#earthobservation — Public Fediverse posts

Satellite view of Ohio — 2026-09-04
Imagery: MODIS_Terra_CorrectedReflectance_TrueColor
https://worldview.earthdata.nasa.gov/?v=-84.82,38.4,-80.52,42.32&l=MODIS_Terra_CorrectedReflectance_TrueColor&t=2026-09-04

Imagery: NASA GIBS #satellite #NASA #EarthObservation

Satellite view of Ohio — 2026-09-04
Imagery: MODIS_Terra_CorrectedReflectance_TrueColor
https://worldview.earthdata.nasa.gov/?v=-84.82,38.4,-80.52,42.32&l=MODIS_Terra_CorrectedReflectance_TrueColor&t=2026-09-04

Imagery: NASA GIBS #satellite #NASA #EarthObservation

Satellite view of Ohio — 2026-09-04
Imagery: MODIS_Terra_CorrectedReflectance_TrueColor
https://worldview.earthdata.nasa.gov/?v=-84.82,38.4,-80.52,42.32&l=MODIS_Terra_CorrectedReflectance_TrueColor&t=2026-09-04

Imagery: NASA GIBS #satellite #NASA #EarthObservation

Satellite view of Ohio — 2026-09-04
Imagery: MODIS_Terra_CorrectedReflectance_TrueColor
https://worldview.earthdata.nasa.gov/?v=-84.82,38.4,-80.52,42.32&l=MODIS_Terra_CorrectedReflectance_TrueColor&t=2026-09-04

Imagery: NASA GIBS #satellite #NASA #EarthObservation

Satellite view of Ohio — 2026-09-04
Imagery: MODIS_Terra_CorrectedReflectance_TrueColor
https://worldview.earthdata.nasa.gov/?v=-84.82,38.4,-80.52,42.32&l=MODIS_Terra_CorrectedReflectance_TrueColor&t=2026-09-04

Imagery: NASA GIBS #satellite #NASA #EarthObservation

Setúbal, Portugal, increases its resilience to floods | EU Space Support Office https://www.byteseu.com/2338239/ #EarthObservation #Portugal

https://www.europesays.com/dk/159668/ Tallinn, European Green Capital 2023 #EarthObservation #Estonia #ForestryAndBiodiversity #Tallinn

In 2025, an area equivalent to **eight Norways** burned across the planet.

That sounds like a catastrophe.
- It isn't quite that simple.

Not every fire is a disaster. Some are natural. Some are deliberate. Some are tiny. Some are enormous.

So what actually happened?

Our latest feature digs into the satellite data behind **265 million hectares of recorded burned area** — and asks a more interesting question than simply *how many fires were there?*

**What the hell was actually going on?**

🔥 **EIGHT NORWAYS BURNED IN ONE YEAR**
A new feature from RABAGAS Magazine.
https://rabagas.ghost.io/eight-norways-burned-in-one-year/

#Rabagasmagazine #Wildfires #ClimateScience #EarthObservation #ClimateCrisis #SatelliteData #DataJournalism #Climate

In 2025, an area equivalent to **eight Norways** burned across the planet.

That sounds like a catastrophe.
- It isn't quite that simple.

Not every fire is a disaster. Some are natural. Some are deliberate. Some are tiny. Some are enormous.

So what actually happened?

Our latest feature digs into the satellite data behind **265 million hectares of recorded burned area** — and asks a more interesting question than simply *how many fires were there?*

**What the hell was actually going on?**

🔥 **EIGHT NORWAYS BURNED IN ONE YEAR**
A new feature from RABAGAS Magazine.
https://rabagas.ghost.io/eight-norways-burned-in-one-year/

#Rabagasmagazine #Wildfires #ClimateScience #EarthObservation #ClimateCrisis #SatelliteData #DataJournalism #Climate

In 2025, an area equivalent to **eight Norways** burned across the planet.

That sounds like a catastrophe.
- It isn't quite that simple.

Not every fire is a disaster. Some are natural. Some are deliberate. Some are tiny. Some are enormous.

So what actually happened?

Our latest feature digs into the satellite data behind **265 million hectares of recorded burned area** — and asks a more interesting question than simply *how many fires were there?*

**What the hell was actually going on?**

🔥 **EIGHT NORWAYS BURNED IN ONE YEAR**
A new feature from RABAGAS Magazine.
https://rabagas.ghost.io/eight-norways-burned-in-one-year/

#Rabagasmagazine #Wildfires #ClimateScience #EarthObservation #ClimateCrisis #SatelliteData #DataJournalism #Climate

In 2025, an area equivalent to **eight Norways** burned across the planet.

That sounds like a catastrophe.
- It isn't quite that simple.

Not every fire is a disaster. Some are natural. Some are deliberate. Some are tiny. Some are enormous.

So what actually happened?

Our latest feature digs into the satellite data behind **265 million hectares of recorded burned area** — and asks a more interesting question than simply *how many fires were there?*

**What the hell was actually going on?**

🔥 **EIGHT NORWAYS BURNED IN ONE YEAR**
A new feature from RABAGAS Magazine.
https://rabagas.ghost.io/eight-norways-burned-in-one-year/

#Rabagasmagazine #Wildfires #ClimateScience #EarthObservation #ClimateCrisis #SatelliteData #DataJournalism #Climate

In 2025, an area equivalent to **eight Norways** burned across the planet.

That sounds like a catastrophe.
- It isn't quite that simple.

Not every fire is a disaster. Some are natural. Some are deliberate. Some are tiny. Some are enormous.

So what actually happened?

