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#geoai — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #geoai, aggregated by home.social.

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

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

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

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

  5. 📅 12th August
    🕕 6:00 PM onwards
    📍 Birkbeck, London

    🔗 Speaker profile: linkedin.com/in/teffen
    🔗 RSVP & details: lgm.jsonsingh.com

    Join us for an evening of geospatial talks, practical ideas, and community discussion. Please spread the word! 🌍

    #LondonGeoMeetup #LGM5 #Geospatial #GIS #GeoAI #Geocoding #MachineLearning #WebDevelopment #OpenSource #LondonTech #Mapping

  6. 📅 12th August
    🕕 6:00 PM onwards
    📍 Birkbeck, London

    🔗 Speaker profile: linkedin.com/in/teffen
    🔗 RSVP & details: lgm.jsonsingh.com

    Join us for an evening of geospatial talks, practical ideas, and community discussion. Please spread the word! 🌍

    #LondonGeoMeetup #LGM5 #Geospatial #GIS #GeoAI #Geocoding #MachineLearning #WebDevelopment #OpenSource #LondonTech #Mapping

  7. 📅 12th August
    🕕 6:00 PM onwards
    📍 Birkbeck, London

    🔗 Speaker profile: linkedin.com/in/teffen
    🔗 RSVP & details: lgm.jsonsingh.com

    Join us for an evening of geospatial talks, practical ideas, and community discussion. Please spread the word! 🌍

    #LondonGeoMeetup #LGM5 #Geospatial #GIS #GeoAI #Geocoding #MachineLearning #WebDevelopment #OpenSource #LondonTech #Mapping

  8. Schneider Electric Agrees to Acquire AiDASH for $350 Million

    Schneider Electric has agreed to acquire AiDASH, the satellite and artificial intelligence company helping utilities monitor vegetation, wildfire…
    #France #FR #Europe #EU #SchneiderElectric #AiDASH #GeoAI #gridresilience #satelliteimagery #utilities #VegetationManagement
    europesays.com/france/62064/

  9. The Importance Of Trusted [spatial] Data In The Real World - And How Geovation Is Evolving
    --
    ordnancesurvey.co.uk/blog/how- <-- shared technical/overview article
    --
    geovation.uk/ <-- shared Geovation home page
    --
    H/T @gareth Sumner | Head of Geovation, Leading innovation, connecting innovators with real world problems and championing design thinking
    “… How can technology 👨‍💻 create meaningful impact in the real world? 🌍
    Today that question feels more relevant than ever.
    While much of the conversation around AI focuses on digital tools and experiences, what I really care about is its potential to improve outcomes in the physical world.
    That's where trusted, foundational data becomes critical – and it has become our north star as Geovation continues to evolve…”
    --
    “Geovation is Ordnance Survey (OS)'s innovation programme, pioneered more than 15 years ago to foster a geospatial ecosystem for startups to solve real world challenges. Now its head, Gareth Sumner, considers the importance of trusted data and AI in today's world and how Geovation is evolving into a national data innovation and impact lab: a place where government data, entrepreneurial talent and real-world challenges come together…”
    #Geovation #AI #machinelearning #innovation #usecase #appliedscience #AI #GeoAI #geospatialecosystem #startups #industrysupport #data #realworld #UK #LocationTech #SpatialInnovation #MappingTheFuture #TechStartups #InnovationHub #Entrepreneurship #FoundersUK #GIS #spatial #mapping #BritainMapped #MadeInUK
    @OrdnanceSurvey | @Geovation

