India GIS data
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uav imagery by Lakshyajeet Jalal, acquired 2025-06-14 to 2025-06-15, 5.0 cm per pixel, published on OpenAerialMap.
uav imagery by WebODM, acquired 2026-01-23 to 2026-01-23, 5.0 cm per pixel, published on OpenAerialMap.
Open and free data for assessing the human presence on the planet. The Global Human Settlement Layer (GHSL) project produces global spatial information, evidence-based analytics, and knowledge describing the human presence on the planet. The GHSL relies on the design and implementation of spatial data processing technologies that allow automatic data analytics and information extraction from large amounts of heterogeneous geospatial data including global, fine-scale satellite image data streams, census data, and crowd sourced or volunteered geographic information sources. The JRC, together with the Directorate-General for Regional and Urban Policy (DG REGIO) and Directorate-General for Defence Industry and Space (DG DEFIS) are working towards a regular and operational monitoring of global built-up and population based on the processing of Sentinel Earth Observation data produced by European Copernicus space program. In addition, the EU Agency for the Space Programme (EUSPA) undertakes activities related to user uptake of data, information and services.
This dataset contains the following administrative boundaries: ADM1, ADM1, ADM2, ADM3, ADM4, ADM5. Produced and maintained since 2017, the geoBoundaries Global Database of Political Administrative Boundaries Database www.geoboundaries.org is an open license, standardized resource of boundaries (i.e., state, county) for every country in the world.
Meta and Columbia University - CIESIN provide the High Resolution Settlement Layer as the world's most accurate population datasets. https://ai.meta.com/ai-for-good/datasets/high-resolution-population-density-maps/. This dataset for India, updated in 2026, relies on an updated methodology that uses the Overture Building Footprint dataset. These maps are the distribution of human population spanning India. Each of the 7 TIFF files is a 10 x 10 degree tile (the lower latitude coordinate and longitude coordinates are in the file name). A VRT file is also included.
# EOS-RS Flood Proxy Map: Odisha State, India, Cyclone Dana Floods, 28 Oct 2024, v0.9 The Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS) created this preliminary Flood Proxy Map (FPM) depicting areas that are likely flooded in Odisha State, India, due to heavy rainfall from Cyclone Dana. This map was derived from synthetic aperture radar (SAR) images acquired by the Copernicus Sentinel-1 satellite operated by the European Space Agency (ESA) before (7 Feb 2024 to 16 Oct 2024) and after (28 Oct 2024) the event. The map covers an area indicated by the white polygon. The preliminary map shows areas which are likely flooded (shown by light blue pixels of approximately 30m in size) due to the heavy rainfall from Cyclone Dana. Preliminary validation was conducted using news reports, aerial imagery, and ground-level imagery in selected areas. This map should be used as a guide to identify areas that are likely flooded, and may be less reliable over urban and vegetated areas. This product contains modified Copernicus Sentinel data (2024), processed by ESA and analyzed by the Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS). **More map details and files:** **More map details and files:** **Legal Disclaimer:** **Credits:** Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS), Contains modified Copernicus Sentinel data (2024)
# India Floods: Flood Proxy Maps, Jul 2023 The **Earth Observatory of Singapore – Remote Sensing Lab (EOS-RS)** produced these flood proxy maps for India Floods (Jul 2023) from synthetic aperture radar (SAR) satellite images. Each map is a separate ZIP below with its GeoTIFF, a KMZ for Google Earth, the PNG figures and a text file describing how it was made and how to read it. ## Maps in this dataset - **EOS-RS Flood Proxy Map: New Delhi, India, Floods, 12 Jul 2023, v0.9** - **EOS-RS Flood Proxy Map: Northern Haryana, India, Floods, 12 Jul 2023, v0.4** (superseded) - **EOS-RS Flood Proxy Map: New Delhi, India, Floods, 12 Jul 2023, v0.4** (superseded) **More map details and files:** **More map details and files:** **Credits:** Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS), Contains modified Copernicus Sentinel data (2022-2023)
# India Floods: Flood Proxy Maps, Oct 2022 The **Earth Observatory of Singapore – Remote Sensing Lab (EOS-RS)** produced these flood proxy maps for India Floods (Oct 2022) from synthetic aperture radar (SAR) satellite images. Each map is a separate ZIP below with its GeoTIFF, a KMZ for Google Earth, the PNG figures and a text file describing how it was made and how to read it. ## Maps in this dataset - **EOS-RS Flood Proxy Map: India, Floods, 16 Oct 2022, v0.5** - **EOS-RS Flood Proxy Map: India, Floods, 15 Oct 2022, v0.5** (superseded) - **EOS-RS Flood Proxy Map: India, Floods, 15 Oct 2022, v0.5** - **EOS-RS Flood Proxy Map: India, Floods, 14 Oct 2022, v0.5** **More map details and files:** **More map details and files:** **Credits:** Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS), Advanced Rapid Imaging and Analysis (ARIA), NASA-JPL/Caltech, Contains modified Copernicus Sentinel data (2022)
# India Floods: Flood Proxy Maps, Jun 2022 The **Earth Observatory of Singapore – Remote Sensing Lab (EOS-RS)** produced these flood proxy