What is Satellite Data? Examples, Datasets and Providers 2025
- Overview
- Datasets
- Providers
- Use Cases
- Attributes
- Guide
- FAQ
- Overview
- Datasets
- Providers
- Use Cases
- Attributes
- Guide
- FAQ
What is Satellite Data?
Satellite data refers to information collected by satellites orbiting the Earth. Satellites capture data using sensors and instruments, transmitting it back to Earth for analysis. This data is crucial for monitoring and understanding our planet, enabling applications in weather forecasting, disaster management, agriculture, urban planning, and scientific research.
For instance, during a major hurricane, weather satellites provide real-time data on storm formation, track its path, and predict landfall. This information is vital for emergency response teams and disaster management authorities to make timely decisions and save lives.
What Are Examples of Satellite Data?
Examples of satellite data include datasets offering insights into Earth’s surface, atmosphere, and human activities. Key examples include:
- Satellite Image Data: High-resolution images captured from space, used for mapping and analysis.
- Weather Data: Data on atmospheric conditions, crucial for weather forecasting and climate studies.
- Geospatial Data: Geographic coordinates and mapping information.
- Environmental Monitoring Data: Data on vegetation, deforestation, and natural disasters.
- Maritime Data: Information on shipping routes and ocean conditions.
- Atmospheric Composition: Measurements of gases like CO2, ozone, and pollutants in the atmosphere.
- Topographic Data: Elevation and terrain data for mapping landscapes.
Best Satellite Databases & Datasets
The best satellite datasets provide detailed geospatial imagery, environmental data, and mapping insights. This curated list features the top satellite datasets, selected for accuracy, quality, and trusted providers.
CustomWeather | Satellite Data | Satellite Imagery | Global 5km Resolution Mosaic | Global Weather Data
PREDIK Data-Driven I Geospatial data, Satellite Data, Parking Availability I Parking Occupancy Variance Index worldwide
Worldwide satellite data | Air quality | Pollutants
PREDIK Data-Driven I Satellite Data I Index I Monitor US Companies I Outdoor large surfaces to analyze business & economic activity
Agriculture & Land Health Data | Satellite Data: Agriculture, Vegetation Data, Health Data, Land Productivity
Greenery & Forestry Data | Satellite Data | Forestry, Carbon Emissions, Carbon Storage, Vegetation, Tree Cover Density Data
Worldwide satellite data | Air quality | Pollutants | Ozon(O3)
Worldwide satellite data | Air quality | Pollutants | Ammonia(NH3)
Worldwide satellite data | Air quality | Pollutants | Methane(CH4)
Land Cover & Urban Planning Data | Satellite Data: Land Use, Real Estate, Construction, Flooding Risk & Management, Infrastructure
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Top Satellite Data Providers & Companies
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CustomWeather
CoverageUSAUK+247EStrong data coverage and quality. Ended up licensing hourly and daily weather data in the United States. Strong historical coverage. Team was easy to work with and moved quickly to deliver the data in the format we needed.
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Predik Data-driven
CoverageUSAUK+247VWe wanted to analyse the foot traffic data across Sydney. Predik provided quality traffic density heatmap and raw foot traffic data across Sydney Australia to support us with the use case. Highly recommended.
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SafeGraph
CoverageUSAUK+248VWe are using safegraph data to research on the foot traffic of airports in the U.S. We find it very helpful with lots of documentation. The customer support is awesome. You can post in the slack channel and got a response very quickly
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FarmersEdge
CoverageUSACanada+88We collect data from four primary sources: weather stations, satellite imagery, soil testing and machine telematics.3200Weather stations28000Machines3BData points
Popular Use Cases for Satellite Data
Satellite data is used in various industries for monitoring and analysis. Common use cases include location intelligence, where geospatial data helps businesses and governments make informed decisions about infrastructure and resource allocation, and supply chain monitoring, using satellite imagery to track the movement of goods and monitor key facilities. Another important use case is crop monitoring, leveraging environmental data to assess agricultural health and optimize yields.
Main Attributes of Satellite Data
Below, we outline the most popular attributes associated with this type of data—features that data buyers are actively seeking to meet their needs.
| Attribute | Type | Description | Action |
|---|---|---|---|
| String | The postal code of an address. | View 34 datasets | |
| String | The name of a country. | View 16 datasets | |
| Float | The latitude of a point on earth's surface. Commonly abbreviated as "lat". | View 15 datasets | |
| Float | The longitude of a point on earth's surface. Commonly abbreviated as "long". | View 13 datasets | |
| String | The country code in Alpha-2 format (ISO 3166) | View 6 datasets | |
| String | The ticker symbol of a stock. | View 6 datasets |
Satellite Data Use Cases in Detail
Satellite data is purchased by a diverse range of users, including government agencies, private companies, and research organizations. Key sectors that rely on satellite data include:
- Environmental Monitoring: Satellites track deforestation, monitor air and water quality, observe changes in land use, and assess the impact of natural disasters.
- Agriculture: Precision farming uses satellite data to optimize crop yields, monitor crop health, and estimate production.
- Climate Change and Weather Forecasting: Satellites analyze climate patterns, monitor ice caps and glaciers, and predict weather conditions, including severe weather events.
- Urban Planning and Development: Satellite data helps in mapping urban growth, managing infrastructure development, and monitoring traffic patterns.
