#earthobservation — Public Fediverse posts on home.social

BGDon 🇨🇦 🇺🇸 👨‍💻 @[email protected] · 2026-09-07 · 19:16 UTC

India (ISRO) has successfully launched its first geostationary Earth observation imager.

Operating from a geostationary orbit 36,000 kms above the equator, the new Earth observation satellite delivers continuous, real-time multispectral imaging of the Indian subcontinent and Indian Ocean region:

This satellite is capable of capturing high-resolution optical, near-infrared, and thermal infrared channels to monitor storm formation, sea surface temperatures, and land vegetation indices. https://satnews.com/2026/08/31/isro-deploys-first-geostationary-earth-imager-as-navic-constellation-operates-below-baseline-threshold/ #Space #India #Satellite #EarthObservation #Imaging #SatelliteImaging #OpticalImaging #Infrared #ThermalImaging #GeostationaryOrbit #GSO #IndianSpaceResearchOrganisation #ISRO

#space #india #satellite #earthobservation #imaging #satelliteimaging

BGDon 🇨🇦 🇺🇸 👨‍💻 @BrentD · 2026-09-07 · 19:16 UTC

India (ISRO) has successfully launched its first geostationary Earth observation imager.

Operating from a geostationary orbit 36,000 kms above the equator, the new Earth observation satellite delivers continuous, real-time multispectral imaging of the Indian subcontinent and Indian Ocean region:

This satellite is capable of capturing high-resolution optical, near-infrared, and thermal infrared channels to monitor storm formation, sea surface temperatures, and land vegetation indices. https://satnews.com/2026/08/31/isro-deploys-first-geostationary-earth-imager-as-navic-constellation-operates-below-baseline-threshold/ #Space #India #Satellite #EarthObservation #Imaging #SatelliteImaging #OpticalImaging #Infrared #ThermalImaging #GeostationaryOrbit #GSO #IndianSpaceResearchOrganisation #ISRO

#space #india #satellite #earthobservation #imaging #satelliteimaging

Mbongowo J Mbuh @[email protected] · 2026-09-07 · 17:00 UTC

At night, the Earth tells a different story. 🌃 From orbit, city lights trace where we live and build, a glowing map of human civilization and energy. Remote sensing turns those lights into data on population and growth. 🛰️

#RemoteSensing #NightLights #Geography #Satellites #EarthObservation #Cities

#remotesensing #nightlights #geography #satellites #earthobservation #cities

Barret @[email protected] · 2026-09-05 · 20:00 UTC

Satellite view of Ohio — 2026-09-04
Imagery: MODIS_Terra_CorrectedReflectance_TrueColor
https://worldview.earthdata.nasa.gov/?v=-84.82,38.4,-80.52,42.32&l=MODIS_Terra_CorrectedReflectance_TrueColor&t=2026-09-04

Imagery: NASA GIBS #satellite #NASA #EarthObservation

#satellite #nasa #earthobservation

Barret @barret · 2026-09-05 · 20:00 UTC

Satellite view of Ohio — 2026-09-04
Imagery: MODIS_Terra_CorrectedReflectance_TrueColor
https://worldview.earthdata.nasa.gov/?v=-84.82,38.4,-80.52,42.32&l=MODIS_Terra_CorrectedReflectance_TrueColor&t=2026-09-04

Imagery: NASA GIBS #satellite #NASA #EarthObservation

#satellite #nasa #earthobservation

Barret @[email protected] · 2026-09-05 · 20:00 UTC

Satellite view of Ohio — 2026-09-04
Imagery: MODIS_Terra_CorrectedReflectance_TrueColor
https://worldview.earthdata.nasa.gov/?v=-84.82,38.4,-80.52,42.32&l=MODIS_Terra_CorrectedReflectance_TrueColor&t=2026-09-04

Imagery: NASA GIBS #satellite #NASA #EarthObservation

#satellite #nasa #earthobservation

Barret @[email protected] · 2026-09-05 · 20:00 UTC

Satellite view of Ohio — 2026-09-04
Imagery: MODIS_Terra_CorrectedReflectance_TrueColor
https://worldview.earthdata.nasa.gov/?v=-84.82,38.4,-80.52,42.32&l=MODIS_Terra_CorrectedReflectance_TrueColor&t=2026-09-04

