#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

https://www.europesays.com/ie/?p=672272 Satellogic to provide Merlin maritime intelligence exclusively through SynMax platform #EarthObservation #Éire #IE #Ireland #maritime #Satellogic #Science #SN #Space #SynMax

To Predict Tree Death, Scientists Tapped Gamma Rays To Peer Underground
(Airborne radiation sensors could help forecast and prevent drought-driven tree mortality_
--
https://www.science.org/content/article/predict-tree-death-scientists-tapped-gamma-rays-peer-underground <-- shared technical article
--
https://doi.org/10.1029/2026GL122182 <-- shared paper
--
H/T @hannah Richter
“Over an 18-month period starting in 2023, the dense forests of Western Australia [WA] experienced a record-setting drought. Jarrah trees towering 35 metres high died off in patchy brown splotches, turning 400 square kilometres - 3% of the forest - into brittle, fire-prone stands. The event led researchers to wonder whether there was a better way to predict where such die-offs might occur both there and in other forests, a problem that has long been tricky to solve because important factors such as soil depth are hidden underground…
Now, those same researchers have unveiled a surprising new tool for predicting tree mortality: gamma rays [link above.] Resulting from the natural decay of the potassium-40 isotope from granite-rich bedrock, the radiation acts as a proxy for soil depth, which in turn signals how much water a tree can access during drought. The new method could be applied to other highly weathered soils, which cover one-third of Earth’s ice-free land...”
--
"... PLAIN LANGUAGE SUMMARY: During a record-breaking drought and heat event in 2023–2024, forests in southwestern Australia experienced widespread, patchy die-off. While we know that extreme weather triggers these events, it is often a hidden factor, the thickness of soil and the depth to underlying bedrock, that determines which trees live or die. Trees growing in shallow soil over solid rock are highly vulnerable due to limited water storage. Here, [they] show how to map these hidden zones from the air using gamma rays that are naturally emitted by potassium in the ground. Like southwestern Australia, many parts of the world have highly weathered soils where potassium has been washed out of the upper layers of soil. However, [they] showed that higher potassium areas signal that potassium-rich bedrock is closer to the surface and this is sensitive for tens of meters. By comparing gamma ray maps with ground-based geophysical surveys and satellite data, [they] showed that these potassium hotspots accurately predict where forests are most likely to experience die-off during a drought. These types of soils cover about one-third of the Earth's land, so the method provides a powerful new tool for managers to identify and protect vulnerable forests from future, hotter droughts…”
#GIS #spatial #mapping #spatialanalysis #spatiotemporal #Australia #WesternAustralia #WA #forests #vegetation #bush #jarrah #karri #drought #heat #extremedrought #extremeweather #climatechange #water #waterresources #dieoff #soil #weathering #erosion #moisture #nutrients #airborne #gammarays #GRS #granite #gneiss #bedrock #geology #potassium40 #potassium #K #remotesensing #earthobservation #groundwater #interstitial #subsurface #waterstorage #electricalresistivitytomography

To Predict Tree Death, Scientists Tapped Gamma Rays To Peer Underground
(Airborne radiation sensors could help forecast and prevent drought-driven tree mortality_
--
https://www.science.org/content/article/predict-tree-death-scientists-tapped-gamma-rays-peer-underground <-- shared technical article
--
https://doi.org/10.1029/2026GL122182 <-- shared paper
--
H/T @hannah Richter
“Over an 18-month period starting in 2023, the dense forests of Western Australia [WA] experienced a record-setting drought. Jarrah trees towering 35 metres high died off in patchy brown splotches, turning 400 square kilometres - 3% of the forest - into brittle, fire-prone stands. The event led researchers to wonder whether there was a better way to predict where such die-offs might occur both there and in other forests, a problem that has long been tricky to solve because important factors such as soil depth are hidden underground…
Now, those same researchers have unveiled a surprising new tool for predicting tree mortality: gamma rays [link above.] Resulting from the natural decay of the potassium-40 isotope from granite-rich bedrock, the radiation acts as a proxy for soil depth, which in turn signals how much water a tree can access during drought. The new method could be applied to other highly weathered soils, which cover one-third of Earth’s ice-free land...”
--
"... PLAIN LANGUAGE SUMMARY: During a record-breaking drought and heat event in 2023–2024, forests in southwestern Australia experienced widespread, patchy die-off. While we know that extreme weather triggers these events, it is often a hidden factor, the thickness of soil and the depth to underlying bedrock, that determines which trees live or die. Trees growing in shallow soil over solid rock are highly vulnerable due to limited water storage. Here, [they] show how to map these hidden zones from the air using gamma rays that are naturally emitted by potassium in the ground. Like southwestern Australia, many parts of the world have highly weathered soils where potassium has been washed out of the upper layers of soil. However, [they] showed that higher potassium areas signal that potassium-rich bedrock is closer to the surface and this is sensitive for tens of meters. By comparing gamma ray maps with ground-based geophysical surveys and satellite data, [they] showed that these potassium hotspots accurately predict where forests are most likely to experience die-off during a drought. These types of soils cover about one-third of the Earth's land, so the method provides a powerful new tool for managers to identify and protect vulnerable forests from future, hotter droughts…”
#GIS #spatial #mapping #spatialanalysis #spatiotemporal #Australia #WesternAustralia #WA #forests #vegetation #bush #jarrah #karri #drought #heat #extremedrought #extremeweather #climatechange #water #waterresources #dieoff #soil #weathering #erosion #moisture #nutrients #airborne #gammarays #GRS #granite #gneiss #bedrock #geology #potassium40 #potassium #K #remotesensing #earthobservation #groundwater #interstitial #subsurface #waterstorage #electricalresistivitytomography

