The challenge of using data wisely and ethically

15 FREE SATELLITE IMAGERY DATA SOURCES 1. USGS Earth Explorer Web: earthexplorer.usgs.gov Data Types: Landsat optical, declassified spy (e.g. CORONA) imagery, hyperspectral (e.g. Hyperion) 2. Sentinel / Copernicus Browser Web: https://lnkd.in/dZknHaYp Data Types: Sentinel-2 (optical multispectral), Sentinel-1 (SAR) 3. NASA Earthdata Search Web: search.earthdata.nasa.gov Data Types: Derived Earth science products, land cover, atmosphere, biosphere, cryosphere, etc. 4. NOAA Data Access Viewer Web: coast.noaa.gov (Data Access Viewer) Data Types: Satellite imagery, aerial imagery, LiDAR (especially for coastal regions) 5. Maxar Open Data Program Web: maxar.com (Open Data Program) Data Types: High-resolution optical (for disaster / emergency events), sample data including true color, stereo, building footprints, elevation 6. Geo-Airbus Defense Web: intelligence.airbus.com (sample images) Data Types: Optical (SPOT, Pleiades), Radar (TerraSAR-X), DEM (WorldDEM) 7. NASA Worldview Web: https://lnkd.in/dQ_AjabE Data Types: Scientific satellite product layers (hazards, climate, atmospheric, disaster) — can download associated data layers (GIS Geography) 8. NOAA CLASS (Comprehensive Large Array-data Stewardship System) Web: www.class.noaa.gov Data Types: Oceanic imagery, atmospheric imagery (e.g. GOES, POES), environmental/climate products (aerosols, ozone, etc.) 9. Bhuvan Indian Geo-Platform (ISRO) Web: bhuvan.nrsc.gov.in Data Types: Indian satellite imagery (IRS, Cartosat, ResourceSat, OceanSat), NDVI, elevation models (CartoDEM) 10. JAXA Global ALOS 3D World Web: eorc.jaxa.jp (ALOS portal) Data Types: Global DSM / elevation (30 m) via L-band radar (ALOS) 11. NOAA Digital Coast Web: https://lnkd.in/dSRG6r-Z Data Types: Coastal datasets including imagery, elevation, land cover, radar, infrared, true color composites, and socio-economic data for coastal zones 12. PROBA-V MEP (GeoViewer) Web: viewer.probav.vito.be Data Types: PROBA-V, SPOT-Vegetation, METOP — coarse resolution vegetation / global patterns 13. Satellite Land Cover (Global Land Cover Facility etc.) Web: (global land cover data sources via e.g. landsat, MODIS, AVHRR) Data Types: Global land cover / land use maps (vegetation, agriculture, urban, hydrology, etc.) 14. UNAVCO (SAR Archive / Geodesy Data) Web: unavco.org (SAR archive interface) Data Types: Synthetic Aperture Radar (SAR) data, geodesy / tectonic data, radar imaging for earth science applications 15. INPE (Brazil’s National Institute for Space Research) Web: dgi.inpe.br (INPE Image Catalog) Data Types: CBERS satellite imagery (optical), ResourceSat, UK-DMC, other joint mission data (especially for South America & Africa) Source: gisgeography.com If you find this post valuable, kindly consider reposting. #GIS #Geospatial #RemoteSensing #QGIS #ArcGIS #Landsat #Sentinel #NASA #NOAA #MODIS #GoogleEarthEngine #GEE #Geography #Mapping #Cartography #DataScience #DataViz

