#earthobservation — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #earthobservation, aggregated by home.social.
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Satellite view of Ohio — 2026-09-10
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=2026-09-10Imagery: NASA GIBS #satellite #NASA #EarthObservation
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Satellite view of Ohio — 2026-09-10
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=2026-09-10Imagery: NASA GIBS #satellite #NASA #EarthObservation
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Satellite view of Ohio — 2026-09-10
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=2026-09-10Imagery: NASA GIBS #satellite #NASA #EarthObservation
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Satellite view of Ohio — 2026-09-10
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=2026-09-10Imagery: NASA GIBS #satellite #NASA #EarthObservation
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Satellite view of Ohio — 2026-09-10
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=2026-09-10Imagery: NASA GIBS #satellite #NASA #EarthObservation
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Some of Earth's most important places, rainforests and flood zones, hide under cloud most of the year. Radar (SAR) makes its own signal at a wavelength clouds ignore, mapping the ground day, night, and through storms. Why radar quietly underpins Earth observation.
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Some of Earth's most important places, rainforests and flood zones, hide under cloud most of the year. Radar (SAR) makes its own signal at a wavelength clouds ignore, mapping the ground day, night, and through storms. Why radar quietly underpins Earth observation.
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Some of Earth's most important places, rainforests and flood zones, hide under cloud most of the year. Radar (SAR) makes its own signal at a wavelength clouds ignore, mapping the ground day, night, and through storms. Why radar quietly underpins Earth observation.
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Some of Earth's most important places, rainforests and flood zones, hide under cloud most of the year. Radar (SAR) makes its own signal at a wavelength clouds ignore, mapping the ground day, night, and through storms. Why radar quietly underpins Earth observation.
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A Scalable Cloud-Native Framework for Satellite Rainfall-Driven Landslide Early Warning in Data-Scarce Regions
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https://doi.org/10.5194/egusphere-2026-4588 <-- shared technical article
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https://ee-yunuscool.projects.earthengine.app/view/alert-app <-- shared web map based ALERT, Automated Landslide Early Risk Tracker
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https://doi.org/10.1186/s40677-022-00218-1 <-- shared paper
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H/T @ Yunus Ali Pulpadan | Assistant Professor at Indian Institute of Science Education and Research (IISER), Mohali
“[The authors] are excited to share ALERT — the Automated Landslide Early Risk Tracker, a cloud-native framework and web application developed to support near-real-time, impact-based assessment of rainfall-triggered landslide hazards.
ALERT integrates multiple components within a single scalable framework:
🛰️ Satellite-based rainfall observations
🌦️ Operational weather forecasts
🗺️ Terrain susceptibility information
📈 Rainfall intensity–duration thresholds
🏔️ Debris-flow runout modelling
🏘️ Building exposure
The goal is to move beyond simply identifying intense rainfall and towards understanding where hazardous conditions may trigger landslides and what may lie in the potential path of downstream impacts. A particular motivation behind ALERT is the challenge of developing landslide early-warning capabilities in data-scarce mountainous regions, where dense rain-gauge networks and operational monitoring infrastructure are often limited. The framework incorporates a catalogue of rainfall thresholds while also allowing users to integrate their own thresholds and susceptibility information, making it adaptable across different climatic and geomorphological settings…”
#GIS #spatial #mapping #AI #deeplearning #massmovement #landslide #engineeringgeology #water #precipitation #rainfall #earlywarning #remotesensing #earthobservation #global #webmap #dataportal #risk #hazard #infrastructure #building #weather #forecasting #imagery #debrisflow #model #modeling #ALERT #opendata #climate #geology hydrogeomorphology geomorphology public safety global #regional -
A Scalable Cloud-Native Framework for Satellite Rainfall-Driven Landslide Early Warning in Data-Scarce Regions
--
https://doi.org/10.5194/egusphere-2026-4588 <-- shared technical article
--
https://ee-yunuscool.projects.earthengine.app/view/alert-app <-- shared web map based ALERT, Automated Landslide Early Risk Tracker
--
https://doi.org/10.1186/s40677-022-00218-1 <-- shared paper
--
H/T @ Yunus Ali Pulpadan | Assistant Professor at Indian Institute of Science Education and Research (IISER), Mohali
“[The authors] are excited to share ALERT — the Automated Landslide Early Risk Tracker, a cloud-native framework and web application developed to support near-real-time, impact-based assessment of rainfall-triggered landslide hazards.
