role in numerous sectors, including urban planning, environmental monitoring, disaster management, and natural resource exploration. The ability to visualize and analyze spatial data provides organizations with valuable insights, enabling them to make informed decisions. Advances in technology, such as the integration of artificial intelligence (AI) and machine learning (ML) with GIS, are enhancing the capabilities of these tools, further driving market growth.



    Moreover, the increasing adoption of GIS tools in the construction and agriculture sectors is fueling market expansion. In construction, GIS tools are used for site selection, route planning, and resource management, enhancing operational efficiency and reducing costs. Similarly, in agriculture, GIS tools aid in precision farming, crop monitoring, and soil analysis, leading to improved crop yields and sustainable farming practices. The ability of GIS tools to provide real-time data and analytics is particularly beneficial in these industries, contributing to their widespread adoption.



    The growing importance of location-based services (LBS) in various applications is another key driver for the GIS tools market. LBS are extensively used in navigation, logistics, and transportation, providing real-time location information and route optimization. The proliferation of smartphones and the development of advanced GPS technologies have significantly increased the demand for LBS, thereby boosting the GIS tools market. Additionally, the integration of GIS with other technologies, such as the Internet of Things (IoT) and Big Data, is creating new opportunities for market growth.



    Regionally, North America holds a significant share of the GIS tools market, driven by the high adoption of advanced technologies and the presence of major market players. The Asia Pacific region is expected to witness the highest growth rate during the forecast period, owing to increasing investments in infrastructure development, smart city projects, and the growing use of GIS tools in emerging economies such as China and India. Europe, Latin America, and the Middle East & Africa are also expected to contribute to market growth, driven by various government initiatives and increasing awareness of the benefits of GIS tools.



    Component Analysis



    The GIS tools market can be segmented by component into software, hardware, and services. The software segment is anticipated to dominate the market due to the increasing demand for advanced GIS software solutions that offer enhanced data visualization, spatial analysis, and decision-making capabilities. GIS software encompasses a wide range of applications, including mapping, spatial data analysis, and geospatial data management, making it indispensable for various industries. The continuous development of user-friendly and feature-rich software solutions is expected to drive the growth of this segment.



    Hardware components in the GIS tools market include devices such as GPS units, remote sensing devices, and plotting and digitizing tools. The hardware segment is also expected to witness substantial growth, driven by the increasing use of advanced hardware devices that provide accurate and real-time spatial data. The advancements in GPS technology and the development of sophisticated remote sensing devices are key factors contributing to the growth of the hardware segment. Additionally, the integration of hardware with IoT and AI technologies is enhancing the capabilities of GIS tools, further propelling market expansion.



    The services segment includes consulting, integration, maintenance, and support services related to GIS tools. This segment is expected to grow significantly, driven by the increasing demand for specialized services that help organizations effectively implement and manage GIS solutions. Consulting services assist organizations in selecting the right GIS tools and optimizing their use, while integration services ensure seamless integr

  16. India Gis Substation Export | List of Gis Substation Exporters & Suppliers

    • seair.co.in
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Seair Exim, India Gis Substation Export | List of Gis Substation Exporters & Suppliers [Dataset]. https://www.seair.co.in
    Explore at:
    .bin, .xml, .csv, .xlsAvailable download formats
    Dataset provided by
    Seair Info Solutions PVT
    Authors
    Seair Exim
    Area covered
    India
    Description

    Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

  17. a

    India: Terrain 3D

    • goa-state-gis-esriindia1.hub.arcgis.com
    • hub.arcgis.com
    • +1more
    Updated Mar 21, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    GIS Online (2022). India: Terrain 3D [Dataset]. https://goa-state-gis-esriindia1.hub.arcgis.com/datasets/india-terrain-3d
    Explore at:
    Dataset updated
    Mar 21, 2022
    Dataset authored and provided by
    GIS Online
    Description

    The Terrain 3D layer provides global elevation for your work in 3D.What can you do with this layer?Use this layer to visualize your maps and layers in 3D using applications like the Scene Viewer in ArcGIS Online and ArcGIS Pro. Show me how1) Working with Scenes in ArcGIS Pro or ArcGIS Online Scene Viewer2) Select an appropriate basemap or use your own3) Add your unique 2D and 3D data layers to the scene. Your data are simply added on the elevation. If your data have defined elevation (z coordinates) this information will be honored in the scene4) Share your work as a Web Scene with others in your organization or the publicDataset Coverage To see the coverage of various datasets comprising this service, click here.This layer is part of a larger collection of elevation layers. For more information, see the Elevation Layers group on ArcGIS Online.