To Predict Tree Death, Scientists Tapped Gamma Rays To Peer Underground
(Airborne radiation sensors could help forecast and prevent drought-driven tree mortality_
--
https://www.science.org/content/article/predict-tree-death-scientists-tapped-gamma-rays-peer-underground <-- shared technical article
--
https://doi.org/10.1029/2026GL122182 <-- shared paper
--
H/T @hannah Richter
“Over an 18-month period starting in 2023, the dense forests of Western Australia [WA] experienced a record-setting drought. Jarrah trees towering 35 metres high died off in patchy brown splotches, turning 400 square kilometres - 3% of the forest - into brittle, fire-prone stands. The event led researchers to wonder whether there was a better way to predict where such die-offs might occur both there and in other forests, a problem that has long been tricky to solve because important factors such as soil depth are hidden underground…
Now, those same researchers have unveiled a surprising new tool for predicting tree mortality: gamma rays [link above.] Resulting from the natural decay of the potassium-40 isotope from granite-rich bedrock, the radiation acts as a proxy for soil depth, which in turn signals how much water a tree can access during drought. The new method could be applied to other highly weathered soils, which cover one-third of Earth’s ice-free land...”
--
"... PLAIN LANGUAGE SUMMARY: During a record-breaking drought and heat event in 2023–2024, forests in southwestern Australia experienced widespread, patchy die-off. While we know that extreme weather triggers these events, it is often a hidden factor, the thickness of soil and the depth to underlying bedrock, that determines which trees live or die. Trees growing in shallow soil over solid rock are highly vulnerable due to limited water storage. Here, [they] show how to map these hidden zones from the air using gamma rays that are naturally emitted by potassium in the ground. Like southwestern Australia, many parts of the world have highly weathered soils where potassium has been washed out of the upper layers of soil. However, [they] showed that higher potassium areas signal that potassium-rich bedrock is closer to the surface and this is sensitive for tens of meters. By comparing gamma ray maps with ground-based geophysical surveys and satellite data, [they] showed that these potassium hotspots accurately predict where forests are most likely to experience die-off during a drought. These types of soils cover about one-third of the Earth's land, so the method provides a powerful new tool for managers to identify and protect vulnerable forests from future, hotter droughts…”
#GIS #spatial #mapping #spatialanalysis #spatiotemporal #Australia #WesternAustralia #WA #forests #vegetation #bush #jarrah #karri #drought #heat #extremedrought #extremeweather #climatechange #water #waterresources #dieoff #soil #weathering #erosion #moisture #nutrients #airborne #gammarays #GRS #granite #gneiss #bedrock #geology #potassium40 #potassium #K #remotesensing #earthobservation #groundwater #interstitial #subsurface #waterstorage #electricalresistivitytomography

To Predict Tree Death, Scientists Tapped Gamma Rays To Peer Underground
(Airborne radiation sensors could help forecast and prevent drought-driven tree mortality_
--
https://www.science.org/content/article/predict-tree-death-scientists-tapped-gamma-rays-peer-underground <-- shared technical article
--
https://doi.org/10.1029/2026GL122182 <-- shared paper
--
H/T @hannah Richter
“Over an 18-month period starting in 2023, the dense forests of Western Australia [WA] experienced a record-setting drought. Jarrah trees towering 35 metres high died off in patchy brown splotches, turning 400 square kilometres - 3% of the forest - into brittle, fire-prone stands. The event led researchers to wonder whether there was a better way to predict where such die-offs might occur both there and in other forests, a problem that has long been tricky to solve because important factors such as soil depth are hidden underground…
Now, those same researchers have unveiled a surprising new tool for predicting tree mortality: gamma rays [link above.] Resulting from the natural decay of the potassium-40 isotope from granite-rich bedrock, the radiation acts as a proxy for soil depth, which in turn signals how much water a tree can access during drought. The new method could be applied to other highly weathered soils, which cover one-third of Earth’s ice-free land...”
--
"... PLAIN LANGUAGE SUMMARY: During a record-breaking drought and heat event in 2023–2024, forests in southwestern Australia experienced widespread, patchy die-off. While we know that extreme weather triggers these events, it is often a hidden factor, the thickness of soil and the depth to underlying bedrock, that determines which trees live or die. Trees growing in shallow soil over solid rock are highly vulnerable due to limited water storage. Here, [they] show how to map these hidden zones from the air using gamma rays that are naturally emitted by potassium in the ground. Like southwestern Australia, many parts of the world have highly weathered soils where potassium has been washed out of the upper layers of soil. However, [they] showed that higher potassium areas signal that potassium-rich bedrock is closer to the surface and this is sensitive for tens of meters. By comparing gamma ray maps with ground-based geophysical surveys and satellite data, [they] showed that these potassium hotspots accurately predict where forests are most likely to experience die-off during a drought. These types of soils cover about one-third of the Earth's land, so the method provides a powerful new tool for managers to identify and protect vulnerable forests from future, hotter droughts…”
#GIS #spatial #mapping #spatialanalysis #spatiotemporal #Australia #WesternAustralia #WA #forests #vegetation #bush #jarrah #karri #drought #heat #extremedrought #extremeweather #climatechange #water #waterresources #dieoff #soil #weathering #erosion #moisture #nutrients #airborne #gammarays #GRS #granite #gneiss #bedrock #geology #potassium40 #potassium #K #remotesensing #earthobservation #groundwater #interstitial #subsurface #waterstorage #electricalresistivitytomography

