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#earthobservation — Public Fediverse posts

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

  1. 💧🌏 Greg Cocks @GregCocks ·

    The United States Is Replacing Every Official Latitude, Longitude And Height It Publishes, Existing Coordinates Will Move By As Much As Four Metres, And The Million Survey Marks In The Ground Will No Longer Be What The System Is Measured From
    --
    spacedaily.com/s-the-united-st <-- shared technical article
    --
    beta.ngs.noaa.gov/ <-- shared NGS NSRS Beta Product Release Site
    --
    alturl.com/wuzcg <-- shared NOAA/NGS β SPCS2022 online interactive map
    --
    geodesy.noaa.gov/ <-- shared NOAA National Geodetic Survey (NGS) home page
    --
    crops.extension.iastate.edu/po <-- shared technical article, ‘What You Need to Know About the 202[7] Datum Shift (GPS)’
    --
    geodesy.noaa.gov/GRAV-D/ <-- shared Gravity for the Redefinition of the American Vertical Datum (GRAV-D) home page
    --
    federalregister.gov/documents/ <-- shared US Federal Register page, ‘Updated Implementation Timeline for the Modernized National Spatial Reference System (NSRS)’
    --
    “The National Geodetic Survey has spent years building a replacement for the reference system that fixes every published position in the country. New geodetic-control submissions into the old system stop being accepted after January 13, 2027…
    Every official latitude, longitude and height published in the United States is going to change, by as much as four metres. The ground being described will not have moved at all. What is being replaced is the reference system those numbers are counted from.
    The National Geodetic Survey is retiring the North American Datum of 1983 [NAD83] and the North American Vertical Datum of 1988 [NGVD88.] Those are the horizontal and vertical reference systems that currently underpin surveying, flood mapping, construction and aviation across the country. In their place will come four new terrestrial reference frames and one new geopotential datum. The agency has kept the national reference system since its predecessor, the Survey of the Coast, was founded in 1807.
    || The reference surface is what is changing ||
    ... A coordinate is not a property of a place; it is a measurement of that place against an agreed reference surface. The United States is changing the reference surface. The four metres is the gap between two descriptions of the same unmoved point.
    That figure is not uniform either, and the agency does not present it as a single national number. Its guidance says the magnitude of change depends on which datum a user currently works in, where in the country they are, and which epoch the new coordinates refer to. Four metres is the outer edge of the range. NGS publishes separate maps for ellipsoid height change, orthometric height change, and horizontal change on the North American and Pacific plates…”
    # NAPGD2022
    @USGS @FGDC @ngs @NOAA

    #geoid2022 #geospatialdataact2018 #gravd #gems #nsrs #gnss
  2. 💧🌏 Greg Cocks @[email protected] ·

    The United States Is Replacing Every Official Latitude, Longitude And Height It Publishes, Existing Coordinates Will Move By As Much As Four Metres, And The Million Survey Marks In The Ground Will No Longer Be What The System Is Measured From
    --
    spacedaily.com/s-the-united-st <-- shared technical article
    --
    beta.ngs.noaa.gov/ <-- shared NGS NSRS Beta Product Release Site
    --
    alturl.com/wuzcg <-- shared NOAA/NGS β SPCS2022 online interactive map
    --
    geodesy.noaa.gov/ <-- shared NOAA National Geodetic Survey (NGS) home page
    --
    crops.extension.iastate.edu/po <-- shared technical article, ‘What You Need to Know About the 202[7] Datum Shift (GPS)’
    --
    geodesy.noaa.gov/GRAV-D/ <-- shared Gravity for the Redefinition of the American Vertical Datum (GRAV-D) home page
    --
    federalregister.gov/documents/ <-- shared US Federal Register page, ‘Updated Implementation Timeline for the Modernized National Spatial Reference System (NSRS)’
    --
    “The National Geodetic Survey has spent years building a replacement for the reference system that fixes every published position in the country. New geodetic-control submissions into the old system stop being accepted after January 13, 2027…
    Every official latitude, longitude and height published in the United States is going to change, by as much as four metres. The ground being described will not have moved at all. What is being replaced is the reference system those numbers are counted from.
    The National Geodetic Survey is retiring the North American Datum of 1983 [NAD83] and the North American Vertical Datum of 1988 [NGVD88.] Those are the horizontal and vertical reference systems that currently underpin surveying, flood mapping, construction and aviation across the country. In their place will come four new terrestrial reference frames and one new geopotential datum. The agency has kept the national reference system since its predecessor, the Survey of the Coast, was founded in 1807.
    || The reference surface is what is changing ||
    ... A coordinate is not a property of a place; it is a measurement of that place against an agreed reference surface. The United States is changing the reference surface. The four metres is the gap between two descriptions of the same unmoved point.
    That figure is not uniform either, and the agency does not present it as a single national number. Its guidance says the magnitude of change depends on which datum a user currently works in, where in the country they are, and which epoch the new coordinates refer to. Four metres is the outer edge of the range. NGS publishes separate maps for ellipsoid height change, orthometric height change, and horizontal change on the North American and Pacific plates…”
    #GEOID2022 #GeospatialDataAct2018 #GRAVD #GeMS # NAPGD2022 #NSRS #GNSS #GPS #earthfacing #earthobservation #USA #Nation #NATRF2022 #PATRF2022 #CATRF2022 #MATRF2022 #NAPGD2022 #GEOID2022 #SPCS2022 #geoid #latitude #longitude #height #elevation #reference #datums #coordinates #XYZ #control #GIS #spatial #mapping #fedscience #fedservice
    @USGS @FGDC @ngs @NOAA

    #geoid2022 #geospatialdataact2018 #gravd #gems #nsrs #gnss
  3. 💧🌏 Greg Cocks @[email protected] ·

    The United States Is Replacing Every Official Latitude, Longitude And Height It Publishes, Existing Coordinates Will Move By As Much As Four Metres, And The Million Survey Marks In The Ground Will No Longer Be What The System Is Measured From
    --
    spacedaily.com/s-the-united-st <-- shared technical article
    --
    beta.ngs.noaa.gov/ <-- shared NGS NSRS Beta Product Release Site
    --
    alturl.com/wuzcg <-- shared NOAA/NGS β SPCS2022 online interactive map
    --
    geodesy.noaa.gov/ <-- shared NOAA National Geodetic Survey (NGS) home page
    --
    crops.extension.iastate.edu/po <-- shared technical article, ‘What You Need to Know About the 202[7] Datum Shift (GPS)’
    --
    geodesy.noaa.gov/GRAV-D/ <-- shared Gravity for the Redefinition of the American Vertical Datum (GRAV-D) home page
    --
    federalregister.gov/documents/ <-- shared US Federal Register page, ‘Updated Implementation Timeline for the Modernized National Spatial Reference System (NSRS)’
    --
    “The National Geodetic Survey has spent years building a replacement for the reference system that fixes every published position in the country. New geodetic-control submissions into the old system stop being accepted after January 13, 2027…
    Every official latitude, longitude and height published in the United States is going to change, by as much as four metres. The ground being described will not have moved at all. What is being replaced is the reference system those numbers are counted from.
    The National Geodetic Survey is retiring the North American Datum of 1983 [NAD83] and the North American Vertical Datum of 1988 [NGVD88.] Those are the horizontal and vertical reference systems that currently underpin surveying, flood mapping, construction and aviation across the country. In their place will come four new terrestrial reference frames and one new geopotential datum. The agency has kept the national reference system since its predecessor, the Survey of the Coast, was founded in 1807.
    || The reference surface is what is changing ||
    ... A coordinate is not a property of a place; it is a measurement of that place against an agreed reference surface. The United States is changing the reference surface. The four metres is the gap between two descriptions of the same unmoved point.
    That figure is not uniform either, and the agency does not present it as a single national number. Its guidance says the magnitude of change depends on which datum a user currently works in, where in the country they are, and which epoch the new coordinates refer to. Four metres is the outer edge of the range. NGS publishes separate maps for ellipsoid height change, orthometric height change, and horizontal change on the North American and Pacific plates…”
    #GEOID2022 #GeospatialDataAct2018 #GRAVD #GeMS # NAPGD2022 #NSRS #GNSS #GPS #earthfacing #earthobservation #USA #Nation #NATRF2022 #PATRF2022 #CATRF2022 #MATRF2022 #NAPGD2022 #GEOID2022 #SPCS2022 #geoid #latitude #longitude #height #elevation #reference #datums #coordinates #XYZ #control #GIS #spatial #mapping #fedscience #fedservice
    @USGS @FGDC @ngs @NOAA

