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#spatiotemporal — Public Fediverse posts

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

  1. 💧🌏 Greg Cocks @[email protected] ·

    Rising Waters Swamp Lake Naivasha [Kenya] [earth observation]
    --
    science.nasa.gov/earth/earth-o <-- shared NASA 2026 technical article
    --
    africasacountry.com/2026/04/th <-- shared 2026 technical article
    --
    carrzee.org/wp-content/uploads <-- shared technical report
    --
    earth.gsfc.nasa.gov/gwm/lake/91 <-- shared charting, lake water levels
    --
    doi.org/10.11648/j.ajrs.201806 <-- shared 2018 paper, ‘An Assessment of the Role of Water Hyacinth in the Water Level Changes of Lake Naivasha Using GIS and Remote Sensing’
    --
    apnews.com/article/kenya-water <-- shared 2025 media article, ‘How the invasive water hyacinth is threatening fishermen’s livelihoods on … Kenyan [Lake Naivasha]…’
    --
    apnews.com/article/kenya-risin <-- shared 2025 media article
    --
    sei.org/features/revisiting-th <-- shared 2023 technical article
    --
    theguardian.com/world/2022/mar <-- shared 2022 media rticle
    --
    “Kenya's Lake Naivasha has long been a place of change and reinvention…
    Now the lake faces another major change: rapidly fluctuating water levels. The name Naivasha comes from a Maasai word meaning "that which heaves," an apt description of the freshwater lake over the past 25 years. Satellite altimetry measurements of the lake's depth indicate an increase of about 7 metres (23 feet) since 2010, roughly the height of a two-story building. Over the same period, Landsat observed a roughly 40 percent increase in the lake's area, adding 50 kilometres² (19 miles²) of water, equivalent to roughly 15 Central Parks.
    The human and economic toll of the rising water levels is considerable..”
    #Kenya #LakeNaivasha #Africa #water #hydrology #hydrography #risingwater #waterlevels #GIS #spatial #mapping #spatialanalysis #spatiotemporal #humanimpacts #farming #agriculture #infrastructure #damage #community #satellite #altimetry #economy #cost #impact #change #flood #flooding #innundation
    @nasa

    #kenya #lakenaivasha #africa #water #hydrology #hydrography
  2. 💧🌏 Greg Cocks @[email protected] ·

    Rising Waters Swamp Lake Naivasha [Kenya] [earth observation]
    --
    science.nasa.gov/earth/earth-o <-- shared NASA 2026 technical article
    --
    africasacountry.com/2026/04/th <-- shared 2026 technical article
    --
    carrzee.org/wp-content/uploads <-- shared technical report
    --
    earth.gsfc.nasa.gov/gwm/lake/91 <-- shared charting, lake water levels
    --
    doi.org/10.11648/j.ajrs.201806 <-- shared 2018 paper, ‘An Assessment of the Role of Water Hyacinth in the Water Level Changes of Lake Naivasha Using GIS and Remote Sensing’
    --
    apnews.com/article/kenya-water <-- shared 2025 media article, ‘How the invasive water hyacinth is threatening fishermen’s livelihoods on … Kenyan [Lake Naivasha]…’
    --
    apnews.com/article/kenya-risin <-- shared 2025 media article
    --
    sei.org/features/revisiting-th <-- shared 2023 technical article
    --
    theguardian.com/world/2022/mar <-- shared 2022 media rticle
    --
    “Kenya's Lake Naivasha has long been a place of change and reinvention…
    Now the lake faces another major change: rapidly fluctuating water levels. The name Naivasha comes from a Maasai word meaning "that which heaves," an apt description of the freshwater lake over the past 25 years. Satellite altimetry measurements of the lake's depth indicate an increase of about 7 metres (23 feet) since 2010, roughly the height of a two-story building. Over the same period, Landsat observed a roughly 40 percent increase in the lake's area, adding 50 kilometres² (19 miles²) of water, equivalent to roughly 15 Central Parks.
    The human and economic toll of the rising water levels is considerable..”
    #Kenya #LakeNaivasha #Africa #water #hydrology #hydrography #risingwater #waterlevels #GIS #spatial #mapping #spatialanalysis #spatiotemporal #humanimpacts #farming #agriculture #infrastructure #damage #community #satellite #altimetry #economy #cost #impact #change #flood #flooding #innundation
    @nasa

    #kenya #lakenaivasha #africa #water #hydrology #hydrography
  3. 💧🌏 Greg Cocks @[email protected] ·

    Rising Waters Swamp Lake Naivasha [Kenya] [earth observation]
    --
    science.nasa.gov/earth/earth-o <-- shared NASA 2026 technical article
    --
    africasacountry.com/2026/04/th <-- shared 2026 technical article
    --
    carrzee.org/wp-content/uploads <-- shared technical report
    --
    earth.gsfc.nasa.gov/gwm/lake/91 <-- shared charting, lake water levels
    --
    doi.org/10.11648/j.ajrs.201806 <-- shared 2018 paper, ‘An Assessment of the Role of Water Hyacinth in the Water Level Changes of Lake Naivasha Using GIS and Remote Sensing’
    --
    apnews.com/article/kenya-water <-- shared 2025 media article, ‘How the invasive water hyacinth is threatening fishermen’s livelihoods on … Kenyan [Lake Naivasha]…’
    --
    apnews.com/article/kenya-risin <-- shared 2025 media article
    --
    sei.org/features/revisiting-th <-- shared 2023 technical article
    --
    theguardian.com/world/2022/mar <-- shared 2022 media rticle
    --
    “Kenya's Lake Naivasha has long been a place of change and reinvention…
    Now the lake faces another major change: rapidly fluctuating water levels. The name Naivasha comes from a Maasai word meaning "that which heaves," an apt description of the freshwater lake over the past 25 years. Satellite altimetry measurements of the lake's depth indicate an increase of about 7 metres (23 feet) since 2010, roughly the height of a two-story building. Over the same period, Landsat observed a roughly 40 percent increase in the lake's area, adding 50 kilometres² (19 miles²) of water, equivalent to roughly 15 Central Parks.
    The human and economic toll of the rising water levels is considerable..”
    #Kenya #LakeNaivasha #Africa #water #hydrology #hydrography #risingwater #waterlevels #GIS #spatial #mapping #spatialanalysis #spatiotemporal #humanimpacts #farming #agriculture #infrastructure #damage #community #satellite #altimetry #economy #cost #impact #change #flood #flooding #innundation
    @nasa