Our latest feature digs into the satellite data behind **265 million hectares of recorded burned area** — and asks a more interesting question than simply *how many fires were there?*

**What the hell was actually going on?**

🔥 **EIGHT NORWAYS BURNED IN ONE YEAR**
A new feature from RABAGAS Magazine.
https://rabagas.ghost.io/eight-norways-burned-in-one-year/

#Rabagasmagazine #Wildfires #ClimateScience #EarthObservation #ClimateCrisis #SatelliteData #DataJournalism #Climate

Essential Earth Observation Variables For High-Level Multi-Scale Indicators And Policies
--
https://doi.org/10.1016/j.envsci.2021.12.024 <-- shared paper
--
https://earthobservations.org/about-us/news/remembering-paolo-mazzetti-a-legacy-of-science-kindness-and-collaboration <-- shared author memorial
--
H/T @Paolo Mazzetti | Senior Researcher at the Institute of Technologies and Environmental Intelligence (ITIAm) of CNR
“HIGHLIGHTS:
• Defining Essential Variables (EVs) to describe the global socio-ecological system.
• Setting the objectives of a new Group on Earth Observation (GEO) community activity on EVs.
• Defining criteria for selecting EVs.
• Demonstrating a fully functional workflow on land degradation.
• Presenting a new vision for the mainstreaming of EVs in science-policy interfaces..."
#Earthobservations #Essentialvariables #Indicators #Workflows #Sustainabledevelopmentgoals #Policy #earthobservation #essentialvariables #Indicators #Workflow #sustainabledevelopmentgoals #SDGs #policy #spatial #mapping #remotesensing #EVs #GroupOnEarthObservation #GEO #socioecological #sustainability #earthsystems #Drivers #Pressures #States #Impacts #Responses #sustainability #monitoring #observations #organisation #GlobalEarthObservationSystemofSystems #overview #review #literaturereview #environmental #Essentiality #Evolvability #Unambiguity #Feasibility #ecologicalfootprinting #viability

Mapping Snow On Northern Winter Roads - A Dual-Frequency Polarimetric Radar Approach For Snow Characterization Over Land, Lake And Sea Ice
--
https://doi.org/10.5194/tc-20-4367-2026 <-- shared paper
--
H/T @Monojit Saha | Geospatial Analysis | Remote Sensing | Satellite Altimetry | Cryosphere
“Winter roads are essential transportation links for many remote northern communities, but their safety and reliability depend strongly on snow conditions and ice growth. In this study [link above], [the authors] evaluated a fully polarimetric, dual-frequency Ku- and Ka-band radar approach for retrieving snow depth across landfast sea ice, lake ice, and tundra.
Using field measurements near Churchill, Manitoba, and Resolute Bay, Nunavut [Canada], [they] found that the approach produced snow-depth retrieval bias and error within 3 cm over landfast ice, with encouraging Ku-band performance over frozen ground as well. [They] also developed an interface-detection approach for lake ice that can retrieve both snow depth and ice thickness - a promising direction for characterizing conditions relevant to winter-road planning and safety…”
--
“Winter roads are lifelines for remote northern communities. Built over land, lakes, rivers, and sea ice, these travel routes are increasingly vulnerable to warming temperatures and variable precipitation. To ensure safety and adapt to these changes, operators require high-resolution monitoring of snow depth across these diverse surfaces, as natural snow accumulation dictates ice growth rates, route viability and road stability. This study extends our polarimetric radar method, previously demonstrated on pack ice, to landfast sea ice, tundra, and frozen lakes and assesses how well we can retrieve snow depth over these surfaces. Results indicate consistency with earlier sea ice analyses, maintaining a mean snow depth retrieval bias and error within 3 cm over the landfast ice. Promising performance is also found over frozen ground using Ku-band (mean biases less than 6 cm). To address the specific challenge of lake ice, which includes strong returns from the ice/water interface, we present a new interface-detection technique that simultaneously retrieves snow depth and ice thickness. While current validation focuses on undisturbed snow, this approach could provide a path forward for characterizing the cryospheric environment in a way that can directly support the optimization of winter roads…”
#Cryosphere #RemoteSensing #Snow #SeaIce #LakeIce #WinterRoads #characterisation #ArcticResearch #EarthObservation #PolarScience #maintainence #ploughing #winter #roads #transportation #northern #communities #mines #FirstNation #canada #remotesensing #polarimetric #radar #snowdepth #ice #landfastice #iceroad #tundra #Churchill #Manitoba #ResoluteBay #Nunavut #monitoring #planning #safety #trucking #freight

The Congo Basin is under cloud so often that optical EO barely works there, and I keep landing on SAR. For persistently cloudy regions, what's your actual workflow — radar, fusion, patience?
#RemoteSensing #SAR #EarthObservation #GeoAI

Flood And Landslide Susceptibility Assessment And Multi Hazard Interaction Mapping Using Machine Learning And GIS For Sustainable Settlement Planning In Nepal
--
https://doi.org/10.1007/s44288-026-00670-8 <-- shared paper
--
H/T @Narayan Thapa | Earth Data Modeling
“Nepal lies within an active seismic zone and is influenced by most dynamic climatic systems in the world. It faces compounding floods and landslide threats. Impacts are worst where multi-hazard interactions create spatially linked corridors. Despite frequent co-occurrence, national-scale assessments remain limited. This study presents machine learning and GIS-based approach to map nationwide susceptibility to floods, landslides, and identify their potential interaction zones, and delineate critical multi-hazard flow zones through spatial adjacency analysis. Using Google Earth Engine, the Random Forest model integrates topographic, climatic, environmental, and hydrological datasets to overcome subjective expert-driven methods. The model achieved strong predictive accuracy (AUC: 0.84 for floods, 0.85 for landslides). The results showed 19% of Nepal’s lowlands are medium to very highly susceptible to inundation, threatening approximately 900,000 people and over 3.4 million buildings; whilst in the hilly terrains, 40% is susceptible to slope-failure endangering 200,000 people and about 0.6 million buildings. K-means clustering followed by spatial adjacency analysis identified four spatial zonation: 81% of national area as low-hazard zone, 9% as flood-only zone, 5% as landslide-only zone, and 5% as interaction zones. Critical multi-hazard flow zone covering 7,588 km² represents spatially connected corridors linking interaction zones to downstream flood-prone populated areas, affecting 88 km² built-up land and 1,722 km² cropland. These zones represent susceptibility-based spatial connectivity rather than physically simulated cascading processes. These findings support recommendations for risk-informed land-use planning, resilient infrastructure development and climate adaptation aligned to sustainable development and investment risk screening…”
#GIS #spatial #mapping #GoogleEarthEngine #MachineLearning #RemoteSensing #GeospatialAI #DisasterRiskReduction #MultiHazard #ClimateAdaptation #climatechange #extremeweather #LandUsePlanning #SustainableDevelopment #InfrastructurePlanning #RiskAssessment #NaturalHazards #Nepal #EarthObservation #HinduKushHimalaya #HKH #HinduKush #Himalayas #risk #hazard #assessment #national #regional #spatialanalysis #spatiotemporal #massmovement #landslide #assessment #mitigation #water #hydrology #flood #flooding #sustainability