    #geoid2022 #geospatialdataact2018 #gravd #gems #nsrs #gnss
  4. 💧🌏 Greg Cocks @[email protected] ·

    The United States Is Replacing Every Official Latitude, Longitude And Height It Publishes, Existing Coordinates Will Move By As Much As Four Metres, And The Million Survey Marks In The Ground Will No Longer Be What The System Is Measured From
    --
    spacedaily.com/s-the-united-st <-- shared technical article
    --
    beta.ngs.noaa.gov/ <-- shared NGS NSRS Beta Product Release Site
    --
    alturl.com/wuzcg <-- shared NOAA/NGS β SPCS2022 online interactive map
    --
    geodesy.noaa.gov/ <-- shared NOAA National Geodetic Survey (NGS) home page
    --
    crops.extension.iastate.edu/po <-- shared technical article, ‘What You Need to Know About the 202[7] Datum Shift (GPS)’
    --
    geodesy.noaa.gov/GRAV-D/ <-- shared Gravity for the Redefinition of the American Vertical Datum (GRAV-D) home page
    --
    federalregister.gov/documents/ <-- shared US Federal Register page, ‘Updated Implementation Timeline for the Modernized National Spatial Reference System (NSRS)’
    --
    “The National Geodetic Survey has spent years building a replacement for the reference system that fixes every published position in the country. New geodetic-control submissions into the old system stop being accepted after January 13, 2027…
    Every official latitude, longitude and height published in the United States is going to change, by as much as four metres. The ground being described will not have moved at all. What is being replaced is the reference system those numbers are counted from.
    The National Geodetic Survey is retiring the North American Datum of 1983 [NAD83] and the North American Vertical Datum of 1988 [NGVD88.] Those are the horizontal and vertical reference systems that currently underpin surveying, flood mapping, construction and aviation across the country. In their place will come four new terrestrial reference frames and one new geopotential datum. The agency has kept the national reference system since its predecessor, the Survey of the Coast, was founded in 1807.
    || The reference surface is what is changing ||
    ... A coordinate is not a property of a place; it is a measurement of that place against an agreed reference surface. The United States is changing the reference surface. The four metres is the gap between two descriptions of the same unmoved point.
    That figure is not uniform either, and the agency does not present it as a single national number. Its guidance says the magnitude of change depends on which datum a user currently works in, where in the country they are, and which epoch the new coordinates refer to. Four metres is the outer edge of the range. NGS publishes separate maps for ellipsoid height change, orthometric height change, and horizontal change on the North American and Pacific plates…”
    #GEOID2022 #GeospatialDataAct2018 #GRAVD #GeMS # NAPGD2022 #NSRS #GNSS #GPS #earthfacing #earthobservation #USA #Nation #NATRF2022 #PATRF2022 #CATRF2022 #MATRF2022 #NAPGD2022 #GEOID2022 #SPCS2022 #geoid #latitude #longitude #height #elevation #reference #datums #coordinates #XYZ #control #GIS #spatial #mapping #fedscience #fedservice
    @USGS @FGDC @ngs @NOAA

    #geoid2022 #geospatialdataact2018 #gravd #gems #nsrs #gnss
  5. 💧🌏 Greg Cocks @[email protected] ·

    The United States Is Replacing Every Official Latitude, Longitude And Height It Publishes, Existing Coordinates Will Move By As Much As Four Metres, And The Million Survey Marks In The Ground Will No Longer Be What The System Is Measured From
    --
    spacedaily.com/s-the-united-st <-- shared technical article
    --
    beta.ngs.noaa.gov/ <-- shared NGS NSRS Beta Product Release Site
    --
    alturl.com/wuzcg <-- shared NOAA/NGS β SPCS2022 online interactive map
    --
    geodesy.noaa.gov/ <-- shared NOAA National Geodetic Survey (NGS) home page
    --
    crops.extension.iastate.edu/po <-- shared technical article, ‘What You Need to Know About the 202[7] Datum Shift (GPS)’
    --
    geodesy.noaa.gov/GRAV-D/ <-- shared Gravity for the Redefinition of the American Vertical Datum (GRAV-D) home page
    --
    federalregister.gov/documents/ <-- shared US Federal Register page, ‘Updated Implementation Timeline for the Modernized National Spatial Reference System (NSRS)’
    --
    “The National Geodetic Survey has spent years building a replacement for the reference system that fixes every published position in the country. New geodetic-control submissions into the old system stop being accepted after January 13, 2027…
    Every official latitude, longitude and height published in the United States is going to change, by as much as four metres. The ground being described will not have moved at all. What is being replaced is the reference system those numbers are counted from.
    The National Geodetic Survey is retiring the North American Datum of 1983 [NAD83] and the North American Vertical Datum of 1988 [NGVD88.] Those are the horizontal and vertical reference systems that currently underpin surveying, flood mapping, construction and aviation across the country. In their place will come four new terrestrial reference frames and one new geopotential datum. The agency has kept the national reference system since its predecessor, the Survey of the Coast, was founded in 1807.
    || The reference surface is what is changing ||
    ... A coordinate is not a property of a place; it is a measurement of that place against an agreed reference surface. The United States is changing the reference surface. The four metres is the gap between two descriptions of the same unmoved point.
    That figure is not uniform either, and the agency does not present it as a single national number. Its guidance says the magnitude of change depends on which datum a user currently works in, where in the country they are, and which epoch the new coordinates refer to. Four metres is the outer edge of the range. NGS publishes separate maps for ellipsoid height change, orthometric height change, and horizontal change on the North American and Pacific plates…”
    #GEOID2022 #GeospatialDataAct2018 #GRAVD #GeMS # NAPGD2022 #NSRS #GNSS #GPS #earthfacing #earthobservation #USA #Nation #NATRF2022 #PATRF2022 #CATRF2022 #MATRF2022 #NAPGD2022 #GEOID2022 #SPCS2022 #geoid #latitude #longitude #height #elevation #reference #datums #coordinates #XYZ #control #GIS #spatial #mapping #fedscience #fedservice
    @USGS @FGDC @ngs @NOAA

    #fedservice #fedscience #mapping #spatial #gis #control
  6. Barret @[email protected] ·

    Satellite view of Ohio — 2026-09-13
    Imagery: MODIS_Terra_CorrectedReflectance_TrueColor
    worldview.earthdata.nasa.gov/?

    Imagery: NASA GIBS #satellite #NASA #EarthObservation

    #satellite #nasa #earthobservation
  7. Barret @[email protected] ·

    Satellite view of Ohio — 2026-09-13
    Imagery: MODIS_Terra_CorrectedReflectance_TrueColor
    worldview.earthdata.nasa.gov/?

    Imagery: NASA GIBS #satellite #NASA #EarthObservation

    #satellite #nasa #earthobservation
  8. Barret @[email protected] ·

    Satellite view of Ohio — 2026-09-13
    Imagery: MODIS_Terra_CorrectedReflectance_TrueColor
    worldview.earthdata.nasa.gov/?