ALERT integrates multiple components within a single scalable framework:
🛰️ Satellite-based rainfall observations
🌦️ Operational weather forecasts
🗺️ Terrain susceptibility information
📈 Rainfall intensity–duration thresholds
🏔️ Debris-flow runout modelling
🏘️ Building exposure
The goal is to move beyond simply identifying intense rainfall and towards understanding where hazardous conditions may trigger landslides and what may lie in the potential path of downstream impacts. A particular motivation behind ALERT is the challenge of developing landslide early-warning capabilities in data-scarce mountainous regions, where dense rain-gauge networks and operational monitoring infrastructure are often limited. The framework incorporates a catalogue of rainfall thresholds while also allowing users to integrate their own thresholds and susceptibility information, making it adaptable across different climatic and geomorphological settings…”
#GIS #spatial #mapping #AI #deeplearning #massmovement #landslide #engineeringgeology #water #precipitation #rainfall #earlywarning #remotesensing #earthobservation #global #webmap #dataportal #risk #hazard #infrastructure #building #weather #forecasting #imagery #debrisflow #model #modeling #ALERT #opendata #climate #geology hydrogeomorphology geomorphology public safety global #regional -
A Scalable Cloud-Native Framework for Satellite Rainfall-Driven Landslide Early Warning in Data-Scarce Regions
--
https://doi.org/10.5194/egusphere-2026-4588 <-- shared technical article
--
https://ee-yunuscool.projects.earthengine.app/view/alert-app <-- shared web map based ALERT, Automated Landslide Early Risk Tracker
--
https://doi.org/10.1186/s40677-022-00218-1 <-- shared paper
--
H/T @ Yunus Ali Pulpadan | Assistant Professor at Indian Institute of Science Education and Research (IISER), Mohali
“[The authors] are excited to share ALERT — the Automated Landslide Early Risk Tracker, a cloud-native framework and web application developed to support near-real-time, impact-based assessment of rainfall-triggered landslide hazards.
ALERT integrates multiple components within a single scalable framework:
🛰️ Satellite-based rainfall observations
🌦️ Operational weather forecasts
🗺️ Terrain susceptibility information
📈 Rainfall intensity–duration thresholds
🏔️ Debris-flow runout modelling
🏘️ Building exposure
The goal is to move beyond simply identifying intense rainfall and towards understanding where hazardous conditions may trigger landslides and what may lie in the potential path of downstream impacts. A particular motivation behind ALERT is the challenge of developing landslide early-warning capabilities in data-scarce mountainous regions, where dense rain-gauge networks and operational monitoring infrastructure are often limited. The framework incorporates a catalogue of rainfall thresholds while also allowing users to integrate their own thresholds and susceptibility information, making it adaptable across different climatic and geomorphological settings…”
#GIS #spatial #mapping #AI #deeplearning #massmovement #landslide #engineeringgeology #water #precipitation #rainfall #earlywarning #remotesensing #earthobservation #global #webmap #dataportal #risk #hazard #infrastructure #building #weather #forecasting #imagery #debrisflow #model #modeling #ALERT #opendata #climate #geology hydrogeomorphology geomorphology public safety global #regional -
A Scalable Cloud-Native Framework for Satellite Rainfall-Driven Landslide Early Warning in Data-Scarce Regions
--
https://doi.org/10.5194/egusphere-2026-4588 <-- shared technical article
--
https://ee-yunuscool.projects.earthengine.app/view/alert-app <-- shared web map based ALERT, Automated Landslide Early Risk Tracker
--
https://doi.org/10.1186/s40677-022-00218-1 <-- shared paper
--
H/T @ Yunus Ali Pulpadan | Assistant Professor at Indian Institute of Science Education and Research (IISER), Mohali
“[The authors] are excited to share ALERT — the Automated Landslide Early Risk Tracker, a cloud-native framework and web application developed to support near-real-time, impact-based assessment of rainfall-triggered landslide hazards.