To Predict Tree Death, Scientists Tapped Gamma Rays To Peer Underground
(Airborne radiation sensors could help forecast and prevent drought-driven tree mortality_
--
https://www.science.org/content/article/predict-tree-death-scientists-tapped-gamma-rays-peer-underground <-- shared technical article
--
https://doi.org/10.1029/2026GL122182 <-- shared paper
--
H/T @hannah Richter
“Over an 18-month period starting in 2023, the dense forests of Western Australia [WA] experienced a record-setting drought. Jarrah trees towering 35 metres high died off in patchy brown splotches, turning 400 square kilometres - 3% of the forest - into brittle, fire-prone stands. The event led researchers to wonder whether there was a better way to predict where such die-offs might occur both there and in other forests, a problem that has long been tricky to solve because important factors such as soil depth are hidden underground…
Now, those same researchers have unveiled a surprising new tool for predicting tree mortality: gamma rays [link above.] Resulting from the natural decay of the potassium-40 isotope from granite-rich bedrock, the radiation acts as a proxy for soil depth, which in turn signals how much water a tree can access during drought. The new method could be applied to other highly weathered soils, which cover one-third of Earth’s ice-free land...”
--
"... PLAIN LANGUAGE SUMMARY: During a record-breaking drought and heat event in 2023–2024, forests in southwestern Australia experienced widespread, patchy die-off. While we know that extreme weather triggers these events, it is often a hidden factor, the thickness of soil and the depth to underlying bedrock, that determines which trees live or die. Trees growing in shallow soil over solid rock are highly vulnerable due to limited water storage. Here, [they] show how to map these hidden zones from the air using gamma rays that are naturally emitted by potassium in the ground. Like southwestern Australia, many parts of the world have highly weathered soils where potassium has been washed out of the upper layers of soil. However, [they] showed that higher potassium areas signal that potassium-rich bedrock is closer to the surface and this is sensitive for tens of meters. By comparing gamma ray maps with ground-based geophysical surveys and satellite data, [they] showed that these potassium hotspots accurately predict where forests are most likely to experience die-off during a drought. These types of soils cover about one-third of the Earth's land, so the method provides a powerful new tool for managers to identify and protect vulnerable forests from future, hotter droughts…”
#GIS #spatial #mapping #spatialanalysis #spatiotemporal #Australia #WesternAustralia #WA #forests #vegetation #bush #jarrah #karri #drought #heat #extremedrought #extremeweather #climatechange #water #waterresources #dieoff #soil #weathering #erosion #moisture #nutrients #airborne #gammarays #GRS #granite #gneiss #bedrock #geology #potassium40 #potassium #K #remotesensing #earthobservation #groundwater #interstitial #subsurface #waterstorage #electricalresistivitytomography

Nepal glacier collapse and flood (after)

#china #earthexplorer #earthfromspace #earthobservation #esa #europeanspaceagency #glaciercollapse #landsat9

▶️ 1 new picture from ESA (Flickr) https://commons.wikimedia.org/wiki/File:Nepal_glacier_collapse_and_flood_%28after%29_%2855504451912%29.jpg

Nepal glacier collapse and flood (after)

#china #earthexplorer #earthfromspace #earthobservation #esa #europeanspaceagency #glaciercollapse #landsat9

▶️ 1 new picture from ESA (Flickr) https://commons.wikimedia.org/wiki/File:Nepal_glacier_collapse_and_flood_%28after%29_%2855504451912%29.jpg

Nepal glacier collapse and flood (after)

#china #earthexplorer #earthfromspace #earthobservation #esa #europeanspaceagency #glaciercollapse #landsat9

▶️ 1 new picture from ESA (Flickr) https://commons.wikimedia.org/wiki/File:Nepal_glacier_collapse_and_flood_%28after%29_%2855504451912%29.jpg

Nepal glacier collapse and flood (after)

#china #earthexplorer #earthfromspace #earthobservation #esa #europeanspaceagency #glaciercollapse #landsat9

▶️ 1 new picture from ESA (Flickr) https://commons.wikimedia.org/wiki/File:Nepal_glacier_collapse_and_flood_%28after%29_%2855504451912%29.jpg

ISRO begins the 27-hour countdown for GSLV-F17/EOS-05, set to launch India’s first imaging satellite from geosynchronous orbit https://english.mathrubhumi.com/technology/science/isro-gslv-f17-eos-05-launch-countdown-earth-observation-satellite-cxb4aor8?utm_source=dlvr.it&utm_medium=mastodon #ISRO #GSLVF17 #EOS05 #ISROLaunch #EarthObservation

ISRO begins the 27-hour countdown for GSLV-F17/EOS-05, set to launch India’s first imaging satellite from geosynchronous orbit https://english.mathrubhumi.com/technology/science/isro-gslv-f17-eos-05-launch-countdown-earth-observation-satellite-cxb4aor8?utm_source=dlvr.it&utm_medium=mastodon #ISRO #GSLVF17 #EOS05 #ISROLaunch #EarthObservation

ISRO begins the 27-hour countdown for GSLV-F17/EOS-05, set to launch India’s first imaging satellite from geosynchronous orbit https://english.mathrubhumi.com/technology/science/isro-gslv-f17-eos-05-launch-countdown-earth-observation-satellite-cxb4aor8?utm_source=dlvr.it&utm_medium=mastodon #ISRO #GSLVF17 #EOS05 #ISROLaunch #EarthObservation

ISRO begins the 27-hour countdown for GSLV-F17/EOS-05, set to launch India’s first imaging satellite from geosynchronous orbit https://english.mathrubhumi.com/technology/science/isro-gslv-f17-eos-05-launch-countdown-earth-observation-satellite-cxb4aor8?utm_source=dlvr.it&utm_medium=mastodon #ISRO #GSLVF17 #EOS05 #ISROLaunch #EarthObservation

On-Demand Global Landsat Evapotranspiration Product - Development, Evaluation, And Dissemination
--
https://doi.org/10.1016/j.rse.2026.115633 <-- shared paper
--
https://espa.cr.usgs.gov <-- shared (open data) USGS EROS Science Processing Architecture (ESPA) platform
--
https://etdata.org/ <-- OpenET SSEBop platform implementation (water management)
--
https://www.usgs.gov/landsat-missions/landsat-collection-2-provisional-actual-evapotranspiration-science-product <-- shared USGS Landsat Collection 2 Provisional Actual Evapotranspiration Science Product
--
H/T @mac Friedrichs | Remote Sensing Scientist, KBR | USGS EROS
“This paper summarizes new achievements in developing and distributing the Global Landsat Level-3 Evapotranspiration (ET) product. It is freely available through the USGS EROS Science Processing Architecture (ESPA) platform (2nd link above). 🛰️ …
Since the product launch in June 2020, there have been over 1.2 million Landsat-based ET orders around the world. This indicates increasing awareness and application of the ET data to help understand and manage the relationships among food, energy, and water resources. 🌽💧 …
It features the ESPA workflow and evaluation of the upgraded SSEBop model using a variety of observational datasets and hydrologic regions, and examination against OpenET SSEBop platform implementation (3rd link above.)…”
--
“HIGHLIGHTS
• ESPA platform allows access to on-demand, global, Landsat-based, ET products.
• SSEBop model has been used to create ET data since 1982 through ESPA.
• A quick estimation of field-scale crop consumptive water use can be achieved.
• Numerous orders reflect worldwide extensive interest and utilization of the data.
• Method, workflow, and performance of the actual ET data are presented in the study..."
#EROSScienceProcessingArchitecture #climate #global #Evapotranspiration #ET #GIS #spatial #mapping #remotesensing #earthobservation #water #hydrology #opendata #Landsat #OpenET #SSEBop #WaterManagement #Agriculture #USGS #EROS #datadelivery #food #foodsecurity #energy #water #watersecurity #model #modeling #ESPA #farming #cropland #wateruse #waterresources #workflow
@USGS @EROS