🌍 Top 15 Free Satellite Imagery & Earth Observation Data Sources (2025 Update) Whether you’re a GIS analyst, remote sensing researcher, or environmental professional — here are some of the best portals for accessing free satellite imagery and geospatial datasets 👇 1️⃣ USGS Earth Explorer 🌐 https://lnkd.in/dCPqWusb 🛰️ Landsat (optical), declassified CORONA, Hyperion hyperspectral 2️⃣ Sentinel / Copernicus Browser 🌐 https://lnkd.in/dDBTARNr 🛰️ Sentinel-2 (optical multispectral), Sentinel-1 (SAR) 3️⃣ NASA Earthdata Search 🌐 https://lnkd.in/dZQ9yXZz 🛰️ Land cover, atmosphere, cryosphere, biosphere products 4️⃣ NOAA Data Access Viewer 🌐 https://lnkd.in/dtEdh_qs 🛰️ Satellite, aerial imagery, coastal LiDAR 5️⃣ Maxar Open Data Program 🌐 http://maxar.com/open-data 🛰️ High-resolution disaster imagery, stereo, elevation, footprints 6️⃣ Geo-Airbus Defense 🌐 https://lnkd.in/d3EkT_MV 🛰️ SPOT, Pleiades (optical), TerraSAR-X (radar), WorldDEM 7️⃣ NASA Worldview 🌐 https://lnkd.in/dnujDZpG 🛰️ Interactive visualization of global scientific satellite data 8️⃣ NOAA CLASS (Comprehensive Large Array-data Stewardship System) 🌐 http://class.noaa.gov 🛰️ GOES/POES imagery, aerosols, ozone, environmental data 9️⃣ ISRO Bhuvan 🌐 http://bhuvan.nrsc.gov.in 🛰️ Indian satellite data: IRS, Cartosat, OceanSat, CartoDEM 🔟 JAXA ALOS World 3D (AW3D30) 🌐 http://eorc.jaxa.jp 🛰️ Global 30 m DSM / elevation from ALOS L-band radar 1️⃣1️⃣ NOAA Digital Coast 🌐 https://lnkd.in/dsapmfAa 🛰️ Coastal imagery, elevation, radar, socio-economic data 1️⃣2️⃣ PROBA-V MEP (GeoViewer) 🌐 https://lnkd.in/dwJDSb-9 🛰️ PROBA-V, SPOT-VGT, METOP — global vegetation trends 1️⃣3️⃣ Global Land Cover Facilities 🌐 (global land cover data sources via e.g. landsat, MODIS, AVHRR) 🛰️ Landsat, MODIS, AVHRR — global land use/land cover maps 1️⃣4️⃣ UNAVCO (SAR & Geodesy Data) 🌐 http://unavco.org 🛰️ SAR, tectonic deformation, geodesy data for Earth science 1️⃣5️⃣ INPE (Brazil’s National Institute for Space Research) 🌐 http://dgi.inpe.br 🛰️ CBERS, ResourceSat, UK-DMC — regional optical datasets Follow us: https://lnkd.in/dXzJqUti For More info: https://lnkd.in/dgm-6mv6 #GIS #RemoteSensing #SatelliteImagery #EarthObservation #GeospatialData #NASA #USGS #Sentinel #Landsat #Copernicus