  18. Geographic Information System Analytics Market Analysis, Size, and Forecast...

    • technavio.com
    Updated Jul 15, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Technavio (2024). Geographic Information System Analytics Market Analysis, Size, and Forecast 2024-2028: North America (US and Canada), Europe (France, Germany, UK), APAC (China, India, South Korea), Middle East and Africa , and South America [Dataset]. https://www.technavio.com/report/geographic-information-system-analytics-market-industry-analysis
    Explore at:
    Dataset updated
    Jul 15, 2024
    Dataset provided by
    TechNavio
    Authors
    Technavio
    Time period covered
    2021 - 2025
    Area covered
    United Kingdom, France, Canada, Germany, United States, Global
    Description

    Snapshot img

    Geographic Information System Analytics Market Size 2024-2028

    The geographic information system analytics market size is forecast to increase by USD 12 billion at a CAGR of 12.41% between 2023 and 2028.

    The GIS Analytics Market analysis is experiencing significant growth, driven by the increasing need for efficient land management and emerging methods in data collection and generation. The defense industry's reliance on geospatial technology for situational awareness and real-time location monitoring is a major factor fueling market expansion. Additionally, the oil and gas industry's adoption of GIS for resource exploration and management is a key trend. Building Information Modeling (BIM) and smart city initiatives are also contributing to market growth, as they require multiple layered maps for effective planning and implementation. The Internet of Things (IoT) and Software as a Service (SaaS) are transforming GIS analytics by enabling real-time data processing and analysis.
    Augmented reality is another emerging trend, as it enhances the user experience and provides valuable insights through visual overlays. Overall, heavy investments are required for setting up GIS stations and accessing data sources, making this a promising market for technology innovators and investors alike.
    

    What will be the Size of the GIS Analytics Market during the forecast period?

    Request Free Sample

    The geographic information system analytics market encompasses various industries, including government sectors, agriculture, and infrastructure development. Smart city projects, building information modeling, and infrastructure development are key areas driving market growth. Spatial data plays a crucial role in sectors such as transportation, mining, and oil and gas. Cloud technology is transforming GIS analytics by enabling real-time data access and analysis. Startups are disrupting traditional GIS markets with innovative location-based services and smart city planning solutions. Infrastructure development in sectors like construction and green buildings relies on modern GIS solutions for efficient planning and management. Smart utilities and telematics navigation are also leveraging GIS analytics for improved operational efficiency.
    GIS technology is essential for zoning and land use management, enabling data-driven decision-making. Smart public works and urban planning projects utilize mapping and geospatial technology for effective implementation. Surveying is another sector that benefits from advanced GIS solutions. Overall, the GIS analytics market is evolving, with a focus on providing actionable insights to businesses and organizations.
    

    How is this Geographic Information System Analytics Industry segmented?

    The geographic information system analytics industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

    End-user
    
      Retail and Real Estate
      Government
      Utilities
      Telecom
      Manufacturing and Automotive
      Agriculture
      Construction
      Mining
      Transportation
      Healthcare
      Defense and Intelligence
      Energy
      Education and Research
      BFSI
    
    
    Components
    
      Software
      Services
    
    
    Deployment Modes
    
      On-Premises
      Cloud-Based
    
    
    Applications
    
      Urban and Regional Planning
      Disaster Management
      Environmental Monitoring Asset Management
      Surveying and Mapping
      Location-Based Services
      Geospatial Business Intelligence
      Natural Resource Management
    
    
    Geography
    
      North America
    
        US
        Canada
    
    
      Europe
    
        France
        Germany
        UK
    
    
      APAC
    
        China
        India
        South Korea
    
    
      Middle East and Africa
    
        UAE
    
    
      South America
    
        Brazil
    
    
      Rest of World
    

    By End-user Insights

    The retail and real estate segment is estimated to witness significant growth during the forecast period.