On-Demand Global Landsat Evapotranspiration Product - Development, Evaluation, And Dissemination
--
https://doi.org/10.1016/j.rse.2026.115633 <-- shared paper
--
https://espa.cr.usgs.gov <-- shared (open data) USGS EROS Science Processing Architecture (ESPA) platform
--
https://etdata.org/ <-- OpenET SSEBop platform implementation (water management)
--
https://www.usgs.gov/landsat-missions/landsat-collection-2-provisional-actual-evapotranspiration-science-product <-- shared USGS Landsat Collection 2 Provisional Actual Evapotranspiration Science Product
--
H/T @mac Friedrichs | Remote Sensing Scientist, KBR | USGS EROS
“This paper summarizes new achievements in developing and distributing the Global Landsat Level-3 Evapotranspiration (ET) product. It is freely available through the USGS EROS Science Processing Architecture (ESPA) platform (2nd link above). 🛰️ …
Since the product launch in June 2020, there have been over 1.2 million Landsat-based ET orders around the world. This indicates increasing awareness and application of the ET data to help understand and manage the relationships among food, energy, and water resources. 🌽💧 …
It features the ESPA workflow and evaluation of the upgraded SSEBop model using a variety of observational datasets and hydrologic regions, and examination against OpenET SSEBop platform implementation (3rd link above.)…”
--
“HIGHLIGHTS
• ESPA platform allows access to on-demand, global, Landsat-based, ET products.
• SSEBop model has been used to create ET data since 1982 through ESPA.
• A quick estimation of field-scale crop consumptive water use can be achieved.
• Numerous orders reflect worldwide extensive interest and utilization of the data.
• Method, workflow, and performance of the actual ET data are presented in the study..."
#EROSScienceProcessingArchitecture #climate #global #Evapotranspiration #ET #GIS #spatial #mapping #remotesensing #earthobservation #water #hydrology #opendata #Landsat #OpenET #SSEBop #WaterManagement #Agriculture #USGS #EROS #datadelivery #food #foodsecurity #energy #water #watersecurity #model #modeling #ESPA #farming #cropland #wateruse #waterresources #workflow
@USGS @EROS

On-Demand Global Landsat Evapotranspiration Product - Development, Evaluation, And Dissemination
--
https://doi.org/10.1016/j.rse.2026.115633 <-- shared paper
--
https://espa.cr.usgs.gov <-- shared (open data) USGS EROS Science Processing Architecture (ESPA) platform
--
https://etdata.org/ <-- OpenET SSEBop platform implementation (water management)
--
https://www.usgs.gov/landsat-missions/landsat-collection-2-provisional-actual-evapotranspiration-science-product <-- shared USGS Landsat Collection 2 Provisional Actual Evapotranspiration Science Product
--
H/T @mac Friedrichs | Remote Sensing Scientist, KBR | USGS EROS
“This paper summarizes new achievements in developing and distributing the Global Landsat Level-3 Evapotranspiration (ET) product. It is freely available through the USGS EROS Science Processing Architecture (ESPA) platform (2nd link above). 🛰️ …
Since the product launch in June 2020, there have been over 1.2 million Landsat-based ET orders around the world. This indicates increasing awareness and application of the ET data to help understand and manage the relationships among food, energy, and water resources. 🌽💧 …
It features the ESPA workflow and evaluation of the upgraded SSEBop model using a variety of observational datasets and hydrologic regions, and examination against OpenET SSEBop platform implementation (3rd link above.)…”
--
“HIGHLIGHTS
• ESPA platform allows access to on-demand, global, Landsat-based, ET products.
• SSEBop model has been used to create ET data since 1982 through ESPA.
• A quick estimation of field-scale crop consumptive water use can be achieved.
• Numerous orders reflect worldwide extensive interest and utilization of the data.
• Method, workflow, and performance of the actual ET data are presented in the study..."
#EROSScienceProcessingArchitecture #climate #global #Evapotranspiration #ET #GIS #spatial #mapping #remotesensing #earthobservation #water #hydrology #opendata #Landsat #OpenET #SSEBop #WaterManagement #Agriculture #USGS #EROS #datadelivery #food #foodsecurity #energy #water #watersecurity #model #modeling #ESPA #farming #cropland #wateruse #waterresources #workflow
@USGS @EROS

