Earth observation tools play a critical role in monitoring the planet’s surface, atmosphere, and oceans. These tools, ranging from satellites to software platforms, enable accurate data collection and analysis for environmental research, disaster response, urban planning, and climate studies. In this article, we explore the main categories of earth observation tools and how they are applied across various industries.
1. FlyPix AI
We use FlyPix AI to identify and analyze objects within geospatial imagery, applying AI models that can be trained to detect specific features. The platform supports various types of geospatial data tied to coordinates, allowing us to monitor changes, detect anomalies, and gain insights from images captured by satellites, drones, and other sources. It supports multiple data types including hyperspectral imaging, lidar, and SAR scans, providing flexibility in how we handle spatial information.
The platform is designed to be user-friendly, offering a no-code interface that lets users work with geospatial data regardless of coding experience. This accessibility helps us speed up data analysis and decision-making. Additionally, FlyPix AI scales efficiently, accommodating both small projects and larger operational needs without losing performance.
Key Highlights:
- AI-based object detection and anomaly identification
- Supports satellite, drone, hyperspectral, lidar, and SAR data
- No-code platform accessible to users with varying technical skills
- Enables rapid geospatial data analysis and insights extraction
- Scalable system for diverse project sizes
Who it’s best for:
- Users needing object detection in geospatial imagery
- Teams working with diverse geospatial data sources
- Professionals requiring fast, no-code AI analysis tools
- Organizations monitoring environmental or construction sites
- Analysts looking for scalable geospatial data solutions
Contact Information:
- Website: flypix.ai
- E-mail: info@flypix.ai
- LinkedIn: www.linkedin.com/company/flypix-ai
- Address: Robert-Bosch-Str. 7, 64293 Darmstadt, Germany
- Phone: +49 6151 2776497
2. ICEYE
ICEYE operates a satellite-based earth observation system using synthetic aperture radar (SAR) technology. They manage a large constellation of SAR satellites, which are capable of capturing images in various weather conditions and during both day and night. This allows users to monitor ground activity with high frequency and consistency, regardless of cloud cover or lighting conditions. Their tools are designed for timely detection and monitoring of changes across the globe, supporting use cases in both public and private sectors.
Their solutions are applied in areas such as defense, disaster response, environmental monitoring, maritime tracking, and infrastructure assessment. The system delivers radar imagery and related analytics that help organizations make informed decisions. ICEYE provides services internationally and integrates its tools into workflows that support operational, strategic, and emergency planning needs.
Key Highlights:
- SAR satellite constellation enabling monitoring in all weather and lighting conditions
- Regular and frequent global imaging capabilities
- Applied in defense, disaster recovery, maritime, insurance, and environmental monitoring
- Supports real-time response and long-term planning
- Data access designed for both government and commercial use
Who it’s best for:
- Government agencies involved in defense or security
- Disaster response and recovery organizations
- Environmental and climate monitoring teams
- Insurance and finance sectors needing location-based risk data
- Maritime operators and logistics providers
Contact Information:
- Website: www.iceye.com
- E-mail: press@iceye.com
- Facebook: www.facebook.com/iceye
- Twitter: x.com/iceye_global
- LinkedIn: fi.linkedin.com/company/iceye
- Address: Maarintie 6 02150 Espoo Finland
3. QGIS
QGIS is an open-source geographic information system used for map creation, spatial data editing, and geospatial analysis. It provides a wide range of tools for building, visualizing, and sharing geographic data. Users can design high-quality maps for desktop, mobile, cloud, or print using advanced layout and styling features. The platform supports interactive editing of geographic shapes such as points, lines, and polygons.
QGIS also includes tools for building forms, generating reports, and creating data-driven maps like atlases. Its functionality can be extended using plugins and supports integration with other tools like Orfeo ToolBox for processing satellite imagery. The platform is designed for users ranging from individuals and educators to professional mapping teams.
Key Highlights:
- Advanced map layout and styling options
- Tools for editing and creating geographic data
- Built-in support for generating reports and atlases
- Integrates with other remote sensing tools like Orfeo ToolBox
- Available on multiple platforms including desktop and mobile
Who it’s best for:
- GIS analysts and cartographers
- Academic researchers and educators
- Urban planners and land use specialists
- Environmental consultants and surveyors
- Developers building custom geospatial tools
Contact Information:
- Website: qgis.org
- E-mail: qgis-psc@lists.osgeo.org.
