*Credit of image: Unsplash (Tian-Shan Range, Wensu, Aksu, China) *Landsat, Sentinel, CBERS, and Amazonia satellites in the context of orbital-level multispectral imaging Nowadays, there are plenty of ways to access and use satellite imagery—here's a rundown of some of the main options I use in my personal projects, all of which are free :-) A (very) Quick Overview of Satellite Options First off, let's talk about the satellites and sensors themselves. There are many options today, each with unique capabilities. For agricultural and environmental analysis (what I do on a daily basis), two of the most commonly used satellite programs are Landsat and Sentinel. Each has been part of multiple missions with evolving sensors over the decades, offering increasingly rich data for various applications. Sentinel Sentinel-2, for example, is part of the European Copernicus program and specializes in multispectral imaging. As of now, there are three satellites in the Sentinel-2 series: Sentinel-2A, Sentinel-2B, and Sentinel-2C (the last one launched very recently, in September 2024, here). (Usually my first choice, as it can combine the best spatial, temporal and spectral resolutions). Landsat Landsat, managed by the U.S. Geological Survey (USGS) under the National Land Imaging Program, has been active since the 1970s. Its most recent mission is Landsat-9, which, like its predecessors, provides multispectral imaging for a variety of uses. With so many satellite programs, it's essential to choose based on your specific project needs. Some satellites focus on particular regions of the planet, while others have more global objectives, which leads me to also include other less conventional options here (on the international scene). Brazilian Satellites: CBERS and Amazonia. If you're interested in national programs, Brazil offers two noteworthy options: CBERS (China-Brazil Earth Resources Satellite): This Sino-Brazilian collaboration has launched several missions. The most recent, CBERS-4A, provides orbital-level multispectral imaging alongside earlier CBERS satellites with different sensors. Amazonia-1: Launched in 2021, this is Brazil's first entirely locally-developed satellite. While it offers multispectral imaging like the others, its spatial resolution is relatively lower. Its main goal is to monitor vast forested areas like the Amazon (as the name suggests). Future missions include Amazonia-1B and Amazonia-2. Of all the options above, I would say that the ideal scenario would be to use all available options to have the largest possible amount of imagery for your area. However, this approach raises at least two important questions to consider: What is the purpose of your analysis? (and whether a higher frequency of images is even necessary) How will you handle processing so that all the different images are compatible for analysis? Where to Get Satellite Imagery Once you know your project's requirements and the sensors that meet them, there are several ways to access the data. Whether you need occasional imagery for reports or frequent data for large-scale analysis, here are the main platforms and acquisition methods: Official Data Portals Landsat: Earth Explorer Sentinel: Copernicus Data Space Ecosystem CBERS and Amazonia: INPE Image Catalog Other options include GloVis, for example. 2. Cloud Platforms Google Earth Engine (GEE): Access a huge catalog of satellite data, including Landsat, Sentinel, CBERS, and many other products. It includes a web-based code editor for quick use and APIs for JavaScript (there is a lot already ready to use in JS, so it's pretty much doable even if you're not familiar with the language—I, personally, am not) and Python. Amazon Web Services (AWS): Landsat and Sentinel data are available on AWS. Check out the AWS Open Data Registry for details. APIs and Programmatic Access For more technical users, APIs and Python libraries are powerful tools: Sentinel API: Learn more Landsat API: Learn more CBERS and Amazonia API: INPE STAC Browser Python Libraries: Libraries like pystac-client are great because they support multiple catalogs via the SpatioTemporal Asset Catalog (STAC) standard. With one library, you can access all these providers and much more. Third-Party Tools and Software Sentinel Hub: A commercial service offering easy access to Sentinel and other satellite imagery Earth Data (NASA): A great option for additional datasets, similar to catalogs in GEE GIS Software: Tools like QGIS and ArcGIS often integrate directly with satellite data repositories. In QGIS, you may need a plugin to fetch and process the data. Be sure to check the plugin's maintenance status for continuity. Final Thoughts The satellite and sensor landscape offers an incredible variety of options, but navigating them, especially in the beginning, can feel overwhelming. The good news? Once you identify your needs and the right sensors (lots of work to be done here!), there are plenty of tools and platforms—most of them free—to access the data and put it to work for your project. *Credit of image: Unsplash ( Tian-Shan Range, Wensu, Aksu, China) *Credit of image: Unsplash ( Tian-Shan Range, Wensu, Aksu, China ) Tian-Shan Range, Wensu, Aksu, China *Landsat, Sentinel, CBERS, and Amazonia satellites in the context of orbital-level multispectral imaging *Landsat, Sentinel, CBERS, and Amazonia satellites in the context of orbital-level multispectral imaging Nowadays, there are plenty of ways to access and use satellite imagery—here's a rundown of some of the main options I use in my personal projects, all of which are free :-) A (very) Quick Overview of Satellite Options A (very) Quick Overview of Satellite Options First off, let's talk about the satellites and sensors themselves. There are many options today, each with unique capabilities. For agricultural and environmental analysis (what I do on a daily basis), two of the most commonly used satellite programs are Landsat and Sentinel. Each has been part of multiple missions with evolving sensors over the decades, offering increasingly rich data for various applications. Sentinel Sentinel-2, for example, is part of the European Copernicus program and