🌍 🌍 Top 15 Free Satellite Imagery & Earth Observation Data Sources (2025 Update) Whether you’re a GIS analyst, remote sensing researcher, or environmental professional here are some of the best portals for accessing free satellite imagery and geospatial datasets 👇 1️⃣ USGS Earth Explorer 🌐 https://lnkd.in/dpsxHY2J 🛰️ Landsat (optical), declassified CORONA, Hyperion hyperspectral 2️⃣ Sentinel / Copernicus Browser 🌐 https://lnkd.in/dpR72dnR 🛰️ Sentinel-2 (optical multispectral), Sentinel-1 (SAR) 3️⃣ NASA Earthdata Search 🌐 https://lnkd.in/dSc_gRQ7 🛰️ Land cover, atmosphere, cryosphere, biosphere products 4️⃣ NOAA Data Access Viewer 🌐 https://lnkd.in/dV7QhXuZ 🛰️ Satellite, aerial imagery, coastal LiDAR 5️⃣ Maxar Open Data Program 🌐 http://maxar.com/open-data 🛰️ High-resolution disaster imagery, stereo, elevation, footprints 6️⃣ Geo-Airbus Defense 🌐 https://lnkd.in/dBzwvXE4 🛰️ SPOT, Pleiades (optical), TerraSAR-X (radar), WorldDEM 7️⃣ NASA Worldview 🌐 https://lnkd.in/d4RQ7y3Z 🛰️ Interactive visualization of global scientific satellite data 8️⃣ NOAA CLASS (Comprehensive Large Array-data Stewardship System) 🌐 http://class.noaa.gov 🛰️ GOES/POES imagery, aerosols, ozone, environmental data 9️⃣ ISRO Bhuvan 🌐 http://bhuvan.nrsc.gov.in 🛰️ Indian satellite data: IRS, Cartosat, OceanSat, CartoDEM 🔟 JAXA ALOS World 3D (AW3D30) 🌐 http://eorc.jaxa.jp 🛰️ Global 30 m DSM / elevation from ALOS L-band radar 1️⃣1️⃣ NOAA Digital Coast 🌐 https://lnkd.in/dxpH6-5U 🛰️ Coastal imagery, elevation, radar, socio-economic data 1️⃣2️⃣ PROBA-V MEP (GeoViewer) 🌐 https://lnkd.in/dqfUNNVR 🛰️ PROBA-V, SPOT-VGT, METOP — global vegetation trends 1️⃣3️⃣ Global Land Cover Facilities 🌐 (global land cover data sources via e.g. landsat, MODIS, AVHRR) 🛰️ Landsat, MODIS, AVHRR — global land use/land cover maps 1️⃣4️⃣ UNAVCO (SAR & Geodesy Data) 🌐 http://unavco.org 🛰️ SAR, tectonic deformation, geodesy data for Earth science 1️⃣5️⃣ INPE (Brazil’s National Institute for Space Research) 🌐 http://dgi.inpe.br 🛰️ CBERS, ResourceSat, UK-DMC — regional optical datasets Follow us: https://lnkd.in/d-EFrxSj For More info: https://lnkd.in/dRDuFb-G #GIS #RemoteSensing #SatelliteImagery #EarthObservation #GeospatialData #NASA #USGS #Sentinel #Landsat #Copernicus #gisrseducation #remotesensing #SpatialAnalysis #datasources

Excited to share our new publication in Remote Sensing of Environment! 🛰️ We've developed a breakthrough algorithm that uses thermal infrared observations from MODIS and vertical information from CALIOP to retrieve dust optical depth and effective size across the globe - both over land and ocean. Highlights: ✅ Extended coverage from narrow CALIOP tracks to full global swaths at 10-km resolution ✅ Successfully captures dust particle sizes from near-source regions (7-8 μm) to long-range transport (3-5 μm) ✅ Strong validation against ground-based AERONET and 24 in-situ measurements worldwide. Why it matters: Recent studies reveal substantially coarser dust particles in the atmosphere than previously recognized - yet their transport patterns are not well characterized from current remote sensing and climate models. Our thermal infrared approach fills this critical observational gap. Now, we are preparing the full dataset spanning from 2002 to 2024 for both Terra and Aqua MODIS, which will help scientists better understand: 🌬️ Dust transport and deposition patterns, 🌍 Dust radiative effect, especially in Longwave, 🌊 Ocean fertilization by dust nutrients, etc. If you are interested in the data product, feel free to reach out! Grateful to collaborate with an outstanding team at NASA GSFC, UMBC, NOAA, and international partners! #RemoteSensing #ClimateScience #AtmosphericScience #EarthObservation #NASA 📄 https://lnkd.in/eBWPrgbg

