#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

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

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

🚀 Thinking about building Landsat‑10 in your garage?
Better hurry — NASA’s RFP is out and the clock’s ticking. Early delivery even gets you a bonus.
Details: https://www.usgs.gov/landsat-missions/news/nasa-releases-landsat-10-spacecraft-request-proposal
#EarthObservation #Landsat

Track #algal_blooms on six popular #Alberta #lakes with this satellite based tool https://algalbloomtracker.ca/
Behind the scenes is #Sentinel2 and an algorithm trained on several years of #CHLA lake samples #earthobservation #cyanoHABs

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

Enhancements To The USGS Landsat Level 2 Surface Temperature And Emissivity Product For Collection3 Reprocessing
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https://doi.org/10.1016/j.rse.2026.115563 <-- shared paper
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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
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https://doi.org/10.1371/journal.pwat.0000416 <-- shared paper
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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

Coupled Hydrological And Public Health Risks From Urban Flooding - Integrated Remote Sensing, Machine Learning, And Hydrodynamic–Ecological Modelling
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https://doi.org/10.1016/j.jhydrol.2026.135999 <-- shared paper
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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
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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

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/

Global Performance of #RemoteSensing Based and Reanalysis-Driven Models to Estimate Open Water Evaporation
--
https://doi.org/10.1029/2025WR042363
--
“ABSTRACT: Evaporation plays an essential role in the water cycle, influencing local and regional climates while directly impacting water availability in lakes. However, directly measuring evaporation over water bodies remains challenging due to the high costs of installing and maintaining the required in situ instrumentation. Although several remote sensing algorithms have been providing evaporation estimates, the lack of a global validation hinders our understanding of their relative uncertainties and performances across different regions. Here, [they] analyze[d] the performance of a suite of models that leverage satellite data and meteorological reanalysis to estimate evaporation over lakes worldwide. [They] compare[d] three remote sensing-based models, one reanalysis-driven model and one ensemble approach, using in situ observations from 27 lakes representing a diverse range of geographic and climatic regions. [Their] results demonstrate that, overall, the ensemble outperformed any individual model in terms of accuracy, with a RMSE and a bias of 1.3 and 0.3 mm/day, respectively. These findings highlight the benefits of using an ensemble approach to estimate open water evaporation with satellite-based models at the global scale, leveraging the unique strengths of each model. For the individual models, differences in the representation of heat storage changes and advection effects led to lower values of RMSE and bias, depending on the location and depth of the lakes. This study sets the path for future improvement of open water evaporation algorithms globally, while remote sensing techniques are proven satisfactory to monitoring of water loss in lakes globally, an essential step toward effective large-scale water resources management.
PLAIN LANGUAGE SUMMARY: Water loss through evaporation in lakes and reservoirs directly affects water availability, which highlights the need to monitor these losses. However, measuring evaporation in situ is challenging and expensive. An alternative is to estimate evaporation using remote-sensing models and compare these estimates with in-situ data to verify their accuracy. Here, [they] evaluated four models and their ensemble (the models' mean value) using measurements from 27 lakes and reservoirs worldwide. [They] found that the ensemble presented higher accuracy and consistency than any individual model because it benefits from the strengths of each model. This approach can guide future improvements in estimating open-water evaporation, which is essential for large-scale water-resource management…”
#global #mapping #earthobservation #GIS #spatial #spatialanalysis #spatiotemporal #model #modeling #water #hydrology #surfacewater #waterbody #lake #reservoir #evaporation #evapotranspiration #watercycle #weather #meteorology #usecase #waterresources #watermanagement #waterloss #regional #estimate #policy #planning #instrumentation #comparasion