  10. The Importance Of Trusted [spatial] Data In The Real World - And How Geovation Is Evolving
    --
    ordnancesurvey.co.uk/blog/how- <-- shared technical/overview article
    --
    geovation.uk/ <-- shared Geovation home page
    --
    H/T @gareth Sumner | Head of Geovation, Leading innovation, connecting innovators with real world problems and championing design thinking
    “… How can technology 👨‍💻 create meaningful impact in the real world? 🌍
    Today that question feels more relevant than ever.
    While much of the conversation around AI focuses on digital tools and experiences, what I really care about is its potential to improve outcomes in the physical world.
    That's where trusted, foundational data becomes critical – and it has become our north star as Geovation continues to evolve…”
    --
    “Geovation is Ordnance Survey (OS)'s innovation programme, pioneered more than 15 years ago to foster a geospatial ecosystem for startups to solve real world challenges. Now its head, Gareth Sumner, considers the importance of trusted data and AI in today's world and how Geovation is evolving into a national data innovation and impact lab: a place where government data, entrepreneurial talent and real-world challenges come together…”
    #Geovation #AI #machinelearning #innovation #usecase #appliedscience #AI #GeoAI #geospatialecosystem #startups #industrysupport #data #realworld #UK #LocationTech #SpatialInnovation #MappingTheFuture #TechStartups #InnovationHub #Entrepreneurship #FoundersUK #GIS #spatial #mapping #BritainMapped #MadeInUK
    @OrdnanceSurvey | @Geovation

  11. The Importance Of Trusted [spatial] Data In The Real World - And How Geovation Is Evolving
    --
    ordnancesurvey.co.uk/blog/how- <-- shared technical/overview article
    --
    geovation.uk/ <-- shared Geovation home page
    --
    H/T @gareth Sumner | Head of Geovation, Leading innovation, connecting innovators with real world problems and championing design thinking
    “… How can technology 👨‍💻 create meaningful impact in the real world? 🌍
    Today that question feels more relevant than ever.
    While much of the conversation around AI focuses on digital tools and experiences, what I really care about is its potential to improve outcomes in the physical world.
    That's where trusted, foundational data becomes critical – and it has become our north star as Geovation continues to evolve…”
    --
    “Geovation is Ordnance Survey (OS)'s innovation programme, pioneered more than 15 years ago to foster a geospatial ecosystem for startups to solve real world challenges. Now its head, Gareth Sumner, considers the importance of trusted data and AI in today's world and how Geovation is evolving into a national data innovation and impact lab: a place where government data, entrepreneurial talent and real-world challenges come together…”
    #Geovation #AI #machinelearning #innovation #usecase #appliedscience #AI #GeoAI #geospatialecosystem #startups #industrysupport #data #realworld #UK #LocationTech #SpatialInnovation #MappingTheFuture #TechStartups #InnovationHub #Entrepreneurship #FoundersUK #GIS #spatial #mapping #BritainMapped #MadeInUK
    @OrdnanceSurvey | @Geovation

  12. The Importance Of Trusted [spatial] Data In The Real World - And How Geovation Is Evolving
    --
    ordnancesurvey.co.uk/blog/how- <-- shared technical/overview article
    --
    geovation.uk/ <-- shared Geovation home page
    --
    H/T @gareth Sumner | Head of Geovation, Leading innovation, connecting innovators with real world problems and championing design thinking
    “… How can technology 👨‍💻 create meaningful impact in the real world? 🌍
    Today that question feels more relevant than ever.
    While much of the conversation around AI focuses on digital tools and experiences, what I really care about is its potential to improve outcomes in the physical world.
    That's where trusted, foundational data becomes critical – and it has become our north star as Geovation continues to evolve…”
    --
    “Geovation is Ordnance Survey (OS)'s innovation programme, pioneered more than 15 years ago to foster a geospatial ecosystem for startups to solve real world challenges. Now its head, Gareth Sumner, considers the importance of trusted data and AI in today's world and how Geovation is evolving into a national data innovation and impact lab: a place where government data, entrepreneurial talent and real-world challenges come together…”
    #Geovation #AI #machinelearning #innovation #usecase #appliedscience #AI #GeoAI #geospatialecosystem #startups #industrysupport #data #realworld #UK #LocationTech #SpatialInnovation #MappingTheFuture #TechStartups #InnovationHub #Entrepreneurship #FoundersUK #GIS #spatial #mapping #BritainMapped #MadeInUK
    @OrdnanceSurvey | @Geovation