On-Demand Global Landsat Evapotranspiration Product - Development, Evaluation, And Dissemination
--
https://doi.org/10.1016/j.rse.2026.115633 <-- shared paper
--
https://espa.cr.usgs.gov <-- shared (open data) USGS EROS Science Processing Architecture (ESPA) platform
--
https://etdata.org/ <-- OpenET SSEBop platform implementation (water management)
--
https://www.usgs.gov/landsat-missions/landsat-collection-2-provisional-actual-evapotranspiration-science-product <-- shared USGS Landsat Collection 2 Provisional Actual Evapotranspiration Science Product
--
H/T @mac Friedrichs | Remote Sensing Scientist, KBR | USGS EROS
“This paper summarizes new achievements in developing and distributing the Global Landsat Level-3 Evapotranspiration (ET) product. It is freely available through the USGS EROS Science Processing Architecture (ESPA) platform (2nd link above). 🛰️ …
Since the product launch in June 2020, there have been over 1.2 million Landsat-based ET orders around the world. This indicates increasing awareness and application of the ET data to help understand and manage the relationships among food, energy, and water resources. 🌽💧 …
It features the ESPA workflow and evaluation of the upgraded SSEBop model using a variety of observational datasets and hydrologic regions, and examination against OpenET SSEBop platform implementation (3rd link above.)…”
--
“HIGHLIGHTS
• ESPA platform allows access to on-demand, global, Landsat-based, ET products.
• SSEBop model has been used to create ET data since 1982 through ESPA.
• A quick estimation of field-scale crop consumptive water use can be achieved.
• Numerous orders reflect worldwide extensive interest and utilization of the data.
• Method, workflow, and performance of the actual ET data are presented in the study..."
#EROSScienceProcessingArchitecture #climate #global #Evapotranspiration #ET #GIS #spatial #mapping #remotesensing #earthobservation #water #hydrology #opendata #Landsat #OpenET #SSEBop #WaterManagement #Agriculture #USGS #EROS #datadelivery #food #foodsecurity #energy #water #watersecurity #model #modeling #ESPA #farming #cropland #wateruse #waterresources #workflow
@USGS @EROS

On-Demand Global Landsat Evapotranspiration Product - Development, Evaluation, And Dissemination
--
https://doi.org/10.1016/j.rse.2026.115633 <-- shared paper
--
https://espa.cr.usgs.gov <-- shared (open data) USGS EROS Science Processing Architecture (ESPA) platform
--
https://etdata.org/ <-- OpenET SSEBop platform implementation (water management)
--
https://www.usgs.gov/landsat-missions/landsat-collection-2-provisional-actual-evapotranspiration-science-product <-- shared USGS Landsat Collection 2 Provisional Actual Evapotranspiration Science Product
--
H/T @mac Friedrichs | Remote Sensing Scientist, KBR | USGS EROS
“This paper summarizes new achievements in developing and distributing the Global Landsat Level-3 Evapotranspiration (ET) product. It is freely available through the USGS EROS Science Processing Architecture (ESPA) platform (2nd link above). 🛰️ …
Since the product launch in June 2020, there have been over 1.2 million Landsat-based ET orders around the world. This indicates increasing awareness and application of the ET data to help understand and manage the relationships among food, energy, and water resources. 🌽💧 …
It features the ESPA workflow and evaluation of the upgraded SSEBop model using a variety of observational datasets and hydrologic regions, and examination against OpenET SSEBop platform implementation (3rd link above.)…”
--
“HIGHLIGHTS
• ESPA platform allows access to on-demand, global, Landsat-based, ET products.
• SSEBop model has been used to create ET data since 1982 through ESPA.
• A quick estimation of field-scale crop consumptive water use can be achieved.
• Numerous orders reflect worldwide extensive interest and utilization of the data.
• Method, workflow, and performance of the actual ET data are presented in the study..."
#EROSScienceProcessingArchitecture #climate #global #Evapotranspiration #ET #GIS #spatial #mapping #remotesensing #earthobservation #water #hydrology #opendata #Landsat #OpenET #SSEBop #WaterManagement #Agriculture #USGS #EROS #datadelivery #food #foodsecurity #energy #water #watersecurity #model #modeling #ESPA #farming #cropland #wateruse #waterresources #workflow
@USGS @EROS

https://www.europesays.com/dk/158224/ Copernicus 25th anniversary in Stockholm #EarthObservation #Stockholm #Sweden #TransportAndUrbanPlanning

Mapping Flood Agents In The Northern Pantanal Wetland Using Multiple Spatio-Temporal GIS And Remote Sensing Techniques
--
https://doi.org/10.1007/s13157-026-02082-3 <-- shared paper
--
H/T @renato Gatto de Morais | Geógrafo | Mestre em Recursos Hídricos | Doutorando em Geografia
“Combining MODIS data, TRMM, river discharge, a digital terrain model, and multinomial logistic regression, [the authors] identified three predominant classes of flood origin: local rainfall, bank overflow, and mixed areas. The model achieved a Nagelkerke Pseudo-R² of 0.63 and a classification accuracy of up to 81.2% (10-fold cross-validation). To the best of [their] knowledge, this is the first explicit approach to mapping flood agents for this wetland, a component that has historically remained unmapped despite its recognized influence on habitats and biodiversity…”
--
“The mapping of functional hydrologic units is crucial for enhancing our understanding of flooding and hydroecological processes in large wetlands. These units are typically defined by flooding frequency, duration, and magnitude, but another important hydrologic characteristic is the origin of flooding, known as the flood agent. This study presents an empirical framework utilizing remote sensing and GIS procedures for modeling flood agents in the northern Pantanal wetland. Eleven spatial data layers were derived from multi-year MODIS flood maps, daily rainfall estimates from the TRMM 3B42 grid, in situ discharge data, the BEST Digital Terrain Model, and a hydrographic network layer. These layers were tested for their predictive power in a multinomial logistic regression mapping model. Model performance metrics, along with qualitative validation of mapping outcomes using in situ flooding measurements, and vegetation and soil data from field test sites, support the plausibility of the proposed mapping scheme. However, they also highlight the challenges of flood agent mapping in large tropical wetlands…”
#GIS #spatial #mapping #MODIS #TRMM #riverdischarge #digitalterrainmodel #multinomiallogisticregression #geostatistics #Pantanal #Cuiaba #Brazil #water #hydrology #spatialanalysis #spatiotemporal #remotesensing #earthobservation #flood #flooding #source #type #floodagent #tropical #wetland #habitat #biodiversity #ecosystem #hydrologicunit #hydroecology #model #modeling #rainfall #precipitation #weather #climate #discharge #network #metrics