Mapping Multifunctionality In Remote Patagonian Forest Landscapes Reveals High-Value Ecosystems Beyond Protected Areas
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https://doi.org/10.1038/s43247-026-03515-x <-- shared paper
--
H/T @Peter Potapov | Researcher at the World Resources Institute (WRI)
“This paper is] a strong example of multifunctionality analysis applied to conservation planning. The study mapped six ecosystem functions, including carbon storage, nutrient availability, water regulation, erosion control, habitat quality, and ecological connectivity. [The author] combined satellite data, field soil sampling, and spatial modeling for this comprehensive analysis.
Two findings stand out.
1. Old-growth forests had the highest multifunctionality index of any land cover type.
2. 78.5% of the top multifunctionality hotspots fall outside the region's protected areas, even though PAs already cover more than 54% of the territory.
Together, these results make a clear case for expanding conservation of the remaining Intact Forest Landscapes and primary forests in Patagonia and elsewhere…”
--
“Remote forest landscapes provide critical references for understanding ecosystem functions (EFs) under low anthropogenic pressure, yet their capacity to sustain multiple EFs simultaneously remains poorly understood. [They] assessed landscape multifunctionality in western Patagonia by integrating satellite indicators, field data, and spatial modeling. Six EFs (carbon storage, nutrient availability, water regulation, erosion control, habitat quality, and ecological connectivity) were mapped, and their spatial relationships and hotspot distribution within and outside protected areas (PAs) were analyzed. Old-growth and secondary forests showed the highest functional performance. Strong synergies (ρ ≥ 0.6) between carbon storage and nutrient availability covered >50% of the landscape, whereas strong trade-offs (ρ ≤ –0.6) were spatially limited ( < 6%). Notably, 78% of multifunctionality hotspots occurred outside PAs, indicating that high-functional-value areas extend beyond formal conservation boundaries. These findings reveal spatial mismatches between multifunctionality and protection status and provide a replicable framework for integrating multifunctionality into conservation planning under global change…”
#Patagonia #chile #aysen #coyhaique #landcover #mapping #spatial #spatialpatterns #spatiotemporal #spatialanalysis #forest #vegetation #oldgrowth #secondgrowth #shrubland #grassland #steppe #ecosystem #habitat #nutrients #water #hydrology #erosion #multifunctionality #multifunctionalityanalysis #protectedareas #landuse #conservationplanning #conservation #ecology #carbonstorage #nutrientavailability #waterregulation #erosioncontrol #habitatquality #ecologicalconnectivity #remotesensing #satellite #earthobservation #modeling

GMIA-NEXT - Next-Generation Global Map of Irrigated Areas |
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https://doi.org/10.21203/rs.3.rs-10085674/v1 <-- shared paper
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https://zenodo.org/records/17627111 <-- shared open data
--
H/T @kyle Davis
“Irrigation plays a critical role in global food production and climate adaptation and exercises profound influence over humanity's water use. Yet despite its critical importance, there is a persistent lack of understanding of fine-scale irrigation patterns across the planet, knowledge which is essential for informing global food security and sustainability targets. Utilizing either statistical downscaling or remote sensing approaches, existing global irrigation datasets are constrained by coarse spatial resolutions, a lack of timeliness, or varying robustness and reliability. To address this gap, here [they] integrate[d] multi-source Earth observation and environmental datasets and use[d] machine learning to develop a medium-resolution (30 metre) global irrigated area dataset for the 2023/24 growing season. Within existing cropland extent, we leverage a newly compiled set of georeferenced irrigated (N=230,683) and non-irrigated (N=153,194) ground-truth points and integrate seasonal vegetation metrics derived from Landsat 8/9 imagery with agroecological-zone information and hydroclimatic and topographic variables. [They] subsequently develop and evaluate two machine-learning frameworks, a continental Agro-Ecological Zone (AEZ) tile-based framework and a continental-scale framework, and apply the best-performing approach for each continent. Evaluation using held-out test samples yielded a global accuracy of 80.5 ± 2.1%. The resulting maps were also validated against independent global and national irrigation datasets and statistics, demonstrating broad agreement in the spatial distribution of irrigated areas. This approach is robust and reliable because it is built on a harmonized global ground-truth database, incorporates multiple predictors, and is rigorously validated using independent datasets. All code, ground-truth, and data products are freely and publicly available [link above] and can serve as a robust, scale-neutral, and fully reproducible framework for fine-resolution irrigation mapping. These advances provide the critical and long-needed foundation for near-real-time monitoring and early warning systems, and fine-scale land and water resource management…”
#IrrigatedAreas #Mapping #GIS #spatial #mapping #spatialanalysis #spatiotemporal #global #irrigation #water #hydrology #hydrography #waterresources #farming #agriculture #opendata #remotesensing #earthobservation #geomorphometry #AI #machinelearning #LLM #model #modeling #WaterManagement #opendata #AgroEcologicalZone #AEZ #cropland #irrigatedareas #foodproduction #wateruse #humanimpacts #EarthObservation #remotesensing #earlywarning #monitoring #FoodandAgricultureOrganizationFAO #FAO
@FAO - Food and Agriculture Organization