    Imagery: NASA GIBS #satellite #NASA #EarthObservation

    #earthobservation #nasa #satellite
  9. Barret @[email protected] ·

    Satellite view of Ohio — 2026-09-13
    Imagery: MODIS_Terra_CorrectedReflectance_TrueColor
    worldview.earthdata.nasa.gov/?

    Imagery: NASA GIBS #satellite #NASA #EarthObservation

    #satellite #nasa #earthobservation
  10. Barret @barret ·

    Satellite view of Ohio — 2026-09-13
    Imagery: MODIS_Terra_CorrectedReflectance_TrueColor
    worldview.earthdata.nasa.gov/?

    Imagery: NASA GIBS

    #satellite #nasa #earthobservation
  11. BGDon 🇨🇦 🇺🇸 👨‍💻 @[email protected] ·

    Spying on "reconnaissance spacecraft" in geostationary orbit (GEO), is gaining momentum.

    Company Astranis building Perceptor spacecraft designed to capture satellite activity in GEO orbits.

    FYI, GEO is typically 35,786kms/22,236 miles above Earth ... popular for communications, weather and "reconnaissance" satellites. space.com/space-exploration/sa #Space #Satellite #GEO #GeostationaryOrbit #Perceptor #Astranis #Spacecraft #Reconnaissance #Sensors #OpticalSensors #USSF #EarthObservation #USGov

    #space #satellite #geo #geostationaryorbit #perceptor #astranis
  12. BGDon 🇨🇦 🇺🇸 👨‍💻 @[email protected] ·

    Spying on "reconnaissance spacecraft" in geostationary orbit (GEO), is gaining momentum.

    Company Astranis building Perceptor spacecraft designed to capture satellite activity in GEO orbits.

    FYI, GEO is typically 35,786kms/22,236 miles above Earth ... popular for communications, weather and "reconnaissance" satellites. space.com/space-exploration/sa #Space #Satellite #GEO #GeostationaryOrbit #Perceptor #Astranis #Spacecraft #Reconnaissance #Sensors #OpticalSensors #USSF #EarthObservation #USGov

    #space #satellite #geo #geostationaryorbit #perceptor #astranis
  13. BGDon 🇨🇦 🇺🇸 👨‍💻 @[email protected] ·

    Spying on "reconnaissance spacecraft" in geostationary orbit (GEO), is gaining momentum.

    Company Astranis building Perceptor spacecraft designed to capture satellite activity in GEO orbits.

    FYI, GEO is typically 35,786kms/22,236 miles above Earth ... popular for communications, weather and "reconnaissance" satellites. space.com/space-exploration/sa #Space #Satellite #GEO #GeostationaryOrbit #Perceptor #Astranis #Spacecraft #Reconnaissance #Sensors #OpticalSensors #USSF #EarthObservation #USGov

    #space #satellite #geo #geostationaryorbit #perceptor #astranis
  14. BGDon 🇨🇦 🇺🇸 👨‍💻 @[email protected] ·

    Spying on "reconnaissance spacecraft" in geostationary orbit (GEO), is gaining momentum.

    Company Astranis building Perceptor spacecraft designed to capture satellite activity in GEO orbits.

    FYI, GEO is typically 35,786kms/22,236 miles above Earth ... popular for communications, weather and "reconnaissance" satellites. space.com/space-exploration/sa #Space #Satellite #GEO #GeostationaryOrbit #Perceptor #Astranis #Spacecraft #Reconnaissance #Sensors #OpticalSensors #USSF #EarthObservation #USGov

    #usgov #earthobservation #ussf #opticalsensors #sensors #reconnaissance
  15. BGDon 🇨🇦 🇺🇸 👨‍💻 @BrentD ·

    Spying on "reconnaissance spacecraft" in geostationary orbit (GEO), is gaining momentum.

    Company Astranis building Perceptor spacecraft designed to capture satellite activity in GEO orbits.

    FYI, GEO is typically 35,786kms/22,236 miles above Earth ... popular for communications, weather and "reconnaissance" satellites. space.com/space-exploration/sa

    #space #satellite #geo #geostationaryorbit #perceptor #astranis
  16. Astro Hawk (Ian Kluft) ✅🚀🛰️ @[email protected] ·

    "17 amazing photos taken from the International Space Station – lightning looks crazy from orbit!" by @Spacecom - Day, night and solar eclipse images by astronauts on #ISS show what an awesome view there is up there. skyatnightmagazine.com/space-m #NASA #space #photography #EarthObservation #OverviewEffect #spacegeek

    #iss #nasa #space #photography #earthobservation #overvieweffect
  17. Astro Hawk (Ian Kluft) ✅🚀🛰️ @[email protected] ·

    "17 amazing photos taken from the International Space Station – lightning looks crazy from orbit!" by @Spacecom - Day, night and solar eclipse images by astronauts on #ISS show what an awesome view there is up there. skyatnightmagazine.com/space-m #NASA #space #photography #EarthObservation #OverviewEffect #spacegeek

    #iss #nasa #space #photography #earthobservation #overvieweffect
  18. Astro Hawk (Ian Kluft) ✅🚀🛰️ @[email protected] ·

    "17 amazing photos taken from the International Space Station – lightning looks crazy from orbit!" by @Spacecom - Day, night and solar eclipse images by astronauts on #ISS show what an awesome view there is up there. skyatnightmagazine.com/space-m #NASA #space #photography #EarthObservation #OverviewEffect #spacegeek

    #iss #nasa #space #photography #earthobservation #overvieweffect
  19. Astro Hawk (Ian Kluft) ✅🚀🛰️ @[email protected] ·

    "17 amazing photos taken from the International Space Station – lightning looks crazy from orbit!" by @Spacecom - Day, night and solar eclipse images by astronauts on #ISS show what an awesome view there is up there. skyatnightmagazine.com/space-m #NASA #space #photography #EarthObservation #OverviewEffect #spacegeek

    #spacegeek #overvieweffect #earthobservation #photography #space #nasa
  20. Astro Hawk (Ian Kluft) ✅🚀🛰️ @[email protected] ·

    "17 amazing photos taken from the International Space Station – lightning looks crazy from orbit!" by @Spacecom - Day, night and solar eclipse images by astronauts on #ISS show what an awesome view there is up there. skyatnightmagazine.com/space-m #NASA #space #photography #EarthObservation #OverviewEffect #spacegeek

    #iss #nasa #space #photography #earthobservation #overvieweffect
  21. Denmark @[email protected] ·

    europesays.com/dk/165450/ Copenhagen, Denmark | EU Space Policy #Copenhagen #EarthObservation #ForestryAndBiodiversity

    #forestryandbiodiversity #earthobservation #copenhagen
  22. Jakub Nowosad @[email protected] ·

    Missed the OpenGeoHub Earth Observation Summer School 2026? 🛰️

    You can now explore the slides, links, and other course materials from the sessions in one place:

    github.com/Nowosad/OGH_summer_

    #EarthObservation #RemoteSensing #Geospatial #OpenGeoHub

    #earthobservation #remotesensing #geospatial #opengeohub
  23. Jakub Nowosad @[email protected] ·

    Missed the OpenGeoHub Earth Observation Summer School 2026? 🛰️

    You can now explore the slides, links, and other course materials from the sessions in one place:

    github.com/Nowosad/OGH_summer_

    #EarthObservation #RemoteSensing #Geospatial #OpenGeoHub

    #earthobservation #remotesensing #geospatial #opengeohub
  24. Jakub Nowosad @[email protected] ·

    Missed the OpenGeoHub Earth Observation Summer School 2026? 🛰️

    You can now explore the slides, links, and other course materials from the sessions in one place:

    github.com/Nowosad/OGH_summer_

    #EarthObservation #RemoteSensing #Geospatial #OpenGeoHub

    #opengeohub #geospatial #remotesensing #earthobservation
  25. Jakub Nowosad @[email protected] ·