ALERT integrates multiple components within a single scalable framework:
🛰️ Satellite-based rainfall observations
🌦️ Operational weather forecasts
🗺️ Terrain susceptibility information
📈 Rainfall intensity–duration thresholds
🏔️ Debris-flow runout modelling
🏘️ Building exposure
The goal is to move beyond simply identifying intense rainfall and towards understanding where hazardous conditions may trigger landslides and what may lie in the potential path of downstream impacts. A particular motivation behind ALERT is the challenge of developing landslide early-warning capabilities in data-scarce mountainous regions, where dense rain-gauge networks and operational monitoring infrastructure are often limited. The framework incorporates a catalogue of rainfall thresholds while also allowing users to integrate their own thresholds and susceptibility information, making it adaptable across different climatic and geomorphological settings…”
#GIS #spatial #mapping #AI #deeplearning #massmovement #landslide #engineeringgeology #water #precipitation #rainfall #earlywarning #remotesensing #earthobservation #global #webmap #dataportal #risk #hazard #infrastructure #building #weather #forecasting #imagery #debrisflow #model #modeling #ALERT #opendata #climate #geology hydrogeomorphology geomorphology public safety global #regional -
A Scalable Cloud-Native Framework for Satellite Rainfall-Driven Landslide Early Warning in Data-Scarce Regions
--
https://doi.org/10.5194/egusphere-2026-4588 <-- shared technical article
--
https://ee-yunuscool.projects.earthengine.app/view/alert-app <-- shared web map based ALERT, Automated Landslide Early Risk Tracker
--
https://doi.org/10.1186/s40677-022-00218-1 <-- shared paper
--
H/T @ Yunus Ali Pulpadan | Assistant Professor at Indian Institute of Science Education and Research (IISER), Mohali
“[The authors] are excited to share ALERT — the Automated Landslide Early Risk Tracker, a cloud-native framework and web application developed to support near-real-time, impact-based assessment of rainfall-triggered landslide hazards.
ALERT integrates multiple components within a single scalable framework:
🛰️ Satellite-based rainfall observations
🌦️ Operational weather forecasts
🗺️ Terrain susceptibility information
📈 Rainfall intensity–duration thresholds
🏔️ Debris-flow runout modelling
🏘️ Building exposure
The goal is to move beyond simply identifying intense rainfall and towards understanding where hazardous conditions may trigger landslides and what may lie in the potential path of downstream impacts. A particular motivation behind ALERT is the challenge of developing landslide early-warning capabilities in data-scarce mountainous regions, where dense rain-gauge networks and operational monitoring infrastructure are often limited. The framework incorporates a catalogue of rainfall thresholds while also allowing users to integrate their own thresholds and susceptibility information, making it adaptable across different climatic and geomorphological settings…”
#GIS #spatial #mapping #AI #deeplearning #massmovement #landslide #engineeringgeology #water #precipitation #rainfall #earlywarning #remotesensing #earthobservation #global #webmap #dataportal #risk #hazard #infrastructure #building #weather #forecasting #imagery #debrisflow #model #modeling #ALERT #opendata #climate #geology hydrogeomorphology geomorphology public safety global #regional -
Sub-Seasonal Forecasting Of Cropland Productivity Anomalies Using Satellite Soil Moisture In Water-Limited Environments
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https://doi.org/10.1016/j.rse.2026.115645 <-- shared paper
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H/T @Adebowale Daniel Adebayo | Doctoral Candidate | Geospatial Data Scientist
“When rainfall fails and evaporative demand climbs, root-zone soil moisture is where the deficit registers first and where it carries forward, weeks before crop condition reflects it. In this study [link above], [the authors] used SMAP root-zone soil moisture to forecast crop productivity anomalies across drought-prone croplands of Eastern and Southern Africa, and [they] quantified how much predictive value soil moisture actually carries, over what lead times, and under which hydroclimatic conditions. The contribution of soil moisture was negligible at short leads but grew steadily out to 40 days, and it concentrated in water-limited croplands where soil moisture and vegetation are most tightly coupled. During the 2024 southern African El Niño drought, the soil moisture informed model resolved the spatial pattern of productivity anomalies roughly a month in advance.
Beyond the results themselves, this work is a pointer to how much predictive information soil moisture holds. Leveraging the temporal record of SMAP-related products together with the 100–200 metre resolution NISAR will deliver gives us, [believes the H/T], a clear path to attempt field-scale drought forecasting in the smallholder landscapes where early warning matters most…”
#agriculture #crops #foodsecurity #cropland #productivity #forecasting #rootzone #soilmoisture #SMAP #NIRV #subseasonal #prediction #EasternAfrica #SouthernAfrica #africa #vegetation #anomaly #precipitation #ET #drought #extremeweather #water #hydrology #hydroclimate #productivity #arid #waterlimited #spatialanalysis #spatiotemporal #model #modeling #vegetation #Africa #ElNino #ElNiño #mitigation #prediction #forecast #smallholders #earlywarning #RZSM #SoilMoistureActivePassive #NearInfraredReflectance #NIR #remotesensing #earthobservation -
Sub-Seasonal Forecasting Of Cropland Productivity Anomalies Using Satellite Soil Moisture In Water-Limited Environments
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https://doi.org/10.1016/j.rse.2026.115645 <-- shared paper
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H/T @Adebowale Daniel Adebayo | Doctoral Candidate | Geospatial Data Scientist
“When rainfall fails and evaporative demand climbs, root-zone soil moisture is where the deficit registers first and where it carries forward, weeks before crop condition reflects it. In this study [link above], [the authors] used SMAP root-zone soil moisture to forecast crop productivity anomalies across drought-prone croplands of Eastern and Southern Africa, and [they] quantified how much predictive value soil moisture actually carries, over what lead times, and under which hydroclimatic conditions. The contribution of soil moisture was negligible at short leads but grew steadily out to 40 days, and it concentrated in water-limited croplands where soil moisture and vegetation are most tightly coupled. During the 2024 southern African El Niño drought, the soil moisture informed model resolved the spatial pattern of productivity anomalies roughly a month in advance.