Compound Hydrogeomorphic Cascades And Rapid Upstream To Downstream Hazard Coupling In The Eastern Himalaya
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https://doi.org/10.1038/s41598-026-52915-8 <-- shared paper
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https://doi.org/10.1007/s11600-022-00943-z <-- shared paper
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H/T @Kuldeep Dutta | Geology-Earth Science
“… In hilly regions transitioning rapidly to low gradient alluvial plains, localized hydrometeorological triggers can instantly scale into devastating basin wide disasters. This study dissects the September 2020 cascading hazard in parts of the Arunachal Pradesh-Assam corridor to quantify the rapid coupling between upstream hillslopes and downstream floodplains.
Check out the [attached graphical abstract figure] for an integrated visual workflow of the entire disaster continuum from hillslope failure to floodplain transformation...”
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“Extreme precipitation in the Eastern Himalaya is increasingly associated with coupled hillslope-floodplain hazards. This study examines the 17th-18th September 2020 rainfall event in Arunachal Pradesh initiating landslides and its downstream impacts in Assam, India, using multi-sensor satellite data and long-term rainfall records. Sentinel-2 imagery was used to map landslides and debris flows, Sentinel-1 SAR data to delineate flood extent, and IMD gridded rainfall (1996–2020) to analyse rainfall spell characteristics. The event triggered widespread slope failures, localized landslide damming, and a subsequent breach, generating sediment-laden flows that inundated ~ 100 km² of the Dhemaji floodplain. A backscatter-derived Relative Flood Volume Index (RFVI) indicates spatial variability in inundation intensity, although it does not represent absolute flood volume. Rainfall analysis suggests that antecedent wetness from preceding spells preconditioned slopes, while peak daily rainfall (> 170 mm day−1) initiated landsliding. Power-law scaling shows negligible dependence of intensity on duration (R2 ≈ 0.0004), whereas cumulative rainfall exhibits a stronger relationship with duration (R2 ≈ 0.54). These results indicate distinct roles of rainfall intensity and accumulation in controlling landslide initiation and downstream flooding, respectively, highlighting the importance of compound rainfall forcing in rapid hydrogeomorphic cascades…”
#EarthScience #RemoteSensing #Himalayas #NaturalHazards #ClimateChange #ScientificReports #GeospatialAnalysis #DisasterMitigation #Landslide #trigger #Flooding #massmovement #extremeweather #engineeringgeology #floodplain #innundation #hillslope #fluvial #pluvial #alluvial #sediment #sedimentation #hydrometeorology #ArunachalPradesh #Assam #India #Brahmaputra #risk #hazard #geology #engineeringgeology #remotesensing #earthobservation #spatialanalysis #spatiotemporal #disaster #hydrogeomorphology #workflow

A Scale-Invariance-Based Algorithm Application For Land Surface Temperature Downscaling In Denmark
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https://doi.org/10.3390/rs18132263 <-- shared paper
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https://zenodo.org/records/20863040 <-- shared open data for downscaled LST dataset for Copenhagen
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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