maps for India Floods (Jun 2022) from synthetic aperture radar (SAR) satellite images. Each map is a separate ZIP below with its GeoTIFF, a KMZ for Google Earth, the PNG figures and a text file describing how it was made and how to read it. ## Maps in this dataset - **EOS-RS Flood Proxy Map: India, Floods, 22 Jun 2022, v0.4** - **EOS-RS Flood Proxy Map: India, Floods, 21 Jun 2022, v0.3** **More map details and files:** **More map details and files:**
# EOS-RS Flood Proxy Map: India, Floods, 18 May 2022, v0.4 The Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS) created this preliminary Flood Proxy Map (FPM) depicting areas that are likely flooded in Assam, India due to heavy rains that started on 13 May 2022. This map was derived from synthetic aperture radar (SAR) images acquired by the Copernicus Sentinel-1 satellites operated by the European Space Agency (ESA) before (6 May 2022) and during (18 May 2022) the event. The image covers an area indicated by the large white polygon. Each light blue pixel measures about 30 meters across. This map was validated using reports of flooded areas in New Haflong Railway Station and along the Kampur-Kathiatoli Road. This flood proxy map should be used as a guide to identify areas that are likely flooded, and is less reliable over urban and vegetated areas. The product contains modified Copernicus Sentinel data (2022), processed by ESA and analyzed by the Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS), using the Advanced Rapid Imaging and Analysis (ARIA) system originally developed at NASA's Jet Propulsion Laboratory, California Institute of Technology, and modified at EOS-RS. **More map details and files:** **More map details and files:**
# India Floods: Flood Proxy Maps, Jul 2020 The Advanced Rapid Imaging and Analysis (ARIA) team at NASA's Jet Propulsion Laboratory and Caltech, in collaboration with the Earth Observatory of Singapore (EOS), produced these flood proxy maps for India Floods (Jul 2020) from synthetic aperture radar (SAR) satellite images. Each map is a separate ZIP below with its GeoTIFF, a KMZ for Google Earth, the PNG figures and a text file describing how it was made and how to read it. ## Maps in this dataset - **ARIA-SG Flood Proxy Map: India, Floods, 15 Jul 2020, v0.7 ** - **ARIA-SG Flood Proxy Map: India, Floods, 13 Jul 2020, v0.7 ** **More map details and files:**
# ARIA-SG Flood Proxy Map: India Floods, 30 Sep 2019, v0.1 Derived from synthetic aperture radar data acquired by the Copernicus Sentinel-1 satellites operated by the European Space Agency (ESA) before (21 May) and during (30 Sep) the event. Analysed by the ARIA-SG team at the Earth Observatory of Singapore (EOS) in collaboration with NASA-JPL and Caltech. **More map details and files:**
Points of interest: public-facing amenities, shops, tourist attractions, and landmarks tagged via `amenity`, `shop`, `tourism`, or `man_made`. Useful for general POI reference, urban analysis, and basemap detail. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: amenity, shop, tourism, man_made - Part of the country exports on HDX by HOT
Building footprints across the area: every feature tagged `building=*`, from residential homes to hospitals, schools, and places of worship. Useful for population estimation, damage assessment, and urban planning. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: building - Part of the country exports on HDX by HOT
Water features across the area: rivers, streams, canals, lakes, ponds, and water bodies tagged with `waterway`, `water`, or `natural=water`. Useful for flood-risk modelling, watershed analysis, and environmental basemap context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: waterway, water, natural - Part of the country exports on HDX by HOT
Education facilities: schools, kindergartens, colleges, and universities tagged via `amenity` or `building`. Useful for school-access mapping, education planning, and resource allocation. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: amenity, building - Part of the country exports on HDX by HOT
Sea ports, harbours and ferry terminals. Useful for maritime logistics, supply-chain analysis, and coastal access planning. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: industrial=port, harbour, port, amenity=ferry_terminal, building=ferry_terminal - Part of the country exports on HDX by HOT
Settlements and residential areas: named cities, towns, villages, suburbs, and residential land (`place=*` and `landuse=residential`). Useful for demographic context, settlement-level targeting, and population analysis. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: place, landuse - Part of the country exports on HDX by HOT
Financial services: banks, ATMs, post offices, money transfer agents, and microfinance branches tagged via `amenity`. Useful for financial-inclusion mapping, cash-distribution planning, and economic analysis. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: amenity - Part of the country exports on HDX by HOT
Cultural and historic places: museums, galleries, theatres, places of worship, monuments, and historic sites tagged via `tourism`, `amenity`, `historic`, or `heritage`. Useful for heritage protection, cultural mapping, and tourism context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: tourism, amenity, historic, heritage - Part of the country exports on HDX by HOT