Beyond the results themselves, this work is a pointer to how much predictive information soil moisture holds. Leveraging the temporal record of SMAP-related products together with the 100–200 metre resolution NISAR will deliver gives us, [believes the H/T], a clear path to attempt field-scale drought forecasting in the smallholder landscapes where early warning matters most…”
#agriculture #crops #foodsecurity #cropland #productivity #forecasting #rootzone #soilmoisture #SMAP #NIRV #subseasonal #prediction #EasternAfrica #SouthernAfrica #africa #vegetation #anomaly #precipitation #ET #drought #extremeweather #water #hydrology #hydroclimate #productivity #arid #waterlimited #spatialanalysis #spatiotemporal #model #modeling #vegetation #Africa #ElNino #ElNiño #mitigation #prediction #forecast #smallholders #earlywarning #RZSM #SoilMoistureActivePassive #NearInfraredReflectance #NIR #remotesensing #earthobservation -
Sub-Seasonal Forecasting Of Cropland Productivity Anomalies Using Satellite Soil Moisture In Water-Limited Environments
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https://doi.org/10.1016/j.rse.2026.115645 <-- shared paper
--
H/T @Adebowale Daniel Adebayo | Doctoral Candidate | Geospatial Data Scientist
“When rainfall fails and evaporative demand climbs, root-zone soil moisture is where the deficit registers first and where it carries forward, weeks before crop condition reflects it. In this study [link above], [the authors] used SMAP root-zone soil moisture to forecast crop productivity anomalies across drought-prone croplands of Eastern and Southern Africa, and [they] quantified how much predictive value soil moisture actually carries, over what lead times, and under which hydroclimatic conditions. The contribution of soil moisture was negligible at short leads but grew steadily out to 40 days, and it concentrated in water-limited croplands where soil moisture and vegetation are most tightly coupled. During the 2024 southern African El Niño drought, the soil moisture informed model resolved the spatial pattern of productivity anomalies roughly a month in advance.
Beyond the results themselves, this work is a pointer to how much predictive information soil moisture holds. Leveraging the temporal record of SMAP-related products together with the 100–200 metre resolution NISAR will deliver gives us, [believes the H/T], a clear path to attempt field-scale drought forecasting in the smallholder landscapes where early warning matters most…”
#agriculture #crops #foodsecurity #cropland #productivity #forecasting #rootzone #soilmoisture #SMAP #NIRV #subseasonal #prediction #EasternAfrica #SouthernAfrica #africa #vegetation #anomaly #precipitation #ET #drought #extremeweather #water #hydrology #hydroclimate #productivity #arid #waterlimited #spatialanalysis #spatiotemporal #model #modeling #vegetation #Africa #ElNino #ElNiño #mitigation #prediction #forecast #smallholders #earlywarning #RZSM #SoilMoistureActivePassive #NearInfraredReflectance #NIR #remotesensing #earthobservation -
Sub-Seasonal Forecasting Of Cropland Productivity Anomalies Using Satellite Soil Moisture In Water-Limited Environments
--
https://doi.org/10.1016/j.rse.2026.115645 <-- shared paper
--
H/T @Adebowale Daniel Adebayo | Doctoral Candidate | Geospatial Data Scientist
“When rainfall fails and evaporative demand climbs, root-zone soil moisture is where the deficit registers first and where it carries forward, weeks before crop condition reflects it. In this study [link above], [the authors] used SMAP root-zone soil moisture to forecast crop productivity anomalies across drought-prone croplands of Eastern and Southern Africa, and [they] quantified how much predictive value soil moisture actually carries, over what lead times, and under which hydroclimatic conditions. The contribution of soil moisture was negligible at short leads but grew steadily out to 40 days, and it concentrated in water-limited croplands where soil moisture and vegetation are most tightly coupled. During the 2024 southern African El Niño drought, the soil moisture informed model resolved the spatial pattern of productivity anomalies roughly a month in advance.