Comparative Hydro-Climatic Datasets For Catchment-Wise Linked Water Fluxes And Storage Changes Across South America
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https://doi.org/10.3389/fenvs.2026.1764771 <-- shared paper
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https://doi.org/10.1038/s43247-026-03661-2 <-- shared paper
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https://doi.org/10.1002/joc.6443 <-- shared paper
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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
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https://youtu.be/Ngbm0gsmYAw?si=haqV7t15pGkEmJB8 <-- shared overview video
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#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

Optical, Radar, And Hybrid Indices To Detect Farming Practices In Europe
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https://doi.org/10.1016/j.rse.2026.115553 <-- shared paper
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“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

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

🚨 FEMA’s Hazus v7.2 Is Here — A Major Upgrade For Disaster Risk Modeling
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https://www.fema.gov/flood-maps/products-tools/hazus <-- shared link to FEMA HAZUS download, documentation, use case, etc
--
[I used to work some with Hazus back in the back, but my career changed path; I still appreciate its strength and unity of purpose (sic) #alldataisspatial]
H/T @Laban "L.J." Johnson | Founder, LJ Learn & Concordia Initiative | Crisis Support · Leadership Development · Community Resilience | Bridging worlds to help people rise
“FEMA’s Hazus GIS platform has been updated with a new ArcGIS Pro–based version, bringing faster, more powerful tools for estimating losses from floods, hurricanes, earthquakes, and other natural hazards.
Key updates in Hazus 7.2 include:
• Streamlined workflows for flood and hurricane modeling
• New Earthquake ShakeMap integration using USGS data
• Expanded and improved results exports and reporting (including geodatabase outputs)
• Stronger security with known vulnerabilities addressed
• Performance improvements and optimized installation process
• [Significantly enhanced and comprehensive summary reports for flood and earthquake are now available for download.]
• Full integration with ArcGIS Pro (3.4–3.6) for a modern GIS experience
This release represents a significant step forward in how hazard planners, emergency managers, and GIS professionals analyze and prepare for disaster impacts…”
--
“FEMA’s Hazus program provides software, data, methods, and guidance for estimating risk from natural hazards. Hazus can estimate building damages, economic losses, displaced households, casualties, debris generation and more resulting from a natural hazard event and can be used in all phases of emergency management…”
#HAZUS #fedservice #fedscience #oublicgood #publicsafety #emergencyresponse #software #spatialdata #GIS #spatial #mapping #risk #hazard #riskassessment #naturalhazard #humanimpacts #earthquake #wildfire #spatialanalysis #spatiotemporal #flood #flooding #cost #damage #economic #publicsafety #publichealth #emergencymanagement #opensource #opendata #tsunami #tornado #hurricane #ShakeMap #infrastructure #planning #policy #preparedness #impacts #geology #engineeringgeology #remotesensing #earthobservation
@FEMA

Scientists See More Vegetation In The Himalayas - But It Is Not Good News, Because That Extra “Green” Can Disrupt Water, Snow, And High-Mountain Biodiversity | Plants Growing Higher Across Himalaya As Climate Warms
(Vegetation On The Move: Elevational Shifts And Greening Dynamics Across The Himalayan Alpine Zone)
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https://www.ecoticias.com/en/scientists-see-more-vegetation-in-the-himalayas-but-it-is-not-good-news-because-that-extra-green-can-disrupt-water-snow-and-high-mountain-biodiversity/33120/ <-- shared technical article
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https://news.exeter.ac.uk/faculty-of-environment-science-and-economy/earth-and-environmental-science/plants-growing-higher-across-himalaya-as-climate-warms/ <-- shared technical newsitem
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https://doi.org/10.1002/ecog.08259 <-- shared (2026) paper
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https://doi.org/10.1111/gcb.14919 <-- shared (2020) paper
--
“For years, the biggest climate warning from the Himalaya was easy to picture because glaciers were shrinking on the roof of Asia. Now, researchers are pointing to a quieter signal, one that can look almost harmless from a distance. The mountains are getting greener.
New research [link above] shows alpine vegetation moving higher across six Himalayan regions from 1999 to 2022, pushed in part by warming and reduced snow depth. That might sound like nature recovering, but in this fragile landscape, more plant cover at extreme heights may change how snow is stored, how water runs downhill, and how rivers behave for communities far below…”
#GIS #spatial #mapping #remotesensing #earthobservation #satellite #landsat #landcover #NDVI #Himalaya #Nepal #India #Bhutan #climatechange #glacier #vegetation #alpine #level #greening #spatialanalysis #spatiotemporal #snow #water #ice #hydrography #hydrology #ecosystems #humaninpacts #phenology #model #modeling #HighMountainAsia #greenness #ERA5 #vegetationline #altitude #climatictrends #warming #precipitation #rainfall