Imagery: NASA GIBS #satellite #NASA #EarthObservation

#earthobservation #nasa #satellite

Barret @[email protected] · 2026-09-05 · 20:00 UTC

Satellite view of Ohio — 2026-09-04
Imagery: MODIS_Terra_CorrectedReflectance_TrueColor
https://worldview.earthdata.nasa.gov/?v=-84.82,38.4,-80.52,42.32&l=MODIS_Terra_CorrectedReflectance_TrueColor&t=2026-09-04

Imagery: NASA GIBS #satellite #NASA #EarthObservation

#satellite #nasa #earthobservation

Bytes Europe @[email protected] · 2026-09-05 · 07:22 UTC

Setúbal, Portugal, increases its resilience to floods | EU Space Support Office https://www.byteseu.com/2338239/ #EarthObservation #Portugal

#portugal #earthobservation

OptimusPrimeBot @[email protected] · 2026-09-04 · 01:19 UTC

Nepal glacier collapse and flood (after)

#china #earthexplorer #earthfromspace #earthobservation #esa #europeanspaceagency #glaciercollapse #landsat9

▶️ 1 new picture from ESA (Flickr) https://commons.wikimedia.org/wiki/File:Nepal_glacier_collapse_and_flood_%28after%29_%2855504451912%29.jpg

#china #earthexplorer #earthfromspace #earthobservation #esa #europeanspaceagency

💧🌏 Greg Cocks @[email protected] · 2026-09-03 · 04:22 UTC

On-Demand Global Landsat Evapotranspiration Product - Development, Evaluation, And Dissemination
--
https://doi.org/10.1016/j.rse.2026.115633 <-- shared paper
--
https://espa.cr.usgs.gov <-- shared (open data) USGS EROS Science Processing Architecture (ESPA) platform
--
https://etdata.org/ <-- OpenET SSEBop platform implementation (water management)
--
https://www.usgs.gov/landsat-missions/landsat-collection-2-provisional-actual-evapotranspiration-science-product <-- shared USGS Landsat Collection 2 Provisional Actual Evapotranspiration Science Product
--
H/T @mac Friedrichs | Remote Sensing Scientist, KBR | USGS EROS
“This paper summarizes new achievements in developing and distributing the Global Landsat Level-3 Evapotranspiration (ET) product. It is freely available through the USGS EROS Science Processing Architecture (ESPA) platform (2nd link above). 🛰️ …
Since the product launch in June 2020, there have been over 1.2 million Landsat-based ET orders around the world. This indicates increasing awareness and application of the ET data to help understand and manage the relationships among food, energy, and water resources. 🌽💧 …
It features the ESPA workflow and evaluation of the upgraded SSEBop model using a variety of observational datasets and hydrologic regions, and examination against OpenET SSEBop platform implementation (3rd link above.)…”
--
“HIGHLIGHTS
• ESPA platform allows access to on-demand, global, Landsat-based, ET products.
• SSEBop model has been used to create ET data since 1982 through ESPA.
• A quick estimation of field-scale crop consumptive water use can be achieved.
• Numerous orders reflect worldwide extensive interest and utilization of the data.
• Method, workflow, and performance of the actual ET data are presented in the study..."
#EROSScienceProcessingArchitecture #climate #global #Evapotranspiration #ET #GIS #spatial #mapping #remotesensing #earthobservation #water #hydrology #opendata #Landsat #OpenET #SSEBop #WaterManagement #Agriculture #USGS #EROS #datadelivery #food #foodsecurity #energy #water #watersecurity #model #modeling #ESPA #farming #cropland #wateruse #waterresources #workflow
@USGS @EROS