  13. The Importance Of Trusted [spatial] Data In The Real World - And How Geovation Is Evolving
    --
    ordnancesurvey.co.uk/blog/how- <-- shared technical/overview article
    --
    geovation.uk/ <-- shared Geovation home page
    --
    H/T @gareth Sumner | Head of Geovation, Leading innovation, connecting innovators with real world problems and championing design thinking
    “… How can technology 👨‍💻 create meaningful impact in the real world? 🌍
    Today that question feels more relevant than ever.
    While much of the conversation around AI focuses on digital tools and experiences, what I really care about is its potential to improve outcomes in the physical world.
    That's where trusted, foundational data becomes critical – and it has become our north star as Geovation continues to evolve…”
    --
    “Geovation is Ordnance Survey (OS)'s innovation programme, pioneered more than 15 years ago to foster a geospatial ecosystem for startups to solve real world challenges. Now its head, Gareth Sumner, considers the importance of trusted data and AI in today's world and how Geovation is evolving into a national data innovation and impact lab: a place where government data, entrepreneurial talent and real-world challenges come together…”

    @OrdnanceSurvey | @Geovation

  14. Using Geospatial Analysis and Explainable Machine Learning to Examine Risk Factors of Out-of-Hospital Cardiac Arrest Survival Outcome
    --
    openscholar.uga.edu/record/269 <-- shared technical publication / dissertation
    --
    aag.org/award-grant/william-l- <-- shared @AAG William L. Garrison Award for Best Dissertation in Computational Geography
    --
    [again, way outside any expertise I might have, but fascinating spatial analysis use case…]
    H/T @Jielu Zhang | Postdoctoral Researcher @ Harvard University
    “[The authors] Ph.D. dissertation "Using Geospatial Analysis and Explainable Machine Learning to Examine Risk Factors of Out-of-Hospital Cardiac Arrest Survival Outcome" [1st link above] has received the 2026 biennial William L. Garrison Award for Best Dissertation in Computational Geography from the American Association of Geographers… [2nd link above.]
    In [their] research, [they] develop[ed] Explainable GeoAI and Causal GeoAI methods that combine geographic data and artificial intelligence to expose and ameliorate health disparities by delivering models that not only predict risks but also illuminate how and where to intervene. While [their] dissertation focused on cardiovascular disease, these approaches are broadly applicable to public health, medicine, urban planning, environmental exposure, and resilience research…”
    #explainable #causal #AI #model #modeling #PublicHealth #GIS #spatial #mapping #spatialanalysis #spatiotemporal #AAG2026 #AAG #Award #geostatistics #Georgia #health #risk #hazard #cardiacarrest #cardiovacscular #usecase #metrics #midocine #urbanplanning #resilience #survival #OutofHospital #PhD #Dissertation #CardiacArrest #AutomatedExternalDefibrillator #SpatialOptimization #GeographicallyExplainableArtificialIntelligence #GeoAI #GeoXAI #SpatiallyAwareCausalInference #OverlayedSpatioTemporalOptimization #healthcare #medical #intervention #GIS #spatial #mappingt #spatialanalysis #spatiotemporal #heart #heartattack #AED #survival #survivaloutcomes #machinelearning #AI #publichealth #healthgeographers #counterfactual #explainable #deeplearning #model #modeling

