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#geomorphometry — Public Fediverse posts

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

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  1. GMIA-NEXT - Next-Generation Global Map of Irrigated Areas |
    --
    doi.org/10.21203/rs.3.rs-10085 <-- shared paper
    --
    zenodo.org/records/17627111 <-- shared open data
    --
    H/T @kyle Davis
    “Irrigation plays a critical role in global food production and climate adaptation and exercises profound influence over humanity's water use. Yet despite its critical importance, there is a persistent lack of understanding of fine-scale irrigation patterns across the planet, knowledge which is essential for informing global food security and sustainability targets. Utilizing either statistical downscaling or remote sensing approaches, existing global irrigation datasets are constrained by coarse spatial resolutions, a lack of timeliness, or varying robustness and reliability. To address this gap, here [they] integrate[d] multi-source Earth observation and environmental datasets and use[d] machine learning to develop a medium-resolution (30 metre) global irrigated area dataset for the 2023/24 growing season. Within existing cropland extent, we leverage a newly compiled set of georeferenced irrigated (N=230,683) and non-irrigated (N=153,194) ground-truth points and integrate seasonal vegetation metrics derived from Landsat 8/9 imagery with agroecological-zone information and hydroclimatic and topographic variables. [They] subsequently develop and evaluate two machine-learning frameworks, a continental Agro-Ecological Zone (AEZ) tile-based framework and a continental-scale framework, and apply the best-performing approach for each continent. Evaluation using held-out test samples yielded a global accuracy of 80.5 ± 2.1%. The resulting maps were also validated against independent global and national irrigation datasets and statistics, demonstrating broad agreement in the spatial distribution of irrigated areas. This approach is robust and reliable because it is built on a harmonized global ground-truth database, incorporates multiple predictors, and is rigorously validated using independent datasets. All code, ground-truth, and data products are freely and publicly available [link above] and can serve as a robust, scale-neutral, and fully reproducible framework for fine-resolution irrigation mapping. These advances provide the critical and long-needed foundation for near-real-time monitoring and early warning systems, and fine-scale land and water resource management…”
    #IrrigatedAreas #Mapping #GIS #spatial #mapping #spatialanalysis #spatiotemporal #global #irrigation #water #hydrology #hydrography #waterresources #farming #agriculture #opendata #remotesensing #earthobservation #geomorphometry #AI #machinelearning #LLM #model #modeling #WaterManagement #opendata #AgroEcologicalZone #AEZ #cropland #irrigatedareas #foodproduction #wateruse #humanimpacts #EarthObservation #remotesensing #earlywarning #monitoring #FoodandAgricultureOrganizationFAO #FAO
    @FAO - Food and Agriculture Organization

  2. GMIA-NEXT - Next-Generation Global Map of Irrigated Areas |
    --
    doi.org/10.21203/rs.3.rs-10085 <-- shared paper
    --
    zenodo.org/records/17627111 <-- shared open data
    --
    H/T @kyle Davis
    “Irrigation plays a critical role in global food production and climate adaptation and exercises profound influence over humanity's water use. Yet despite its critical importance, there is a persistent lack of understanding of fine-scale irrigation patterns across the planet, knowledge which is essential for informing global food security and sustainability targets. Utilizing either statistical downscaling or remote sensing approaches, existing global irrigation datasets are constrained by coarse spatial resolutions, a lack of timeliness, or varying robustness and reliability. To address this gap, here [they] integrate[d] multi-source Earth observation and environmental datasets and use[d] machine learning to develop a medium-resolution (30 metre) global irrigated area dataset for the 2023/24 growing season. Within existing cropland extent, we leverage a newly compiled set of georeferenced irrigated (N=230,683) and non-irrigated (N=153,194) ground-truth points and integrate seasonal vegetation metrics derived from Landsat 8/9 imagery with agroecological-zone information and hydroclimatic and topographic variables. [They] subsequently develop and evaluate two machine-learning frameworks, a continental Agro-Ecological Zone (AEZ) tile-based framework and a continental-scale framework, and apply the best-performing approach for each continent. Evaluation using held-out test samples yielded a global accuracy of 80.5 ± 2.1%. The resulting maps were also validated against independent global and national irrigation datasets and statistics, demonstrating broad agreement in the spatial distribution of irrigated areas. This approach is robust and reliable because it is built on a harmonized global ground-truth database, incorporates multiple predictors, and is rigorously validated using independent datasets. All code, ground-truth, and data products are freely and publicly available [link above] and can serve as a robust, scale-neutral, and fully reproducible framework for fine-resolution irrigation mapping. These advances provide the critical and long-needed foundation for near-real-time monitoring and early warning systems, and fine-scale land and water resource management…”