Challenges In The Use Of Local Data For Regional Scale Mapping Of C And N Stocks In The Continuous Permafrost Zone At The Yukon Coastal Plain | Heatwave Risks To Tipping Point Of Permafrost
--
https://doi.org/10.5194/soil-12-113-2026 <-- shared paper
--
https://doi.org/10.1038/s41558-026-02603-2 <-- shared paper
--
https://www.theguardian.com/environment/2026/aug/20/tipping-points-heatwaves-wildfires-permafrost-climate-crisis <-- shared media article
--
https://www.cbc.ca/news/canada/north/permafrost-slumps-herschel-island-qikiqtaruk-yukon-9.7168780 <-- shared media article
--
[putting together two different ‘sorts’/focuses of research/reporting, but…]
H/T @gustaf Hugelius | Professor at Stockholm University
--
“Permafrost soils are particularly vulnerable to climate change. To assess and improve estimations of carbon (C) and nitrogen (N) budgets it is necessary to accurately map soil carbon and nitrogen in the permafrost region. In particular, soil organic carbon (SOC) stocks have been predicted and mapped by many studies from local to pan-Arctic scales. Several studies have been carried out at the Canadian Beaufort Sea coast, though no regional maps of terrestrial carbon stocks based on spatial modelling has been conducted yet. This study combines available field data from the Canadian Yukon coastal plain and uses it to map regional SOC and N stocks using the machine learning algorithm random forest and environmental variables based on remote sensing data. [The authors] developed models using the data for the entire region and separate models for the coastal mainland area and Qikiqtaruk Herschel Island. Each model was used to map SOC and N stocks for its respective area. [They] assessed the performance of the different random forest models by using crossvalidation. [They] further assessed model results using the Area of Applicability (AOA) method and the quantile regression forest approach, comparing the results and discussing their implications within the context of both methods. [They] explore[d] local differences in soil properties and how soil data distribution across the region affects the accuracy of the predictions of SOC and N stocks..."
#permafrost #soils #geology #climatechange #temperature #thawing #melting #emissions #CO2 #methane #carbon #nitrogen #GIS #spatial #mapping #Qikiqtaruk #HerschelIsland #Yukon #Canada #soilorganiccarbon #SOC #arctic #cryosphere #BeaufortSea #coast #coastal #machinelearning #model #modeling #remotesensing #earthobservation #carbonstocks #island #mainland #spatialanalysis #scale

Comparing DESIS Hyperspectral and Landsat 10 Simulated Superspectral Data for Crop Type Classification in California’s Central Valley
--
https://doi.org/10.3390/rs18142282 <-- shared paper
--
https://www.usgs.gov/publications/comparing-desis-hyperspectral-and-landsat-10-simulated-superspectral-data-crop-type <-- shared USGs publication page
--
H/T @USGS
“How can we get better at classifying crops from space? 🛰️🌽
Some types of satellite imagery are better at distinguishing crops than others. A USGS study compared two approaches and found one produced more accurate crop maps.
Here's what the researchers found:
• Hyperspectral imagery achieved 86% accuracy, compared to 75% for simulated superspectral imagery.
• Using just 14 carefully selected hyperspectral bands produced nearly the same results as using all 60 DLR Earth Sensing Imaging Spectrometer (DESIS) bands, showing those wavelengths contain much of the information needed to distinguish crop types.
• Using superspectral imagery on the upcoming Landsat 10 mission will allow for routine tracking of crops and enhance finer crop mapping.
• The findings help scientists identify which wavelengths provide the most useful information for crop mapping and future remote sensing applications.
Better crop maps will help governments and scientists track global agriculture, monitor the current crop season, and study agricultural trends…”
--
“HIGHLIGHTS:
• What are the main findings?
- The 14 DESIS hyperspectral narrowbands (10 nm) aligned with the Landsat 10 (formerly Landsat Next) spectral dataset produced similar accuracy results to the full 60-band DESIS hyperspectral dataset for classifying crop types. These 14 DESIS narrowbands resulted in higher accuracy than the 14 simulated Landsat 10 superspectral broadbands.
- When using DESIS narrowbands, Support Vector Machine (SVM) resulted in higher accuracy than Random Forest (RF).
• What are the implications of the main findings?
- A carefully selected set of 14 DESIS hyperspectral narrowbands (10 nm) can achieve classification accuracy comparable to those obtained using all 60 DESIS narrowbands across the 400–1000 nm range. These 14 strategically positioned narrowbands classified crop types with higher classification accuracy than the corresponding 14 Landsat 10 superspectral broadbands within the same spectral range.
- This study underscores the importance of multi-temporal imagery across the full crop-growing season for achieving more detailed and accurate crop type classifications. Such temporal coverage is more feasible with the planned Landsat 10 routine acquisition of broadband imagery than with task-based hyperspectral collections…”
#hyperspectral #superspectral #optimalbands #randomforest #supportvectormachine #agriculture #crops #croptype #classifaction #croplands #California #CentralValley #GIS #spatial #mapping #remotesensing #earthobservation #imagery #DESIS #Landsat #Landsat10 #satellite #spatialanalysis #spatiotemporal #global #AI #machinelearning #model #modeling #SupportVectorMachine #SVM #RandomForest #RF #GoogleEarthEngine
@USGS