  15. Using Geospatial Analysis and Explainable Machine Learning to Examine Risk Factors of Out-of-Hospital Cardiac Arrest Survival Outcome
    --
    openscholar.uga.edu/record/269 <-- shared technical publication / dissertation
    --
    aag.org/award-grant/william-l- <-- shared @AAG William L. Garrison Award for Best Dissertation in Computational Geography
    --
    [again, way outside any expertise I might have, but fascinating spatial analysis use case…]
    H/T @Jielu Zhang | Postdoctoral Researcher @ Harvard University
    “[The authors] Ph.D. dissertation "Using Geospatial Analysis and Explainable Machine Learning to Examine Risk Factors of Out-of-Hospital Cardiac Arrest Survival Outcome" [1st link above] has received the 2026 biennial William L. Garrison Award for Best Dissertation in Computational Geography from the American Association of Geographers… [2nd link above.]
    In [their] research, [they] develop[ed] Explainable GeoAI and Causal GeoAI methods that combine geographic data and artificial intelligence to expose and ameliorate health disparities by delivering models that not only predict risks but also illuminate how and where to intervene. While [their] dissertation focused on cardiovascular disease, these approaches are broadly applicable to public health, medicine, urban planning, environmental exposure, and resilience research…”
    #explainable #causal #AI #model #modeling #PublicHealth #GIS #spatial #mapping #spatialanalysis #spatiotemporal #AAG2026 #AAG #Award #geostatistics #Georgia #health #risk #hazard #cardiacarrest #cardiovacscular #usecase #metrics #midocine #urbanplanning #resilience #survival #OutofHospital #PhD #Dissertation #CardiacArrest #AutomatedExternalDefibrillator #SpatialOptimization #GeographicallyExplainableArtificialIntelligence #GeoAI #GeoXAI #SpatiallyAwareCausalInference #OverlayedSpatioTemporalOptimization #healthcare #medical #intervention #GIS #spatial #mappingt #spatialanalysis #spatiotemporal #heart #heartattack #AED #survival #survivaloutcomes #machinelearning #AI #publichealth #healthgeographers #counterfactual #explainable #deeplearning #model #modeling

  16. Using Geospatial Analysis and Explainable Machine Learning to Examine Risk Factors of Out-of-Hospital Cardiac Arrest Survival Outcome
    --
    openscholar.uga.edu/record/269 <-- shared technical publication / dissertation
    --
    aag.org/award-grant/william-l- <-- shared @AAG William L. Garrison Award for Best Dissertation in Computational Geography
    --
    [again, way outside any expertise I might have, but fascinating spatial analysis use case…]
    H/T @Jielu Zhang | Postdoctoral Researcher @ Harvard University
    “[The authors] Ph.D. dissertation "Using Geospatial Analysis and Explainable Machine Learning to Examine Risk Factors of Out-of-Hospital Cardiac Arrest Survival Outcome" [1st link above] has received the 2026 biennial William L. Garrison Award for Best Dissertation in Computational Geography from the American Association of Geographers… [2nd link above.]
    In [their] research, [they] develop[ed] Explainable GeoAI and Causal GeoAI methods that combine geographic data and artificial intelligence to expose and ameliorate health disparities by delivering models that not only predict risks but also illuminate how and where to intervene. While [their] dissertation focused on cardiovascular disease, these approaches are broadly applicable to public health, medicine, urban planning, environmental exposure, and resilience research…”
    #explainable #causal #AI #model #modeling #PublicHealth #GIS #spatial #mapping #spatialanalysis #spatiotemporal #AAG2026 #AAG #Award #geostatistics #Georgia #health #risk #hazard #cardiacarrest #cardiovacscular #usecase #metrics #midocine #urbanplanning #resilience #survival #OutofHospital #PhD #Dissertation #CardiacArrest #AutomatedExternalDefibrillator #SpatialOptimization #GeographicallyExplainableArtificialIntelligence #GeoAI #GeoXAI #SpatiallyAwareCausalInference #OverlayedSpatioTemporalOptimization #healthcare #medical #intervention #GIS #spatial #mappingt #spatialanalysis #spatiotemporal #heart #heartattack #AED #survival #survivaloutcomes #machinelearning #AI #publichealth #healthgeographers #counterfactual #explainable #deeplearning #model #modeling