#erosscienceprocessingarchitecture #climate #global #evapotranspiration #et #gis

💧🌏 Greg Cocks @[email protected] · 2026-09-03 · 04:22 UTC

On-Demand Global Landsat Evapotranspiration Product - Development, Evaluation, And Dissemination
--
https://doi.org/10.1016/j.rse.2026.115633 <-- shared paper
--
https://espa.cr.usgs.gov <-- shared (open data) USGS EROS Science Processing Architecture (ESPA) platform
--
https://etdata.org/ <-- OpenET SSEBop platform implementation (water management)
--
https://www.usgs.gov/landsat-missions/landsat-collection-2-provisional-actual-evapotranspiration-science-product <-- shared USGS Landsat Collection 2 Provisional Actual Evapotranspiration Science Product
--
H/T @mac Friedrichs | Remote Sensing Scientist, KBR | USGS EROS
“This paper summarizes new achievements in developing and distributing the Global Landsat Level-3 Evapotranspiration (ET) product. It is freely available through the USGS EROS Science Processing Architecture (ESPA) platform (2nd link above). 🛰️ …
Since the product launch in June 2020, there have been over 1.2 million Landsat-based ET orders around the world. This indicates increasing awareness and application of the ET data to help understand and manage the relationships among food, energy, and water resources. 🌽💧 …
It features the ESPA workflow and evaluation of the upgraded SSEBop model using a variety of observational datasets and hydrologic regions, and examination against OpenET SSEBop platform implementation (3rd link above.)…”
--
“HIGHLIGHTS
• ESPA platform allows access to on-demand, global, Landsat-based, ET products.
• SSEBop model has been used to create ET data since 1982 through ESPA.
• A quick estimation of field-scale crop consumptive water use can be achieved.
• Numerous orders reflect worldwide extensive interest and utilization of the data.
• Method, workflow, and performance of the actual ET data are presented in the study..."
#EROSScienceProcessingArchitecture #climate #global #Evapotranspiration #ET #GIS #spatial #mapping #remotesensing #earthobservation #water #hydrology #opendata #Landsat #OpenET #SSEBop #WaterManagement #Agriculture #USGS #EROS #datadelivery #food #foodsecurity #energy #water #watersecurity #model #modeling #ESPA #farming #cropland #wateruse #waterresources #workflow
@USGS @EROS

#erosscienceprocessingarchitecture #climate #global #evapotranspiration #et #gis

💧🌏 Greg Cocks @[email protected] · 2026-09-03 · 04:22 UTC

On-Demand Global Landsat Evapotranspiration Product - Development, Evaluation, And Dissemination
--
https://doi.org/10.1016/j.rse.2026.115633 <-- shared paper
--
https://espa.cr.usgs.gov <-- shared (open data) USGS EROS Science Processing Architecture (ESPA) platform
--
https://etdata.org/ <-- OpenET SSEBop platform implementation (water management)
--
https://www.usgs.gov/landsat-missions/landsat-collection-2-provisional-actual-evapotranspiration-science-product <-- shared USGS Landsat Collection 2 Provisional Actual Evapotranspiration Science Product
--
H/T @mac Friedrichs | Remote Sensing Scientist, KBR | USGS EROS
“This paper summarizes new achievements in developing and distributing the Global Landsat Level-3 Evapotranspiration (ET) product. It is freely available through the USGS EROS Science Processing Architecture (ESPA) platform (2nd link above). 🛰️ …
Since the product launch in June 2020, there have been over 1.2 million Landsat-based ET orders around the world. This indicates increasing awareness and application of the ET data to help understand and manage the relationships among food, energy, and water resources. 🌽💧 …
It features the ESPA workflow and evaluation of the upgraded SSEBop model using a variety of observational datasets and hydrologic regions, and examination against OpenET SSEBop platform implementation (3rd link above.)…”
--
“HIGHLIGHTS
• ESPA platform allows access to on-demand, global, Landsat-based, ET products.
• SSEBop model has been used to create ET data since 1982 through ESPA.
• A quick estimation of field-scale crop consumptive water use can be achieved.
• Numerous orders reflect worldwide extensive interest and utilization of the data.
• Method, workflow, and performance of the actual ET data are presented in the study..."
#EROSScienceProcessingArchitecture #climate #global #Evapotranspiration #ET #GIS #spatial #mapping #remotesensing #earthobservation #water #hydrology #opendata #Landsat #OpenET #SSEBop #WaterManagement #Agriculture #USGS #EROS #datadelivery #food #foodsecurity #energy #water #watersecurity #model #modeling #ESPA #farming #cropland #wateruse #waterresources #workflow
@USGS @EROS