Enhancements To The USGS Landsat Level 2 Surface Temperature And Emissivity Product For Collection3 Reprocessing
--
https://doi.org/10.1016/j.rse.2026.115563 <-- shared paper
--
H/T @terry Sohl | USGS EROS Science Branch Chief
“HIGHLIGHTS:
• C3 advances Landsat TIR atmospheric correction, emissivity correction, and uncertainty estimates.
• C3 enables global surface temperature products, including polar regions.
• C3 retrievals improve accuracy and consistency across validation sites.
• Split window and single channel methods diverge at extreme temperature conditions.
• C3 and Landsat 10 support multi-decadal climate monitoring.
ABSTRACT: The Landsat program provides the longest continuous global record of thermal infrared observations of the Earth's surface, underpinning critical applications in climate monitoring, water resources, ecosystem dynamics, urban heat analysis, and natural hazard assessment. The release of a global inventory of Landsat Collection 2 Level 2 surface temperature products by the U.S. Geological Survey (USGS) marked a major milestone in operational provision of Landsat thermal infrared analysis-ready data. Ongoing validations and community uses of Collection 2 have identified opportunities to further improve accuracy, uncertainty characterization, and emissivity correction across diverse atmospheric and surface conditions. In preparation for the planned Landsat Collection 3 reprocessing of the Landsat data record in the late 2020s, the USGS is implementing a coordinated set of enhancements to the Level 2 surface temperature products. These include revised emissivity estimation that leverages external datasets, improved atmospheric characterization and uncertainty propagation, expanded dynamic range for high temperature targets, consideration of split window atmospheric correction algorithm for Landsat 8 and 9, and decoupling of thermal infrared processing from visible to shortwave infrared constraints to enable surface temperature retrievals under low or no solar illumination conditions. These changes are designed to improve product quality and consistency across the Landsat record. Beyond near-term performance gains, the Collection 3 design establishes a scalable processing architecture to accommodate the expanded spectral and radiometric measurement capabilities of the forthcoming Landsat 10 mission. By preserving continuity across the Landsat 4–9 record while enabling future algorithm evolution, Landsat Collection 3 will provide a foundation for long-term, multi-decadal Earth system thermal infrared observations…”
#GIS #spatial #mapping #satellite #remotesening #earthobservation #Landsat #thermalinfrared #TIR #surface #temperature #emissivity #thermal #infrared #analysisreadydata #Collection2 #Collection3 #opendata #atmosphericcorrection #global #climate #monitoring #waterresources #ecosystems #dynamics #urbanheat #spatialanalysis #spatiotemporal #naturalhazards #updates #EROS #USGS
@USGS EROS | @USGS

Enhancements To The USGS Landsat Level 2 Surface Temperature And Emissivity Product For Collection3 Reprocessing
--
https://doi.org/10.1016/j.rse.2026.115563 <-- shared paper
--
H/T @terry Sohl | USGS EROS Science Branch Chief
“HIGHLIGHTS:
• C3 advances Landsat TIR atmospheric correction, emissivity correction, and uncertainty estimates.
• C3 enables global surface temperature products, including polar regions.
• C3 retrievals improve accuracy and consistency across validation sites.
• Split window and single channel methods diverge at extreme temperature conditions.
• C3 and Landsat 10 support multi-decadal climate monitoring.
ABSTRACT: The Landsat program provides the longest continuous global record of thermal infrared observations of the Earth's surface, underpinning critical applications in climate monitoring, water resources, ecosystem dynamics, urban heat analysis, and natural hazard assessment. The release of a global inventory of Landsat Collection 2 Level 2 surface temperature products by the U.S. Geological Survey (USGS) marked a major milestone in operational provision of Landsat thermal infrared analysis-ready data. Ongoing validations and community uses of Collection 2 have identified opportunities to further improve accuracy, uncertainty characterization, and emissivity correction across diverse atmospheric and surface conditions. In preparation for the planned Landsat Collection 3 reprocessing of the Landsat data record in the late 2020s, the USGS is implementing a coordinated set of enhancements to the Level 2 surface temperature products. These include revised emissivity estimation that leverages external datasets, improved atmospheric characterization and uncertainty propagation, expanded dynamic range for high temperature targets, consideration of split window atmospheric correction algorithm for Landsat 8 and 9, and decoupling of thermal infrared processing from visible to shortwave infrared constraints to enable surface temperature retrievals under low or no solar illumination conditions. These changes are designed to improve product quality and consistency across the Landsat record. Beyond near-term performance gains, the Collection 3 design establishes a scalable processing architecture to accommodate the expanded spectral and radiometric measurement capabilities of the forthcoming Landsat 10 mission. By preserving continuity across the Landsat 4–9 record while enabling future algorithm evolution, Landsat Collection 3 will provide a foundation for long-term, multi-decadal Earth system thermal infrared observations…”
#GIS #spatial #mapping #satellite #remotesening #earthobservation #Landsat #thermalinfrared #TIR #surface #temperature #emissivity #thermal #infrared #analysisreadydata #Collection2 #Collection3 #opendata #atmosphericcorrection #global #climate #monitoring #waterresources #ecosystems #dynamics #urbanheat #spatialanalysis #spatiotemporal #naturalhazards #updates #EROS #USGS
@USGS EROS | @USGS