    Missed the OpenGeoHub Earth Observation Summer School 2026? 🛰️

    You can now explore the slides, links, and other course materials from the sessions in one place:

    github.com/Nowosad/OGH_summer_

    #EarthObservation #RemoteSensing #Geospatial #OpenGeoHub

    #earthobservation #remotesensing #geospatial #opengeohub
  26. Jakub Nowosad @nowosad ·

    Missed the OpenGeoHub Earth Observation Summer School 2026? 🛰️

    You can now explore the slides, links, and other course materials from the sessions in one place:

    github.com/Nowosad/OGH_summer_

    #earthobservation #remotesensing #geospatial #opengeohub
  27. Bytes Europe @[email protected] ·

    Peatlands around Pärnu, Estonia | EU Space Support Office byteseu.com/2361525/ #EarthObservation #Estonia

    #estonia #earthobservation
  28. UK @[email protected] ·

    europesays.com/uk/1201474/ Peatlands around Pärnu, Estonia | EU Space Support Office #EarthObservation #EU #Europe #European #EuropeanUnion

    #europeanunion #european #europe #eu #earthobservation
  29. Switzerland @[email protected] ·

    europesays.com/ch/130072/ Snowfall in the Alps currently in line with historical averages #Alps #EarthObservation #EnergyAndEnvironment

    #energyandenvironment #earthobservation #alps
  30. 💧🌏 Greg Cocks @[email protected] ·

    Sub-Seasonal Forecasting Of Cropland Productivity Anomalies Using Satellite Soil Moisture In Water-Limited Environments
    --
    doi.org/10.1016/j.rse.2026.115 <-- shared paper
    --
    H/T @Adebowale Daniel Adebayo | Doctoral Candidate | Geospatial Data Scientist
    “When rainfall fails and evaporative demand climbs, root-zone soil moisture is where the deficit registers first and where it carries forward, weeks before crop condition reflects it. In this study [link above], [the authors] used SMAP root-zone soil moisture to forecast crop productivity anomalies across drought-prone croplands of Eastern and Southern Africa, and [they] quantified how much predictive value soil moisture actually carries, over what lead times, and under which hydroclimatic conditions. The contribution of soil moisture was negligible at short leads but grew steadily out to 40 days, and it concentrated in water-limited croplands where soil moisture and vegetation are most tightly coupled. During the 2024 southern African El Niño drought, the soil moisture informed model resolved the spatial pattern of productivity anomalies roughly a month in advance.
    Beyond the results themselves, this work is a pointer to how much predictive information soil moisture holds. Leveraging the temporal record of SMAP-related products together with the 100–200 metre resolution NISAR will deliver gives us, [believes the H/T], a clear path to attempt field-scale drought forecasting in the smallholder landscapes where early warning matters most…”
    #agriculture #crops #foodsecurity #cropland #productivity #forecasting #rootzone #soilmoisture #SMAP #NIRV #subseasonal #prediction #EasternAfrica #SouthernAfrica #africa #vegetation #anomaly #precipitation #ET #drought #extremeweather #water #hydrology #hydroclimate #productivity #arid #waterlimited #spatialanalysis #spatiotemporal #model #modeling #vegetation #Africa #ElNino #ElNiño #mitigation #prediction #forecast #smallholders #earlywarning #RZSM #SoilMoistureActivePassive #NearInfraredReflectance #NIR #remotesensing #earthobservation

    #agriculture #crops #foodsecurity #cropland #productivity #forecasting
  31. 💧🌏 Greg Cocks @[email protected] ·

    Interferometric Synthetic Aperture Radar (InSAR) For Monitoring Seasonal Snow
    --
    doi.org/10.1029/2025WR042866 <-- shared paper
    --
    eos.org/features/satellite-rad <-- shared technical article
    --
    H/T @Jack Tarricone, PhD | Assistant Research Scientist @ NASA GSFC/UMD ESSIC | Remote Sensing and Snow Hydrology
    “[The authors] review[ed] 25 years of progress in using InSAR to measure changes in snow water equivalent (SWE) and snow depth and discuss[ed] what’s needed to extend these methods to basin-scale snow monitoring with NISAR. [They] hope it’s a useful resource for people interested in snow, SAR/InSAR, remote sensing, and hydrology in general…”
    #GIS #spatial #mapping #remotesensing #earthobservation #InterferometricSyntheticApertureRadar #InSAR #literaturereview #research #history #monitoring #spatialanalysis #spatiotemporal #seasonal #snow #water #hydrology #waterresources #snowpack #snowmelt #ablation #melt #runoff #snowwaterequivalent #SWE #NISAR #snowdepth #basin #snowphase #estimation #change #spatial #GIS #mapping #temporal #model #modeling #algorithm #ecosystems #environment #habitat #agriculture #farming #snowmass #satellite

    #gis #spatial #mapping #remotesensing #earthobservation #interferometricsyntheticapertureradar
  32. 💧🌏 Greg Cocks @[email protected] ·

    Cities In Great Britain Most Vulnerable To Extreme Heat Revealed
    (OS index examines which ‘urban heat islands’ suffer the most – and which cope the best with rising temperatures)
    --
    theguardian.com/environment/20 <-- shared media article
    --
    ordnancesurvey.co.uk/news/new- <-- shared technical article, OS Heat Vulnerability Index
    --
    H/T @joe Clarkson | Campaign Manager - Diffusion PR
    “[The H/T] work[ed] … closely with Ordnance Survey (OS) on new research into which of Britain's cities are most vulnerable to retaining extreme heat, and how that vulnerability shifts between now and the turn of the century as record temperatures continue to climb…
    The newly commissioned OS Heat Vulnerability Index scored 71 cities across Britain using #4EI satellite temperature readings, @Met Office climate modelling projections from 2040 to 2100, and Ordnance Survey data on the makeup of natural and made environments in our cities. Put together, it measures how global warming will impact future heat vulnerability, and how urban heat islands form; a process in which hard surfaces absorb solar radiation through the day to keep centres warm overnight, while rural environments cool.
    Anyone who has been unfortunate enough to stand on a Tube platform or walk through central London this summer, or tried to sleep through a heatwave in a flat that hasn't cooled in months already knows what retained heat feels like. But it's more than an uncomfortable feeling. Extreme heat is claiming an increasing number of lives each year, and location-based intelligence like this is essential to support decisions on how we effectively mitigate and protect against climate change to save lives and protect critical infrastructure.
    What this analysis does is put a number on extreme heat, and shows where it's heading. As Britain's climate continues to warm, the capacity of our cities to cool themselves naturally will only matter more…”
    #ClimateChange #Heat #UrbanHeat #Heatwave #Climate #Warming #Infrastructure #London #Portsmouth #Resilience #OrdnanceSurvey #Geospatial #Data #extremeweather #extremeweather #publichealth #publicsafety #deaths #UK #GreatBritain #OS #HeatVulnerabilityIndex #vulnerability #spatialanalysis #mapping #model #modeling #analysis #spatiotemporal #climate #climatemodeling #spatial #mapping #remotesensing #earthobservation #solarradiation #natural #manmade #retainedheat #mitigation #planning #policy #infrastructure #concrete #asphalt #buildings #hardsurfaces #globalwarming #urbanheatislands #cities #urban
    @Ordnance Survey

    #4ei #climatechange #heat #urbanheat #heatwave #climate
  33. 💧🌏 Greg Cocks @[email protected] ·

