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#humanexposure — Public Fediverse posts

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

  1. 💧🌏 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
  2. 💧🌏 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
  3. 💧🌏 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
  4. 💧🌏 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
  5. 💧🌏 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
  6. Chuck Darwin @[email protected] ·

    Ocean spray emits more PFAS than industrial polluters, study finds

    Ocean waves crashing on the world’s shores emit more PFAS into the air than the world’s industrial polluters, new research has found, raising concerns about environmental contamination and human exposure along coastlines.

    The study measured levels of PFAS released from the bubbles that burst when waves crash, spraying aerosols into the air.

    It found sea spray levels were hundreds of thousands times higher than levels in the water.

    The contaminated spray likely affects groundwater, surface water, vegetation, and agricultural products near coastlines that are far from industrial sources of PFAS, said Ian Cousins, a Stockholm University researcher and the study’s lead author.

    “There is evidence that the ocean can be an important source [of PFAS air emissions],” Cousins said.
    “It is definitely impacting the coastline.”

    PFAS are a class of 15,000 chemicals used across dozens of industries to make products resistant to water, stains and heat.

    Though the compounds are highly effective, they are also linked to cancer, kidney disease, birth defects, decreased immunity, liver problems and a range of other serious diseases.

    They are dubbed “forever chemicals” because they do not naturally break down and are highly mobile once in the environment, so they continuously move through the ground, water and air.

    PFAS have been detected in all corners of the globe, from penguin eggs in Antarctica to polar bears in the Arctic.

    EPA has limited six ‘forever chemicals’ in drinking water – but there are 15,000

    theguardian.com/environment/20

    #OceanSpray #PFAS #IndustrialPolluters #EnvironmentalContamination #HumanExposure #Coastlines #SeaSpray #Groundwater #SurfaceWater #Vegetation #AgriculturalProducts #ForeverChemicals #Cancer #KidneyDisease #BirthDefects #Immunity #LiverProblems #Antarctica #Arctic #TheGuardian

    #oceanspray #pfas #industrialpolluters #environmentalcontamination #humanexposure #coastlines
  7. Sam Harrison @[email protected] ·

    New #ECHA investigation finds substances causing cancer, genetic mutations or harming reproduction are present in childcare products, such as car seats, bibs and baby changing mats. echa.europa.eu/-/echa-s-invest

    #CMR #CLP #carcinogen #mutagen #humanexposure

    #humanexposure #mutagen #carcinogen #clp #cmr #echa