    #kenya #lakenaivasha #africa #water #hydrology #hydrography
  4. 💧🌏 Greg Cocks @[email protected] ·

    Rising Waters Swamp Lake Naivasha [Kenya] [earth observation]
    --
    science.nasa.gov/earth/earth-o <-- shared NASA 2026 technical article
    --
    africasacountry.com/2026/04/th <-- shared 2026 technical article
    --
    carrzee.org/wp-content/uploads <-- shared technical report
    --
    earth.gsfc.nasa.gov/gwm/lake/91 <-- shared charting, lake water levels
    --
    doi.org/10.11648/j.ajrs.201806 <-- shared 2018 paper, ‘An Assessment of the Role of Water Hyacinth in the Water Level Changes of Lake Naivasha Using GIS and Remote Sensing’
    --
    apnews.com/article/kenya-water <-- shared 2025 media article, ‘How the invasive water hyacinth is threatening fishermen’s livelihoods on … Kenyan [Lake Naivasha]…’
    --
    apnews.com/article/kenya-risin <-- shared 2025 media article
    --
    sei.org/features/revisiting-th <-- shared 2023 technical article
    --
    theguardian.com/world/2022/mar <-- shared 2022 media rticle
    --
    “Kenya's Lake Naivasha has long been a place of change and reinvention…
    Now the lake faces another major change: rapidly fluctuating water levels. The name Naivasha comes from a Maasai word meaning "that which heaves," an apt description of the freshwater lake over the past 25 years. Satellite altimetry measurements of the lake's depth indicate an increase of about 7 metres (23 feet) since 2010, roughly the height of a two-story building. Over the same period, Landsat observed a roughly 40 percent increase in the lake's area, adding 50 kilometres² (19 miles²) of water, equivalent to roughly 15 Central Parks.
    The human and economic toll of the rising water levels is considerable..”
    #Kenya #LakeNaivasha #Africa #water #hydrology #hydrography #risingwater #waterlevels #GIS #spatial #mapping #spatialanalysis #spatiotemporal #humanimpacts #farming #agriculture #infrastructure #damage #community #satellite #altimetry #economy #cost #impact #change #flood #flooding #innundation
    @nasa

    #innundation #flooding #flood #change #impact #cost
  5. 💧🌏 Greg Cocks @GregCocks ·

    Rising Waters Swamp Lake Naivasha [Kenya] [earth observation]
    --
    science.nasa.gov/earth/earth-o <-- shared NASA 2026 technical article
    --
    africasacountry.com/2026/04/th <-- shared 2026 technical article
    --
    carrzee.org/wp-content/uploads <-- shared technical report
    --
    earth.gsfc.nasa.gov/gwm/lake/91 <-- shared charting, lake water levels
    --
    doi.org/10.11648/j.ajrs.201806 <-- shared 2018 paper, ‘An Assessment of the Role of Water Hyacinth in the Water Level Changes of Lake Naivasha Using GIS and Remote Sensing’
    --
    apnews.com/article/kenya-water <-- shared 2025 media article, ‘How the invasive water hyacinth is threatening fishermen’s livelihoods on … Kenyan [Lake Naivasha]…’
    --
    apnews.com/article/kenya-risin <-- shared 2025 media article
    --
    sei.org/features/revisiting-th <-- shared 2023 technical article
    --
    theguardian.com/world/2022/mar <-- shared 2022 media rticle
    --
    “Kenya's Lake Naivasha has long been a place of change and reinvention…
    Now the lake faces another major change: rapidly fluctuating water levels. The name Naivasha comes from a Maasai word meaning "that which heaves," an apt description of the freshwater lake over the past 25 years. Satellite altimetry measurements of the lake's depth indicate an increase of about 7 metres (23 feet) since 2010, roughly the height of a two-story building. Over the same period, Landsat observed a roughly 40 percent increase in the lake's area, adding 50 kilometres² (19 miles²) of water, equivalent to roughly 15 Central Parks.
    The human and economic toll of the rising water levels is considerable..”