    To Predict Tree Death, Scientists Tapped Gamma Rays To Peer Underground
    (Airborne radiation sensors could help forecast and prevent drought-driven tree mortality_
    --
    science.org/content/article/pr <-- shared technical article
    --
    doi.org/10.1029/2026GL122182 <-- shared paper
    --
    H/T @hannah Richter
    “Over an 18-month period starting in 2023, the dense forests of Western Australia [WA] experienced a record-setting drought. Jarrah trees towering 35 metres high died off in patchy brown splotches, turning 400 square kilometres - 3% of the forest - into brittle, fire-prone stands. The event led researchers to wonder whether there was a better way to predict where such die-offs might occur both there and in other forests, a problem that has long been tricky to solve because important factors such as soil depth are hidden underground…
    Now, those same researchers have unveiled a surprising new tool for predicting tree mortality: gamma rays [link above.] Resulting from the natural decay of the potassium-40 isotope from granite-rich bedrock, the radiation acts as a proxy for soil depth, which in turn signals how much water a tree can access during drought. The new method could be applied to other highly weathered soils, which cover one-third of Earth’s ice-free land...”
    --
    "... PLAIN LANGUAGE SUMMARY: During a record-breaking drought and heat event in 2023–2024, forests in southwestern Australia experienced widespread, patchy die-off. While we know that extreme weather triggers these events, it is often a hidden factor, the thickness of soil and the depth to underlying bedrock, that determines which trees live or die. Trees growing in shallow soil over solid rock are highly vulnerable due to limited water storage. Here, [they] show how to map these hidden zones from the air using gamma rays that are naturally emitted by potassium in the ground. Like southwestern Australia, many parts of the world have highly weathered soils where potassium has been washed out of the upper layers of soil. However, [they] showed that higher potassium areas signal that potassium-rich bedrock is closer to the surface and this is sensitive for tens of meters. By comparing gamma ray maps with ground-based geophysical surveys and satellite data, [they] showed that these potassium hotspots accurately predict where forests are most likely to experience die-off during a drought. These types of soils cover about one-third of the Earth's land, so the method provides a powerful new tool for managers to identify and protect vulnerable forests from future, hotter droughts…”
    #GIS #spatial #mapping #spatialanalysis #spatiotemporal #Australia #WesternAustralia #WA #forests #vegetation #bush #jarrah #karri #drought #heat #extremedrought #extremeweather #climatechange #water #waterresources #dieoff #soil #weathering #erosion #moisture #nutrients #airborne #gammarays #GRS #granite #gneiss #bedrock #geology #potassium40 #potassium #K #remotesensing #earthobservation #groundwater #interstitial #subsurface #waterstorage #electricalresistivitytomography

    #gis #spatial #mapping #spatialanalysis #spatiotemporal #australia
  34. 💧🌏 Greg Cocks @[email protected] ·

    Mapping Flood Agents In The Northern Pantanal Wetland Using Multiple Spatio-Temporal GIS And Remote Sensing Techniques
    --
    doi.org/10.1007/s13157-026-020 <-- shared paper
    --
    H/T @renato Gatto de Morais | Geógrafo | Mestre em Recursos Hídricos | Doutorando em Geografia
    “Combining MODIS data, TRMM, river discharge, a digital terrain model, and multinomial logistic regression, [the authors] identified three predominant classes of flood origin: local rainfall, bank overflow, and mixed areas. The model achieved a Nagelkerke Pseudo-R² of 0.63 and a classification accuracy of up to 81.2% (10-fold cross-validation). To the best of [their] knowledge, this is the first explicit approach to mapping flood agents for this wetland, a component that has historically remained unmapped despite its recognized influence on habitats and biodiversity…”
    --
    “The mapping of functional hydrologic units is crucial for enhancing our understanding of flooding and hydroecological processes in large wetlands. These units are typically defined by flooding frequency, duration, and magnitude, but another important hydrologic characteristic is the origin of flooding, known as the flood agent. This study presents an empirical framework utilizing remote sensing and GIS procedures for modeling flood agents in the northern Pantanal wetland. Eleven spatial data layers were derived from multi-year MODIS flood maps, daily rainfall estimates from the TRMM 3B42 grid, in situ discharge data, the BEST Digital Terrain Model, and a hydrographic network layer. These layers were tested for their predictive power in a multinomial logistic regression mapping model. Model performance metrics, along with qualitative validation of mapping outcomes using in situ flooding measurements, and vegetation and soil data from field test sites, support the plausibility of the proposed mapping scheme. However, they also highlight the challenges of flood agent mapping in large tropical wetlands…”
    #GIS #spatial #mapping #MODIS #TRMM #riverdischarge #digitalterrainmodel #multinomiallogisticregression #geostatistics #Pantanal #Cuiaba #Brazil #water #hydrology #spatialanalysis #spatiotemporal #remotesensing #earthobservation #flood #flooding #source #type #floodagent #tropical #wetland #habitat #biodiversity #ecosystem #hydrologicunit #hydroecology #model #modeling #rainfall #precipitation #weather #climate #discharge #network #metrics

    #gis #spatial #mapping #modis #trmm #riverdischarge
  35. 💧🌏 Greg Cocks @[email protected] ·

    Comparing DESIS Hyperspectral and Landsat 10 Simulated Superspectral Data for Crop Type Classification in California’s Central Valley
    --
    doi.org/10.3390/rs18142282 <-- shared paper
    --
    usgs.gov/publications/comparin <-- shared USGs publication page
    --
    H/T @USGS
    “How can we get better at classifying crops from space? 🛰️🌽
    Some types of satellite imagery are better at distinguishing crops than others. A USGS study compared two approaches and found one produced more accurate crop maps.
    Here's what the researchers found:
    • Hyperspectral imagery achieved 86% accuracy, compared to 75% for simulated superspectral imagery.
    • Using just 14 carefully selected hyperspectral bands produced nearly the same results as using all 60 DLR Earth Sensing Imaging Spectrometer (DESIS) bands, showing those wavelengths contain much of the information needed to distinguish crop types.
    • Using superspectral imagery on the upcoming Landsat 10 mission will allow for routine tracking of crops and enhance finer crop mapping.
    • The findings help scientists identify which wavelengths provide the most useful information for crop mapping and future remote sensing applications.
    Better crop maps will help governments and scientists track global agriculture, monitor the current crop season, and study agricultural trends…”
    --
    “HIGHLIGHTS:
    • What are the main findings?
    - The 14 DESIS hyperspectral narrowbands (10 nm) aligned with the Landsat 10 (formerly Landsat Next) spectral dataset produced similar accuracy results to the full 60-band DESIS hyperspectral dataset for classifying crop types. These 14 DESIS narrowbands resulted in higher accuracy than the 14 simulated Landsat 10 superspectral broadbands.
    - When using DESIS narrowbands, Support Vector Machine (SVM) resulted in higher accuracy than Random Forest (RF).
    • What are the implications of the main findings?
    - A carefully selected set of 14 DESIS hyperspectral narrowbands (10 nm) can achieve classification accuracy comparable to those obtained using all 60 DESIS narrowbands across the 400–1000 nm range. These 14 strategically positioned narrowbands classified crop types with higher classification accuracy than the corresponding 14 Landsat 10 superspectral broadbands within the same spectral range.
    - This study underscores the importance of multi-temporal imagery across the full crop-growing season for achieving more detailed and accurate crop type classifications. Such temporal coverage is more feasible with the planned Landsat 10 routine acquisition of broadband imagery than with task-based hyperspectral collections…”
    #hyperspectral #superspectral #optimalbands #randomforest #supportvectormachine #agriculture #crops #croptype #classifaction #croplands #California #CentralValley #GIS #spatial #mapping #remotesensing #earthobservation #imagery #DESIS #Landsat #Landsat10 #satellite #spatialanalysis #spatiotemporal #global #AI #machinelearning #model #modeling #SupportVectorMachine #SVM #RandomForest #RF #GoogleEarthEngine
    @USGS