    @FAO - Food and Agriculture Organization

  3. Remote Sensing And The New Global River Science
    --
    doi.org/10.1038/s44221-026-006 <-- shared paper
    --
    “Rivers impact the well-being of humans and the environment. As they increasingly face planetary-scale stressors, it is critically important to monitor and understand rivers at the global scale. As the only synoptic resource for global primary data on rivers, satellite remote sensing has recently begun to provide unprecedented opportunities for the monitoring, understanding, and prediction of global river behaviour. Despite these advances, the role of satellite remote sensing in global river science has still not been fully explored. New satellite systems and algorithms will enable substantial improvements in river measurements, provide new answers to long-standing or newly emerging scientific questions, and eventually update basic knowledge of rivers to advance global river science. In this [paper they] explore how remote sensing has been used to study the world’s rivers, examine challenges and opportunities for further advancing our understanding of rivers using existing and upcoming sensors, and identify possible solutions and future research directions…”
    #GIS #spatial #mapping #water #hydrology #satellite #remotsesensing #earthobservation #hydrography #spatialanalysis #spatiotemporal #physicalgeography #change #river #global #model #modeling #research #hydrogeomorphology #geomorphometry #riverine #humanimpacts #waterquality #waterresources #watermanagement #infrastructure #lake #reservoir #dam #impoundment #canals #avulsion #overbank #flood #flooding #erosion #sedimentation #morphology #network #downstream

  4. Remote Sensing And The New Global River Science
    --
    doi.org/10.1038/s44221-026-006 <-- shared paper
    --
    “Rivers impact the well-being of humans and the environment. As they increasingly face planetary-scale stressors, it is critically important to monitor and understand rivers at the global scale. As the only synoptic resource for global primary data on rivers, satellite remote sensing has recently begun to provide unprecedented opportunities for the monitoring, understanding, and prediction of global river behaviour. Despite these advances, the role of satellite remote sensing in global river science has still not been fully explored. New satellite systems and algorithms will enable substantial improvements in river measurements, provide new answers to long-standing or newly emerging scientific questions, and eventually update basic knowledge of rivers to advance global river science. In this [paper they] explore how remote sensing has been used to study the world’s rivers, examine challenges and opportunities for further advancing our understanding of rivers using existing and upcoming sensors, and identify possible solutions and future research directions…”

  5. 📘 Geomorphometry: Concepts, Software, Applications (2nd ed.) by Reuter, Grohmann & Lecours is coming this fall!

    A new edition covering approaches and applications in quantitative terrain analysis and Earth surface processes.

    shop.elsevier.com/books/geomor

  6. 📘 Geomorphometry: Concepts, Software, Applications (2nd ed.) by Reuter, Grohmann & Lecours is coming this fall!

    A new edition covering approaches and applications in quantitative terrain analysis and Earth surface processes.