Enhancements To The USGS Landsat Level 2 Surface Temperature And Emissivity Product For Collection3 Reprocessing
--
https://doi.org/10.1016/j.rse.2026.115563 <-- shared paper
--
H/T @terry Sohl | USGS EROS Science Branch Chief
“HIGHLIGHTS:
• C3 advances Landsat TIR atmospheric correction, emissivity correction, and uncertainty estimates.
• C3 enables global surface temperature products, including polar regions.
• C3 retrievals improve accuracy and consistency across validation sites.
• Split window and single channel methods diverge at extreme temperature conditions.
• C3 and Landsat 10 support multi-decadal climate monitoring.
ABSTRACT: The Landsat program provides the longest continuous global record of thermal infrared observations of the Earth's surface, underpinning critical applications in climate monitoring, water resources, ecosystem dynamics, urban heat analysis, and natural hazard assessment. The release of a global inventory of Landsat Collection 2 Level 2 surface temperature products by the U.S. Geological Survey (USGS) marked a major milestone in operational provision of Landsat thermal infrared analysis-ready data. Ongoing validations and community uses of Collection 2 have identified opportunities to further improve accuracy, uncertainty characterization, and emissivity correction across diverse atmospheric and surface conditions. In preparation for the planned Landsat Collection 3 reprocessing of the Landsat data record in the late 2020s, the USGS is implementing a coordinated set of enhancements to the Level 2 surface temperature products. These include revised emissivity estimation that leverages external datasets, improved atmospheric characterization and uncertainty propagation, expanded dynamic range for high temperature targets, consideration of split window atmospheric correction algorithm for Landsat 8 and 9, and decoupling of thermal infrared processing from visible to shortwave infrared constraints to enable surface temperature retrievals under low or no solar illumination conditions. These changes are designed to improve product quality and consistency across the Landsat record. Beyond near-term performance gains, the Collection 3 design establishes a scalable processing architecture to accommodate the expanded spectral and radiometric measurement capabilities of the forthcoming Landsat 10 mission. By preserving continuity across the Landsat 4–9 record while enabling future algorithm evolution, Landsat Collection 3 will provide a foundation for long-term, multi-decadal Earth system thermal infrared observations…”
#GIS #spatial #mapping #satellite #remotesening #earthobservation #Landsat #thermalinfrared #TIR #surface #temperature #emissivity #thermal #infrared #analysisreadydata #Collection2 #Collection3 #opendata #atmosphericcorrection #global #climate #monitoring #waterresources #ecosystems #dynamics #urbanheat #spatialanalysis #spatiotemporal #naturalhazards #updates #EROS #USGS
@USGS EROS | @USGS

Enhancements To The USGS Landsat Level 2 Surface Temperature And Emissivity Product For Collection3 Reprocessing
--
https://doi.org/10.1016/j.rse.2026.115563 <-- shared paper
--
H/T @terry Sohl | USGS EROS Science Branch Chief
“HIGHLIGHTS:
• C3 advances Landsat TIR atmospheric correction, emissivity correction, and uncertainty estimates.
• C3 enables global surface temperature products, including polar regions.
• C3 retrievals improve accuracy and consistency across validation sites.
• Split window and single channel methods diverge at extreme temperature conditions.
• C3 and Landsat 10 support multi-decadal climate monitoring.
ABSTRACT: The Landsat program provides the longest continuous global record of thermal infrared observations of the Earth's surface, underpinning critical applications in climate monitoring, water resources, ecosystem dynamics, urban heat analysis, and natural hazard assessment. The release of a global inventory of Landsat Collection 2 Level 2 surface temperature products by the U.S. Geological Survey (USGS) marked a major milestone in operational provision of Landsat thermal infrared analysis-ready data. Ongoing validations and community uses of Collection 2 have identified opportunities to further improve accuracy, uncertainty characterization, and emissivity correction across diverse atmospheric and surface conditions. In preparation for the planned Landsat Collection 3 reprocessing of the Landsat data record in the late 2020s, the USGS is implementing a coordinated set of enhancements to the Level 2 surface temperature products. These include revised emissivity estimation that leverages external datasets, improved atmospheric characterization and uncertainty propagation, expanded dynamic range for high temperature targets, consideration of split window atmospheric correction algorithm for Landsat 8 and 9, and decoupling of thermal infrared processing from visible to shortwave infrared constraints to enable surface temperature retrievals under low or no solar illumination conditions. These changes are designed to improve product quality and consistency across the Landsat record. Beyond near-term performance gains, the Collection 3 design establishes a scalable processing architecture to accommodate the expanded spectral and radiometric measurement capabilities of the forthcoming Landsat 10 mission. By preserving continuity across the Landsat 4–9 record while enabling future algorithm evolution, Landsat Collection 3 will provide a foundation for long-term, multi-decadal Earth system thermal infrared observations…”
#GIS #spatial #mapping #satellite #remotesening #earthobservation #Landsat #thermalinfrared #TIR #surface #temperature #emissivity #thermal #infrared #analysisreadydata #Collection2 #Collection3 #opendata #atmosphericcorrection #global #climate #monitoring #waterresources #ecosystems #dynamics #urbanheat #spatialanalysis #spatiotemporal #naturalhazards #updates #EROS #USGS
@USGS EROS | @USGS

Enhancements To The USGS Landsat Level 2 Surface Temperature And Emissivity Product For Collection3 Reprocessing
--
https://doi.org/10.1016/j.rse.2026.115563 <-- shared paper
--
H/T @terry Sohl | USGS EROS Science Branch Chief
“HIGHLIGHTS:
• C3 advances Landsat TIR atmospheric correction, emissivity correction, and uncertainty estimates.
• C3 enables global surface temperature products, including polar regions.
• C3 retrievals improve accuracy and consistency across validation sites.
• Split window and single channel methods diverge at extreme temperature conditions.
• C3 and Landsat 10 support multi-decadal climate monitoring.
ABSTRACT: The Landsat program provides the longest continuous global record of thermal infrared observations of the Earth's surface, underpinning critical applications in climate monitoring, water resources, ecosystem dynamics, urban heat analysis, and natural hazard assessment. The release of a global inventory of Landsat Collection 2 Level 2 surface temperature products by the U.S. Geological Survey (USGS) marked a major milestone in operational provision of Landsat thermal infrared analysis-ready data. Ongoing validations and community uses of Collection 2 have identified opportunities to further improve accuracy, uncertainty characterization, and emissivity correction across diverse atmospheric and surface conditions. In preparation for the planned Landsat Collection 3 reprocessing of the Landsat data record in the late 2020s, the USGS is implementing a coordinated set of enhancements to the Level 2 surface temperature products. These include revised emissivity estimation that leverages external datasets, improved atmospheric characterization and uncertainty propagation, expanded dynamic range for high temperature targets, consideration of split window atmospheric correction algorithm for Landsat 8 and 9, and decoupling of thermal infrared processing from visible to shortwave infrared constraints to enable surface temperature retrievals under low or no solar illumination conditions. These changes are designed to improve product quality and consistency across the Landsat record. Beyond near-term performance gains, the Collection 3 design establishes a scalable processing architecture to accommodate the expanded spectral and radiometric measurement capabilities of the forthcoming Landsat 10 mission. By preserving continuity across the Landsat 4–9 record while enabling future algorithm evolution, Landsat Collection 3 will provide a foundation for long-term, multi-decadal Earth system thermal infrared observations…”
#GIS #spatial #mapping #satellite #remotesening #earthobservation #Landsat #thermalinfrared #TIR #surface #temperature #emissivity #thermal #infrared #analysisreadydata #Collection2 #Collection3 #opendata #atmosphericcorrection #global #climate #monitoring #waterresources #ecosystems #dynamics #urbanheat #spatialanalysis #spatiotemporal #naturalhazards #updates #EROS #USGS
@USGS EROS | @USGS

