#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

#Rasuwa #flood: Why did #earlywarning fail despite systems in place?

This report names two main factors:
* tech - sensors, servers, networks
* cross-border communications

I think in addition to these local/regional factors, a global question:

there are #satellite systems seeing this happen in near-realtime -
and "AI"s analyzing.
yet noone cares to issue a warning .... (?)

https://myrepublica.nagariknetwork.com/news/rasuwa-flood-why-did-early-warning-fail-despite-systems-in-place-64-74.html

#Nepal #Tibet #glacierCollapse #landslide
#AI #earthobservation

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

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

The Latest Data Confirms - Forest Fires Are Getting Worse
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https://www.wri.org/insights/global-trends-forest-fires <-- shared technical article
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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
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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
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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
--
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
--
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

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

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
--
#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
--
“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

🚨 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

[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
--
“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

#Mexico City is sinking #earthobservation #subsidence #radar #SAR #NISAR https://www.nasa.gov/missions/nisar/us-indian-space-mission-maps-extreme-subsidence-in-mexico-city/

@coreyspowell
10/
In short: It’s not an apocalypse; it’s a data corrective. It proves that the engine room of our planet is a highly active, rapidly changing environment, and it took a constellation of advanced satellites sixteen years of data-crunching to finally reveal what happened right under our feet.

#Geophysics
#Geomagnetism
#EarthsCore
#Geodynamics
#OuterCore
#Geodynamo
#ESASwarm
#CryoSat
#SatelliteData
#EarthObservation
#GeomagneticField
#WorldMagneticModel
#WMM

I was really honored to give a talk (remotely) at NASA Goddard today! Thanks for the invitation, and I hope we'll stay in touch!

#RemoteSensing #NighttimeLights #NightLightRemoteSensing #VIIRS_DNB #SDGSat1 #ESA #EarthExplorer #EarthObservation #LightPollution

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
--
https://philipperufin.github.io/blog/mozfields-2023/ <-- shared associated technical article from one of the paper’s authors
--
#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

Detecting Land Use And Land Cover Changes And Quantifying Soil Erosion And Sediment Export Using GIS And Remote Sensing In The GERD Catchment, Ethiopia
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https://doi.org/10.1016/j.iswcr.2026.100657 <-- shared paper
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https://infonile.org/en/2023/05/battling-for-survival-along-the-warming-source-of-the-blue-nile/ <-- shared technical media article
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https://doi.org/10.1007/978-3-031-65241-7_4 <-- shared technical book chapter
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https://doi.org/10.3390/rs8121020 <-- shared 2016 paper
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#landuse #landcover #RUSLE #model #soil #erosion #sedimentation #GERD #catchment #NorthAfrica #Ethiopia #AbbayBasin #sustainability #landmanagement #agriculture #farmland #foodsecurity #water #hydrogology #reservior #watermanagement #watersecurity #waterresources #catchment #GrandEthiopianRenaissanceDam #BlueNile #hydrography #impoundment #GIS #spatial #mapping #remotesensing #earthobservation #thematic #spatialanalysis #spatiotemporal #landsat #elevation #DEM #CHIRPS #rainfall #precipitation #LULC #AI #forest #grazing #grassland #field #crops #cropland #waterbodies #urban #biophysical #risk #hazard #mitigation #soilquality

A paper that I co-authored was just published (#OpenAccess) a few minutes ago in Nature 🎉 https://www.nature.com/articles/s41586-026-10260-w

Here's a short thread about what we did and what we learned 👇

#LightPollution #Energy #ALAN #RemoteSensing #NightLightRemoteSensing #EarthObservation #VIIRS_DNB

Global Atlas Will Track Human And Climate Impact On River Systems
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https://news.cornell.edu/stories/2026/03/global-atlas-will-track-human-and-climate-impact-river-systems
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“Rivers are critical resources that affect everything from watersheds to agriculture to energy. But rivers, in turn, have been impacted by humans, often in the form of hydraulic infrastructure such as dams and wells.
A new [Cornell] project… will create a global record that shows how river systems around the world have changed under human influence over the last 75 years…”
#GIS #spatial #mapping #research #spatialanalysis #spatiotemporal #water #waterresources #river #remotesensing #earthobservation #climatechange #climate #change #resources #humanimpacts #survey #monitoring #hydraulic #infrastructure #dams #wells #engineered #canals #global #spatialdata #opendata #history #anthropocene #freshwater #DARE #sediment #discharge #transport #temperature #fish #biodiversity #atlas #ecology #ecosystems #riverine #delta #model #modeling #machinelearning #AI
#CornellUniversity | #CornellDuffieldCollegeofEngineering

Observing The Tidal Pulse Of Rivers From Wide-Swath Satellite Altimetry
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https://doi.org/10.1038/s41586-026-10287-z <-- shared paper
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https://dahiti.dgfi.tum.de/en/products/river-tides/map/ <-- shared interactive map, ‘River Tides from SWOT’
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#SWOT #RemoteSensing #Hydrology #EarthObservation #ClimateScience #CoastalSystems #Rivers #OpenScience #opendata #tide #tidal #dynamics #exchange #estuary #estuarine #webmap #wetlands #ecosystems #habitat #elevation #marine #freshwater #water #hydrography #hydrology #river #GIS #spatial #mapping #satellite #altimetry #coast #coastal #GIS #spatial #mapping #spatialanalysis #spatiotemporal #SurfaceWaterandOceanTopography #global #coverage #monitoring #model #modeling #riverine #fluvial #carbonbudgets #nitrogencycle #sedimentation #sealevelrise #SLR #megadroughts #extraction #pumping #regulations #groundwater #intrusion #risk #hazard #naturalhazards #stormsurge #waterresources #tidalrange #rivermouth