  17. Using Geospatial Analysis and Explainable Machine Learning to Examine Risk Factors of Out-of-Hospital Cardiac Arrest Survival Outcome
    --
    openscholar.uga.edu/record/269 <-- shared technical publication / dissertation
    --
    aag.org/award-grant/william-l- <-- shared @AAG William L. Garrison Award for Best Dissertation in Computational Geography
    --
    [again, way outside any expertise I might have, but fascinating spatial analysis use case…]
    H/T @Jielu Zhang | Postdoctoral Researcher @ Harvard University
    “[The authors] Ph.D. dissertation "Using Geospatial Analysis and Explainable Machine Learning to Examine Risk Factors of Out-of-Hospital Cardiac Arrest Survival Outcome" [1st link above] has received the 2026 biennial William L. Garrison Award for Best Dissertation in Computational Geography from the American Association of Geographers… [2nd link above.]
    In [their] research, [they] develop[ed] Explainable GeoAI and Causal GeoAI methods that combine geographic data and artificial intelligence to expose and ameliorate health disparities by delivering models that not only predict risks but also illuminate how and where to intervene. While [their] dissertation focused on cardiovascular disease, these approaches are broadly applicable to public health, medicine, urban planning, environmental exposure, and resilience research…”
    #explainable #causal #AI #model #modeling #PublicHealth #GIS #spatial #mapping #spatialanalysis #spatiotemporal #AAG2026 #AAG #Award #geostatistics #Georgia #health #risk #hazard #cardiacarrest #cardiovacscular #usecase #metrics #midocine #urbanplanning #resilience #survival #OutofHospital #PhD #Dissertation #CardiacArrest #AutomatedExternalDefibrillator #SpatialOptimization #GeographicallyExplainableArtificialIntelligence #GeoAI #GeoXAI #SpatiallyAwareCausalInference #OverlayedSpatioTemporalOptimization #healthcare #medical #intervention #GIS #spatial #mappingt #spatialanalysis #spatiotemporal #heart #heartattack #AED #survival #survivaloutcomes #machinelearning #AI #publichealth #healthgeographers #counterfactual #explainable #deeplearning #model #modeling

  18. Using Geospatial Analysis and Explainable Machine Learning to Examine Risk Factors of Out-of-Hospital Cardiac Arrest Survival Outcome
    --
    openscholar.uga.edu/record/269 <-- shared technical publication / dissertation
    --
    aag.org/award-grant/william-l- <-- shared @AAG William L. Garrison Award for Best Dissertation in Computational Geography
    --
    [again, way outside any expertise I might have, but fascinating spatial analysis use case…]
    H/T @Jielu Zhang | Postdoctoral Researcher @ Harvard University
    “[The authors] Ph.D. dissertation "Using Geospatial Analysis and Explainable Machine Learning to Examine Risk Factors of Out-of-Hospital Cardiac Arrest Survival Outcome" [1st link above] has received the 2026 biennial William L. Garrison Award for Best Dissertation in Computational Geography from the American Association of Geographers… [2nd link above.]
    In [their] research, [they] develop[ed] Explainable GeoAI and Causal GeoAI methods that combine geographic data and artificial intelligence to expose and ameliorate health disparities by delivering models that not only predict risks but also illuminate how and where to intervene. While [their] dissertation focused on cardiovascular disease, these approaches are broadly applicable to public health, medicine, urban planning, environmental exposure, and resilience research…”