2025 NASA Space Apps Challenge -3 DAYS 🛰️📡Through the Radar Looking Glass: Revealing Earth Processes with SAR Difficulty Level: Intermediate to Advanced ⭐Background Earth #remotesensing helps us acquire information from a bird’s eye view. #Spaceborne and #airborne instruments image the planet and provide #Earthobservations to inform decision makers in addition to #fieldsurveys conducted on the ground. Many of these instruments conduct passive remote sensing by measuring energy from the Sun that reflects off Earth, but #radar instruments conduct active remote sensing to image Earth. Active remote sensing instruments emit and receive their own sources of energy. Radar sensors use energy in the #microwave band of the #electromagneticspectrum. A #SAR instrument “synthesizes” a long antenna by combining a sequence of acquisitions from its actual, shorter antenna to provide higher spatial resolution data. SAR instruments send out a #pulse of energy that reacts with Earth’s surface and is reflected back to the instrument and recorded. SAR instruments can be used to study forest structure, soil moisture, wetlands, ocean topography, sea ice, and more. SAR data can be collected day or night and even in cloudy weather, which allows for critical data collection during disaster events like oil spills, wildfires, hurricanes, etc. Public SAR data is available for several instruments (see Resources tab) at different spatial resolutions, polarizations, and frequencies. Radar images are more than just typical satellite images that you may see with your Global Positioning System (#GPS) app. Radar data is most sensitive to two things: roughness and moisture content (the dielectric constant). Furthermore, since water has a high dielectric constant, SAR data also highlights water bodies, flood inundation, and soil moisture. In addition, sensors employing different frequencies/wavelengths (e.g., #C-band, #L-band, #P-band, etc.) provide data from varying penetration depths on Earth. Analyzing the data collected by these different sensors can enable studies such as monitoring different layers of a forest canopy (e.g., branches and leaves vs. soil and litter). ⭐Objectives Your challenge is to peer through the looking glass… by analyzing radar remote sensing data from SAR instruments that employ different polarizations and frequencies to reveal information about physical drivers on Earth. As you climb through the mirror like Alice to a world turned upside down, you will discover that data in each frequency reveals a different clue. Oil spills are seen in one wavelength but not the others, forest canopies and understories are highlighted only in certain polarizations. More riddles await you! (...) Find here more details, data and resources related to this challenge: https://lnkd.in/dmR8zXUY #LearnLaunchLead

🌍 Introducing Cryo-Scope: Real-Time Arctic Permafrost & Methane Risk Intelligence Platform ❄️ NASA International Space Apps Challenge We’re excited to share Cryo-Scope — a real-time platform that fuses NASA climate data and Sentinel-5P methane observations to assess Arctic permafrost instability and methane risk with unprecedented transparency and speed. 🔬 What Cryo-Scope Does: Cryo-Scope continuously analyzes surface temperature anomalies using NASA POWER reanalysis data and correlates them with methane concentration maps from Copernicus Sentinel-5P (TROPOMI). The system flags extreme anomaly episodes (+3σ events) and generates a Permafrost Destabilization Risk Index—both numerically and visually. 🧩 How It Works: 🌡️ Z-score–based anomaly detection against multi-decade baselines 🛰️ Methane retrieval from Sentinel Hub Processing API ⚖️ Lightweight fusion model for composite risk scoring 📊 Interactive dashboard (Next.js + TypeScript + Recharts) 📄 NASA-formatted, publication-ready PDF reports with methodology, uncertainty, and provenance tracking 🤖 AI Transparency: AI (Gemini 2.0 Flash via OpenRouter) is used only for narrative synthesis, never for metric generation — ensuring scientific reproducibility and integrity. 🚀 Why It Matters: Cryo-Scope empowers researchers and policymakers with: ✅ Faster climate intelligence synthesis ✅ Statistically sound extreme-event detection ✅ Shareable scientific reporting output ✅ Open-science architecture for educational use 💡 Built With: Next.js • TypeScript • Tailwind • Recharts • jsPDF • NASA POWER • Sentinel-5P • Copernicus • Supabase (future) • Netlify 🎥 Watch the Demo: https://lnkd.in/gcTBuR7P 🌐 Try It Live: https://lnkd.in/gfCXXpWr 💻 GitHub: https://lnkd.in/gqBGH3nA Cryo-Scope represents a new step toward open, explainable, and ethically grounded climate intelligence — combining rigorous Earth data science with human-readable insights. #CryoScope #ClimateTech #NASAData #EarthObservation #AIforScience #OpenScience #Permafrost #MethaneMonitoring #Nextjs #Copernicus #Sentinel5P #DataFusion #ClimateIntelligence #SustainabilityInnovation Developed by: Md Shakhawat Hossain Department of ECE | North South University