    #hyperspectral #superspectral #optimalbands #randomforest #supportvectormachine #agriculture
  36. 💧🌏 Greg Cocks @[email protected] ·

    Impact Of Urbanization Driven Land Use And Land Cover Change On Ecological Environmental Quality In Rupandehi Nepal Assessed Using The Remote Sensing Ecological Index
    --
    doi.org/10.1007/s44288-026-006 <-- shared paper
    --
    kathmandupost.com/money/2026/0 <-- shared media article
    --
    H/T@ Gaurav Parajulim
    “[The authors] studied how the ecological quality of Nepal's Rupandehi District has changed over three decades (1993–2023), using satellite imagery and the Remote Sensing Ecological Index (RSEI) to track the health of the landscape year by year and to understand how urbanization-driven land use change has reshaped it.
    What [they] found tells a nuanced story: as Butwal and Bhairahawa grew and built-up land expanded, ecological quality shifted in ways that a single number can't capture, some areas recovered, others declined, and the patterns rarely moved in a straight line…”
    --
    “Rapid urbanization and population growth are major drivers of land use and land cover (LULC) change and can substantially alter ecological environmental quality (EEQ). This study assessed the spatiotemporal dynamics of LULC and their effect on EEQ in Rupandehi District, Nepal, over a 30-year period (1993–2023). Four ecological indicators representing greenness, wetness, dryness, and heat were derived from Landsat imagery in Google Earth Engine (GEE), and LULC was classified using a Support Vector Machine (SVM). The Remote Sensing Ecological Index (RSEI) was then constructed from these indicators using Principal Component Analysis (PCA) in ArcGIS Pro, and its spatial structure was examined using global and local spatial autocorrelation. The mean RSEI followed a non-linear trajectory, rising from 0.59 in 1993 to 0.635 in 2004, declining to 0.55 in 2013, and recovering to 0.67 in 2023, indicating an overall improvement in EEQ with a temporary mid-period decline. Over the same period, built-up areas expanded substantially and agricultural land declined, whereas forest cover fluctuated but showed a slight net increase by 2023, and barren land decreased markedly. Higher EEQ was concentrated in the forested northern hills, while lower values occurred in the urban centers of Butwal and Bhairahawa, closely matching the spatial pattern of LULC change. The results indicate that ecological quality reflects the combined influence of all land cover classes rather than any single class. This study provides a transferable and reproducible workflow for long-term ecological assessment based on openly available Landsat data, with the analysis code shared in a public repository, offering practical guidance for sustainable land management and environmentally responsible urban development...”
    #GIS #spatial #mapping #RemoteSensing #GIS #RSEI #EnvironmentalMonitoring #Nepal #Research #GoogleEarthEngine #ArcGIS #EcologicalQuality #spatialautocorrelation #ecology #environment #earthobservation #RemoteSensingEcologicalIndex #landscape #urbanisation #urban #development #landuse #change #spatialanalysis #spatiotemporal

    #gis #spatial #mapping #remotesensing #rsei #environmentalmonitoring
  37. 💧🌏 Greg Cocks @[email protected] ·

    The Latest Data Confirms - Forest Fires Are Getting Worse
    --
    wri.org/insights/global-trends <-- shared technical article
    --
    alturl.com/efp6m <-- shared (focused) #GlobalNatureWatch web map
    --
    science.nasa.gov/earth/explore <-- shared NASA technical article, ‘Wildfires and Climate Change’
    --
    doi.org/10.3389/frsen.2022.825 <-- shared paper
    --
    doi.org/10.1073/pnas.2505418122 <-- shared paper
    --
    doi.org/10.1088/1748-9326/add6 <-- shared paper
    --
    globalnaturewatch.org/dashboar <-- shared Global Nature Watch dashboard
    --
    youtu.be/-0-pv1Bqm-U?si=IHcZJN <-- shared overview video
    --
    grist.org/wildfires/the-us-has <-- shared technical article, ‘Fire is responsible for a quarter of US forest loss since 2021’
    --
    nytimes.com/2026/04/29/climate <-- shared media article
    --
    H/T @ World Resources Institute
    [‘topical’ - Europe, North America, indeed globally, more & more…]
    “New data shows that forest fires are getting worse, burning more than twice as much tree cover today as they did 20 years ago, largely due to climate change…
    The latest data [2nd link above] confirms [that] forest fires are becoming more widespread and destructive around the globe. Updated data from researchers [3rd link above] shows that between 2001 and 2025 forest fires now burn over twice as much tree cover each year as they did two decades ago, and more than three times as much in the tropics.
    This increased fire activity has been starkly visible in recent years. Record-setting blazes are becoming the norm, with four of the five worst years for global forest fires occurring since 2021. As fires worsen - including in historically low-risk areas, like rainforests - they are becoming an increasingly prevalent driver of global forest loss…”
    #GlobalForestWatch #GlobalNatureWatch #deforestation #fire #wildfire #forest #vegetation #climatechange #risk #hazard #loss #ecosystems #GIS #spatial #mapping #remotesensing #earthobservation #spatialanalysis #spatiotemporal #global #worldwide #forestfire #damage #destruction #fireactivity #forestLOSS
    @WRI | @Global Nature Watch

    #globalnaturewatch #globalforestwatch #deforestation #fire #wildfire #forest
  38. 💧🌏 Greg Cocks @[email protected] ·

    Flood And Landslide Susceptibility Assessment And Multi Hazard Interaction Mapping Using Machine Learning And GIS For Sustainable Settlement Planning In Nepal
    --
    doi.org/10.1007/s44288-026-006 <-- shared paper
    --
    H/T @Narayan Thapa | Earth Data Modeling
    “Nepal lies within an active seismic zone and is influenced by most dynamic climatic systems in the world. It faces compounding floods and landslide threats. Impacts are worst where multi-hazard interactions create spatially linked corridors. Despite frequent co-occurrence, national-scale assessments remain limited. This study presents machine learning and GIS-based approach to map nationwide susceptibility to floods, landslides, and identify their potential interaction zones, and delineate critical multi-hazard flow zones through spatial adjacency analysis. Using Google Earth Engine, the Random Forest model integrates topographic, climatic, environmental, and hydrological datasets to overcome subjective expert-driven methods. The model achieved strong predictive accuracy (AUC: 0.84 for floods, 0.85 for landslides). The results showed 19% of Nepal’s lowlands are medium to very highly susceptible to inundation, threatening approximately 900,000 people and over 3.4 million buildings; whilst in the hilly terrains, 40% is susceptible to slope-failure endangering 200,000 people and about 0.6 million buildings. K-means clustering followed by spatial adjacency analysis identified four spatial zonation: 81% of national area as low-hazard zone, 9% as flood-only zone, 5% as landslide-only zone, and 5% as interaction zones. Critical multi-hazard flow zone covering 7,588 km² represents spatially connected corridors linking interaction zones to downstream flood-prone populated areas, affecting 88 km² built-up land and 1,722 km² cropland. These zones represent susceptibility-based spatial connectivity rather than physically simulated cascading processes. These findings support recommendations for risk-informed land-use planning, resilient infrastructure development and climate adaptation aligned to sustainable development and investment risk screening…”
    #GIS #spatial #mapping #GoogleEarthEngine #MachineLearning #RemoteSensing #GeospatialAI #DisasterRiskReduction #MultiHazard #ClimateAdaptation #climatechange #extremeweather #LandUsePlanning #SustainableDevelopment #InfrastructurePlanning #RiskAssessment #NaturalHazards #Nepal #EarthObservation #HinduKushHimalaya #HKH #HinduKush #Himalayas #risk #hazard #assessment #national #regional #spatialanalysis #spatiotemporal #massmovement #landslide #assessment #mitigation #water #hydrology #flood #flooding #sustainability

    #gis #spatial #mapping #googleearthengine #machinelearning #remotesensing
  39. 💧🌏 Greg Cocks @[email protected] ·