From orbit, the Earth stops being a map and becomes a living thing. 🌍 Clouds move like breath, cities glow like stories, rivers write their names into the land. This is what a geographer sees from above — not borders, but patterns. Satellites gather the signals; remote sensing turns light into meaning; GeoAI learns the planet’s rhythm. 🛰️

#RemoteSensing #GeoAI #Geography #Satellites #EarthObservation

EU delays release of Copernicus imagery over Gulf of Oman

https://fed.brid.gy/r/https://spacenews.com/eu-delays-release-of-copernicus-imagery-over-gulf-of-oman/

Refined Modeling of Arctic Circumpolar Building Stock Increases Estimated Mid-Century Permafrost Degradation Damages
--
https://doi.org/10.1029/2026EF008578 <-- shared paper
--
https://www.thearcticinstitute.org/climate-change-geopolitics-monitoring-thawing-permafrost/ | https://www.thearcticinstitute.org/dwindling-arctic-sea-ice-impacts-permafrost-health/ <-- shared technical articles
--
https://www.theguardian.com/cities/2016/oct/14/thawing-permafrost-destroying-arctic-cities-norilsk-russia <-- shared media article
--
https://news.grida.no/new-map-shows-extent-of-permafrost-in-northern-hemisphere <-- shared technical article
--
H/T @elias Manos
“Why the increase?
Our understanding of climate risk is only as good as our understanding of our exposure to hazards. The better we can account for what is at risk, the better we can measure risk in a changing world.
In this new study [link above], [they] investigate[d] how damage to the building stock across the Arctic, a key impact of permafrost degradation, is underestimated because of underdeveloped exposure information. With National Science Foundation (NSF) supercomputers and 400 TB of Vantor satellite imagery, [they] detected building footprints across the Arctic and classified their use types using deep learning models. Then, using Polar Geospatial Center's ArcticDEM digital surface model, [they] estimated the total floor space of each residential building. This move from 2D to 3D representation of the building stock was the largest contributor to increased building damage.
Properly estimating this consequence is necessary for understanding the near future of the Arctic economy. Knowing the magnitude of damages is critical for sustaining the communities and livelihoods of more than 5 million people that call the Arctic home. There are also much broader implications. With the Arctic continuing to emerge as a strategic centerpiece in global affairs and the global economy, accurately quantifying the physical shocks to its built environment will allow researchers to more effectively represent the Arctic in global climate economic models. More precise international policymaking will also be enabled by these improvements.
Ultimately, this research highlights a similar challenge in completely different regions of the world (e.g., Southeast Asia, Sub-Saharan Africa) where exposure is constantly evolving alongside rapid population growth and urbanization. Building stock information can quickly become outdated as these changes occur; satellite remote sensing and AI are key players in keeping up with these changes and supporting data-driven disaster risk management…”
#arctic #circumpolar #permafrost #model #modeling #spatialanalysis #spatiotemporal #GIS #spatial #mapping #melting #degradation #damage #cost #economics #risk #hazard #climaterisk #climatechange #remotesensing #HPC #earthobservation #ArcticDEM #buildingfootprint #LLM #AI #machinelearning #engineering #economy #buildingstock #community #policy #planning #geopolitics #risk #management @UConn Research

IHI explores Kuva hyperspectral satellites for Japan’s multi-sensor constellation

https://fed.brid.gy/r/https://spacenews.com/ihi-explores-kuva-hyperspectral-satellites-for-japans-multi-sensor-constellation/

Comparative Hydro-Climatic Datasets For Catchment-Wise Linked Water Fluxes And Storage Changes Across South America
--
https://doi.org/10.3389/fenvs.2026.1764771 <-- shared paper
--
https://doi.org/10.1038/s43247-026-03661-2 <-- shared paper
--
https://doi.org/10.1002/joc.6443 <-- shared paper
--
https://www.pik-potsdam.de/en/news/latest-news/from-droughts-to-floods-climate-change-and-migration-in-peru | https://publications.iom.int/books/evaluacion-de-la-evidencia-cambio-climatico-y-migracion-en-el-peru <-- shared 2021 Peru hydroclimate technical article | report
--
https://youtu.be/Ngbm0gsmYAw?si=haqV7t15pGkEmJB8 <-- shared overview video
--
#water #GIS #spatial #mappping #spatialanalysis #spatiotemporal #remotesensing #earthobservation #Hydrology #Hydroclimatology #ClimateChange #extremeweather #WaterResources #WaterSecurity uncertainity #SouthAmerica #ClimateData #PeerReview #OpenScience #Hydrometeorology #opendata #datasets #rainfall #precipitation #fluvial #heatwave #temperature #changing #consistency #flood #flooding #drought #riskmanagement #risk #hazard #earthsystems #resilience #waterquality #waterpollution #model #modeling #monitoring #records #hydroclimate #hydrogeomorphology #review #SouthAmerica #planning #policy #sustainability #evapotranspiration #runoff #waterstorage #SAHCD