- Facebook: www.facebook.com/people/QGIS
4. Orfeo ToolBox
Orfeo ToolBox (OTB) is an open-source software package for processing remote sensing images. It supports large-scale analysis of high-resolution optical, multispectral, and radar imagery. OTB includes a broad set of tools for tasks like ortho-rectification, image fusion (pansharpening), classification, and SAR processing. The software can be used through command line, Python, C++, or directly within QGIS.
OTB is designed to be flexible and scalable, suitable for running on everything from laptops to computing clusters. It is hardware-accelerated, which helps users work with large datasets efficiently. The tool is maintained by a community of users and developers, and it comes with extensive documentation. Users have full control over processing workflows and can adapt the tools to specific project needs.
Key Highlights:
- Processes large-scale satellite imagery including SAR and multispectral
- Offers tools for classification, fusion, and geometric correction
- Integrates with QGIS and runs on Linux, Windows, and macOS
- Accessible via multiple interfaces including command line and Python
- Community-driven and extensible for custom workflows
Who it’s best for:
- Remote sensing professionals and data scientists
- Research institutions working with satellite imagery
- Developers creating custom earth observation pipelines
- Organizations needing open-source alternatives to commercial tools
- Users processing large geospatial datasets on various systems
Contact Information:
- Website: www.orfeo-toolbox.org
- Twitter: x.com/orfeotoolbox
5. Planet
Planet offers satellite-based earth observation tools focused on high-frequency image collection. Their platform delivers daily, high-resolution imagery of Earth’s surface, which helps users monitor changes over time and space. With access to both current and historical data, organizations can observe patterns and detect changes in land use, vegetation, infrastructure, and other physical features.
Their tools support decision-making in sectors such as agriculture, environmental monitoring, and government planning. The system allows users to view recent and past imagery with consistent temporal coverage, enabling comparison and analysis over extended periods. Planet’s archive and data services are designed to fit into operational workflows where regular earth observation is needed.
Key Highlights:
- Daily high-resolution satellite imagery
- Archive access for time-series analysis
- Supports monitoring of land use, agriculture, and infrastructure
- Enables detection of spatial changes at consistent intervals
- Tools designed for integration into analytic workflows
Who it’s best for:
- Environmental monitoring agencies
- Agricultural planning and crop assessment teams
- Government institutions tracking land or urban change
- Research organizations using long-term spatial data
- Analysts needing frequent earth observation updates
Contact Information:
- Website: www.planet.com
- E-mail: press@planet.com
- Facebook: www.facebook.com/PlanetLabs
- Twitter: x.com/planet
- LinkedIn: www.linkedin.com/company/planet-labs
- Instagram: www.instagram.com/planetlabs
- Address: 645 Harrison Street 4th Floor San Francisco, CA 94107
6. Raster Vision
Raster Vision is an open source framework designed to apply deep learning techniques to geospatial imagery. It supports three main computer vision tasks: chip classification, object detection, and semantic segmentation. The tool provides a complete training pipeline that includes handling raster and vector data, data augmentation, and model customization. Raster Vision can process multiband imagery, including RGBIR and Sentinel-2, and is built on the PyTorch framework. It supports modifying neural network input layers to accommodate different image types without losing pre-trained model weights.
The system also allows for defining areas of interest using polygons to limit where training chips are generated, which helps reduce annotation effort. Georeferenced outputs from trained models are suitable for use in further spatial analysis. Raster Vision also provides functionality for running its pipelines in the cloud, including through AWS Batch. It is designed to handle large-scale geospatial datasets by breaking them into smaller chips that can be used in training deep learning models.