    shop.elsevier.com/books/geomor

    #Geomorphometry #GIScience #EarthScience

  7. How Space Weather Could Bust The AI Boom
    --
    spacenews.com/how-space-weathe <-- shared technical article
    --
    futurism.com/artificial-intell <-- shared technical article, “AI Data Centers Pushing Electric Grid Into Meltdown”
    --
    doi.org/10.1146/annurev-earth- <-- shared 2026 paper, “Magnetic Storms and Geoelectric Hazards”
    --
    #AI #datcenters #infrastructure #impacts #solarstorms #spaceweather #risk #hazards #overloading #electricity #energy #powersupply #energygrid #vulnerable #transmission #energy #demand #consumers #geoelectrical #geomagnetism #blackout #damage #cost #economics #equipment #transformers #carringtonevent #NERC #grid #reliability #electricaldemand #utilities #magneticstorm #electromagneticinduction #extremeevent #historicalevent #hazardanalysis #spaceweather #history #Carrington #geoelectric #humanimpacts #risk #hazard #monitoring #network #geology #geomagnetism #impedance #rock #soil #utilities #electricaltransmission #powerlines #magnetotelluric #sensor #blackout #brownout #energy #geoelectrichazard #geoelectric #GIS #spatial #mapping #spatialanalysis #spatiotemporal #model #modeling #geomagnetism #geomagneticstorm #telecommunication #electronics #hardened #geography #mitigation #preparedness #geomorphology #geomorphometry #surfacegeology #cost #economics #disaster #impacts #technology #InternetOfThings #internet #USA #review #CONUS #numericalmodeling #realtimemonitoring #AIBoom #Bust
    @North American Electric Reliability Corporation (NERC)

  8. How Space Weather Could Bust The AI Boom
    --
    spacenews.com/how-space-weathe <-- shared technical article
    --
    futurism.com/artificial-intell <-- shared technical article, “AI Data Centers Pushing Electric Grid Into Meltdown”
    --
    doi.org/10.1146/annurev-earth- <-- shared 2026 paper, “Magnetic Storms and Geoelectric Hazards”
    --

    @North American Electric Reliability Corporation (NERC)

  9. 🌟Besided the 𝗯𝗶𝗲𝗻𝗻𝗶𝗮𝗹 Geomorphometry 𝗰𝗼𝗻𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝘀𝗲𝗿𝗶𝗲𝘀 and the thematic session at 𝗘𝗚𝗨 and 𝗔𝗢𝗚𝗦, the International Society for Geomorphometry ISG this year organizes a session at AGU 2926: EP025 - Novel data, methods and application in Geomorphometry

    The call for abstract is now open until 𝗔𝘂𝗴𝘂𝘀𝘁 𝟱!

    👉𝗦𝘂𝗯𝗺𝗶𝘁 your abstract here:
    lnkd.in/dbSfSmrY

    👉𝗝𝗼𝗶𝗻 𝗼𝘂𝗿 𝗴𝗿𝗼𝘂𝗽 on LinkedIn:
    lnkd.in/dwUYwc4N

    👉𝗟𝗲𝗮𝗿𝗻 𝗺𝗼𝗿𝗲 about the 𝗜𝗦𝗚 at:
    lnkd.in/d5WKpW6n

    #AGU26
    #geomorphometry

  10. 🌟Besided the 𝗯𝗶𝗲𝗻𝗻𝗶𝗮𝗹 Geomorphometry 𝗰𝗼𝗻𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝘀𝗲𝗿𝗶𝗲𝘀 and the thematic session at 𝗘𝗚𝗨 and 𝗔𝗢𝗚𝗦, the International Society for Geomorphometry ISG this year organizes a session at AGU 2926: EP025 - Novel data, methods and application in Geomorphometry

    The call for abstract is now open until 𝗔𝘂𝗴𝘂𝘀𝘁 𝟱!