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

    #RemoteSensing #GeoAI #Geography #Satellites #EarthObservation

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

    #RemoteSensing #GeoAI #Geography #Satellites #EarthObservation

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

    #RemoteSensing #GeoAI #Geography #Satellites #EarthObservation

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

    #RemoteSensing #GeoAI #Geography #Satellites #EarthObservation

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

    #RemoteSensing #GeoAI #Geography #Satellites #EarthObservation

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

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

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

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

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

  29. 環境部報告指全國PM2.5濃度下降,成大研究:氣候變遷改變台灣空汙熱區分佈
    中央通訊社 2026-06-21 16:00:00 CST
    全國PM2.5濃度近年有所改善,各縣市持續引入科技執法與人工智慧檢測。然而成大研究警示,氣候變遷將重塑空污版圖,未來台灣東北部、中彰與高屏地區恐逆勢成為PM2.5新熱區,挑戰現行防制策略。
    https://www.thenewslens.com/article/268699
    #氣候變遷 #Geo-AI #全球暖化 #呼吸道 #空氣污染防制總檢討 #PM2.5 #台灣空汙風險分布 #空氣污染 #環境 #濕沉降作用
  30. Permafrost Distribution, Degradation, And Potential Mass Movement Cascades In The Western Himalaya Using Machine Learning And Numerical Models
    --
    doi.org/10.1038/s44304-026-002 <-- shared paper
    --
    doi.org/10.1038/s41598-025-220 <-- shared (earlier) paper
    --
    doi.org/10.1080/2150704X.2025. <-- shared (earlier) paper
    --
    H/T @abhinav Alangadan
    “Can we develop a first-order understanding of permafrost degradation and glacial lakes exposed to degradation-induced mass movements in the Himalaya?
    [The authors] tried to address this question. The study [first link above] integrates machine learning, statistical modeling, and numerical modeling to investigate high-resolution permafrost distribution, potential degradation, and associated mass-movement hazards in the Kinnaur district of Himachal Pradesh, India.
    Using rock glaciers as proxies, [they] generated a high-resolution permafrost distribution using machine learning, while potential degradation zones were delineated using the 0°C isotherm as a first-order indicator. [They] further identified glacial lakes located near potentially degrading permafrost zones and reconstructed their bathymetry. A detailed scenario-based GLOF process-chain simulation was then carried out for Kashang Lake using r.avaflow and HEC-RAS.
    [Their] results indicate that seven glacial lakes in #Kinnaur are located close to potentially degrading permafrost zones. The simulations further show that a potential GLOF from Kashang Lake could inundate critical downstream infrastructure, including nearly 11 km of National Highway 5…”
    #permafrost #distribution #GIS #spatial #mapping #Himalayas #India #Kinnaur #HimachalPradesh #KashangLake #massmovement #engineeringgeology #machinelearning #AI #model #modeling #numericalmodel #glaciallakes #glaciet #glacial #glaciallakeoutburstflood #GLOF #cryosphere #geostatistics #rockglaciers #GeoAI #bathymetry #processchainsimulation #HECRAS #avaflow #risk #hazard #mitigation #riskassessment #infrastructure #HEP #publicsafety #downstream #avalanche

  31. Permafrost Distribution, Degradation, And Potential Mass Movement Cascades In The Western Himalaya Using Machine Learning And Numerical Models
    --
    doi.org/10.1038/s44304-026-002 <-- shared paper
    --
    doi.org/10.1038/s41598-025-220 <-- shared (earlier) paper
    --
    doi.org/10.1080/2150704X.2025. <-- shared (earlier) paper
    --
    H/T @abhinav Alangadan
    “Can we develop a first-order understanding of permafrost degradation and glacial lakes exposed to degradation-induced mass movements in the Himalaya?
    [The authors] tried to address this question. The study [first link above] integrates machine learning, statistical modeling, and numerical modeling to investigate high-resolution permafrost distribution, potential degradation, and associated mass-movement hazards in the Kinnaur district of Himachal Pradesh, India.
    Using rock glaciers as proxies, [they] generated a high-resolution permafrost distribution using machine learning, while potential degradation zones were delineated using the 0°C isotherm as a first-order indicator. [They] further identified glacial lakes located near potentially degrading permafrost zones and reconstructed their bathymetry. A detailed scenario-based GLOF process-chain simulation was then carried out for Kashang Lake using r.avaflow and HEC-RAS.
    [Their] results indicate that seven glacial lakes in #Kinnaur are located close to potentially degrading permafrost zones. The simulations further show that a potential GLOF from Kashang Lake could inundate critical downstream infrastructure, including nearly 11 km of National Highway 5…”
    #permafrost #distribution #GIS #spatial #mapping #Himalayas #India #Kinnaur #HimachalPradesh #KashangLake #massmovement #engineeringgeology #machinelearning #AI #model #modeling #numericalmodel #glaciallakes #glaciet #glacial #glaciallakeoutburstflood #GLOF #cryosphere #geostatistics #rockglaciers #GeoAI #bathymetry #processchainsimulation #HECRAS #avaflow #risk #hazard #mitigation #riskassessment #infrastructure #HEP #publicsafety #downstream #avalanche