Hello Mastodon, an #introduction.
I'm a geospatial scientist with a PhD in Earth System and Geoinformation Science. I work in remote sensing and #GeoAI, mostly on drought, vegetation, and land — in Africa and the US Great Plains.
I'll mostly post maps, model results, and #GoogleEarthEngine and Python tutorials (#geopandas, #rasterio). I'm also building a national GIS data portal for #Cameroon.
#RemoteSensing #GIS #EarthObservation #Python

Remote Sensing, Real Impact - Technology-Driven Conservation At The Jane Goodall Institute
(How the Jane Goodall Institute [JGI] is using satellite imagery and spatial technology to help people and animals thrive.)
--
https://www.geoweeknews.com/news/conservation-at-the-jane-goodall-institute <-- shared technical article
--
https://www.iceye.com/blog/government/solutions/how-the-jane-goodall-institute-uses-iceye-sar-to-protect-ecosystems <-- shared technical article
--
[this post should not be seen as endorsement of a particular provider and/or approach]
“Dr. Jane Goodall’s groundbreaking research at Gombe National Park in Tanzania began in 1960, and transformed our understanding of chimpanzees and redefined the relationship between humans and animals. Dr. Goodall dedicated her life to conservation and community empowerment. Her recent passing marks the end of an extraordinary career in ethology and conservation science. Yet her legacy lives on powerfully through the Jane Goodall Institute [JGI] and the countless individuals and communities she inspired worldwide. Her pioneering work revealed that chimpanzees make and use tools, have complex social structures, and possess individual personalities; discoveries that fundamentally challenged our understanding of what it means to be human, for the better…
The institute's current work embodies Dr. Goodall's profound philosophy: that humanity can only reach its full potential "when our clever brains and our compassionate hearts are connected."
This principle guides every aspect of JGI's conservation science strategy, from analyzing satellite data to providing local communities with the tools they need to strengthen their environment. Dr. Goodall's vision that conservation must be rooted in compassion, scientific rigor, and respect for local communities continues to shape the institute's innovative approach to using technology for conservation action.
As time has gone on, geospatial technologies have become increasingly indispensable to this mission, enabling JGI to monitor forest health in real-time, map critical chimpanzee habitats and migration corridors, and measure the tangible impact of community-led conservation initiatives. But perhaps most importantly, these technologies help the communities understand that the lives of people, animals and their shared environment are all interconnected…”
#ConservationTechnology #illegal #Deforestation #hunting #mining #GombeNationalPark #remotesensing #radar #earthobservation #chimpanzee #conservation #communityempowerment #JaneGoodallInstitute #JGI #satellite #spatialanalysis #spatiotemporal #GIS #spatial #mapping #habitat #destruction #migration #corridors #monitoring #conservationscience #strategy #resource #cloudcover #alerts #foresthealth #protection #SAR #vegetation #ecosystems #rainforest #greatape #disease #foodsecurity #DRC #Tanzania #CongoBasin #nationalpark #ranger #parkranger #security #safety #alerts #wildlifetrafficking
@JaneGoodallInstitute @iceeye

ICEYE to double radar-satellite capacity by late 2027 as demand surges

PARIS — Finland’s ICEYE expects to double global production to 100 radar satellites by the end of 2027,…
#NewsBeep #News #Space #CA #Canada #circulated-c4isrnet #circulated-defense-news #defense-news #dn-dnr #Earthobservation #Europe #Finland #ICEYE #Science #surveillance #syntheric-aperture-radar
https://www.newsbeep.com/ca/760249/

ICEYE to double radar-satellite capacity by late 2027 as demand surges

PARIS — Finland’s ICEYE expects to double global production to 100 radar satellites by the end of 2027,…
#NewsBeep #News #Space #AU #Australia #circulated-c4isrnet #circulated-defense-news #defense-news #dn-dnr #Earthobservation #Europe #Finland #Iceye #Science #surveillance #syntheric-aperture-radar
https://www.newsbeep.com/au/759429/

🚀 Registration is now open for the Agentic AI for Earth Observation Workshop! 👉 Register now: agentic-eo.berlin/attend/regis... @[email protected] @[email protected] #EarthObservation #LLM #GeoAI #geospatial #ai #Agents #gischat #geosky 🌍🛰️

Bringing imagery and communications under one roof

https://fed.brid.gy/r/https://spacenews.com/bringing-imagery-and-communications-under-one-roof/

National-Scale Field Delineation In Mozambique Refines Our Understanding Of Cropland Distribution, Field Size, And Deforestation Actors.
--
https://doi.org/10.1088/1748-9326/ae5cb4 <-- shared paper
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https://philipperufin.github.io/blog/mozfields-2023/ <-- shared associated technical article from one of the paper’s authors
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#foodsecurity #subsistence #smallholder #farms #farming #agriculture #crops #Mozambique #subSaharan #Africa #GIS #spatial #mapping #remotesensing #earthobservation #policy #planning #cropland #spatialanalysis #spatiotemporal #field #deforestation #countrywide #landuse #sustainability #delineation #satellite #SPOT #model #modeling #deeplearning #AI #machinelearning #survey #GeoAI #spatialdata

‘This Feels Fragile’ - How A Satellite-Smashing Chain Reaction Could Spiral Out Of Control [space junk]
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Today, the space around Earth can no longer be considered empty. More than 30,000 objects are in orbit, and that figure is rising exponentially
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https://www.theguardian.com/science/ng-interactive/2026/mar/31/this-feels-fragile-how-a-satellite-smashing-chain-reaction-could-spiral-out-of-control <-- shared interactive technical/media article, with outstanding visualisations
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https://www.space-track.org/ | https://celestrak.org/ | https://planet4589.org/space/stats/ <-- various satellite tracking efforts
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#spacejunk #spacedebris #visualisation #spatialanalysis #orbit #spatiotemporal #satellite #fragments #history #Sputnik #risk #hazard #mitigation #deorbiting #reentry #orbitallanes #military #communication #weather #remotesensing #astronomy #earthobservation #lightpollution #orbitaltraffic #collision #debris #usecase #logistics #crowded #coordination #planning #tracking #technology
@TheGuardian