    👉𝗦𝘂𝗯𝗺𝗶𝘁 your abstract here:
    lnkd.in/dbSfSmrY

    👉𝗝𝗼𝗶𝗻 𝗼𝘂𝗿 𝗴𝗿𝗼𝘂𝗽 on LinkedIn:
    lnkd.in/dwUYwc4N

    👉𝗟𝗲𝗮𝗿𝗻 𝗺𝗼𝗿𝗲 about the 𝗜𝗦𝗚 at:
    lnkd.in/d5WKpW6n

    #AGU26
    #geomorphometry

  11. The Growing Threat of Flooding on Transportation Infrastructure Across Texas Through 2100
    --
    doi.org/10.1029/2026EF008207 <--shared paper
    --
    H/T @Rakibul Ahasan
    “[The researchers] modeled flood susceptibility across Texas at 30 m resolution and projected how it shifts through 2100. The headline is not just that flood risk grows, but that it moves, into places current planning and regulatory maps are not watching. The July 2025 Kerrville flooding sat squarely inside the kind of inland hazard expansion this model projects.
    KEY TAKEAWAYS:
    ● 95% of new flood exposure by 2100 is inland, away from the coast, shifting the resilience problem into interior river basins that planning has historically deprioritized.
    ● Where [they] benchmarked against FEMA's National Flood Hazard Layer, the model flags substantial hidden risk in rapidly urbanizing peri-urban areas, most notably in Greater Houston.
    ● Climate change alone expands the flood-susceptible footprint by 10–12% by 2100, before any new road or land-use development, so this is a conservative floor, not a ceiling.
    ● Half the state's roads and rail and 80% of its bridges already sit in flood-susceptible zones today.
    ● [They] accounted for both factor-importance and spatial-scale uncertainty, using a Monte Carlo weight-perturbation ensemble and multiscale analysis across nested neighborhoods.
    The practical takeaway: this is a statewide screening layer, not a replacement for site-level hydraulic studies. It shows planners and policymakers where the gap between today's protection and tomorrow's risk is widest, and where unmapped peri-urban growth is walking into exposure that regulatory maps still call safe…”
    #water #hydrology #hydrography #extremeweather #flood #flooding #Texas #TX #USA #transportation #infrastructure #humanimpacts #risk #hazard #cost #economics #floodsusceptibility #GIS #spatial #mapping #raster #elevation #modeling #model #spatialanalysis #planning #regulation #warning #Kerrville #hazardmapping #floodexposure #inland #coast #urban #urbanisation #development #growth #Houston #lowlying #climatechange #landuse #development #geostatstics #MonteCarlo #regionalscreening #naturalhazard #infrastructureresilience #floodmapping #hydrogeomorphology #geomorphometry #aginginfrastructure

  12. The Growing Threat of Flooding on Transportation Infrastructure Across Texas Through 2100
    --
    doi.org/10.1029/2026EF008207 <--shared paper
    --
    H/T @Rakibul Ahasan
    “[The researchers] modeled flood susceptibility across Texas at 30 m resolution and projected how it shifts through 2100. The headline is not just that flood risk grows, but that it moves, into places current planning and regulatory maps are not watching. The July 2025 Kerrville flooding sat squarely inside the kind of inland hazard expansion this model projects.
    KEY TAKEAWAYS:
    ● 95% of new flood exposure by 2100 is inland, away from the coast, shifting the resilience problem into interior river basins that planning has historically deprioritized.
    ● Where [they] benchmarked against FEMA's National Flood Hazard Layer, the model flags substantial hidden risk in rapidly urbanizing peri-urban areas, most notably in Greater Houston.
    ● Climate change alone expands the flood-susceptible footprint by 10–12% by 2100, before any new road or land-use development, so this is a conservative floor, not a ceiling.
    ● Half the state's roads and rail and 80% of its bridges already sit in flood-susceptible zones today.
    ● [They] accounted for both factor-importance and spatial-scale uncertainty, using a Monte Carlo weight-perturbation ensemble and multiscale analysis across nested neighborhoods.
    The practical takeaway: this is a statewide screening layer, not a replacement for site-level hydraulic studies. It shows planners and policymakers where the gap between today's protection and tomorrow's risk is widest, and where unmapped peri-urban growth is walking into exposure that regulatory maps still call safe…”

  13. Sea Levels Rising Dramatically In Some Areas Due To Land Subsidence [global]
    --
    phys.org/news/2026-05-sea-area <-- shared technical article
    --
    doi.org/10.1038/s41467-026-722 <-- 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, doi.org/10.1038/s41561-023-013, 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

  14. Sea Levels Rising Dramatically In Some Areas Due To Land Subsidence [global]
    --
    phys.org/news/2026-05-sea-area <-- shared technical article
    --
    doi.org/10.1038/s41467-026-722 <-- shared paper
    --
    [#VLM = vertical land motion; = absolute sea-level; = relative sea-level; = (global) Glacial Isostatic Adjustment; = Interferometric Synthetic Aperture Radar; = Global Navigation Satellite System (~GPS); = paper, doi.org/10.1038/s41561-023-013, interpolated VLM reconstruction based on the joint analysis of GNSS, tide gauges (TGs), and satellite altimetry]