[G]lobal Decline In Endorheic Basin Water Storages
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https://doi.org/10.1038/s41561-018-0265-7 <-- shared paper
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https://en.wikipedia.org/wiki/Endorheic_basin <-- shared Wikipedia page
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“Endorheic (hydrologically landlocked) basins spatially concur with arid/semi-arid climates. Given limited precipitation but high potential evaporation, their water storage is vulnerable to subtle flux perturbations, which are exacerbated by global warming and human activities. Increasing regional evidence suggests a probably recent net decline in endorheic water storage, but this remains unquantified at a global scale. By integrating satellite observations and hydrological modelling, [they] reveal[ed] that during 2002–2016 the global endorheic system experienced a widespread water loss of about 106.3 Gt/yr, attributed to comparable losses in surface water, soil moisture and groundwater. This decadal decline, disparate from water storage fluctuations in exorheic basins, appears less sensitive to El Niño–Southern Oscillation-driven climate variability, which implies a possible response to longer-term climate conditions and human water management. In the mass-conserved hydrosphere, such an endorheic water loss not only exacerbates local water stress, but also imposes excess water on exorheic basins, leading to a potential sea level rise that matches the contribution of nearly half of the land glacier retreat (excluding Greenland and Antarctica). Given these dual ramifications, [they] suggest the necessity for long-term monitoring of water storage variation in the global endorheic system and the inclusion of its net contribution to future sea level budgeting…”
#water #hydrology #hydrography #global #waterresources #waterstorage #Endorheic #Basin #watersecurity #arid #semiarid #rainfall #precipitation #spatialanalysis #spatiotemporal #globalwarming #climatechange #humanimpacts #anthropogenic #regional #remotesensing #GIS #spatial #mapping #earthobservation #surfacewater #groundwater #soilmoisture #exorheic #watermanagement #hydrosphere #waterstress #SLR #sealevelrise #monitoring #waterbudgets

Decoupling Of Surface Water Storage From Precipitation In Global Drylands Due To Anthropogenic Activity
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https://doi.org/10.1038/s44221-024-00367-7 <-- shared paper
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“The availability of surface water in global drylands is essential for both human society and ecosystems. However, the long-term drivers of change in surface water storage, particularly those related to anthropogenic activities, remain unclear. Here [they] use[d] multi-mission remote sensing data to construct monthly time series of water storage changes from 1985 to 2020 for 105,400 lakes and reservoirs in global drylands. An increase of 2.20 km³ per year in surface water storage is found primarily due to the construction of new reservoirs. For lakes and old reservoirs (constructed before 1983), conversely, the trend in storage is minor when aggregated globally, but they dominate surface water storage trends in 91% of individual global dryland basins. Further analysis reveals that long-term storage changes in these water bodies are primarily linked to anthropogenic factors - including human-induced warming and water-management practices - rather than to precipitation changes, as previously thought. These findings reveal a decoupling of surface water storage from precipitation in global drylands, raising concerns about societal and ecosystem sustainability…”
#water #hydrology #hydrography #waterstorage #waterresources #surfacewater #global #drylands #precipitation #rainfall #watersecurity #ecosystems #habitat #publichealth #anthropogenic #GIS #spatial #mapping #remotesensing #earthobservation #spatiotemporal #spatialanalysis #monitoring #geostatistics #engineering #reservoirs #infrastructure #lakes #waterbodies #globalwarming #climatechange #sustainability #planning #baseline