Railway lines and stations tagged `railway=*`: rail lines, tram tracks, and stations. Useful for transport accessibility analysis and basemap context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: railway - Part of the country exports on HDX by HOT
Airports and aviation infrastructure: airports, heliports, helipads, runways, terminals, and emergency landing sites tagged via `aeroway`, `building`, or `emergency`. Useful for logistics, evacuation routing, and aerial-response planning. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: aeroway, building, emergency - Part of the country exports on HDX by HOT
Health facilities: hospitals, clinics, pharmacies, doctors, and dentists tagged via `amenity` or `healthcare`. Useful for service-access analysis, emergency response, and healthcare gap mapping. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: amenity, healthcare - Part of the country exports on HDX by HOT
Road network across the area tagged `highway=*`: motorways, residential streets, service roads, footways, and trails. Useful for routing, accessibility analysis, and evacuation planning. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: highway - Part of the country exports on HDX by HOT
Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) is a biophysical dimensionless quantity (its values range from 0/no absorption to 1/total absorption) used to assess the greenness and health of vegetation. FAPAR anomalies can be used as an indicator to detect and monitor the impacts of agricultural drought on the growth and productivity of vegetation. The data is presented in 10-day time composite of the Visible Infrared Imaging Radiometer Suite (VIIRS).
GLIDEnumbers are GLobal unique IDEntifiers for Disasters. Each disaster is registered in a record that contains a GLIDEnumber that uniquely identifies it and allows information to be interoperable across multiple disaster information sources, both structured and textual. Accessing disaster information can be a time consuming and laborious task. Not only is data scattered but frequently identification of the disaster can be confusing in countries with many disaster events and across borders. To address both of these issues, Asian Disaster Reduction Center (ADRC) proposed a globally common Unique ID code for disasters. Among the institutions using actively GLIDEnumbers are UN-OCHA (ReliefWeb, FSCC, HDX), UNDRR, UNDP, WMO, IFRC, FAO, the European Commission and the Centre for Research on the Epidemiology of Disasters (CRED), among many others. Country datasets are only produced for countries with at least one GLIDE event since 1 January 2022. The global dataset contains all events available from the GLIDE API, including those not assigned to a country.
Retirement Notice: This item is in mature support as of September 2025 and will retire in December 2027. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. India District Boundaries provides a 2022 boundary with a total population count. The layer is designed to be used for mapping and analysis. It can be enriched with additional attributes using data enrichment tools in ArcGIS Online. The 2022 boundaries are provided by Michael Bauer Research GmbH. These were published in December 2022. Other administrative boundaries for this country are also available: Country State Subdistrict
Retirement Notice: This item is in mature support as of September 2025 and will retire in December 2027. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. India Country Boundary provides a 2022 boundary with a total population count. The layer is designed to be used for mapping and analysis. It can be enriched with additional attributes using data enrichment tools in ArcGIS Online. The 2022 boundaries are provided by Michael Bauer Research GmbH. These were published in December 2022. Other administrative boundaries for this country are also available: State District Subdistrict
Retirement Notice: This item is in mature support as of September 2025 and will retire in December 2027. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. India State Boundaries provides a 2022 boundary with a total population count. The layer is designed to be used for mapping and analysis. It can be enriched with additional attributes using data enrichment tools in ArcGIS Online. The 2022 boundaries are provided by Michael Bauer Research GmbH. These were published in December 2022. Other administrative boundaries for this country are also available: Country District Subdistrict
Retirement Notice: This item is in mature support as of September 2025 and will retire in December 2027. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. India Subdistrict Boundaries provides a 2022 boundary with a total population count. The layer is designed to be used for mapping and analysis. It can be enriched with additional attributes using data enrichment tools in ArcGIS Online. The 2022 boundaries are provided by Michael Bauer Research GmbH. These were published in December 2022. Other administrative boundaries for this country are also available: Country State District
uav imagery by Bhuvan, acquired 2025-04-22 to 2025-04-23, 2.9 cm per pixel, published on OpenAerialMap.
uav imagery by Prasanna, acquired 2025-06-01 to 2025-06-02, 2.4 cm per pixel, published on OpenAerialMap.
geoBoundaries ADM3 boundaries for India: 6836 units, representing 2018. Source: Pathways Data Pvt. Ltd., lgdirectory.gov.in. Open Data Commons Open Database License 1.0
geoBoundaries ADM1 boundaries for India: 36 units, representing 2011. Source: DataMeet India community, Election Commission of India.