Breakthrough in Earth Observation: Constellr's Real-Time Atlas Satellites Earth Observation has evolved from early conceptual visions in the 17th century to practical milestones in the 20th century, including the first crude image of Earth captured by a V-2 rocket in October 1946, Sputnik's launch in 1957 for sustained orbital access, and NASA's TIROS-1 in 1960 as the first weather satellite. The iconic 1972 Apollo 17 Blue Marble image further underscored EO's role in planetary understanding and protection. Today, EO is a rapidly growing space technology application, shifting from mere inspiration to data-driven impact for business and policy decisions. It enables monitoring of farmland, power systems, and mineral resources more cost-effectively from space than on ground, leveraging advances in hyperspectral imaging, synthetic aperture radar, and algorithms for detailed planetary insights. The industry is booming, with commercial players accounting for 90% of satellite launches in 2023, up from 15% in 2014, though adoption is still mostly public-sector focused. According to the World Economic Forum's Executive's Playbook on Earth Observation, EO could contribute $3.8 trillion to global GDP by 2030 and cut two gigatonnes of annual greenhouse gas emissions. Constellr's innovation stands out, having launched two satellites with a third in preparation, using 100-200kg models that achieve superior performance at under 1% of large satellite costs, aided by falling launch prices. AI assists in mission planning, data processing, and customization, enabling real-time monitoring for food security, climate change, and even dual-use security applications like detecting activity at ammunition sites. Current EO applications span precision agriculture, supply chain monitoring, ESG reporting, and disaster early warnings, requiring organizations to integrate EO systematically through value articulation, strategic alignment, and execution via open-source data or partnerships. What impact do you think real-time Earth Observation will have on climate action? Reply with your thoughts and experiences! #EarthObservation #Constellr #SpaceTech #ClimateMonitoring #SatelliteInnovation

ICYMI, a couple of weeks ago we published a short blog post that highlights some new tutorials for working with NASA Harmonized #Landsat and #Sentinel-2 (HLS) data in the cloud. Through a collaboration with NASA, HLS data are now available on Microsoft Azure—Microsoft’s cloud platform—and accessible through Microsoft’s Planetary Computer. If you have not heard of the HLS Project before- it was created in response to the needs of the U.S. Federal Government identified by the Satellite Needs Working Group (SNWG) biennial survey. In that assessment, federal agencies and end users identified a need for more frequent Landsat-like observations to track short-term changes in vegetation and other land components to support agricultural monitoring and land cover classification at moderate to high resolution in both the visible and thermal components of the electromagnetic spectrum. HLS provides a seamless set of surface reflectance records from the Operational Land Imager (OLI) aboard the NASA/USGS Landsat-8/9 and Multi-Spectral Instrument (MSI) aboard the European Space Agency's Sentinel-2A/B remote sensing satellites. Learn more at: https://lnkd.in/e5eQUNVS Image: This HLS 30-meter reflectance vegetative false color (Bands 11, 8A, and 4) imagery from the Multi-Spectral Instruments (MSI) aboard the European Union’s Copernicus Sentinel-2A and Sentinel-2B satellites shows Italy’s Mt. Etna erupting on June 2, 2025. This imagery layer is useful for looking at vegetation, which appears in shades of green. Lava flows appear orange, burned areas appear bright red, while bare ground appears light red/pink. Credit: NASA Worldview

NASA-ISRO Satellite Sends First Radar Images of Earth’s Surface, Planet Releases First Light Image From Pelican-3; Multiple Pelican Launches Slated for the Next Year, Planet Ships 2 More Pelicans and 36 SuperDoves to Launch Site, Milestone for MicroCarb: First Earth Observations, HydroGNSS mission lands in California, Maxar retires its name, rebrands as Vantor and Lanteris, Albedo Drops its Commercial Imagery Business, KSAT launches Integrated Mission Services, scikit-eo - A Python package for Remote Sensing Data Analysis by Yonatan Tarazona, AgERA5 in Climate Engine was updated to version 2, A Desert Intersection, Earth from Space: Kilauea lava lake, Hawaii, Understanding the long-term impact of earthquakes on slopes, Educating customers may be half the battle for nascent hyperspectral sector, Countdown to launch – Copernicus Sentinel-1D lifts off in November, The 9th Edition of the Copernicus Ocean State Report warns that climate change, biodiversity loss, and pollution currently affect all ocean basins https://lnkd.in/dAwWrnqa #earthobservation #remotesensing #machinelearning #deeplearning #python

🛰️🌐 Next-gen satellite incoming! 🚀 Space-tech firm GalaxEye plans to launch the world’s first multi-sensor EO satellite in 2026 🔭. Could this reshape Earth observation and space research globally?👇 #SpaceTech #Satellite #Innovation #Science #Technology https://lnkd.in/gqjpk_Gp