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

Impact Of Urbanization Driven Land Use And Land Cover Change On Ecological Environmental Quality In Rupandehi Nepal Assessed Using The Remote Sensing Ecological Index
--
https://doi.org/10.1007/s44288-026-00650-y <-- shared paper
--
https://kathmandupost.com/money/2026/02/18/rupandehi-s-continued-urban-sprawl-comes-at-a-cost-for-agriculture-in-the-periphery <-- shared media article
--
H/T@ Gaurav Parajulim
“[The authors] studied how the ecological quality of Nepal's Rupandehi District has changed over three decades (1993–2023), using satellite imagery and the Remote Sensing Ecological Index (RSEI) to track the health of the landscape year by year and to understand how urbanization-driven land use change has reshaped it.
What [they] found tells a nuanced story: as Butwal and Bhairahawa grew and built-up land expanded, ecological quality shifted in ways that a single number can't capture, some areas recovered, others declined, and the patterns rarely moved in a straight line…”
--
“Rapid urbanization and population growth are major drivers of land use and land cover (LULC) change and can substantially alter ecological environmental quality (EEQ). This study assessed the spatiotemporal dynamics of LULC and their effect on EEQ in Rupandehi District, Nepal, over a 30-year period (1993–2023). Four ecological indicators representing greenness, wetness, dryness, and heat were derived from Landsat imagery in Google Earth Engine (GEE), and LULC was classified using a Support Vector Machine (SVM). The Remote Sensing Ecological Index (RSEI) was then constructed from these indicators using Principal Component Analysis (PCA) in ArcGIS Pro, and its spatial structure was examined using global and local spatial autocorrelation. The mean RSEI followed a non-linear trajectory, rising from 0.59 in 1993 to 0.635 in 2004, declining to 0.55 in 2013, and recovering to 0.67 in 2023, indicating an overall improvement in EEQ with a temporary mid-period decline. Over the same period, built-up areas expanded substantially and agricultural land declined, whereas forest cover fluctuated but showed a slight net increase by 2023, and barren land decreased markedly. Higher EEQ was concentrated in the forested northern hills, while lower values occurred in the urban centers of Butwal and Bhairahawa, closely matching the spatial pattern of LULC change. The results indicate that ecological quality reflects the combined influence of all land cover classes rather than any single class. This study provides a transferable and reproducible workflow for long-term ecological assessment based on openly available Landsat data, with the analysis code shared in a public repository, offering practical guidance for sustainable land management and environmentally responsible urban development...”
#GIS #spatial #mapping #RemoteSensing #GIS #RSEI #EnvironmentalMonitoring #Nepal #Research #GoogleEarthEngine #ArcGIS #EcologicalQuality #spatialautocorrelation #ecology #environment #earthobservation #RemoteSensingEcologicalIndex #landscape #urbanisation #urban #development #landuse #change #spatialanalysis #spatiotemporal

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

The Latest Data Confirms - Forest Fires Are Getting Worse
--
https://www.wri.org/insights/global-trends-forest-fires <-- shared technical article
--
http://alturl.com/efp6m <-- shared (focused) #GlobalNatureWatch web map
--
https://science.nasa.gov/earth/explore/wildfires-and-climate-change/ <-- shared NASA technical article, ‘Wildfires and Climate Change’
--
https://doi.org/10.3389/frsen.2022.825190 <-- shared paper
--
https://doi.org/10.1073/pnas.2505418122 <-- shared paper
--
https://doi.org/10.1088/1748-9326/add606 <-- shared paper
--
https://globalnaturewatch.org/dashboards/global/ <-- shared Global Nature Watch dashboard
--
https://youtu.be/-0-pv1Bqm-U?si=IHcZJNiVphosbeVt <-- shared overview video
--
https://grist.org/wildfires/the-us-has-lost-a-quarter-of-its-forest-cover-to-fire-since-2001/ <-- shared technical article, ‘Fire is responsible for a quarter of US forest loss since 2021’
--
https://www.nytimes.com/2026/04/29/climate/wri-report-forest-loss.html <-- shared media article
--
H/T @ World Resources Institute
[‘topical’ - Europe, North America, indeed globally, more & more…]
“New data shows that forest fires are getting worse, burning more than twice as much tree cover today as they did 20 years ago, largely due to climate change…
The latest data [2nd link above] confirms [that] forest fires are becoming more widespread and destructive around the globe. Updated data from researchers [3rd link above] shows that between 2001 and 2025 forest fires now burn over twice as much tree cover each year as they did two decades ago, and more than three times as much in the tropics.
This increased fire activity has been starkly visible in recent years. Record-setting blazes are becoming the norm, with four of the five worst years for global forest fires occurring since 2021. As fires worsen - including in historically low-risk areas, like rainforests - they are becoming an increasingly prevalent driver of global forest loss…”
#GlobalForestWatch #GlobalNatureWatch #deforestation #fire #wildfire #forest #vegetation #climatechange #risk #hazard #loss #ecosystems #GIS #spatial #mapping #remotesensing #earthobservation #spatialanalysis #spatiotemporal #global #worldwide #forestfire #damage #destruction #fireactivity #forestLOSS
@WRI | @Global Nature Watch

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

Identifying Agricultural Consumptive-Use Patterns To Support Adaptive Water Management In California’s Santa Clara Valley Via Remote Sensing And Machine Learning
--
https://doi.org/10.1371/journal.pwat.0000416 <-- shared paper
--
H/T @Guillaume Wright | Executive Editor, PLOS
“💧 With drought [and high temperatures] gripping many areas of the world right now... [the H/T] wanted to highlight a new paper in PLOS Water this week with a very timely focus on hydroclimatic stresses and what can be done to mitigate this through water management practices when it comes to agriculture.
[The authors] investigate[d] adaptive water management practices in California’s Santa Clara Valley via remote sensing and machine learning techniques. They [found] good evidence for use of customized agricultural water-management plans for irrigation monitoring, conservation planning, and adaptive water management in groundwater-dependent regions such as is found in California…”
#GIS #spatial #mapping #California #SantaClara #SantaClaraValley #custom #watermanagement #practices #waterresources #agriculture #remotesensing #spatialanalysis #machinelearning #earthobservation #AI #planning #wateruse #efficiency #water #hydrology #irrigation #conservation #adaptivewatermanagement #model #modeling #drought #extremeweather #hydroclimate #stress #crop #cropland #evapotranspiration #ET #NDVI #PRISM #precipitation #rainfall #watermanagementplan #groundwater