Beyond the results themselves, this work is a pointer to how much predictive information soil moisture holds. Leveraging the temporal record of SMAP-related products together with the 100–200 metre resolution NISAR will deliver gives us, [believes the H/T], a clear path to attempt field-scale drought forecasting in the smallholder landscapes where early warning matters most…”
#agriculture #crops #foodsecurity #cropland #productivity #forecasting #rootzone #soilmoisture #SMAP #NIRV #subseasonal #prediction #EasternAfrica #SouthernAfrica #africa #vegetation #anomaly #precipitation #ET #drought #extremeweather #water #hydrology #hydroclimate #productivity #arid #waterlimited #spatialanalysis #spatiotemporal #model #modeling #vegetation #Africa #ElNino #ElNiño #mitigation #prediction #forecast #smallholders #earlywarning #RZSM #SoilMoistureActivePassive #NearInfraredReflectance #NIR #remotesensing #earthobservation -
Sub-Seasonal Forecasting Of Cropland Productivity Anomalies Using Satellite Soil Moisture In Water-Limited Environments
--
https://doi.org/10.1016/j.rse.2026.115645 <-- shared paper
--
H/T @Adebowale Daniel Adebayo | Doctoral Candidate | Geospatial Data Scientist
“When rainfall fails and evaporative demand climbs, root-zone soil moisture is where the deficit registers first and where it carries forward, weeks before crop condition reflects it. In this study [link above], [the authors] used SMAP root-zone soil moisture to forecast crop productivity anomalies across drought-prone croplands of Eastern and Southern Africa, and [they] quantified how much predictive value soil moisture actually carries, over what lead times, and under which hydroclimatic conditions. The contribution of soil moisture was negligible at short leads but grew steadily out to 40 days, and it concentrated in water-limited croplands where soil moisture and vegetation are most tightly coupled. During the 2024 southern African El Niño drought, the soil moisture informed model resolved the spatial pattern of productivity anomalies roughly a month in advance.
Beyond the results themselves, this work is a pointer to how much predictive information soil moisture holds. Leveraging the temporal record of SMAP-related products together with the 100–200 metre resolution NISAR will deliver gives us, [believes the H/T], a clear path to attempt field-scale drought forecasting in the smallholder landscapes where early warning matters most…”
#agriculture #crops #foodsecurity #cropland #productivity #forecasting #rootzone #soilmoisture #SMAP #NIRV #subseasonal #prediction #EasternAfrica #SouthernAfrica #africa #vegetation #anomaly #precipitation #ET #drought #extremeweather #water #hydrology #hydroclimate #productivity #arid #waterlimited #spatialanalysis #spatiotemporal #model #modeling #vegetation #Africa #ElNino #ElNiño #mitigation #prediction #forecast #smallholders #earlywarning #RZSM #SoilMoistureActivePassive #NearInfraredReflectance #NIR #remotesensing #earthobservation -
Sentinel-2 cloud masking: SCL band, s2cloudless, or Fmask? I've been burned by each in different scenes. What's your default in 2026, and why?
#RemoteSensing #Sentinel2 #EarthObservation #GIS -
Sentinel-2 cloud masking: SCL band, s2cloudless, or Fmask? I've been burned by each in different scenes. What's your default in 2026, and why?
#RemoteSensing #Sentinel2 #EarthObservation #GIS -
Sentinel-2 cloud masking: SCL band, s2cloudless, or Fmask? I've been burned by each in different scenes. What's your default in 2026, and why?
#RemoteSensing #Sentinel2 #EarthObservation #GIS -
Sentinel-2 cloud masking: SCL band, s2cloudless, or Fmask? I've been burned by each in different scenes. What's your default in 2026, and why?
#RemoteSensing #Sentinel2 #EarthObservation #GIS -
Sentinel-2 cloud masking: SCL band, s2cloudless, or Fmask? I've been burned by each in different scenes. What's your default in 2026, and why?