Key Highlights:
- Supports chip classification, object detection, and semantic segmentation
- Handles both raster and vector data
- Works with multiband imagery
- Produces georeferenced outputs
- Allows for custom model selection via TorchHub
- Based on PyTorch and Torchvision
- Includes data augmentation options using Albumentations
- Supports area of interest specification
- Can be run in the cloud (e.g., AWS Batch)
Who it’s best for:
- Developers working with remote sensing data
- GIS specialists exploring deep learning applications
- Teams needing scalable, cloud-based image analysis
- Users looking to integrate custom models into EO workflows
- Researchers working on object detection in satellite imagery
Contact Information:
- Website: rastervision.io
7. Copernicus
Copernicus is the Earth observation program of the European Union that combines satellite and ground-based data for environmental monitoring. It provides open access to imagery and processed datasets that support research and public services across a wide range of fields. The system includes multiple satellite families (Sentinels) and in situ data sources, enabling comprehensive observation from space, land, sea, and air.
The platform offers processed information services in areas such as atmosphere, marine, land, climate change, and emergency management. By organizing and analyzing large datasets, Copernicus helps track environmental trends, identify anomalies, and produce forecasts. The system is used for generating maps, monitoring changes over time, and extracting statistics based on satellite and sensor data.
Key Highlights:
- Combines satellite and ground-based observation data
- Includes Sentinel satellite missions and in situ sensors
- Covers topics such as land, ocean, atmosphere, and climate
- Provides open access to processed data and imagery
- Enables mapping, forecasting, and long-term monitoring
Who it’s best for:
- Public authorities working on environmental policy
- Emergency response and disaster management teams
- Researchers in climate and earth sciences
- Marine and atmospheric monitoring agencies
- Institutions needing free, standardized geospatial datasets
Contact Information:
- Website: www.copernicus.eu
- E-mail: support@euspace-programme.eu
- Facebook: www.facebook.com/CopernicusEU
- Twitter: x.com/CopernicusEU
- Instagram: www.instagram.com/copernicus_eu
- Phone: +32 486 90 6428
8. openEO
openEO provides a standard interface that connects programming languages like R, Python, and JavaScript to cloud-based earth observation platforms. Instead of downloading large datasets, users can access and process satellite data directly in the cloud. The platform simplifies how users interact with massive geospatial datasets that are usually stored in fragmented formats, like tiles or granules.
This approach enables analysis of remote sensing data without the need for local storage or high-end computing power. Users can write processing workflows and run them directly on the cloud back-end, then retrieve only the results they need. The tool is designed to streamline large-scale analysis for those working with multi-temporal or high-resolution satellite imagery.
Key Highlights:
- API to access and process satellite data in the cloud
- Connects with R, Python, and JavaScript
- Removes need to download large datasets
- Supports unified access to various back-end systems
- Focused on simplifying remote sensing workflows
Who it’s best for:
- Developers working with earth observation data
- Researchers analyzing satellite imagery at scale
- Data scientists using Python or R for geospatial tasks
- Institutions with limited local storage or compute capacity
- Teams needing repeatable, cloud-based EO workflows
Contact Information:
- Website: openeo.org
- E-mail: openeo.psc@uni-muenster.de
- LinkedIn: www.linkedin.com/company/openeospec
9. BlackSky
BlackSky delivers satellite-based observation tools focused on high-frequency monitoring and real-time analysis. Their platform supports tasks that require fast access to satellite imagery, such as change detection, motion tracking, and situational awareness. The system provides imagery at frequent intervals throughout the day, allowing users to observe dynamic activities and locations.
In addition to 2D imagery, the platform supports 3D analysis and surface modeling through multi-frame captures. Users can create digital surface models and run viewshed analyses for locations of interest. The tool is suited for missions that require up-to-date spatial intelligence, particularly when operating under time-sensitive conditions.
Key Highlights:
- High-frequency satellite image collection
- Supports 3D surface modeling and motion analysis
- Delivers rapid access to imagery after capture
- Enables pattern recognition through recurring observations
- Focused on situational awareness and change tracking
Who it’s best for:
- Organizations monitoring time-sensitive activity
- Users requiring frequent updates on specific areas
- Analysts conducting 3D terrain assessments
- Teams working on national security or emergency operations
- Stakeholders needing real-time geospatial insights
Contact Information:
- Website: www.blacksky.com
- Twitter: x.com/BlackSky_Inc
- LinkedIn: www.linkedin.com/company/blackskyinc
- Address: 1000 Dexter Ave N, Suite 300 Seattle, WA 98109
10. GeoIQ
GeoIQ focuses on geospatial analytics using location-based data such as demographics, foot traffic, and points of interest. Their platform helps users evaluate urban locations by integrating multiple datasets to understand spatial characteristics. It supports decision-making with location intelligence derived from ground-level and environmental data.