    Enhancements To The USGS Landsat Level 2 Surface Temperature And Emissivity Product For Collection3 Reprocessing
    --
    doi.org/10.1016/j.rse.2026.115 <-- shared paper
    --
    H/T @terry Sohl | USGS EROS Science Branch Chief
    “HIGHLIGHTS:
    • C3 advances Landsat TIR atmospheric correction, emissivity correction, and uncertainty estimates.
    • C3 enables global surface temperature products, including polar regions.
    • C3 retrievals improve accuracy and consistency across validation sites.
    • Split window and single channel methods diverge at extreme temperature conditions.
    • C3 and Landsat 10 support multi-decadal climate monitoring.
    ABSTRACT: The Landsat program provides the longest continuous global record of thermal infrared observations of the Earth's surface, underpinning critical applications in climate monitoring, water resources, ecosystem dynamics, urban heat analysis, and natural hazard assessment. The release of a global inventory of Landsat Collection 2 Level 2 surface temperature products by the U.S. Geological Survey (USGS) marked a major milestone in operational provision of Landsat thermal infrared analysis-ready data. Ongoing validations and community uses of Collection 2 have identified opportunities to further improve accuracy, uncertainty characterization, and emissivity correction across diverse atmospheric and surface conditions. In preparation for the planned Landsat Collection 3 reprocessing of the Landsat data record in the late 2020s, the USGS is implementing a coordinated set of enhancements to the Level 2 surface temperature products. These include revised emissivity estimation that leverages external datasets, improved atmospheric characterization and uncertainty propagation, expanded dynamic range for high temperature targets, consideration of split window atmospheric correction algorithm for Landsat 8 and 9, and decoupling of thermal infrared processing from visible to shortwave infrared constraints to enable surface temperature retrievals under low or no solar illumination conditions. These changes are designed to improve product quality and consistency across the Landsat record. Beyond near-term performance gains, the Collection 3 design establishes a scalable processing architecture to accommodate the expanded spectral and radiometric measurement capabilities of the forthcoming Landsat 10 mission. By preserving continuity across the Landsat 4–9 record while enabling future algorithm evolution, Landsat Collection 3 will provide a foundation for long-term, multi-decadal Earth system thermal infrared observations…”
    #GIS #spatial #mapping #satellite #remotesening #earthobservation #Landsat #thermalinfrared #TIR #surface #temperature #emissivity #thermal #infrared #analysisreadydata #Collection2 #Collection3 #opendata #atmosphericcorrection #global #climate #monitoring #waterresources #ecosystems #dynamics #urbanheat #spatialanalysis #spatiotemporal #naturalhazards #updates #EROS #USGS
    @USGS EROS | @USGS

    #gis #spatial #mapping #satellite #remotesening #earthobservation
  40. 💧🌏 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
  41. 💧🌏 Greg Cocks @[email protected] ·

    Geospatial Data As Bioethical Evidence
    --
    doi.org/10.4401/jgsg-111 <-- shared paper
    --
    theconversation.com/gaza-we-an <-- shared technical article
    --
    scientificamerican.com/article <-- shared 2023 technical article
    --
    “Satellite imagery now documents systematic patterns of infrastructure destruction at spatial resolutions and temporal cadences that were unavailable during the atrocities of the twentieth century. Whether and how such data may enter bioethical deliberation, however, remains under-theorized. Quantitative remote sensing produces damage percentages, not normative claims, and bridging the two without committing an is-ought fallacy requires an explicit epistemological procedure. The contribution developed here is normative and epistemological rather than empirical. A six-component admissibility framework integrates, for the first time, geospatial evidence, population-level bioethical principlism, and the coherentist verification epistemology of political fact-checking into a single reproducible procedure for the bioethical use of satellite imagery. The first component specifies evidence admissibility criteria tailored to bioethical rather than strictly legal use. The second requires coherentist triangulation across methodologically independent remote sensing studies. The third operates as a bioethical relevance filter mapping infrastructure categories onto population-level social determinants of health. The fourth operationalizes principlism by translating health justice, accountability, solidarity, and sustainability into measurable geospatial observables. The fifth establishes ethical representation safeguards against voyeuristic or dehumanizing uses of destruction imagery. The sixth demands explicit epistemic humility regarding uncertainty, data missingness, and attribution limits. The Gaza conflict provides the case in point. Two independently produced geospatial studies, one based on SAR coherent change detection and one on very-high-resolution optical analysis, converge on extensive damage to civilian healthcare, water, sanitation, and educational infrastructure, and thereby satisfy the coherentist triangulation requirement of the framework. The resulting inference licenses bioethical claims of systematic survival infrastructure degradation while preserving transparent boundaries between what satellite evidence can and cannot establish about genocidal intent…”
    #geoethics #GIS #spatial #mapping #remotesensing #earthobservation #imagery #satellite #opendata #conflict #war #military #destruction #infrastructure #spatiotemporal #bioethical #evidence #damagepercentages #spatialanalysis #change #quantitative #metrics #normative #epistemological #admissibility #framework #factchecking #controlled #publicsafety #publichealth #healthjustice #geospatialobservables #observation #uncertainty #controls #boundaries #changedetection #coherentisttriangulation #example #gaza

    #geoethics #gis #spatial #mapping #remotesensing #earthobservation
  42. 💧🌏 Greg Cocks @[email protected] ·

    Scientists See More Vegetation In The Himalayas - But It Is Not Good News, Because That Extra “Green” Can Disrupt Water, Snow, And High-Mountain Biodiversity | Plants Growing Higher Across Himalaya As Climate Warms
    (Vegetation On The Move: Elevational Shifts And Greening Dynamics Across The Himalayan Alpine Zone)
    --
    ecoticias.com/en/scientists-se <-- shared technical article
    --
    news.exeter.ac.uk/faculty-of-e <-- shared technical newsitem
    --
    doi.org/10.1002/ecog.08259 <-- shared (2026) paper
    --
    doi.org/10.1111/gcb.14919 <-- shared (2020) paper
    --
    “For years, the biggest climate warning from the Himalaya was easy to picture because glaciers were shrinking on the roof of Asia. Now, researchers are pointing to a quieter signal, one that can look almost harmless from a distance. The mountains are getting greener.
    New research [link above] shows alpine vegetation moving higher across six Himalayan regions from 1999 to 2022, pushed in part by warming and reduced snow depth. That might sound like nature recovering, but in this fragile landscape, more plant cover at extreme heights may change how snow is stored, how water runs downhill, and how rivers behave for communities far below…”
    #GIS #spatial #mapping #remotesensing #earthobservation #satellite #landsat #landcover #NDVI #Himalaya #Nepal #India #Bhutan #climatechange #glacier #vegetation #alpine #level #greening #spatialanalysis #spatiotemporal #snow #water #ice #hydrography #hydrology #ecosystems #humaninpacts #phenology #model #modeling #HighMountainAsia #greenness #ERA5 #vegetationline #altitude #climatictrends #warming #precipitation #rainfall

    #gis #spatial #mapping #remotesensing #earthobservation #satellite
  43. 💧🌏 Greg Cocks @[email protected] ·