Drivers Of Forest Disturbance In Southeast Asia [incl. spatial analysis]
--
https://doi.org/10.1016/j.jag.2026.105220 <-- shared paper 🔗
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https://github.com/shijuanchen/SEA_forest_dis <-- shared GitHub ‘data repository 🔗
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#GIS #spatial #mapping #spatialanalysis #spatiotemporal #forest #vegetation #Forestdisturbance #Forestdegradation #Deforestation #remotesensing #SoutheastAsia #Asia #tropicalforests #timeseriesanalysis #geostatistics #disturbance #clearing #planting #agriculture #earthobservation #imagery #CCDC #changedetection #landcover #landuse #change #plantation #cultivation #slashandburn #planning #mitigation #catalogue #conservation #management #landmanagement #machinelearning #imageanalysis #AI

Processing [#USGS] 3DEP [#OpenData] LiDAR Point Clouds with Purdue's Data to Science Open Source Pipelines [overview/tutorial]
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https://youtu.be/oicXic8cVqU?si=cz41PgHOC5v-53SY <-- shared video
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https://github.com/gdslab/3dep_tutorial/blob/main/usgs_3dep_tutorial.ipynb <-- #Data2Science project and #Github repositories
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#GIS #spatial #mapping #KnowledgeBase #NSGIC #USGS #3dep #pointcloud #remotesensing #earthobservation #processing #pipelines #opendata #fedscience #publicgood #DataToScience #opensource #overview #tutorial #derivateproducts #workflow #stakeholders #elevation #USA #national #TheNationalMap #tools #3DEPfortheNation #3DEPFTN
#USGS | #NSGIC | #PurdueUniversity

Remotely Sensed Soil Moisture Can Capture Dynamics Relevant To Plant Water Uptake
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https://doi.org/10.1029/2022WR033814 <-- shared (2023) paper
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#GIS #spatial #mapping #remotesensing #global #soil #moisture #earthobservation #Lband #satellite #landsurface #landuse #biosphere #hydrosphere #microwave #vegetation #botany #roots #agriculture #pluvial #rainfall #taproot #planthealth #foodsecurity #production #rootzones #spatialanalysis #spatiotemporal #grasslands #croplands #shrubs #trees #seasonal #water #hydrology #wateruptake #SMAP
@nasa @nasa Goddard @AGU

Satellites Help Tackle Landfill Methane Leaks
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https://www.esa.int/Applications/Observing_the_Earth/Space_for_our_climate/Satellites_help_tackle_landfill_methane_leaks <-- shared (ESA) technical article
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https://www.ghgsat.com/en/case-studies/landfill-gas/ <-- details of GHGSat usage for landfill gases
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#ESA ##GHGSat #landfill #methane #remotesensing #earthobservation #spatialanalysis #GIS #spatial #mapping #spatiotemporal #greenhousegas #emissions #pollution #GlobalMethanePledge #satellite #Copernicus #Sentinel #Sentinel5P #climatechange #MEDUSA #wastemanagement #waste #oilandgas #landfillsites
@europeanspaceagency

Earth Is Getting Dimmer—and the Northern Hemisphere Is Losing Brightness Faster Than Scientists Expected
(New research challenges the idea that the hemispheres’ matching brightness is a fundamental property of the planet)
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https://www.smithsonianmag.com/smart-news/earth-is-getting-dimmer-and-the-northern-hemisphere-is-losing-brightness-faster-than-scientists-expected-180987578/ <-- shared technical article
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https://doi.org/10.1073/pnas.2511595122 <-- shared paper
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https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc:C00787 <-- shared earth observation datasets, NOAA Climate Data Record (CDR) of AMSU-A Level 1c Brightness Temperature, Version 1.0
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#GIS #spatial #mapping #spatialanalysis #global #spatiotemporal #remotesensing #earthobservation #earthshine #albedo #brightness #oceanwarming #NorthernHemisphere #SouthernHemisphere #satellite #atmosphere #climate #radiantenergy #darkening #cloud #ASR #watervapour #ocean #marine #aerosol #future
@NCEI

Frozen No More - A Case Study Of Arctic Permafrost Impacts Of Oil And Gas Withdrawal
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https://doi.org/10.1038/s41598-024-76292-2 <-- shared paper
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#GIS #spatial #mapping #remotesening #earthobservation #oil #gas #oilandgas #O&G #energy #extraction #drilling #exploration #subsurface #permafrost #melting #humanimpacts #climatechange #oilextraction #risk #hazard #riskassessment #water #hydrology #sediment #tundra #oilwellpads #NorthSlope #Alaska #arctic #spatialanalysis #spatiotemporal #remediation #drillpad #oilpad #lease #industry #habitat #ecosystem #fieldwork #sampling #geology #engineeringgeology #impact

Frozen No More - A Case Study Of Arctic Permafrost Impacts Of Oil And Gas Withdrawal
--
https://doi.org/10.1038/s41598-024-76292-2 <-- shared paper
--
#GIS #spatial #mapping #remotesening #earthobservation #oil #gas #oilandgas #O&G #energy #extraction #drilling #exploration #subsurface #permafrost #melting #humanimpacts #climatechange #oilextraction #risk #hazard #riskassessment #water #hydrology #sediment #tundra #oilwellpads #NorthSlope #Alaska #arctic #spatialanalysis #spatiotemporal #remediation #drillpad #oilpad #lease #industry #habitat #ecosystem #fieldwork #sampling #geology #engineeringgeology #impact

Frozen No More - A Case Study Of Arctic Permafrost Impacts Of Oil And Gas Withdrawal
--
https://doi.org/10.1038/s41598-024-76292-2 <-- shared paper
--
#GIS #spatial #mapping #remotesening #earthobservation #oil #gas #oilandgas #O&G #energy #extraction #drilling #exploration #subsurface #permafrost #melting #humanimpacts #climatechange #oilextraction #risk #hazard #riskassessment #water #hydrology #sediment #tundra #oilwellpads #NorthSlope #Alaska #arctic #spatialanalysis #spatiotemporal #remediation #drillpad #oilpad #lease #industry #habitat #ecosystem #fieldwork #sampling #geology #engineeringgeology #impact