    @nasa

    #kenya #lakenaivasha #africa #water #hydrology #hydrography
  6. 💧🌏 Greg Cocks @[email protected] ·

    The Radiative Effects Of Water Vapour From Terrestrial Evapotranspiration
    --
    doi.org/10.1088/1748-9326/adde <-- shared paper/letter
    --
    zenodo.org/records/15413219 | zenodo.org/records/15416936 <-- shared open data, for “Model information and output for "The radiative effects…” ”
    --
    doi.org/10.1007/s11269-025-041 <-- shared paper
    --
    H/T @jan Umsonst | Earth System Nerd
    “Water vapour accounts for roughly 50% of the modern greenhouse effect. Over continental regions, evapotranspiration (ET) is often limited by water availability. In this study, [the authors] spatially quantify how much of the total atmospheric water vapour evaporated most recently from land and calculate the relative contribution of that water vapour to the atmospheric radiative budget. Using a combination of tracer-enabled Earth system model simulations and radiative transfer calculations, [they were] able to explicitly quantify the 3D distribution of terrestrial vs. oceanic water vapour, and the spatial contribution of each to the surface and top of atmosphere radiative budgets. [They found] that over many continental regions, more than half of the total column-integrated water vapour originates from land ET, and that this vapour contributes up to 30 W/m² of longwave radiation into the surface in the annual mean (about 10% of the total). Understanding how terrestrial ET impacts the base-state of water vapour distribution and the water vapour greenhouse effect is critical to understanding how and where changes in terrestrial ET, driven by climate change, land use, etc, will modify the radiative properties of the atmosphere and thus the climate system…”
    #water #hydrology #greehouseeffect #highperformancecomputing #HPC #evapotranspiration #Radiative #WaterVapour #spatial #spatialanalysis #spatiotemporal #atmosphere #model #modeling #earthsystemmodelling #terrestrial #oceanic #vapour #climatechange #landuse #changes #climatesystem

    #water #hydrology #greehouseeffect #highperformancecomputing #hpc #evapotranspiration
  7. 💧🌏 Greg Cocks @[email protected] ·

    The Radiative Effects Of Water Vapour From Terrestrial Evapotranspiration
    --
    doi.org/10.1088/1748-9326/adde <-- shared paper/letter
    --
    zenodo.org/records/15413219 | zenodo.org/records/15416936 <-- shared open data, for “Model information and output for "The radiative effects…” ”
    --
    doi.org/10.1007/s11269-025-041 <-- shared paper
    --
    H/T @jan Umsonst | Earth System Nerd
    “Water vapour accounts for roughly 50% of the modern greenhouse effect. Over continental regions, evapotranspiration (ET) is often limited by water availability. In this study, [the authors] spatially quantify how much of the total atmospheric water vapour evaporated most recently from land and calculate the relative contribution of that water vapour to the atmospheric radiative budget. Using a combination of tracer-enabled Earth system model simulations and radiative transfer calculations, [they were] able to explicitly quantify the 3D distribution of terrestrial vs. oceanic water vapour, and the spatial contribution of each to the surface and top of atmosphere radiative budgets. [They found] that over many continental regions, more than half of the total column-integrated water vapour originates from land ET, and that this vapour contributes up to 30 W/m² of longwave radiation into the surface in the annual mean (about 10% of the total). Understanding how terrestrial ET impacts the base-state of water vapour distribution and the water vapour greenhouse effect is critical to understanding how and where changes in terrestrial ET, driven by climate change, land use, etc, will modify the radiative properties of the atmosphere and thus the climate system…”
    #water #hydrology #greehouseeffect #highperformancecomputing #HPC #evapotranspiration #Radiative #WaterVapour #spatial #spatialanalysis #spatiotemporal #atmosphere #model #modeling #earthsystemmodelling #terrestrial #oceanic #vapour #climatechange #landuse #changes #climatesystem

    #water #hydrology #greehouseeffect #highperformancecomputing #hpc #evapotranspiration
  8. 💧🌏 Greg Cocks @[email protected] ·

    The Radiative Effects Of Water Vapour From Terrestrial Evapotranspiration
    --
    doi.org/10.1088/1748-9326/adde <-- shared paper/letter
    --
    zenodo.org/records/15413219 | zenodo.org/records/15416936 <-- shared open data, for “Model information and output for "The radiative effects…” ”
    --
    doi.org/10.1007/s11269-025-041 <-- shared paper
    --
    H/T @jan Umsonst | Earth System Nerd
    “Water vapour accounts for roughly 50% of the modern greenhouse effect. Over continental regions, evapotranspiration (ET) is often limited by water availability. In this study, [the authors] spatially quantify how much of the total atmospheric water vapour evaporated most recently from land and calculate the relative contribution of that water vapour to the atmospheric radiative budget. Using a combination of tracer-enabled Earth system model simulations and radiative transfer calculations, [they were] able to explicitly quantify the 3D distribution of terrestrial vs. oceanic water vapour, and the spatial contribution of each to the surface and top of atmosphere radiative budgets. [They found] that over many continental regions, more than half of the total column-integrated water vapour originates from land ET, and that this vapour contributes up to 30 W/m² of longwave radiation into the surface in the annual mean (about 10% of the total). Understanding how terrestrial ET impacts the base-state of water vapour distribution and the water vapour greenhouse effect is critical to understanding how and where changes in terrestrial ET, driven by climate change, land use, etc, will modify the radiative properties of the atmosphere and thus the climate system…”
    #water #hydrology #greehouseeffect #highperformancecomputing #HPC #evapotranspiration #Radiative #WaterVapour #spatial #spatialanalysis #spatiotemporal #atmosphere #model #modeling #earthsystemmodelling #terrestrial #oceanic #vapour #climatechange #landuse #changes #climatesystem

    #water #hydrology #greehouseeffect #highperformancecomputing #hpc #evapotranspiration
  9. 💧🌏 Greg Cocks @[email protected] ·