#RemoteSensing #Sentinel2 #EarthObservation #GIS -
Interferometric Synthetic Aperture Radar (InSAR) For Monitoring Seasonal Snow
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https://doi.org/10.1029/2025WR042866 <-- shared paper
--
https://eos.org/features/satellite-radar-advances-could-transform-global-snow-monitoring <-- shared technical article
--
H/T @Jack Tarricone, PhD | Assistant Research Scientist @ NASA GSFC/UMD ESSIC | Remote Sensing and Snow Hydrology
“[The authors] review[ed] 25 years of progress in using InSAR to measure changes in snow water equivalent (SWE) and snow depth and discuss[ed] what’s needed to extend these methods to basin-scale snow monitoring with NISAR. [They] hope it’s a useful resource for people interested in snow, SAR/InSAR, remote sensing, and hydrology in general…”
#GIS #spatial #mapping #remotesensing #earthobservation #InterferometricSyntheticApertureRadar #InSAR #literaturereview #research #history #monitoring #spatialanalysis #spatiotemporal #seasonal #snow #water #hydrology #waterresources #snowpack #snowmelt #ablation #melt #runoff #snowwaterequivalent #SWE #NISAR #snowdepth #basin #snowphase #estimation #change #spatial #GIS #mapping #temporal #model #modeling #algorithm #ecosystems #environment #habitat #agriculture #farming #snowmass #satellite -
Interferometric Synthetic Aperture Radar (InSAR) For Monitoring Seasonal Snow
--
https://doi.org/10.1029/2025WR042866 <-- shared paper
--
https://eos.org/features/satellite-radar-advances-could-transform-global-snow-monitoring <-- shared technical article
--
H/T @Jack Tarricone, PhD | Assistant Research Scientist @ NASA GSFC/UMD ESSIC | Remote Sensing and Snow Hydrology
“[The authors] review[ed] 25 years of progress in using InSAR to measure changes in snow water equivalent (SWE) and snow depth and discuss[ed] what’s needed to extend these methods to basin-scale snow monitoring with NISAR. [They] hope it’s a useful resource for people interested in snow, SAR/InSAR, remote sensing, and hydrology in general…”
#GIS #spatial #mapping #remotesensing #earthobservation #InterferometricSyntheticApertureRadar #InSAR #literaturereview #research #history #monitoring #spatialanalysis #spatiotemporal #seasonal #snow #water #hydrology #waterresources #snowpack #snowmelt #ablation #melt #runoff #snowwaterequivalent #SWE #NISAR #snowdepth #basin #snowphase #estimation #change #spatial #GIS #mapping #temporal #model #modeling #algorithm #ecosystems #environment #habitat #agriculture #farming #snowmass #satellite -
Interferometric Synthetic Aperture Radar (InSAR) For Monitoring Seasonal Snow
--
https://doi.org/10.1029/2025WR042866 <-- shared paper
--
https://eos.org/features/satellite-radar-advances-could-transform-global-snow-monitoring <-- shared technical article
--
H/T @Jack Tarricone, PhD | Assistant Research Scientist @ NASA GSFC/UMD ESSIC | Remote Sensing and Snow Hydrology
“[The authors] review[ed] 25 years of progress in using InSAR to measure changes in snow water equivalent (SWE) and snow depth and discuss[ed] what’s needed to extend these methods to basin-scale snow monitoring with NISAR. [They] hope it’s a useful resource for people interested in snow, SAR/InSAR, remote sensing, and hydrology in general…”
#GIS #spatial #mapping #remotesensing #earthobservation #InterferometricSyntheticApertureRadar #InSAR #literaturereview #research #history #monitoring #spatialanalysis #spatiotemporal #seasonal #snow #water #hydrology #waterresources #snowpack #snowmelt #ablation #melt #runoff #snowwaterequivalent #SWE #NISAR #snowdepth #basin #snowphase #estimation #change #spatial #GIS #mapping #temporal #model #modeling #algorithm #ecosystems #environment #habitat #agriculture #farming #snowmass #satellite -
Interferometric Synthetic Aperture Radar (InSAR) For Monitoring Seasonal Snow
--
https://doi.org/10.1029/2025WR042866 <-- shared paper
--
https://eos.org/features/satellite-radar-advances-could-transform-global-snow-monitoring <-- shared technical article
--
H/T @Jack Tarricone, PhD | Assistant Research Scientist @ NASA GSFC/UMD ESSIC | Remote Sensing and Snow Hydrology
“[The authors] review[ed] 25 years of progress in using InSAR to measure changes in snow water equivalent (SWE) and snow depth and discuss[ed] what’s needed to extend these methods to basin-scale snow monitoring with NISAR. [They] hope it’s a useful resource for people interested in snow, SAR/InSAR, remote sensing, and hydrology in general…”