Users apply GeoIQ to assess sites for retail expansion, market segmentation, or urban planning. By combining human movement data with spatial context, the tool supports predictions and rankings based on custom business goals. It enables data-driven strategies using real-world urban signals.
Key Highlights:
- Location intelligence from demographics and footfall data
- Integrates points of interest and urban activity indicators
- Supports site prioritization for commercial planning
- Useful for evaluating and forecasting location performance
- Geospatial insights focused on business applications
Who it’s best for:
- Retail and commercial businesses planning expansion
- Analysts evaluating site potential or market coverage
- Urban planners assessing usage patterns
- Organizations using location signals for decision-making
- Marketing and strategy teams working with geospatial data
Contact Information:
- Website: geoiq.ai
- E-mail: hello@geoiq.io
- Twitter: x.com/geoiq_ai
- LinkedIn: www.linkedin.com/company/geoiq-ai
- Instagram: www.instagram.com/geoiq.ai
- Address: UrbanVault 762, 19th Main Rd, Garden Layout, Sector 3, HSR Layout, Bengaluru, Karnataka 560102
- Phone: +91 9538488535
11. STEP (Science Toolbox Exploitation Platform)
STEP is a platform developed by the European Space Agency to support scientific use of Earth observation data. It provides access to open-source toolboxes designed to work with data from Sentinel satellites, as well as from past ESA and partner missions. The platform includes both an Optical Toolbox and a Microwave Toolbox, which are built on a shared architecture known as SNAP. These toolboxes offer sensor-specific and generic processing tools for image analysis and geospatial workflows.
Users can work with data from multiple satellite sensors and perform operations such as visualization, pre-processing, and analysis directly within the SNAP environment. STEP also functions as a community hub, offering documentation, tutorials, and a forum for scientific users and developers. The tool supports long-term scientific projects and operational workflows involving satellite data.
Key Highlights:
- Includes Optical and Microwave Toolboxes
- Built on SNAP architecture for multi-sensor support
- Processes Sentinel and legacy mission data
- Supports scientific workflows and custom analysis
- Offers documentation, training, and community support
Who it’s best for:
- Scientists working with Sentinel data
- Researchers analyzing optical and radar imagery
- Developers building on EO processing tools
- Academic users and research institutions
- Users needing access to ESA satellite toolkits
Contact Information:
- Website: step.esa.int
- Facebook: www.facebook.com/EuropeanSpaceAgency
- Twitter: x.com/esa
- LinkedIn: www.linkedin.com/company/european-space-agency
- Instagram: www.instagram.com/europeanspaceagency
12. ArcGIS Pro (Esri)
ArcGIS Pro is a desktop-based geographic information system used for managing, visualizing, and analyzing spatial data. It supports 2D, 3D, and time-enabled (4D) data layers, making it suitable for a wide range of mapping and analytical tasks. The platform allows users to combine data from various sources and perform detailed spatial analysis, including pattern detection and forecasting.
The software includes tools for map creation, data editing, and advanced geoprocessing. It integrates with other components in the ArcGIS ecosystem, allowing data to be shared across web and mobile platforms. ArcGIS Pro is commonly used in industries that rely on spatial data for decision-making and infrastructure planning.