Frozen No More - A Case Study Of Arctic Permafrost Impacts Of Oil And Gas Withdrawal
--
https://doi.org/10.1038/s41598-024-76292-2 <-- shared paper
--
#GIS #spatial #mapping #remotesening #earthobservation #oil #gas #oilandgas #O&G #energy #extraction #drilling #exploration #subsurface #permafrost #melting #humanimpacts #climatechange #oilextraction #risk #hazard #riskassessment #water #hydrology #sediment #tundra #oilwellpads #NorthSlope #Alaska #arctic #spatialanalysis #spatiotemporal #remediation #drillpad #oilpad #lease #industry #habitat #ecosystem #fieldwork #sampling #geology #engineeringgeology #impact

Frozen No More - A Case Study Of Arctic Permafrost Impacts Of Oil And Gas Withdrawal
--
https://doi.org/10.1038/s41598-024-76292-2 <-- shared paper
--
#GIS #spatial #mapping #remotesening #earthobservation #oil #gas #oilandgas #O&G #energy #extraction #drilling #exploration #subsurface #permafrost #melting #humanimpacts #climatechange #oilextraction #risk #hazard #riskassessment #water #hydrology #sediment #tundra #oilwellpads #NorthSlope #Alaska #arctic #spatialanalysis #spatiotemporal #remediation #drillpad #oilpad #lease #industry #habitat #ecosystem #fieldwork #sampling #geology #engineeringgeology #impact

A Multi-Level, Multi-Scale Comparison Of Lidar- And LANDSAT-Based Habitat Selection Models Of Mexican Spotted Owls In A Post-Fire Landscape
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https://doi.org/10.1016/j.ecoinf.2025.103168 <-- shared paper
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#GIS #spatial #mapping #Habitat #suitability #Megafire #Scaling #Habitatsuitability #selection #model #modeling #framework #Strixoccidentalis #Wildfire #bushfire #remotesening #LIDAR #elevation #ecosystem #LANDSAT #comparasion #mexican #spottedowl #avian #postfire #landscape #vegetation #ecosystem #damage #risk #hazard #earthobservation #scaling #scale #multifactor #homerange #microhabitat #ecology #recovery #spatialanalysis #spatiotemporal #modelperformance #reliability #accuracy #precision #forest #integration #conservation #landscape #fireaffected #spatialdisagreement

A Multi-Level, Multi-Scale Comparison Of Lidar- And LANDSAT-Based Habitat Selection Models Of Mexican Spotted Owls In A Post-Fire Landscape
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https://doi.org/10.1016/j.ecoinf.2025.103168 <-- shared paper
--
#GIS #spatial #mapping #Habitat #suitability #Megafire #Scaling #Habitatsuitability #selection #model #modeling #framework #Strixoccidentalis #Wildfire #bushfire #remotesening #LIDAR #elevation #ecosystem #LANDSAT #comparasion #mexican #spottedowl #avian #postfire #landscape #vegetation #ecosystem #damage #risk #hazard #earthobservation #scaling #scale #multifactor #homerange #microhabitat #ecology #recovery #spatialanalysis #spatiotemporal #modelperformance #reliability #accuracy #precision #forest #integration #conservation #landscape #fireaffected #spatialdisagreement

A Multi-Level, Multi-Scale Comparison Of Lidar- And LANDSAT-Based Habitat Selection Models Of Mexican Spotted Owls In A Post-Fire Landscape
--
https://doi.org/10.1016/j.ecoinf.2025.103168 <-- shared paper
--
#GIS #spatial #mapping #Habitat #suitability #Megafire #Scaling #Habitatsuitability #selection #model #modeling #framework #Strixoccidentalis #Wildfire #bushfire #remotesening #LIDAR #elevation #ecosystem #LANDSAT #comparasion #mexican #spottedowl #avian #postfire #landscape #vegetation #ecosystem #damage #risk #hazard #earthobservation #scaling #scale #multifactor #homerange #microhabitat #ecology #recovery #spatialanalysis #spatiotemporal #modelperformance #reliability #accuracy #precision #forest #integration #conservation #landscape #fireaffected #spatialdisagreement

A Multi-Level, Multi-Scale Comparison Of Lidar- And LANDSAT-Based Habitat Selection Models Of Mexican Spotted Owls In A Post-Fire Landscape
--
https://doi.org/10.1016/j.ecoinf.2025.103168 <-- shared paper
--
#GIS #spatial #mapping #Habitat #suitability #Megafire #Scaling #Habitatsuitability #selection #model #modeling #framework #Strixoccidentalis #Wildfire #bushfire #remotesening #LIDAR #elevation #ecosystem #LANDSAT #comparasion #mexican #spottedowl #avian #postfire #landscape #vegetation #ecosystem #damage #risk #hazard #earthobservation #scaling #scale #multifactor #homerange #microhabitat #ecology #recovery #spatialanalysis #spatiotemporal #modelperformance #reliability #accuracy #precision #forest #integration #conservation #landscape #fireaffected #spatialdisagreement

A Multi-Level, Multi-Scale Comparison Of Lidar- And LANDSAT-Based Habitat Selection Models Of Mexican Spotted Owls In A Post-Fire Landscape
--
https://doi.org/10.1016/j.ecoinf.2025.103168 <-- shared paper
--
#GIS #spatial #mapping #Habitat #suitability #Megafire #Scaling #Habitatsuitability #selection #model #modeling #framework #Strixoccidentalis #Wildfire #bushfire #remotesening #LIDAR #elevation #ecosystem #LANDSAT #comparasion #mexican #spottedowl #avian #postfire #landscape #vegetation #ecosystem #damage #risk #hazard #earthobservation #scaling #scale #multifactor #homerange #microhabitat #ecology #recovery #spatialanalysis #spatiotemporal #modelperformance #reliability #accuracy #precision #forest #integration #conservation #landscape #fireaffected #spatialdisagreement

Artificial Intelligence in Earth Science - A GeoAI Perspective
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https://doi.org/10.1029/2025JH000691 <-- shared paper
--
#GIS #spatial #mapping #GeoAI #earthscience #geology #engineeringgeology #AI #artificialintelligence #risk #hazard #decisionmaking #disasterresponse #hurricane #publichealth #disaster #response #spatialanalysis #model #modeling #bigdata #analysis #productionpipeline #temporal #multidimensional #realtime #forecasting #visualisation #challenges #environmental #remotesensing #earthobservation #usecase #crossdomain #semantic #reasoning #informatics #research #multimodal #generativeAI #earthsystems #reliable #trustworthy