    The Radiative Effects Of Water Vapour From Terrestrial Evapotranspiration
    --
    doi.org/10.1088/1748-9326/adde <-- shared paper/letter
    --
    zenodo.org/records/15413219 | zenodo.org/records/15416936 <-- shared open data, for “Model information and output for "The radiative effects…” ”
    --
    doi.org/10.1007/s11269-025-041 <-- shared paper
    --
    H/T @jan Umsonst | Earth System Nerd
    “Water vapour accounts for roughly 50% of the modern greenhouse effect. Over continental regions, evapotranspiration (ET) is often limited by water availability. In this study, [the authors] spatially quantify how much of the total atmospheric water vapour evaporated most recently from land and calculate the relative contribution of that water vapour to the atmospheric radiative budget. Using a combination of tracer-enabled Earth system model simulations and radiative transfer calculations, [they were] able to explicitly quantify the 3D distribution of terrestrial vs. oceanic water vapour, and the spatial contribution of each to the surface and top of atmosphere radiative budgets. [They found] that over many continental regions, more than half of the total column-integrated water vapour originates from land ET, and that this vapour contributes up to 30 W/m² of longwave radiation into the surface in the annual mean (about 10% of the total). Understanding how terrestrial ET impacts the base-state of water vapour distribution and the water vapour greenhouse effect is critical to understanding how and where changes in terrestrial ET, driven by climate change, land use, etc, will modify the radiative properties of the atmosphere and thus the climate system…”
    #water #hydrology #greehouseeffect #highperformancecomputing #HPC #evapotranspiration #Radiative #WaterVapour #spatial #spatialanalysis #spatiotemporal #atmosphere #model #modeling #earthsystemmodelling #terrestrial #oceanic #vapour #climatechange #landuse #changes #climatesystem

    #climatesystem #changes #landuse #climatechange #vapour #oceanic
  10. 💧🌏 Greg Cocks @GregCocks ·

    The Radiative Effects Of Water Vapour From Terrestrial Evapotranspiration
    --
    doi.org/10.1088/1748-9326/adde <-- shared paper/letter
    --
    zenodo.org/records/15413219 | zenodo.org/records/15416936 <-- shared open data, for “Model information and output for "The radiative effects…” ”
    --
    doi.org/10.1007/s11269-025-041 <-- shared paper
    --
    H/T @jan Umsonst | Earth System Nerd
    “Water vapour accounts for roughly 50% of the modern greenhouse effect. Over continental regions, evapotranspiration (ET) is often limited by water availability. In this study, [the authors] spatially quantify how much of the total atmospheric water vapour evaporated most recently from land and calculate the relative contribution of that water vapour to the atmospheric radiative budget. Using a combination of tracer-enabled Earth system model simulations and radiative transfer calculations, [they were] able to explicitly quantify the 3D distribution of terrestrial vs. oceanic water vapour, and the spatial contribution of each to the surface and top of atmosphere radiative budgets. [They found] that over many continental regions, more than half of the total column-integrated water vapour originates from land ET, and that this vapour contributes up to 30 W/m² of longwave radiation into the surface in the annual mean (about 10% of the total). Understanding how terrestrial ET impacts the base-state of water vapour distribution and the water vapour greenhouse effect is critical to understanding how and where changes in terrestrial ET, driven by climate change, land use, etc, will modify the radiative properties of the atmosphere and thus the climate system…”

    #water #hydrology #greehouseeffect #highperformancecomputing #hpc #evapotranspiration
  11. 💧🌏 Greg Cocks @[email protected] ·

    Annual High-Resolution Global Ambient Population Estimates From 1975 To 2024
    --
    doi.org/10.31223/X5MV3R <-- shared paper
    --
    landscan.ornl.gov/ <-- shared webmap and data link (via download -> LandScan Mosaic Time Series)
    --
    gee-community-catalog.org/proj <-- shared link to GEE community catalog collection ‘LandScan Mosaic Annual Global Ambient Population Time Series’
    --
    H/T @andrew Zimmer || Geographer | Research Scientist @ Oak Ridge National Laboratory
    “LSM-TS provides annual global estimates of ambient population from 1975–2024 at ~90 m resolution, creating a spatially and temporally consistent reconstruction of population change designed for longitudinal analysis. Reconstruction of historical populations are driven by current LandScan Mosaic building-level population distributions, scaled by built-surface change from #GHSL … and calibrated to annual national-level estimates from U.S. Census Bureau…”
    --
    “LandScan is a globally recognized, R&D100-winning population data platform developed at Oak Ridge National Laboratory (ORNL). Its datasets provide human population distribution estimates down to 100 meter grid resolution. LandScan supports disaster response, humanitarian aid, environmental analysis, and urban planning by providing insights into where people live and how they move…”
    --
    “Gridded population data support assessments of human exposure, settlement change, infrastructure demand, and access to services, yet global datasets combining annual coverage over multiple decades with fine spatial resolution remain limited. LandScan Mosaic Time Series provides 50 annual estimates of global ambient population distribution at 3 arc-second resolution from 1975 through 2024. The series is anchored to the 2024 LandScan Mosaic surface, produced through a building-level population modeling workflow. Historical surfaces are reconstructed using annualized changes in built surface and derived first-level administrative population trajectories. Every layer, including 2024, is normalized to administrative targets scaled to annual country totals from the U.S. Census Bureau International Database. The dataset is distributed as 50 single-band Cloud Optimized GeoTIFFs on an identical WGS84 grid, with values representing estimated persons per cell. Its common grid and methodology support fine-scale longitudinal analysis of ambient population distribution while documented validation and limitations guide appropriate reuse…”
    #demographics #change #spatiotemporal #1975 #2024 #population #change #grid #global #LandScan #POPGRID #LSMTS #ambientpopulation #GHSL #OakRidge #ORNL #usecase #opendata #disasterresponse #humanitarianaid #environmentalanalysis #urbanplanning #humanexposure #settlementchange #city #rural #infrastructure #demand #accesstoservices #GIS #spatial #mapping #building #outline #model #modeling
    @OAK Ridge National Laboratory | National Security Sciences at ORNL | @POPGRID Data Collaborative