#GIS #spatial #mapping #remotesensing #earthobservation #InterferometricSyntheticApertureRadar #InSAR #literaturereview #research #history #monitoring #spatialanalysis #spatiotemporal #seasonal #snow #water #hydrology #waterresources #snowpack #snowmelt #ablation #melt #runoff #snowwaterequivalent #SWE #NISAR #snowdepth #basin #snowphase #estimation #change #spatial #GIS #mapping #temporal #model #modeling #algorithm #ecosystems #environment #habitat #agriculture #farming #snowmass #satellite -
Interferometric Synthetic Aperture Radar (InSAR) For Monitoring Seasonal Snow
--
https://doi.org/10.1029/2025WR042866 <-- shared paper
--
https://eos.org/features/satellite-radar-advances-could-transform-global-snow-monitoring <-- shared technical article
--
H/T @Jack Tarricone, PhD | Assistant Research Scientist @ NASA GSFC/UMD ESSIC | Remote Sensing and Snow Hydrology
“[The authors] review[ed] 25 years of progress in using InSAR to measure changes in snow water equivalent (SWE) and snow depth and discuss[ed] what’s needed to extend these methods to basin-scale snow monitoring with NISAR. [They] hope it’s a useful resource for people interested in snow, SAR/InSAR, remote sensing, and hydrology in general…”
#GIS #spatial #mapping #remotesensing #earthobservation #InterferometricSyntheticApertureRadar #InSAR #literaturereview #research #history #monitoring #spatialanalysis #spatiotemporal #seasonal #snow #water #hydrology #waterresources #snowpack #snowmelt #ablation #melt #runoff #snowwaterequivalent #SWE #NISAR #snowdepth #basin #snowphase #estimation #change #spatial #GIS #mapping #temporal #model #modeling #algorithm #ecosystems #environment #habitat #agriculture #farming #snowmass #satellite -
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 -
Essential Earth Observation Variables For High-Level Multi-Scale Indicators And Policies
--
https://doi.org/10.1016/j.envsci.2021.12.024 <-- shared paper
--
https://earthobservations.org/about-us/news/remembering-paolo-mazzetti-a-legacy-of-science-kindness-and-collaboration <-- shared author memorial
--
H/T @Paolo Mazzetti | Senior Researcher at the Institute of Technologies and Environmental Intelligence (ITIAm) of CNR
“HIGHLIGHTS:
• Defining Essential Variables (EVs) to describe the global socio-ecological system.
• Setting the objectives of a new Group on Earth Observation (GEO) community activity on EVs.
• Defining criteria for selecting EVs.
• Demonstrating a fully functional workflow on land degradation.
• Presenting a new vision for the mainstreaming of EVs in science-policy interfaces..."
#Earthobservations #Essentialvariables #Indicators #Workflows #Sustainabledevelopmentgoals #Policy #earthobservation #essentialvariables #Indicators #Workflow #sustainabledevelopmentgoals #SDGs #policy #spatial #mapping #remotesensing #EVs #GroupOnEarthObservation #GEO #socioecological #sustainability #earthsystems #Drivers #Pressures #States #Impacts #Responses #sustainability #monitoring #observations #organisation #GlobalEarthObservationSystemofSystems #overview #review #literaturereview #environmental #Essentiality #Evolvability #Unambiguity #Feasibility #ecologicalfootprinting #viability -
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 -
Satellites, HAPS, and aircraft are quietly becoming something more than relays. They're turning into compute nodes.
The Datacom Industry Association Aerospace #WorkingGroup just released a whitepaper on this shift: "Aerospace-enabled Services — The Edge-Cloud Continuum Beyond the Atmosphere."
📄 Read the whitepaper now: https://datacom-ia.eu/2026/07/24/aerospace-wg-releases-whitepaper-on-edge-cloud-continuum-beyond-the-atmosphere/
#Aerospace #EdgeComputing #NTN #EarthObservation #HAPS #Satellite #DigitalInfrastructure #DIA
-
IHI explores Kuva hyperspectral satellites for Japan’s multi-sensor constellation
-
ICEYE to double radar-satellite capacity by late 2027 as demand surges
PARIS — Finland’s ICEYE expects to double global production to 100 radar satellites by the end of 2027,…
#NewsBeep #News #Space #CA #Canada #circulated-c4isrnet #circulated-defense-news #defense-news #dn-dnr #Earthobservation #Europe #Finland #ICEYE #Science #surveillance #syntheric-aperture-radar
https://www.newsbeep.com/ca/760249/ -
ICEYE to double radar-satellite capacity by late 2027 as demand surges
PARIS — Finland’s ICEYE expects to double global production to 100 radar satellites by the end of 2027,…
#NewsBeep #News #Space #AU #Australia #circulated-c4isrnet #circulated-defense-news #defense-news #dn-dnr #Earthobservation #Europe #Finland #Iceye #Science #surveillance #syntheric-aperture-radar
https://www.newsbeep.com/au/759429/ -
[G]lobal Decline In Endorheic Basin Water Storages
--
https://doi.org/10.1038/s41561-018-0265-7 <-- shared paper
--
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 -
Sea Levels Rising Dramatically In Some Areas Due To Land Subsidence [global]