  15. Geomorphometry Coffee Talk on YouTube: “Geomorphometry with GRASS” by Corey White.

    DEM fusion tools, terrain uncertainty modeling, and overland flow simulation. Also a good look at how GRASS plugs into reproducible terrain workflows via Python and Jupyter, plus the open addon ecosystem for sharing methods.
    youtu.be/4la_zOc6OG8

    youtu.be/4la_zOc6OG8

  16. Geomorphometry Coffee Talk on YouTube: “Geomorphometry with GRASS” by Corey White.

    DEM fusion tools, terrain uncertainty modeling, and overland flow simulation. Also a good look at how GRASS plugs into reproducible terrain workflows via Python and Jupyter, plus the open addon ecosystem for sharing methods.
    youtu.be/4la_zOc6OG8
    #geomorphometry #geospatial #hydrology #GRASS
    youtu.be/4la_zOc6OG8

  17. USGS CoNED (TopoBathy) WebMap Viewer & (Open) Data Downloader
    --
    topotools.cr.usgs.gov/topobath <-- shared Viewer webmap & download selector
    --
    usgs.gov/coastal-changes-and-i <-- shared USGS CoNED overview/entry page
    --
    [I used to shore dive in the Straits Of Juan de Fucca, Washington State side, and Crescent Lake - so I chose that area as a CoNED example to explore; good memories, including of the 18 Wheeler Burger with pie & coffee in Joyce, WA on drizzly days]
    ,
    @USGS

  18. In two hours: International Society for Geomorphometry Coffee Talk: with @grassgis by Corey White

    Link: uqac.zoom.us/j/87983675737
    Wednesday, April 1, 2026, 10AM ET, 16:00 CET, 23:00 JST
    timeanddate.com/worldclock/con

  19. In two hours: International Society for Geomorphometry Coffee Talk: #Geomorphometry with @grassgis by Corey White

    Link: uqac.zoom.us/j/87983675737
    Wednesday, April 1, 2026, 10AM ET, 16:00 CET, 23:00 JST
    timeanddate.com/worldclock/con

  20. RE: fosstodon.org/@grassgis/116247

    🌍💻 Passionate about #geomorphometry & #gis ? This one’s for you!

    Join Corey T. White (NC State & GRASS Dev Team) on April 1st for a relaxed Caffe Talk ☕ on working with @grassgis , from 🌪 post-hurricane analysis to 🗻 DEM fusion and 🔍 terrain uncertainty.

    #Python 🐍, R & #Jupyter integration and a growing open add-on ecosystem.

    👇 Don’t miss it:
    📅 Apr 1, 2026 | 14:00 UTC
    🖥 uqac.zoom.us/j/87983675737

  21. RE: fosstodon.org/@grassgis/116247

    🌍💻 Passionate about #geomorphometry & #gis ? This one’s for you!

    Join Corey T. White (NC State & GRASS Dev Team) on April 1st for a relaxed Caffe Talk ☕ on working with @grassgis , from 🌪 post-hurricane analysis to 🗻 DEM fusion and 🔍 terrain uncertainty.

    #Python 🐍, R & #Jupyter integration and a growing open add-on ecosystem.

    👇 Don’t miss it:
    📅 Apr 1, 2026 | 14:00 UTC
    🖥 uqac.zoom.us/j/87983675737

  22. Coffee Talk: Geomorphometry with GRASS with Corey White (Center for Geospatial Analytics @ NC State University; GRASS Core Development Team Member) will discuss GRASS as a high-performance, extensible engine for . Examples include post–hurricane analysis, DEM fusion & terrain uncertainty. Also: Python/R/Jupyter integration + an open add-on ecosystem for sharing methods.

    Apr 1, 2026 14:00 UTC
    Time: tinyurl.com/5n2dbbxf
    Zoom: uqac.zoom.us/j/87983675737

  23. Coffee Talk: Geomorphometry with GRASS with Corey White (Center for Geospatial Analytics @ NC State University; GRASS Core Development Team Member) will discuss GRASS as a high-performance, extensible #geospatial engine for #geomorphometry. Examples include post–hurricane analysis, DEM fusion & terrain uncertainty. Also: Python/R/Jupyter integration + an open add-on ecosystem for sharing methods.

    Apr 1, 2026 14:00 UTC
    Time: tinyurl.com/5n2dbbxf
    Zoom: uqac.zoom.us/j/87983675737