    #ghsl #demographics #change #spatiotemporal #population #grid
  12. 💧🌏 Greg Cocks @[email protected] ·

    Annual High-Resolution Global Ambient Population Estimates From 1975 To 2024
    --
    doi.org/10.31223/X5MV3R <-- shared paper
    --
    landscan.ornl.gov/ <-- shared webmap and data link (via download -> LandScan Mosaic Time Series)
    --
    gee-community-catalog.org/proj <-- shared link to GEE community catalog collection ‘LandScan Mosaic Annual Global Ambient Population Time Series’
    --
    H/T @andrew Zimmer || Geographer | Research Scientist @ Oak Ridge National Laboratory
    “LSM-TS provides annual global estimates of ambient population from 1975–2024 at ~90 m resolution, creating a spatially and temporally consistent reconstruction of population change designed for longitudinal analysis. Reconstruction of historical populations are driven by current LandScan Mosaic building-level population distributions, scaled by built-surface change from #GHSL … and calibrated to annual national-level estimates from U.S. Census Bureau…”
    --
    “LandScan is a globally recognized, R&D100-winning population data platform developed at Oak Ridge National Laboratory (ORNL). Its datasets provide human population distribution estimates down to 100 meter grid resolution. LandScan supports disaster response, humanitarian aid, environmental analysis, and urban planning by providing insights into where people live and how they move…”
    --
    “Gridded population data support assessments of human exposure, settlement change, infrastructure demand, and access to services, yet global datasets combining annual coverage over multiple decades with fine spatial resolution remain limited. LandScan Mosaic Time Series provides 50 annual estimates of global ambient population distribution at 3 arc-second resolution from 1975 through 2024. The series is anchored to the 2024 LandScan Mosaic surface, produced through a building-level population modeling workflow. Historical surfaces are reconstructed using annualized changes in built surface and derived first-level administrative population trajectories. Every layer, including 2024, is normalized to administrative targets scaled to annual country totals from the U.S. Census Bureau International Database. The dataset is distributed as 50 single-band Cloud Optimized GeoTIFFs on an identical WGS84 grid, with values representing estimated persons per cell. Its common grid and methodology support fine-scale longitudinal analysis of ambient population distribution while documented validation and limitations guide appropriate reuse…”
    #demographics #change #spatiotemporal #1975 #2024 #population #change #grid #global #LandScan #POPGRID #LSMTS #ambientpopulation #GHSL #OakRidge #ORNL #usecase #opendata #disasterresponse #humanitarianaid #environmentalanalysis #urbanplanning #humanexposure #settlementchange #city #rural #infrastructure #demand #accesstoservices #GIS #spatial #mapping #building #outline #model #modeling
    @OAK Ridge National Laboratory | National Security Sciences at ORNL | @POPGRID Data Collaborative

    #ghsl #demographics #change #spatiotemporal #population #grid
  13. 💧🌏 Greg Cocks @[email protected] ·

    Annual High-Resolution Global Ambient Population Estimates From 1975 To 2024
    --
    doi.org/10.31223/X5MV3R <-- shared paper
    --
    landscan.ornl.gov/ <-- shared webmap and data link (via download -> LandScan Mosaic Time Series)
    --
    gee-community-catalog.org/proj <-- shared link to GEE community catalog collection ‘LandScan Mosaic Annual Global Ambient Population Time Series’
    --
    H/T @andrew Zimmer || Geographer | Research Scientist @ Oak Ridge National Laboratory
    “LSM-TS provides annual global estimates of ambient population from 1975–2024 at ~90 m resolution, creating a spatially and temporally consistent reconstruction of population change designed for longitudinal analysis. Reconstruction of historical populations are driven by current LandScan Mosaic building-level population distributions, scaled by built-surface change from #GHSL … and calibrated to annual national-level estimates from U.S. Census Bureau…”
    --
    “LandScan is a globally recognized, R&D100-winning population data platform developed at Oak Ridge National Laboratory (ORNL). Its datasets provide human population distribution estimates down to 100 meter grid resolution. LandScan supports disaster response, humanitarian aid, environmental analysis, and urban planning by providing insights into where people live and how they move…”
    --
    “Gridded population data support assessments of human exposure, settlement change, infrastructure demand, and access to services, yet global datasets combining annual coverage over multiple decades with fine spatial resolution remain limited. LandScan Mosaic Time Series provides 50 annual estimates of global ambient population distribution at 3 arc-second resolution from 1975 through 2024. The series is anchored to the 2024 LandScan Mosaic surface, produced through a building-level population modeling workflow. Historical surfaces are reconstructed using annualized changes in built surface and derived first-level administrative population trajectories. Every layer, including 2024, is normalized to administrative targets scaled to annual country totals from the U.S. Census Bureau International Database. The dataset is distributed as 50 single-band Cloud Optimized GeoTIFFs on an identical WGS84 grid, with values representing estimated persons per cell. Its common grid and methodology support fine-scale longitudinal analysis of ambient population distribution while documented validation and limitations guide appropriate reuse…”
    #demographics #change #spatiotemporal #1975 #2024 #population #change #grid #global #LandScan #POPGRID #LSMTS #ambientpopulation #GHSL #OakRidge #ORNL #usecase #opendata #disasterresponse #humanitarianaid #environmentalanalysis #urbanplanning #humanexposure #settlementchange #city #rural #infrastructure #demand #accesstoservices #GIS #spatial #mapping #building #outline #model #modeling
    @OAK Ridge National Laboratory | National Security Sciences at ORNL | @POPGRID Data Collaborative