  32. Permafrost Distribution, Degradation, And Potential Mass Movement Cascades In The Western Himalaya Using Machine Learning And Numerical Models
    --
    doi.org/10.1038/s44304-026-002 <-- shared paper
    --
    doi.org/10.1038/s41598-025-220 <-- shared (earlier) paper
    --
    doi.org/10.1080/2150704X.2025. <-- shared (earlier) paper
    --
    H/T @abhinav Alangadan
    “Can we develop a first-order understanding of permafrost degradation and glacial lakes exposed to degradation-induced mass movements in the Himalaya?
    [The authors] tried to address this question. The study [first link above] integrates machine learning, statistical modeling, and numerical modeling to investigate high-resolution permafrost distribution, potential degradation, and associated mass-movement hazards in the Kinnaur district of Himachal Pradesh, India.
    Using rock glaciers as proxies, [they] generated a high-resolution permafrost distribution using machine learning, while potential degradation zones were delineated using the 0°C isotherm as a first-order indicator. [They] further identified glacial lakes located near potentially degrading permafrost zones and reconstructed their bathymetry. A detailed scenario-based GLOF process-chain simulation was then carried out for Kashang Lake using r.avaflow and HEC-RAS.
    [Their] results indicate that seven glacial lakes in #Kinnaur are located close to potentially degrading permafrost zones. The simulations further show that a potential GLOF from Kashang Lake could inundate critical downstream infrastructure, including nearly 11 km of National Highway 5…”
    #permafrost #distribution #GIS #spatial #mapping #Himalayas #India #Kinnaur #HimachalPradesh #KashangLake #massmovement #engineeringgeology #machinelearning #AI #model #modeling #numericalmodel #glaciallakes #glaciet #glacial #glaciallakeoutburstflood #GLOF #cryosphere #geostatistics #rockglaciers #GeoAI #bathymetry #processchainsimulation #HECRAS #avaflow #risk #hazard #mitigation #riskassessment #infrastructure #HEP #publicsafety #downstream #avalanche

  33. Permafrost Distribution, Degradation, And Potential Mass Movement Cascades In The Western Himalaya Using Machine Learning And Numerical Models
    --
    doi.org/10.1038/s44304-026-002 <-- shared paper
    --
    doi.org/10.1038/s41598-025-220 <-- shared (earlier) paper
    --
    doi.org/10.1080/2150704X.2025. <-- shared (earlier) paper
    --
    H/T @abhinav Alangadan
    “Can we develop a first-order understanding of permafrost degradation and glacial lakes exposed to degradation-induced mass movements in the Himalaya?
    [The authors] tried to address this question. The study [first link above] integrates machine learning, statistical modeling, and numerical modeling to investigate high-resolution permafrost distribution, potential degradation, and associated mass-movement hazards in the Kinnaur district of Himachal Pradesh, India.
    Using rock glaciers as proxies, [they] generated a high-resolution permafrost distribution using machine learning, while potential degradation zones were delineated using the 0°C isotherm as a first-order indicator. [They] further identified glacial lakes located near potentially degrading permafrost zones and reconstructed their bathymetry. A detailed scenario-based GLOF process-chain simulation was then carried out for Kashang Lake using r.avaflow and HEC-RAS.
    [Their] results indicate that seven glacial lakes in #Kinnaur are located close to potentially degrading permafrost zones. The simulations further show that a potential GLOF from Kashang Lake could inundate critical downstream infrastructure, including nearly 11 km of National Highway 5…”
    #permafrost #distribution #GIS #spatial #mapping #Himalayas #India #Kinnaur #HimachalPradesh #KashangLake #massmovement #engineeringgeology #machinelearning #AI #model #modeling #numericalmodel #glaciallakes #glaciet #glacial #glaciallakeoutburstflood #GLOF #cryosphere #geostatistics #rockglaciers #GeoAI #bathymetry #processchainsimulation #HECRAS #avaflow #risk #hazard #mitigation #riskassessment #infrastructure #HEP #publicsafety #downstream #avalanche