Key Highlights:
- Supports 2D, 3D, and time-enabled geospatial data
- Combines data from multiple sources for analysis
- Offers advanced spatial analytics and visualization
- Enables sharing across desktop, web, and mobile tools
- Part of the larger ArcGIS ecosystem
Who it’s best for:
- GIS professionals and analysts
- Government and infrastructure planners
- Environmental and urban researchers
- Organizations managing complex spatial data
- Users requiring interactive maps and spatial models
Contact Information:
- Website: www.esri.com
- Facebook: www.facebook.com/esrigis
- Twitter: x.com/Esri
- LinkedIn: www.linkedin.com/company/esri
- Instagram: www.instagram.com/esrigram
- Address: 4, A. Petrickogo Str. Kiev Ukraine
- Phone: +380445024121
13. Open Data Cube
Open Data Cube (ODC) is an open-source platform that simplifies access to and analysis of satellite imagery and geospatial data. It provides tools for organizing and processing large Earth observation datasets, making it easier to track environmental and land changes over time. Users can load and query data across multiple time periods and locations, enabling consistent spatial analysis.
The platform is designed for scalability and is used by governments, research institutions, and development programs to support data-driven decision-making. ODC helps manage long-term satellite archives and supports applications such as land cover mapping, water detection, and resource monitoring.
Key Highlights:
- Open-source software for satellite data management
- Enables time-series analysis across geospatial layers
- Supports scalable data storage and processing
- Suitable for monitoring land and environmental changes
- Designed for long-term, large-scale EO datasets
Who it’s best for:
- Scientists analyzing long-term earth changes
- National and regional government agencies
- Environmental monitoring organizations
- Research teams using time-series satellite data
- Users building EO data platforms or archives
Contact Information:
- Website: www.opendatacube.org
- Twitter: x.com/opendatacube
14. Cloud Optimized GeoTIFF (COG)
Cloud Optimized GeoTIFF (COG) is a format for storing geospatial raster data that allows more efficient access and use in cloud environments. A COG file is a standard GeoTIFF with an internal layout designed for HTTP range requests, which enables software to access only the needed portions of a file. This approach improves performance and reduces bandwidth and storage duplication when processing large satellite or aerial imagery datasets.
One of the main advantages of COG is that it is compatible with traditional GIS software while also enabling advanced cloud-native workflows. Different applications can simultaneously access a single COG file online without having to download or replicate the data. This makes it easier to build real-time analysis pipelines and simplifies data distribution for providers who only need to produce one format.
Key Highlights:
- Efficient streaming access to imagery using HTTP range requests
- Reduces data duplication in cloud workflows
- Compatible with traditional GIS tools
- Enables real-time and cloud-native image processing
- Based on standard GeoTIFF format with optimized structure
Who it’s best for:
- Data providers distributing large-scale geospatial imagery
- Developers building cloud-native EO applications
- GIS users needing compatibility with legacy software
- Teams aiming to reduce data storage and duplication
- Organizations focused on real-time EO data access
Contact Information:
- Website: cogeo.org
- Twitter: x.com/cogeotiff
15. GRASS GIS
GRASS GIS is an open-source geographic information system known for its capabilities in raster, vector, and spatial data processing. It supports modeling and analysis related to terrain, ecosystems, hydrology, and remote sensing imagery. The system includes a temporal framework and a Python API, facilitating time series analysis and customizable geospatial workflows.
Its design allows for efficient processing of large datasets across different hardware setups. GRASS GIS is commonly used in academic research, environmental modeling, and geospatial data management. It provides a robust platform for users requiring advanced spatial analysis and programming capabilities.
Key Highlights:
- Handles raster, vector, and geospatial processing
- Includes tools for terrain and ecosystem modeling
- Supports hydrological analysis and image processing
- Offers temporal data framework and Python API
- Optimized for large-scale geospatial analysis
Who it’s best for:
- Researchers conducting environmental and spatial studies
- Professionals modeling terrain and water systems
- Developers building geospatial applications
- Users needing advanced time series analysis
- Organizations managing large geospatial datasets
Contact Information:
- Website: grass.osgeo.org
- Twitter: x.com/grassgis
- LinkedIn: www.linkedin.com/company/grass-gis
Conclusion
Earth observation tools have become essential for collecting and analyzing data about the Earth’s surface and environment. They provide valuable insights by combining satellite imagery, aerial data, and advanced processing techniques. These tools support a wide range of applications, from environmental monitoring and urban planning to agriculture and security. As technology advances, earth observation platforms continue to evolve, offering more accessible, scalable, and precise ways to understand changes on our planet. Choosing the right tool depends on the specific needs, data types, and analysis requirements of the user or organization.