    #ghsl #demographics #change #spatiotemporal #population #grid
  14. 💧🌏 Greg Cocks @[email protected] ·

    Annual High-Resolution Global Ambient Population Estimates From 1975 To 2024
    --
    doi.org/10.31223/X5MV3R <-- shared paper
    --
    landscan.ornl.gov/ <-- shared webmap and data link (via download -> LandScan Mosaic Time Series)
    --
    gee-community-catalog.org/proj <-- shared link to GEE community catalog collection ‘LandScan Mosaic Annual Global Ambient Population Time Series’
    --
    H/T @andrew Zimmer || Geographer | Research Scientist @ Oak Ridge National Laboratory
    “LSM-TS provides annual global estimates of ambient population from 1975–2024 at ~90 m resolution, creating a spatially and temporally consistent reconstruction of population change designed for longitudinal analysis. Reconstruction of historical populations are driven by current LandScan Mosaic building-level population distributions, scaled by built-surface change from #GHSL … and calibrated to annual national-level estimates from U.S. Census Bureau…”
    --
    “LandScan is a globally recognized, R&D100-winning population data platform developed at Oak Ridge National Laboratory (ORNL). Its datasets provide human population distribution estimates down to 100 meter grid resolution. LandScan supports disaster response, humanitarian aid, environmental analysis, and urban planning by providing insights into where people live and how they move…”
    --
    “Gridded population data support assessments of human exposure, settlement change, infrastructure demand, and access to services, yet global datasets combining annual coverage over multiple decades with fine spatial resolution remain limited. LandScan Mosaic Time Series provides 50 annual estimates of global ambient population distribution at 3 arc-second resolution from 1975 through 2024. The series is anchored to the 2024 LandScan Mosaic surface, produced through a building-level population modeling workflow. Historical surfaces are reconstructed using annualized changes in built surface and derived first-level administrative population trajectories. Every layer, including 2024, is normalized to administrative targets scaled to annual country totals from the U.S. Census Bureau International Database. The dataset is distributed as 50 single-band Cloud Optimized GeoTIFFs on an identical WGS84 grid, with values representing estimated persons per cell. Its common grid and methodology support fine-scale longitudinal analysis of ambient population distribution while documented validation and limitations guide appropriate reuse…”
    #demographics #change #spatiotemporal #1975 #2024 #population #change #grid #global #LandScan #POPGRID #LSMTS #ambientpopulation #GHSL #OakRidge #ORNL #usecase #opendata #disasterresponse #humanitarianaid #environmentalanalysis #urbanplanning #humanexposure #settlementchange #city #rural #infrastructure #demand #accesstoservices #GIS #spatial #mapping #building #outline #model #modeling
    @OAK Ridge National Laboratory | National Security Sciences at ORNL | @POPGRID Data Collaborative

    #modeling #model #outline #building #mapping #spatial
  15. 💧🌏 Greg Cocks @GregCocks ·

    Annual High-Resolution Global Ambient Population Estimates From 1975 To 2024
    --
    doi.org/10.31223/X5MV3R <-- shared paper
    --
    landscan.ornl.gov/ <-- shared webmap and data link (via download -> LandScan Mosaic Time Series)
    --
    gee-community-catalog.org/proj <-- shared link to GEE community catalog collection ‘LandScan Mosaic Annual Global Ambient Population Time Series’
    --
    H/T @andrew Zimmer || Geographer | Research Scientist @ Oak Ridge National Laboratory
    “LSM-TS provides annual global estimates of ambient population from 1975–2024 at ~90 m resolution, creating a spatially and temporally consistent reconstruction of population change designed for longitudinal analysis. Reconstruction of historical populations are driven by current LandScan Mosaic building-level population distributions, scaled by built-surface change from … and calibrated to annual national-level estimates from U.S. Census Bureau…”
    --
    “LandScan is a globally recognized, R&D100-winning population data platform developed at Oak Ridge National Laboratory (ORNL). Its datasets provide human population distribution estimates down to 100 meter grid resolution. LandScan supports disaster response, humanitarian aid, environmental analysis, and urban planning by providing insights into where people live and how they move…”
    --
    “Gridded population data support assessments of human exposure, settlement change, infrastructure demand, and access to services, yet global datasets combining annual coverage over multiple decades with fine spatial resolution remain limited. LandScan Mosaic Time Series provides 50 annual estimates of global ambient population distribution at 3 arc-second resolution from 1975 through 2024. The series is anchored to the 2024 LandScan Mosaic surface, produced through a building-level population modeling workflow. Historical surfaces are reconstructed using annualized changes in built surface and derived first-level administrative population trajectories. Every layer, including 2024, is normalized to administrative targets scaled to annual country totals from the U.S. Census Bureau International Database. The dataset is distributed as 50 single-band Cloud Optimized GeoTIFFs on an identical WGS84 grid, with values representing estimated persons per cell. Its common grid and methodology support fine-scale longitudinal analysis of ambient population distribution while documented validation and limitations guide appropriate reuse…”
    #1975 #2024
    @OAK Ridge National Laboratory | National Security Sciences at ORNL | @POPGRID Data Collaborative

    #ghsl #demographics #change #spatiotemporal #population #grid
  16. 💧🌏 Greg Cocks @[email protected] ·