  34. Permafrost Distribution, Degradation, And Potential Mass Movement Cascades In The Western Himalaya Using Machine Learning And Numerical Models
    --
    doi.org/10.1038/s44304-026-002 <-- shared paper
    --
    doi.org/10.1038/s41598-025-220 <-- shared (earlier) paper
    --
    doi.org/10.1080/2150704X.2025. <-- shared (earlier) paper
    --
    H/T @abhinav Alangadan
    “Can we develop a first-order understanding of permafrost degradation and glacial lakes exposed to degradation-induced mass movements in the Himalaya?
    [The authors] tried to address this question. The study [first link above] integrates machine learning, statistical modeling, and numerical modeling to investigate high-resolution permafrost distribution, potential degradation, and associated mass-movement hazards in the Kinnaur district of Himachal Pradesh, India.
    Using rock glaciers as proxies, [they] generated a high-resolution permafrost distribution using machine learning, while potential degradation zones were delineated using the 0°C isotherm as a first-order indicator. [They] further identified glacial lakes located near potentially degrading permafrost zones and reconstructed their bathymetry. A detailed scenario-based GLOF process-chain simulation was then carried out for Kashang Lake using r.avaflow and HEC-RAS.
    [Their] results indicate that seven glacial lakes in are located close to potentially degrading permafrost zones. The simulations further show that a potential GLOF from Kashang Lake could inundate critical downstream infrastructure, including nearly 11 km of National Highway 5…”

  35. Last week, the 1st #GeoAI conference took place at #UGent! I had the opportunity to attend interesting talks, engage in discussions about the future of the domain, host a workshop about the #DarkSideOfGeoAI, and, last but not least, present our work on #VISQAM, funded by #NFDI4Earth and made 100% in-house at IFGI, Uni Münster.

    Check out our proceedings paper about VISQAM, an open dataset that comprises 1200 thematic geographic maps annotated with 4500+ QA pairs: doi.org/10.5281/zenodo.20273244.

  36. Last week, the 1st #GeoAI conference took place at #UGent! I had the opportunity to attend interesting talks, engage in discussions about the future of the domain, host a workshop about the #DarkSideOfGeoAI, and, last but not least, present our work on #VISQAM, funded by #NFDI4Earth and made 100% in-house at IFGI, Uni Münster.

    Check out our proceedings paper about VISQAM, an open dataset that comprises 1200 thematic geographic maps annotated with 4500+ QA pairs: doi.org/10.5281/zenodo.20273244.

  37. Last week, the 1st #GeoAI conference took place at #UGent! I had the opportunity to attend interesting talks, engage in discussions about the future of the domain, host a workshop about the #DarkSideOfGeoAI, and, last but not least, present our work on #VISQAM, funded by #NFDI4Earth and made 100% in-house at IFGI, Uni Münster.

    Check out our proceedings paper about VISQAM, an open dataset that comprises 1200 thematic geographic maps annotated with 4500+ QA pairs: doi.org/10.5281/zenodo.20273244.

  38. Last week, the 1st #GeoAI conference took place at #UGent! I had the opportunity to attend interesting talks, engage in discussions about the future of the domain, host a workshop about the #DarkSideOfGeoAI, and, last but not least, present our work on #VISQAM, funded by #NFDI4Earth and made 100% in-house at IFGI, Uni Münster.

    Check out our proceedings paper about VISQAM, an open dataset that comprises 1200 thematic geographic maps annotated with 4500+ QA pairs: doi.org/10.5281/zenodo.20273244.