    The GIS analytics market analysis is witnessing significant growth due to the increasing demand for advanced technologies in various industries. In the retail sector, for instance, retailers are utilizing GIS analytics to gain a competitive edge by analyzing customer demographics and buying patterns through real-time location monitoring and multiple layered maps. The retail industry's success relies heavily on these insights for effective marketing strategies. Moreover, the defense industries are integrating GIS analytics into their operations for infrastructure development, permitting, and public safety. Building Information Modeling (BIM) and 4D GIS software are increasingly being adopted for construction project workflows, while urban planning and designing require geospatial data for smart city planning and site selection.

    The oil and gas industry is leveraging satellite imaging and IoT devices for land acquisition and mining operations. In the public sector,

  19. I

    India Satellite Imagery Services Market Report

    • marketreportanalytics.com
    doc, pdf, ppt
    Updated May 5, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Market Report Analytics (2025). India Satellite Imagery Services Market Report [Dataset]. https://www.marketreportanalytics.com/reports/india-satellite-imagery-services-market-87644
    Explore at:
    pdf, doc, pptAvailable download formats
    Dataset updated
    May 5, 2025
    Dataset authored and provided by
    Market Report Analytics
    License

    https://www.marketreportanalytics.com/privacy-policyhttps://www.marketreportanalytics.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    India
    Variables measured
    Market Size
    Description

    The India satellite imagery services market, valued at $0.28 billion in 2025, is poised for robust growth, exhibiting a Compound Annual Growth Rate (CAGR) of 17.43% from 2025 to 2033. This expansion is driven by increasing government initiatives promoting digitalization and infrastructure development, coupled with rising demand across diverse sectors. The geospatial data acquisition and mapping application segment dominates the market, fueled by the need for precise and up-to-date geographical information for urban planning, infrastructure projects, and natural resource management. Furthermore, the growing adoption of satellite imagery in surveillance and security, conservation research, and disaster management further contributes to market growth. Key end-users include government agencies, construction firms, transportation and logistics companies, the military and defense sector, and the agriculture and forestry industries. The market is highly competitive, with both domestic and international players such as Airbus SE, Hexagon AB, and MapmyIndia vying for market share. The continued technological advancements in satellite technology, coupled with decreasing data acquisition costs, are expected to further accelerate market expansion. However, factors like data security concerns and the need for specialized expertise could pose challenges to the market's trajectory. The projected market size in 2033, considering the given CAGR, would signify substantial growth, making India a key player in the global satellite imagery services landscape. The competitive landscape is dynamic, with both established global players and emerging Indian companies contributing to innovation and market penetration. The government's push for digital India, including initiatives focusing on geospatial data utilization, is a significant catalyst for growth. Future market expansion will likely be influenced by advancements in high-resolution imaging, AI-driven analytics for image processing, and the growing adoption of cloud-based solutions for data storage and accessibility. The focus on sustainable development and environmental monitoring will also drive demand for satellite imagery services in areas like precision agriculture and natural resource management. The market's success hinges on addressing data privacy concerns and ensuring robust data security infrastructure. The integration of satellite imagery with other data sources, such as IoT and GIS, will further enhance its value proposition and drive wider adoption across sectors. Recent developments include: January 2023: The Indian Space Research Organization's National Remote Sensing Center released satellite images of Joshimath, a town in Uttarakhand that is slowly sinking due to land subsidence, and the images show that a rapid subsidence of 5.4 cm was observed in a span of twelve days between December last week and January first week., June 2022: Pataa Navigations, an India-based software firm, and Indian National Space Promotion and Authorisation Centre (IN-SPACe) signed an MoU to enable access to ISRO's Geospatial Services and APIs for the creation of an addressing system during the opening of the In-Space headquarters. The company would launch an addressing revolution in India by providing access to satellite image-based digital addresses. Through this MoU, the partnership would be for the ISRO portals Bhuvan, VEDAS, and MOSDAC services.. Key drivers for this market are: Government Initiatives to Foster the Growth of Satellite Imagery Services in India, Increasing Importance on Disaster Management and Mitigation Efforts. Potential restraints include: Government Initiatives to Foster the Growth of Satellite Imagery Services in India, Increasing Importance on Disaster Management and Mitigation Efforts. Notable trends are: Government Initiatives to Foster the Growth of Satellite Imagery Services in India.