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

Coupled Hydrological And Public Health Risks From Urban Flooding - Integrated Remote Sensing, Machine Learning, And Hydrodynamic–Ecological Modelling
--
https://doi.org/10.1016/j.jhydrol.2026.135999 <-- shared paper
--
https://youtu.be/VHzYLvSYR7k?si=5oGGPeH6T0dFusfY <-- recent overview video created about the research
--
https://doi.org/10.1016/j.wroa.2025.100396 <-- share (earlier) paper
--
H/T @RAHUL DEOPA | Research Scholar (IIT Roorkee)
“… [U]rban floods are not merely hydraulic events; they also transport sewage, pathogens, and other contaminants across streets and communities, leading to significant public health risks…
How do we quantify microbial contamination in near real time during a flood event, when emergency conditions make field sampling unsafe, sparse, or even impossible?...
[The authors] explored whether Earth observation data, combined with machine learning, could bridge this critical monitoring gap. By combining Landsat-derived water surface temperature, machine learning, a coupled MIKE+ Flood–ECO Lab hydrodynamic–ecological model, and Quantitative Microbial Risk Assessment (QMRA), [they] estimated microbial concentrations (𝘌. 𝘤𝘰𝘭𝘪), simulated their fate and transport during floods, and quantified the associated human health risks.
The takeaway: predicting flood risk isn't just about where the water goes; it's about what it's carrying and who it puts in harm's way. Earth observation and machine learning can help close that gap when it matters most, during the emergency, not weeks after…”
#publichealth #risk #hazard #watersecurity #Floodrisk #Humanhealthrisk #Urbanflooding #Hydrodynamicmodelling #waterquality #model #modeling #SupportVectorRegression #flood #flooding #urban #city #sewage #pathogens #contaminant #disease #streets #community #quantification #remotesensing #GIS #spatial #mapping #earthobservation #spatialanalysis #water #hydrology #climatechange #extremeweather #spatiotemporal #AI #machineleraning #fateandtransport #hydrodynamic #microbial #rainfall #drainage #streamflow #topography #hydrogeomorphology #Delhi #India #floodplain

A Scale-Invariance-Based Algorithm Application For Land Surface Temperature Downscaling In Denmark
--
https://doi.org/10.3390/rs18132263 <-- shared paper
--
https://zenodo.org/records/20863040 <-- shared open data for downscaled LST dataset for Copenhagen
--
H/T @CLIM4cities
#urbanclimate #downscaling #landsurfacetemperature #LST #AI #machinelearning #scaleinvariance #residualcorrection #Sentinel #Landsat #satellite #remotesensing #earthobservation #CLIM4cities #UrbanClimate #ClimateServices #MachineLearning #ClimateAdaptation #heatwave #temperature #ontheground #Copenhagen #Denmark #impervioussurface #asphalt #roof #concrete #albedo #heatabsorption #mitigation #urban #urbancentre #treecover #vegetation #urbanheatisland #planning #design #hotspots #monitoring #spatialanalysis #spatiotemporal #model #modeling #usecase #operational #climatechange #extremeweather #evidencebased #adapation #sustainability #urbanplanning #climateresilience #EssentialClimateVariable #ECV
@+ATLANTIC | @Danish Meteorological Institute | @ESA Φ-lab Collaborative Innovation Network | @CLIM4cities

Optical, Radar, And Hybrid Indices To Detect Farming Practices In Europe
--
https://doi.org/10.1016/j.rse.2026.115553 <-- shared paper
--
“HIGHLIGHTS:
• [they] compare[d] Sentinel-1 and Sentinel-2 time series to detect farming practices.
• HyBRIS index is introduced, temporally weighting BSI and VH/VV into a daily index.
• Time-series minima and maxima are used to predict sowing, harvest, and tillage.
• Validation is performed across several years, crop types, and European locations.
• Phenology detection is improved compared to HRL-Cropland.
ABSTRACT: Arable farming practices dictate both crop cycles and soil dynamics, and are central to agriculture's environmental impact and its mitigation. Sowing and harvesting mark the beginning and end of the growing season, while tillage modifies soil structure during the dormant period. Although well-established methods exist for delineating the growing season using phenology and optical data, the detection of farming practices, particularly tillage, remains underexplored. This study investigates the strengths of radar and optical data to retrieve sowing, harvest, and tillage dates at the field level, and proposes a novel Hybrid Bare Soil Radar Index (HyBRIS). Based on Sentinel-1 and Sentinel-2, HyBRIS merges optical and radar data into a single index using a temporally weighted mean. Local minima and maxima of the time series are used to detect farming practices across European sites. Validation is carried out against a reference dataset comprising 238 fields in 11 EU countries, including 462 sowing, 374 harvest, and 388 tillage events covering more than 40 crop types over 8 years. Compared to the Copernicus High Resolution Layer Croplands product (HRL-Cropland), the proposed method based on HyBRIS time series improved sowing and harvest dates detection (MAE 26 and 23 days, respectively). Additionally, this method enabled tillage dates estimation during dormant periods (MAE = 28 days), but tended to overestimate the number of tillage events (producer's accuracy = 97%, user's accuracy = 70%). Incorporating soil moisture data is advised for reducing false positives. The results highlight the potential of optical, radar, and hybrid indices for monitoring agricultural management and supporting environmental stewardship…”
#Sowing #Harvest #tillage #tillagedetection #cropland #CroplandManagement #remotesensing #earthobservation #sentinel #Copernicus #cropland #satellite #optical #radar #sensor #landuse #landcover #landsurface #phenology #agricultural #monitoring #GIS #spatial #mapping #spatialanalysis #spatiotemporal #arable #farming #agriculture #soil #substrate #environment #sustainability #environmentalstewardship #growingseason #Europe #region #model #modeling

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

☀️ Good morning from #FOSS4GE2026 !

A new day has started in Timișoara, with sessions on ☁️ Cloud GIS , #QGIS 🧭, #MapLibre 🗺️, #GeoServer 🛠️, 🛰️ Earth Observation, 🤖 AI, 🌆Digital Twins, and much more.

We look forward to inspiring discussions, live demonstrations, and interesting conversations with the open geospatial community. See you around! 🌍

#OpenSource #Geospatial #GIS #EarthObservation #digitaltwins

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.)
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https://www.geoweeknews.com/news/conservation-at-the-jane-goodall-institute <-- shared technical article
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https://www.iceye.com/blog/government/solutions/how-the-jane-goodall-institute-uses-iceye-sar-to-protect-ecosystems <-- shared technical article
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[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

🚀 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 🌍🛰️