specializes in multispectral imaging. As of now, there are three satellites in the Sentinel-2 series: Sentinel-2A, Sentinel-2B, and Sentinel-2C (the last one launched very recently, in September 2024, here ). (Usually my first choice, as it can combine the best spatial, temporal and spectral resolutions). here Landsat Landsat, managed by the U.S. Geological Survey (USGS) under the National Land Imaging Program, has been active since the 1970s. Its most recent mission is Landsat-9, which, like its predecessors, provides multispectral imaging for a variety of uses. With so many satellite programs, it's essential to choose based on your specific project needs. Some satellites focus on particular regions of the planet, while others have more global objectives, which leads me to also include other less conventional options here (on the international scene). Brazilian Satellites: CBERS and Amazonia. If you're interested in national programs, Brazil offers two noteworthy options: Brazilian Satellites: Brazilian Satellites: CBERS (China-Brazil Earth Resources Satellite): This Sino-Brazilian collaboration has launched several missions. The most recent, CBERS-4A, provides orbital-level multispectral imaging alongside earlier CBERS satellites with different sensors. Amazonia-1: Launched in 2021, this is Brazil's first entirely locally-developed satellite. While it offers multispectral imaging like the others, its spatial resolution is relatively lower. Its main goal is to monitor vast forested areas like the Amazon (as the name suggests). Future missions include Amazonia-1B and Amazonia-2. Of all the options above, I would say that the ideal scenario would be to use all available options to have the largest possible amount of imagery for your area. However, this approach raises at least two important questions to consider: ideal use all available options What is the purpose of your analysis? (and whether a higher frequency of images is even necessary) How will you handle processing so that all the different images are compatible for analysis? What is the purpose of your analysis? (and whether a higher frequency of images is even necessary) purpose How will you handle processing so that all the different images are compatible for analysis? processing Where to Get Satellite Imagery Where to Get Satellite Imagery Once you know your project's requirements and the sensors that meet them, there are several ways to access the data. Whether you need occasional imagery for reports or frequent data for large-scale analysis, here are the main platforms and acquisition methods: Official Data Portals Official Data Portals Official Data Portals Landsat: Earth Explorer Sentinel: Copernicus Data Space Ecosystem CBERS and Amazonia: INPE Image Catalog Landsat: Earth Explorer Earth Explorer Sentinel: Copernicus Data Space Ecosystem Copernicus Data Space Ecosystem CBERS and Amazonia: INPE Image Catalog INPE Image Catalog Other options include GloVis , for example. GloVis 2. Cloud Platforms 2. Cloud Platforms Google Earth Engine (GEE): Access a huge catalog of satellite data, including Landsat, Sentinel, CBERS, and many other products. It includes a web-based code editor for quick use and APIs for JavaScript (there is a lot already ready to use in JS, so it's pretty much doable even if you're not familiar with the language—I, personally, am not) and Python. Amazon Web Services (AWS): Landsat and Sentinel data are available on AWS. Check out the AWS Open Data Registry for details. Google Earth Engine (GEE) : Access a huge catalog of satellite data, including Landsat, Sentinel, CBERS, and many other products. It includes a web-based code editor for quick use and APIs for JavaScript (there is a lot already ready to use in JS, so it's pretty much doable even if you're not familiar with the language—I, personally, am not) and Python. Google Earth Engine (GEE) Amazon Web Services (AWS): Landsat and Sentinel data are available on AWS. Check out the AWS Open Data Registry for details. AWS Open Data Registry APIs and Programmatic Access APIs and Programmatic Access APIs and Programmatic Access For more technical users, APIs and Python libraries are powerful tools: Sentinel API: Learn more Landsat API: Learn more CBERS and Amazonia API: INPE STAC Browser Python Libraries: Libraries like pystac-client are great because they support multiple catalogs via the SpatioTemporal Asset Catalog (STAC) standard. With one library, you can access all these providers and much more. Sentinel API : Learn more Sentinel API Landsat API : Learn more Landsat API CBERS and Amazonia API: INPE STAC Browser INPE STAC Browser Python Libraries: Libraries like pystac-client are great because they support multiple catalogs via the SpatioTemporal Asset Catalog (STAC) standard. With one library, you can access all these providers and much more. pystac-client Third-Party Tools and Software Third-Party Tools and Software Third-Party Tools and Software Sentinel Hub: A commercial service offering easy access to Sentinel and other satellite imagery Earth Data (NASA): A great option for additional datasets, similar to catalogs in GEE GIS Software: Tools like QGIS and ArcGIS often integrate directly with satellite data repositories. In QGIS, you may need a plugin to fetch and process the data. Be sure to check the plugin's maintenance status for continuity. Sentinel Hub: A commercial service offering easy access to Sentinel and other satellite imagery Sentinel Hub: Earth Data (NASA) : A great option for additional datasets, similar to catalogs in GEE Earth Data (NASA) GIS Software: Tools like QGIS and ArcGIS often integrate directly with satellite data repositories. In QGIS, you may need a plugin to fetch and process the data. Be sure to check the plugin's maintenance status for continuity. QGIS Final Thoughts The satellite and sensor landscape offers an incredible variety of options, but navigating them, especially in the beginning, can feel overwhelming. The good news? Once you identify your needs and the right sensors (lots of work to be done here!), there are plenty of tools and platforms—most of them free—to access the data and put it to work for your project.