--
https://phys.org/news/2026-05-sea-areas-due-subsidence.html <-- shared technical article
--
https://doi.org/10.1038/s41467-026-72293-z <-- shared paper
--
[#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 -
Bringing imagery and communications under one roof
https://fed.brid.gy/r/https://spacenews.com/bringing-imagery-and-communications-under-one-roof/
-
Active Faults Greece - A Comprehensive Geomorphology-Based 1:25,000 Fault Database
--
https://doi.org/10.1038/s41597-025-06283-z <-- shared paper
--
https://activefaults.eagme.gr/en/ <-- shared Hellenic DataBase of Active Faults (HeDBAF) access
--
#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 -
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
--
https://infonile.org/en/2023/05/battling-for-survival-along-the-warming-source-of-the-blue-nile/ <-- shared technical media article
--
https://doi.org/10.1007/978-3-031-65241-7_4 <-- shared technical book chapter
--
https://doi.org/10.3390/rs8121020 <-- shared 2016 paper
--
#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 -
Remote Sensing And Process Attribution Uncertainties In The Dharali Event [Himalayas, India]
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https://doi.org/10.1038/s44304-026-00211-w <-- shared paper review
--
https://doi.org/10.1038/s44304-026-00191-x <-- shared paper that was reviewed
--
https://doi.org/10.1016/j.nhres.2025.11.001 <-- related shared paper
--
#Dharali #disaster #BhagirathiBasin #India #NorthernIndia #Himalayas #GIS #spatial #mapping #remotesensing #satellite #imagery #earthobservation #trigger #risk #hazard #damage #infrastructure #mountain #geomorphology #glacier #glacial #debrisflow #publicsafety #landuse #paraglacial #rainfall #precipitation #extremeweather #massmovement #landslide #spatialanalysis #spatiotemporal #Bhagirathi #River #water #hydrology #icepatchcollapse -
Overland Flow Pathways [England]
--
https://environment.data.gov.uk/dataset/36e7f4d3-61b2-4e64-aaa2-2b85bceb61a9 <-- shared technical resource / overview
--
#GIS #spatial #mapping #environment #Elevation #Hydrography #hydrology #remotesensing #survey #hydrologicflow #flow #catchment #DigitalElevationModel #LiDAR #remotesensing #earthobservation #opendata #UK #England #Britain #overlandflow #water #hydrology #risk #hazard #pollution #soil #erosion #flood #flooding #risk #hazard #naturalhazard #network #polyline #DTM #landscape #slope #D8 #watershed #ponding #flowdirection #environment #hydroenforced #digitalterrainmodel
#OrdnanceSurvey | #UKEnvironmentAgency -
Observing The Tidal Pulse Of Rivers From Wide-Swath Satellite Altimetry
--
https://doi.org/10.1038/s41586-026-10287-z <-- shared paper
--
https://dahiti.dgfi.tum.de/en/products/river-tides/map/ <-- shared interactive map, ‘River Tides from SWOT’
--
#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 -
Drivers Of Forest Disturbance In Southeast Asia [incl. spatial analysis]
--
https://doi.org/10.1016/j.jag.2026.105220 <-- shared paper 🔗
--
https://github.com/shijuanchen/SEA_forest_dis <-- shared GitHub ‘data repository 🔗
--
#GIS #spatial #mapping #spatialanalysis #spatiotemporal #forest #vegetation #Forestdisturbance #Forestdegradation #Deforestation #remotesensing #SoutheastAsia #Asia #tropicalforests #timeseriesanalysis #geostatistics #disturbance #clearing #planting #agriculture #earthobservation #imagery #CCDC #changedetection #landcover #landuse #change #plantation #cultivation #slashandburn #planning #mitigation #catalogue #conservation #management #landmanagement #machinelearning #imageanalysis #AI -
Predictability Of Earth’s Greenness [incl. spatial]
--
https://doi.org/10.1016/j.isprsjprs.2026.02.038 <-- shared paper
--
https://phys.org/news/2026-02-global-greening-earth-green-shifting.html <-- shared technical article
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https://www.vox.com/down-to-earth/2024/2/7/24057308/earth-global-greening-climate-change-carbon <-- shared technical media article
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https://doi.org/10.1038/s41893-019-0220-7 <-- shared (2019) paper
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#Earth #greenness #deeplearning #AI #usecase #productivity #vegetation #foliage #greening #forecasting #geomorphometry #vegetationindex #NDVI #GIS #spatial #mapping #earthobservation #remotesensing #spatialanalysis #spatiotemporal #satellite #global #landuse #landcover #management #biomass #agriculture #crops #environment #ecosystems #forestcover #sustainability #foodsecurity #soilmoisture #treecover #temperature #parameters #forest #forested #landmanagement #agronomic #irrigation #fertilisation #croprotation #pestcontrol #attentionmodel #metrics