    Decoupling Of Surface Water Storage From Precipitation In Global Drylands Due To Anthropogenic Activity
    --
    doi.org/10.1038/s44221-024-003 <-- shared paper
    --
    “The availability of surface water in global drylands is essential for both human society and ecosystems. However, the long-term drivers of change in surface water storage, particularly those related to anthropogenic activities, remain unclear. Here [they] use[d] multi-mission remote sensing data to construct monthly time series of water storage changes from 1985 to 2020 for 105,400 lakes and reservoirs in global drylands. An increase of 2.20 km³ per year in surface water storage is found primarily due to the construction of new reservoirs. For lakes and old reservoirs (constructed before 1983), conversely, the trend in storage is minor when aggregated globally, but they dominate surface water storage trends in 91% of individual global dryland basins. Further analysis reveals that long-term storage changes in these water bodies are primarily linked to anthropogenic factors - including human-induced warming and water-management practices - rather than to precipitation changes, as previously thought. These findings reveal a decoupling of surface water storage from precipitation in global drylands, raising concerns about societal and ecosystem sustainability…”
    #water #hydrology #hydrography #waterstorage #waterresources #surfacewater #global #drylands #precipitation #rainfall #watersecurity #ecosystems #habitat #publichealth #anthropogenic #GIS #spatial #mapping #remotesensing #earthobservation #spatiotemporal #spatialanalysis #monitoring #geostatistics #engineering #reservoirs #infrastructure #lakes #waterbodies #globalwarming #climatechange #sustainability #planning #baseline

    #water #hydrology #hydrography #waterstorage #waterresources #surfacewater
  44. 💧🌏 Greg Cocks @[email protected] ·

    Remote Sensing And GIS-Supported Framework Of Pre-Monsoon Drought Assessment In Bangladesh (2000–2022) Using CHIRPS-Based SPI-3 And MODIS-Derived Vegetation And Temperature Indices
    --
    doi.org/10.1007/s12665-026-128 <-- shared paper
    --
    H/T MD. ABDULLAH AL MAMUNM | Studying PhD in Rural and Environmental Sciences
    “১ বছর ২০ দিন লেগে গেল! প্রথম ৪ জন রিভিউয়ারের প্রায় ৫০+ কমেন্টের পর মনে হয়েছিল আর এগোব না। তবে আমার সুপারভাইজার বলেছিলেন, “রিজেকশনের চেয়ে কমেন্ট ফেস করা ভালো।”
    --
    #GIS #spatial #mapping #remotesensing #Bangladesh #earthobservation #water #hydrology #premoonsoon #moonsoon #drought #CHIRPS #MODIS #SPI #vegetation #temperature #indices #parameters #SPI #NDVI #VCI #TCI #VHI #monitoring #droughts #agriculture #farming #crop #cultivation #yield #foodsecurity #weather #rainfall #precipitation #Pearsoncorrelation #geostatistics #irrigation #watersecurity #foodsecurity #policy #planning

    #gis #spatial #mapping #remotesensing #bangladesh #earthobservation
  45. 💧🌏 Greg Cocks @[email protected] ·

    Scale Dependence In Remotely Sensed Biodiversity: Leveraging Continental-Scale Imaging Spectroscopy From The National Ecological Observatory Network [spatial analysis]
    --
    doi.org/10.1002/rse2.70068 <-- shared paper
    --
    doi.org/10.1038/s41559-022-017 <-- shared paper
    --
    #spectraldiversity #spectroscopy #spatialscale #US #NEON #NationalEcologicalObservatoryNetwork #species #ecology #humanimpacts #remotesensing #biodiversity #earthobservation #GIS #spatial #mapping #scale #scale #diversity #metrics #ecosystems #spectral #richness #scaledependency #principalcompoenent #divergence #spatialanalysis #raster #topography #climate #geomorphology #regression #geostatistics #vegetation #plant #area #region #largescale #continent #forest #tree

    #spectraldiversity #spectroscopy #spatialscale #us #neon #nationalecologicalobservatorynetwork
  46. 💧🌏 Greg Cocks @[email protected] ·

    A Review Of Evolving Remote Sensing And Automated Techniques In Rock Glacier Mapping
    --
    doi.org/10.1016/j.earscirev.20 <-- shared paper
    --
    #GIS #spatial #mapping #rockglacier #glaciers #permafrost #remotesensing #interferometry #earthobservation #spatialanalysis #machinelearning #AI #machinelearning #ML #deeplearning #CNN #metrics #inventory #earthobservation #GeoAI #geostatistics #InSAR #LiDAR #radar #satellite #review #literaturereview #geomorphology #geomorphometry #hydrology #geohazard #risk #hazard #engineeringgeology #biodiversity #permafrost #cryosphere #ice #snow #geology #assessment #survey #research
    @Geospatial Research Institute Toi Hangarau | @University of Canterbury

    #gis #spatial #mapping #rockglacier #glaciers #permafrost
  47. Sebastian Büttrich @ ITU @[email protected] ·

    Our Danish Student #Cubesat Project's second #satellite, #DISCO 2, successfully deployed today

    Also pictured: #Earth

    #Denmark #Greenland #EarthObservation #Sband #VHF

    #cubesat #satellite #disco #earth #denmark #greenland
  48. 💧🌏 Greg Cocks @[email protected] ·

    A Review Of Current Best Practices And Future Directions In Assimilating GRACE/-FO Terrestrial Water Storage Data Into Numerical Models
    --
    doi.org/10.5194/hess-30-985-20 <-- shared technical article/review 📖 🔗
    --
    grace.jpl.nasa.gov/ <-- @nasa @JPL home page, Gravity Recovery and Climate Experiment (GRACE)
    --
    #GRACE #GRACEFO #DataAssimilation #EarthObservation #Hydrology #WaterResources #ClimateScience #RemoteSensing #CRC1502 #GIS #spatial #mapping #remotesensing #satellite #earthobservation #water #hydrology #model #modeling #landsurface #hydrogeomorphology #geomorphology #geomorphometry #waterresources #waterstorage #monitoring #groundwater #trends #spatialanalysis #spatiotemporal #droughts #floods #extremeweather #literature #review #summary #watercycle #geostatistics #humanimpacts #irrigation #watermanagement #anthropogenic #pumping #extraction #AI #ML #machinelearning

    #grace #gracefo #dataassimilation #earthobservation #hydrology #waterresources
  49. 💧🌏 Greg Cocks @[email protected] ·

    Drivers Of Forest Disturbance In Southeast Asia [incl. spatial analysis]
    --
    doi.org/10.1016/j.jag.2026.105 <-- shared paper 🔗
    --
    github.com/shijuanchen/SEA_for <-- shared GitHub ‘data repository 🔗
    --
    #GIS #spatial #mapping #spatialanalysis #spatiotemporal #forest #vegetation #Forestdisturbance #Forestdegradation #Deforestation #remotesensing #SoutheastAsia #Asia #tropicalforests #timeseriesanalysis #geostatistics #disturbance #clearing #planting #agriculture #earthobservation #imagery #CCDC #changedetection #landcover #landuse #change #plantation #cultivation #slashandburn #planning #mitigation #catalogue #conservation #management #landmanagement #machinelearning #imageanalysis #AI

    #gis #spatial #mapping #spatialanalysis #spatiotemporal #forest
  50. 💧🌏 Greg Cocks @[email protected] ·

    Turbidity And Fecal Indicator Bacteria In Recreational Marine Waters Increase Following The 2018 Woolsey Fire [incl. remote sensing]
    --
    doi.org/10.1038/s41598-022-059 <-- shared paper
    --
    science.nasa.gov/earth/earth-o <-- shared (NASA) technical / earth observation article
    --
    yubanet.com/california/woolsey <-- shared technical article
    --
    ui.adsabs.harvard.edu/abs/2022 <-- shared (Harvard) technical article
    --
    jpl.nasa.gov/news/california-f <-- shared (NASA) TECHNICAL ARTICLE
    --
    #GIS #spatial #mapping #earthobservation #remotesensing #wildfire #runoff #sediment #marine #ocean #coast #coastal #waterquality #turbidity #bacteria #fecal #coliform #enterococcus #WoolseyFire #California #USA #statistics #regression #geostatistics #insitu #sampling #burnarea #plume #ecosystems #habitat #publichealth #environmentalhealth #monitoring

    #gis #spatial #mapping #earthobservation #remotesensing #wildfire