  20. G

    Geospatial Analytics Market Report

    • marketresearchforecast.com
    doc, pdf, ppt
    Updated Jan 10, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Market Research Forecast (2025). Geospatial Analytics Market Report [Dataset]. https://www.marketresearchforecast.com/reports/geospatial-analytics-market-1650
    Explore at:
    doc, ppt, pdfAvailable download formats
    Dataset updated
    Jan 10, 2025
    Dataset authored and provided by
    Market Research Forecast
    License

    https://www.marketresearchforecast.com/privacy-policyhttps://www.marketresearchforecast.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The Geospatial Analytics Market size was valued at USD 79.06 USD billion in 2023 and is projected to reach USD 202.74 USD billion by 2032, exhibiting a CAGR of 14.4 % during the forecast period. The growing adoption of location-based technologies and the increasing need for data-driven decision-making in various industries are key factors driving market growth. Geospatial analytics captures, produces and displays GIS (geographic information system)-maps and pictures that may be weather maps, GPS or satellite photos. The geospatial analysis as a tool works with state of art technology in every formats namely; the GPS, sensors that locates, social media, mobile devices, multi of the satellite imagery to produce data visualizations that are facilitating trend-finding in complex relations between people and places as well are the situations' understanding. Visualizations are depicted through the use of maps, graphs, figures, and cartograms that illustrate the entire historical picture as well as a current changing trend. This is why the forecast becomes more confident and the situation is anticipated better. Recent developments include: February 2024: Placer.ai and Esri, a Geographic Information System (GIS) technology provider, partnered to empower customers with enhanced analytics capabilities, integrating consumer behavior analysis. Additionally, the agreement will foster collaborations to unlock further features by synergizing our respective product offerings., December 2023: CKS and Esri India Technologies Pvt Ltd teamed up to introduce the 'MMGEIS' program, focusing on students from 8th grade to undergraduates, to position India as a global leader in geospatial technology through skill development and innovation., December 2023: In collaboration with Bayanat, the UAE Space Agency revealed the initiation of the operational phase of the Geospatial Analytics Platform during its participation in organizing the Space at COP28 initiatives., November 2023: USAID unveiled its inaugural Geospatial Strategy, designed to harness geospatial data and technology for more targeted international program delivery. The strategy foresees a future where geographic methods enhance the effectiveness of USAID's efforts by pinpointing development needs, monitoring program implementation, and evaluating outcomes based on location., May 2023: TomTom International BV, a geolocation technology specialist, expanded its partnership with Alteryx, Inc. Through this partnership, Alteryx will use TomTom’s Maps APIs and location data to integrate spatial data into Alteryx’s products and location insights packages, such as Alteryx Designer., May 2023: Oracle Corporation announced the launch of Oracle Spatial Studio 23.1, available in the Oracle Cloud Infrastructure (OCI) marketplace and for on-premises deployment. Users can browse, explore, and analyze geographic data stored in and managed by Oracle using a no-code mapping tool., May 2023: CAPE Analytics, a property intelligence company, announced an enhanced insurance offering by leveraging Google geospatial data. Google’s geospatial data can help CAPE create appropriate solutions for insurance carriers., February 2023: HERE Global B.V. announced a collaboration with Cognizant, an information technology, services, and consulting company, to offer digital customer experience using location data. In this partnership, Cognizant will utilize the HERE location platform’s real-time traffic data, weather, and road attribute data to develop spatial intelligent solutions for its customers., July 2022: Athenium Analytics, a climate risk analytics company, launched a comprehensive tornado data set on the Esri ArcGIS Marketplace. This offering, which included the last 25 years of tornado insights from Athenium Analytics, would extend its Bronze partner relationship with Esri. . Key drivers for this market are: Advancements in Technologies to Fuel Market Growth. Potential restraints include: Lack of Standardization Coupled with Shortage of Skilled Workforce to Limit Market Growth. Notable trends are: Rise of Web-based GIS Platforms Will Transform Market.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Neha Prabhavalkar (2020). India GIS Data [Dataset]. https://www.kaggle.com/nehaprabhavalkar/india-gis-data/discussion
Organization logo

India GIS Data

Geospatial data files for India

Explore at:
11 scholarly articles cite this dataset (View in Google Scholar)
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Sep 11, 2020
Dataset provided by
Kagglehttp://kaggle.com/
Authors
Neha Prabhavalkar
License

https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

Area covered
India
Description

Content

This dataset contains various geospatial file formats of India such as shape files, project files, etc that are useful for geospatial analysis.

Acknowledgements

The files were collected from Igismap - https://www.igismap.com/

Search
Clear search
Close search
Google apps
Main menu