Sea Levels Rising Dramatically In Some Areas Due To Land Subsidence [global]
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https://phys.org/news/2026-05-sea-areas-due-subsidence.html <-- shared technical article
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https://doi.org/10.1038/s41467-026-72293-z <-- shared paper
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[#VLM = vertical land motion; #ASL = absolute sea-level; #RSL = relative sea-level; #GIA = (global) Glacial Isostatic Adjustment; #inSAR = Interferometric Synthetic Aperture Radar; #GNSS = Global Navigation Satellite System (~GPS); #OE24 = paper, https://doi.org/10.1038/s41561-023-01357-2, interpolated VLM reconstruction based on the joint analysis of GNSS, tide gauges (TGs), and satellite altimetry]
#GIS #spatial #mapping #remotesensing #earthobservation #sealevel #verticallandmotion #absolutesealevel #relativesealevel #GlacialIsostaticAdjustment #geomorphometry #SLR #sealevelrise #coast #coastal #flood #flooding #subsidence #landmass #landsubsidence #global #globalsealevelrise #climatechange #city #urban #farmlands #population #demographics #cities #planning #community #elevation #monitoring #spatialanalysis #spatiotemporal #altimetry

A 481-Metre-High Landslide-Tsunami In A Cruise Ship–Frequented Alaska Fjord
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https://doi.org/10.1126/science.aec3187 <-- shared paper
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https://www.nytimes.com/2026/05/06/science/tsunami-landslide-alaska-climate-arctic.html <-- shared media article
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#naturalhazard #glacier #glacial #melting #risk #hazard #climatechance #extremeweather #tsunami #runup #riskassessment #spatialanalysis #spatiotemporal #cryosphere #disaster #publicsafety #damage #infrastructure #Alaska #fjord #landslide #massmovement #engineeringeology #geology #cruiseship #humanimpacts #water #hydrology #caseexample #monitoring #coast #coastal #marine #wave #microseismicity #remotesensing #earthobservation #tourism #averteddisaster #readiness #awareness #planning #safety #deglaciating

All Four Sentinel-1 Satellites Are Now Live

https://orbitaltoday.com/2026/05/03/all-four-sentinel-1-satellites-are-now-live-and-europes-earth-watch-just-got-stronger/

#HackerNews #Sentinel1 #Satellites #EarthObservation #SpaceTechnology #Europe

Characterizing Wildfire Behavior With ECOSTRESS Land Surface Temperature Across Four California Case Studies
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https://doi.org/10.1016/j.ecoinf.2026.103777 <-- shared paper
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#GIS #spatial #mapping #ECOSTRESS #remotesensing #earthobservation #wildfire #increased #frequency #intensity #forestfire #monitoring #hotspot #detection #Rateofspread #HotspotBurn #severity #spatialanalysis #spatiotemporal #VIIRS #fireradiativepower #FRP #landsurface #temperature #California #casestudy #burn #severity #dNBR #landsat #satellite #WesternUSA #extremeweather #climatechange #water #hydrology #hydrometeorology #drought #humanactivity #humanimpacts #ECOsystemSpaceborneThermalRadiometerExperimentonSpaceStation #ISS #spacestation #LST #rateofspread
@nasa

National-Scale Field Delineation In Mozambique Refines Our Understanding Of Cropland Distribution, Field Size, And Deforestation Actors.
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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

Active Faults Greece - A Comprehensive Geomorphology-Based 1:25,000 Fault Database
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https://doi.org/10.1038/s41597-025-06283-z <-- shared paper
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https://activefaults.eagme.gr/en/ <-- shared Hellenic DataBase of Active Faults (HeDBAF) access
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#GIS #spatial #mapping #Greece #Europe #geology #fault #faulting #remotesensing #earthobservation #seismology #seismic #earthquake #paleoseismology #activefault #risk #hazard #naturaldisasters #DEM #elevation #ActiveFaultsGreece #AFG #database #faulttraces #engineeringeology #spatialanalysis #geomorphology #landsurface #planning #hazardassessment