    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

    #explainable #causal #ai #model #modeling #publichealth
  17. 💧🌏 Greg Cocks @[email protected] ·

    Beyond The 100-Year Flood - Probabilistic Flood Hazard Assessment For King And Pierce Counties Under Future Climate Scenarios
    --
    doi.org/10.5194/nhess-26-3231- <-- shared #openacess paper
    --
    [part of my old stomping ground as an engineering geologist]
    H/T @Kees Nederhoff
    “Flood maps are usually built from a single design storm. For King and Pierce Counties in the Pacific Northwest (USA), [the authors] tried the opposite - simulate 82 years of actual coastal and river conditions (plus 18 synthetic years) with SFINCS and let the statistics fall out cell by cell. That took about 5,400 yearly simulations and 194,000 CPU hours on USGS's Hovenweep HPC. Worth it!
    The design-event shortcut turns out to hide a real hazard. A deterministic 10-year event underestimated flood depths by up to half a meter compared to the continuous runs.
    The bigger surprise [to the authors] was how one-sided the climate signal is. One metre of sea level rise takes King County's expected annual flooded area from 161 --> 787 hectares, almost a factor of five. Changes in storminess over the same horizon barely register. And somewhere between 100 and 150 cm of SLR, land that never floods today starts flooding fast. If you plan adaptation in Puget Sound, that threshold matters more than any single return-period map.
    [They] also propose Expected Annual Flooded Area (EAFA) as a probability-weighted alternative to the binary "inside or outside the 100-year zone" label…”
    #USGS #supercomputing #Hovenweep #HPC #coast #coastal #PNW #Seattle #PacificNorthwest #risk #hazard #riskmanagement #model #modeling #CFRM #deterministic #probabilistic #climatechange #extremeweather #fedscience #WA #KingCounty #PierceCounty #WashingtonState #USA #flood #flooding #compoundflooding #floodmaps #SFINCS #storm #weather #climate #climatechange #rainfall #precipitation #sealevel #sealevelrise #SLR #100yearflood #floodhazardmapping #returnperiods #pluvial #fluvial #spatialanalysis #spatiotemporal #remotesensing #streamgage #history #historicflooding #projections #predictions
    #USGS

    #openacess #usgs #supercomputing #hovenweep #hpc #coast
  18. 💧🌏 Greg Cocks @[email protected] ·

    Comparative Hydro-Climatic Datasets For Catchment-Wise Linked Water Fluxes And Storage Changes Across South America
    --
    doi.org/10.3389/fenvs.2026.176 <-- shared paper
    --
    doi.org/10.1038/s43247-026-036 <-- shared paper
    --
    doi.org/10.1002/joc.6443 <-- shared paper
    --
    pik-potsdam.de/en/news/latest- | publications.iom.int/books/eva <-- shared 2021 Peru hydroclimate technical article | report
    --
    youtu.be/Ngbm0gsmYAw?si=haqV7t <-- shared overview video
    --
    #water #GIS #spatial #mappping #spatialanalysis #spatiotemporal #remotesensing #earthobservation #Hydrology #Hydroclimatology #ClimateChange #extremeweather #WaterResources #WaterSecurity uncertainity #SouthAmerica #ClimateData #PeerReview #OpenScience #Hydrometeorology #opendata #datasets #rainfall #precipitation #fluvial #heatwave #temperature #changing #consistency #flood #flooding #drought #riskmanagement #risk #hazard #earthsystems #resilience #waterquality #waterpollution #model #modeling #monitoring #records #hydroclimate #hydrogeomorphology #review #SouthAmerica #planning #policy #sustainability #evapotranspiration #runoff #waterstorage #SAHCD

    #water #gis #spatial #mappping #spatialanalysis #spatiotemporal
  19. 💧🌏 Greg Cocks @[email protected] ·

    Comparative Hydro-Climatic Datasets For Catchment-Wise Linked Water Fluxes And Storage Changes Across South America
    --
    doi.org/10.3389/fenvs.2026.176 <-- shared paper
    --
    doi.org/10.1038/s43247-026-036 <-- shared paper
    --
    doi.org/10.1002/joc.6443 <-- shared paper
    --
    pik-potsdam.de/en/news/latest- | publications.iom.int/books/eva <-- shared 2021 Peru hydroclimate technical article | report
    --
    youtu.be/Ngbm0gsmYAw?si=haqV7t <-- shared overview video
    --
    #water #GIS #spatial #mappping #spatialanalysis #spatiotemporal #remotesensing #earthobservation #Hydrology #Hydroclimatology #ClimateChange #extremeweather #WaterResources #WaterSecurity uncertainity #SouthAmerica #ClimateData #PeerReview #OpenScience #Hydrometeorology #opendata #datasets #rainfall #precipitation #fluvial #heatwave #temperature #changing #consistency #flood #flooding #drought #riskmanagement #risk #hazard #earthsystems #resilience #waterquality #waterpollution #model #modeling #monitoring #records #hydroclimate #hydrogeomorphology #review #SouthAmerica #planning #policy #sustainability #evapotranspiration #runoff #waterstorage #SAHCD

    #water #gis #spatial #mappping #spatialanalysis #spatiotemporal
  20. 💧🌏 Greg Cocks @[email protected] ·

