Exploring Open Source Geospatial Data: Raster and Vector Sources

When disaster strikes, having access to accurate geospatial data can mean the difference between effective response and chaos. Open source geospatial data has transformed how emergency managers, researchers, and planners prepare for and respond to disasters. These freely available datasets provide critical information about terrain, infrastructure, and environmental conditions without the barriers of cost or licensing restrictions.

Primary raster data sources for disaster management 🔗

Raster data forms the backbone of satellite-based Earth observation. These grid-based datasets capture information across vast areas, making them essential for monitoring disasters at regional and global scales.

Landsat satellite imagery 🔗

The Landsat programme represents the world’s longest-running system of satellites for moderate-resolution optical remote sensing. As a joint effort between USGS and NASA, Landsat has been collecting data since 1972. The current Landsat-8 and Landsat-9 satellites capture images with 30-meter multispectral resolution and 15-meter panchromatic resolution, covering the entire Earth every 16 days.

For disaster management, Landsat’s strength lies in its historical archive and consistent data collection. In 2008, USGS made Landsat data accessible via the internet for free, which led to substantial increases in downloads and rapid expansion of science and operational applications. This data helps track changes over time, assess flood extents, monitor drought conditions, and evaluate post-disaster recovery.

Copernicus Sentinel missions 🔗

The European Union’s Copernicus programme provides some of the most comprehensive Earth observation data available today. The Copernicus Data Space Ecosystem offers free instant access to data from Sentinel missions, with over 12 terabytes of data generated daily. The Sentinel-2 satellites provide high-resolution multispectral imaging with 10-meter resolution, while Sentinel-1 radar satellites can capture data regardless of cloud cover or darkness.

What sets Copernicus apart is its full, free and open data policy that allows anyone anywhere in the world to access and use the data. This has inspired similar policies globally and made real-time disaster monitoring accessible to organizations of all sizes.

Vector data from GNSS and ground surveys 🔗

While satellite imagery provides broad coverage, precise vector data is essential for detailed mapping and ground-level analysis during disasters. Vector data represents features as points, lines, and polygons with exact coordinates.

Global Navigation Satellite System applications 🔗

GNSS data plays an important role in disaster management by providing precise positioning information that enables accurate field mapping and real-time tracking. GNSS technology allows emergency responders to map damaged infrastructure, mark evacuation routes, and coordinate rescue operations with centimeter-level accuracy.

During disasters, GNSS data becomes critical for deformation monitoring. Continuously Operating Reference Stations provide data for structural deformation monitoring, helping assess building safety and track ground movement in earthquake or landslide-prone areas. This real-time capability makes GNSS indispensable for rapid damage assessment.

Field surveys and crowdsourced data 🔗

Traditional ground surveys complement satellite data by providing detailed, verified information about specific locations. Modern surveying combines GNSS receivers with mobile mapping systems to rapidly acquire detailed geospatial data in disaster-affected areas. These surveys help verify satellite observations and provide ground truth for damage assessments.

ISRO Bhuvan: India’s geospatial platform 🔗

India’s space agency ISRO has developed Bhuvan as a comprehensive geospatial platform specifically designed for Indian applications. Bhuvan provides extensive access to satellite imagery and geospatial data covering the entire country, supporting applications in disaster management, developmental planning, and environmental conservation.

The platform uses data from Indian satellites including Resourcesat, Cartosat-1, and Cartosat-2 to deliver high-resolution imagery. Bhuvan offers data that is ten times more detailed than some global alternatives, with coverage down to the village level across India’s 750,000 villages. For disaster management, Bhuvan provides real-time information from automatic weather stations, potential fishing zone data, forest fire alerts, and periodic agricultural drought assessments.

During the COVID-19 pandemic, Bhuvan was customized to create a dashboard that facilitated tracking hotspots and managing food supply chains. The platform caters to 150,000 unique users daily, recording 20 million hits, making it an essential tool for emergency response in India.

NASA’s Earth observation portals 🔗

NASA provides multiple platforms for accessing Earth observation data, with tools designed for different user needs and technical capabilities.

NASA Earthdata 🔗

Earthdata Search enables data discovery, search, comparison, visualization, and access across NASA’s Earth science data holdings. The platform provides access to petabytes of unrestricted Earth science data, from MODIS daily global coverage to Landsat’s high-resolution imagery. Users can filter datasets, customize outputs, and download data directly through the web interface.

The platform includes data from NASA’s fleet of Earth observation satellites covering climate, land, ocean, and atmospheric studies. Through Earthdata Search, users can access data from NOAA, ESA, JAXA, and ISRO, making it a truly international repository for disaster-related geospatial data.

USGS Earth Explorer 🔗

For users specifically interested in Landsat and aerial photography, USGS Earth Explorer provides a dedicated interface. The platform offers satellite images, aerial photographs, and cartographic products from multiple sources. Earth Explorer includes access to MODIS land data products, ASTER imagery, and digital elevation models essential for terrain analysis during disasters.

Data quality and verification considerations 🔗

While open source data offers tremendous opportunities, users must approach it with appropriate caution. Not all freely available data meets the same quality standards, and using poor-quality data can lead to flawed decisions during critical disaster response.

Accuracy and resolution requirements 🔗

Different disaster management tasks require different levels of data accuracy. Combining free and open software, open data, and open standards creates a sustainable ecosystem for disaster response, but users must verify that spatial resolution meets their specific needs. A 30-meter resolution satellite image suitable for regional flood mapping may be inadequate for assessing individual building damage.

Temporal currency and update frequency 🔗

Data age matters significantly in disaster contexts. Satellite imagery from last year cannot show current flood conditions. Users must verify acquisition dates and understand update frequencies. Sentinel-2 provides data every 5 days for most locations, while Landsat has a 16-day revisit cycle. For rapid disaster response, knowing these timelines helps set realistic expectations.

Boundary and licensing verification 🔗

Even within open data repositories, usage terms vary. Some datasets restrict commercial use or require attribution. Boundary data, particularly for sensitive areas, may have intentional inaccuracies for security reasons. Users should always review metadata, check licensing agreements, and verify that data boundaries align with their operational areas.

Cross-validation with multiple sources 🔗

Best practices recommend using multiple data sources to verify findings. When satellite imagery shows potential damage, ground surveys or higher-resolution data should confirm observations. The integration of GNSS, remote sensing, and GIS data enhances disaster management capabilities by providing cross-validation and comprehensive situational awareness.

What do you think? How can disaster management agencies balance the need for rapid data access with thorough quality verification? What steps should organizations take to ensure their teams can effectively evaluate and use open source geospatial data during emergency response?

References

1. https://dataspace.copernicus.eu/data-collections/complementary-data
2. https://www.sciencedirect.com/science/article/pii/S0034425719300719
3. https://dataspace.copernicus.eu/
4. https://www.copernicus.eu/en/copernicus-and-free-open-source-software-community
5. https://www.mdpi.com/2220-9964/1/2/166
6. https://geospatialworld.net/article/disaster-risk-reduction-and-management-using-geospatial-data/
7. https://www.ogc.org/blog-article/bhuvan-transforming-indias-governance-with-geospatial-insights/
8. https://yourstory.com/2024/07/isro-geoportal-bhuvan-advanced-geospatial-data
9. https://www.earthdata.nasa.gov/data/tools/earthdata-search
10. https://opengeospatialdata.springeropen.com/articles/10.1186/s40965-020-00078-2