- Disaster Response and Management: Satellites assist in damage assessment, coordinate relief efforts after natural disasters, and create early warning systems.
- Navigation and Geospatial Services: Supporting GPS and location-based services, satellite data enhances mapping accuracy and provides imagery for various geospatial applications.
How Do You Collect Satellite Data?
Satellite data is collected using different types of satellites equipped with various sensors. These sensors capture data in multiple spectral bands, ranging from visible light to infrared and microwave. The data is then transmitted to ground stations for processing and analysis. Key methods include:
- Optical Satellite Imaging: Captures images in visible and near-infrared light.
- Synthetic Aperture Radar (SAR) Imaging: Uses radar to produce high-resolution images, regardless of weather conditions.
- Radiometers: Measure thermal radiation to monitor temperature changes and environmental conditions.
This type of geospatial data allows for the creation of detailed databases that can be used for various analytical purposes.
Main Satellite Data Attributes
These attributes describe the fundamental components of satellite data.
| Attribute | Description | Example |
|---|---|---|
| Geospatial Coordinates | Latitude and longitude defining the area captured. | E.g., 40.7128, -74.0060. |
| Imagery Type | The type of data captured by the satellite. | E.g., Optical, Radar, Infrared. |
| Resolution | Spatial, temporal, or spectral resolution of the data. | E.g., 10 meters per pixel. |
| Capture Date & Time | Timestamp indicating when the data was collected. | E.g., 2024-11-29, 10:00 UTC. |
| Spectral Bands | Specific wavelengths of light captured in the imagery. | E.g., Red, Green, Blue, Near Infrared. |
| Cloud Cover | Percentage of the image obscured by clouds. | E.g., 12%. |
| Metadata | Information about the satellite and sensor used. | E.g., Landsat-8, Sentinel-2. |
| Environmental Data | Measurements derived from satellite imagery. | E.g., Vegetation Index (NDVI), Surface Temperature. |
How to Analyse Satellite Data?
Analyzing satellite data involves several steps, including data preprocessing, classification, and interpretation. Specialized software and algorithms are used to process raw satellite data into meaningful information. Common analysis techniques include:
- Image Classification: Categorizing pixels in an image into different land cover types.
- Change Detection: Identifying changes in a specific area over time by comparing satellite images from different dates.
- Spatial Analysis: Examining spatial relationships and patterns within the data.
These techniques are essential for tasks like environmental monitoring and urban development planning. For more in-depth information on these topics, explore our sections on Map Data and GIS Data.
Frequently Asked Questions
Where Can I Find Satellite Data?
You can access satellite data from a variety of sources, including government agencies, private companies, and research institutions. NASA, NOAA, and ESA offer extensive datasets that are often free for public use. For more specialized or commercial needs, marketplaces like Datarade can connect you with leading satellite data providers. If you’re not sure where to start, we recommend exploring our curated list of providers to find the best fit for your project.
How Frequently is Satellite Data Updated?
The update frequency of satellite data depends on the provider and type of satellite. Some datasets are updated as frequently as every hour, providing near real-time insights, while others might be updated daily, weekly, or even on-demand. If you need continuous monitoring for projects like environmental tracking or disaster management, we suggest opting for datasets that offer hourly or daily updates for the most timely insights.
What is the Resolution of Satellite Data?
Satellite data resolution can vary widely. High-resolution imagery might offer up to 30 centimeters per pixel, which is ideal for detailed mapping and precision analysis. Broader resolutions, like 5 kilometers per pixel, are more suited for larger-scale observations. When choosing a dataset, we recommend considering your specific use case. For example, urban planning may require high resolution, while agricultural monitoring might do well with medium or broader resolutions.
How is Satellite Data Delivered?
Satellite data is typically delivered in formats like XML, maps, shapefiles, or through APIs, depending on your needs. This flexibility ensures easy integration into your existing systems, whether you’re using GIS platforms or custom-built applications. If you’re looking for a easy way to work with satellite data, we recommend starting with APIs for real-time data access or shapefiles if you’re working within GIS tools.
What Geographic Areas Do Satellite Data Cover?
Satellite data offers global coverage, with the ability to zoom in on specific regions or countries. Whether you need data for a particular country or a global dataset, satellite imagery typically covers over 200 countries. We suggest verifying the coverage area with your provider, especially if you’re focusing on regions with complex geographical features or lesser-known areas.
How is Real-Time Satellite Tracking Achieved?
Real-time satellite tracking is made possible through APIs that provide up-to-the-minute information about the position, orbit, and other details of satellites. This is crucial for applications that require continuous monitoring, such as satellite fleet management or global surveillance. If real-time data is important for your project, we recommend looking for APIs that offer continuous tracking and updates.
How Much Does Satellite Data Cost?
The cost of satellite data varies depending on factors like resolution, geographic coverage, data type, and update frequency. Some providers offer one-off purchases, while others have monthly or yearly subscription plans. You might also encounter custom pricing based on your specific needs. If you’re unsure, our platform offers free samples or demos to help you evaluate the data before committing. We recommend exploring different pricing models to find the one that fits your budget and requirements.
What Similar Data Types Complement Satellite Data?
Satellite data is closely related to several other geospatial categories, including location data, and point of interest (POI) data.