    Comparative Hydro-Climatic Datasets For Catchment-Wise Linked Water Fluxes And Storage Changes Across South America
    --
    doi.org/10.3389/fenvs.2026.176 <-- shared paper
    --
    doi.org/10.1038/s43247-026-036 <-- shared paper
    --
    doi.org/10.1002/joc.6443 <-- shared paper
    --
    pik-potsdam.de/en/news/latest- | publications.iom.int/books/eva <-- shared 2021 Peru hydroclimate technical article | report
    --
    youtu.be/Ngbm0gsmYAw?si=haqV7t <-- shared overview video
    --
    #water #GIS #spatial #mappping #spatialanalysis #spatiotemporal #remotesensing #earthobservation #Hydrology #Hydroclimatology #ClimateChange #extremeweather #WaterResources #WaterSecurity uncertainity #SouthAmerica #ClimateData #PeerReview #OpenScience #Hydrometeorology #opendata #datasets #rainfall #precipitation #fluvial #heatwave #temperature #changing #consistency #flood #flooding #drought #riskmanagement #risk #hazard #earthsystems #resilience #waterquality #waterpollution #model #modeling #monitoring #records #hydroclimate #hydrogeomorphology #review #SouthAmerica #planning #policy #sustainability #evapotranspiration #runoff #waterstorage #SAHCD

    #water #gis #spatial #mappping #spatialanalysis #spatiotemporal
  21. 💧🌏 Greg Cocks @[email protected] ·

    Comparative Hydro-Climatic Datasets For Catchment-Wise Linked Water Fluxes And Storage Changes Across South America
    --
    doi.org/10.3389/fenvs.2026.176 <-- shared paper
    --
    doi.org/10.1038/s43247-026-036 <-- shared paper
    --
    doi.org/10.1002/joc.6443 <-- shared paper
    --
    pik-potsdam.de/en/news/latest- | publications.iom.int/books/eva <-- shared 2021 Peru hydroclimate technical article | report
    --
    youtu.be/Ngbm0gsmYAw?si=haqV7t <-- shared overview video
    --
    #water #GIS #spatial #mappping #spatialanalysis #spatiotemporal #remotesensing #earthobservation #Hydrology #Hydroclimatology #ClimateChange #extremeweather #WaterResources #WaterSecurity uncertainity #SouthAmerica #ClimateData #PeerReview #OpenScience #Hydrometeorology #opendata #datasets #rainfall #precipitation #fluvial #heatwave #temperature #changing #consistency #flood #flooding #drought #riskmanagement #risk #hazard #earthsystems #resilience #waterquality #waterpollution #model #modeling #monitoring #records #hydroclimate #hydrogeomorphology #review #SouthAmerica #planning #policy #sustainability #evapotranspiration #runoff #waterstorage #SAHCD

    #sahcd #waterstorage #runoff #evapotranspiration #sustainability #policy
  22. 💧🌏 Greg Cocks @GregCocks ·

    Comparative Hydro-Climatic Datasets For Catchment-Wise Linked Water Fluxes And Storage Changes Across South America
    --
    doi.org/10.3389/fenvs.2026.176 <-- shared paper
    --
    doi.org/10.1038/s43247-026-036 <-- shared paper
    --
    doi.org/10.1002/joc.6443 <-- shared paper
    --
    pik-potsdam.de/en/news/latest- | publications.iom.int/books/eva <-- shared 2021 Peru hydroclimate technical article | report
    --
    youtu.be/Ngbm0gsmYAw?si=haqV7t <-- shared overview video
    --
    uncertainity

    #water #gis #spatial #mappping #spatialanalysis #spatiotemporal
  23. 💧🌏 Greg Cocks @[email protected] ·

    Vertical Land Motion And Human Exposure Across India's Coastal Regions
    --
    doi.org/10.1029/2025GL120539 <-- shared paper 🔗
    --
    indiaspend.com/climate-change/ <-- shared media article 🔗
    --
    #SeaLevelRise #Subsidence #India #InSAR #radar #Postdoc #GIS #spatial #mapping #inSAR #LandSubsidence #remotesensing #coast #coastal #coastline #India #earthobservation #subsidence #rise #urban #city #SLR #ClimateChange #spatialanalysis #spatiotemporal #marine #ocean #water #hydrology #risk #hazard #humanimpacts #flood #flooding #model #modeling #floodrisk #infrastructure #damage #costs #economics #verticallandmotion #VLM #ESA #Sentinel #Ahmedabad #Chennai #Amaravathi #Kochi #Kakinada #Kolkata #deltas #estuary #demographics #population #coastalsubsidence #landuse #planning #mitigation #farmland #agriculture #foodsecurity #groundwater #pumping #extraction

    #sealevelrise #subsidence #india #insar #radar #postdoc
  24. 💧🌏 Greg Cocks @[email protected] ·

    Thirty Years of the U.S. National Land Cover Database - Impacts and Future Direction
    --
    doi.org/10.14358/PERS.25-00121 <-- shared paper
    --
    “Editor's choice article for the October Issue of Photogrammetric Engineering and Remote Sensing.”
    #GIS #spatial #mapping #remotesensing #opendata #earthobservation #landcover #USA #NLCD #MRLCC #history #datacollection #impervioussurface #classifaction #landform #forestcanopy #fedscience #fedservice #deeplearning #AI #spatialanalysis #change #monitoring #usecase #research #landmanagement #management #policy #planning #support #agriculture #urbanplanning #environment #ecosystems #biodiversity #conservation #water #hydrology #humanhealth #risk #hazard #soils #naturalhazard #spatiotemporal #landchange #forestry #watermanagement #waterquality #publicsafety #groundwater #NCLA #wildfire #stormwater #extremeweather
    #USGS #EROS #NASA #USFS

    #gis #spatial #mapping #remotesensing #opendata #earthobservation