#erosscienceprocessingarchitecture #climate #global #evapotranspiration #et #gis

💧🌏 Greg Cocks @[email protected] · 2026-09-03 · 04:22 UTC

On-Demand Global Landsat Evapotranspiration Product - Development, Evaluation, And Dissemination
--
https://doi.org/10.1016/j.rse.2026.115633 <-- shared paper
--
https://espa.cr.usgs.gov <-- shared (open data) USGS EROS Science Processing Architecture (ESPA) platform
--
https://etdata.org/ <-- OpenET SSEBop platform implementation (water management)
--
https://www.usgs.gov/landsat-missions/landsat-collection-2-provisional-actual-evapotranspiration-science-product <-- shared USGS Landsat Collection 2 Provisional Actual Evapotranspiration Science Product
--
H/T @mac Friedrichs | Remote Sensing Scientist, KBR | USGS EROS
“This paper summarizes new achievements in developing and distributing the Global Landsat Level-3 Evapotranspiration (ET) product. It is freely available through the USGS EROS Science Processing Architecture (ESPA) platform (2nd link above). 🛰️ …
Since the product launch in June 2020, there have been over 1.2 million Landsat-based ET orders around the world. This indicates increasing awareness and application of the ET data to help understand and manage the relationships among food, energy, and water resources. 🌽💧 …
It features the ESPA workflow and evaluation of the upgraded SSEBop model using a variety of observational datasets and hydrologic regions, and examination against OpenET SSEBop platform implementation (3rd link above.)…”
--
“HIGHLIGHTS
• ESPA platform allows access to on-demand, global, Landsat-based, ET products.
• SSEBop model has been used to create ET data since 1982 through ESPA.
• A quick estimation of field-scale crop consumptive water use can be achieved.
• Numerous orders reflect worldwide extensive interest and utilization of the data.
• Method, workflow, and performance of the actual ET data are presented in the study..."
#EROSScienceProcessingArchitecture #climate #global #Evapotranspiration #ET #GIS #spatial #mapping #remotesensing #earthobservation #water #hydrology #opendata #Landsat #OpenET #SSEBop #WaterManagement #Agriculture #USGS #EROS #datadelivery #food #foodsecurity #energy #water #watersecurity #model #modeling #ESPA #farming #cropland #wateruse #waterresources #workflow
@USGS @EROS

#workflow #waterresources #wateruse #cropland #farming #espa

💧🌏 Greg Cocks @GregCocks · 2026-09-03 · 04:22 UTC

On-Demand Global Landsat Evapotranspiration Product - Development, Evaluation, And Dissemination
--
https://doi.org/10.1016/j.rse.2026.115633 <-- shared paper
--
https://espa.cr.usgs.gov <-- shared (open data) USGS EROS Science Processing Architecture (ESPA) platform
--
https://etdata.org/ <-- OpenET SSEBop platform implementation (water management)
--
https://www.usgs.gov/landsat-missions/landsat-collection-2-provisional-actual-evapotranspiration-science-product <-- shared USGS Landsat Collection 2 Provisional Actual Evapotranspiration Science Product
--
H/T @mac Friedrichs | Remote Sensing Scientist, KBR | USGS EROS
“This paper summarizes new achievements in developing and distributing the Global Landsat Level-3 Evapotranspiration (ET) product. It is freely available through the USGS EROS Science Processing Architecture (ESPA) platform (2nd link above). 🛰️ …
Since the product launch in June 2020, there have been over 1.2 million Landsat-based ET orders around the world. This indicates increasing awareness and application of the ET data to help understand and manage the relationships among food, energy, and water resources. 🌽💧 …
It features the ESPA workflow and evaluation of the upgraded SSEBop model using a variety of observational datasets and hydrologic regions, and examination against OpenET SSEBop platform implementation (3rd link above.)…”
--
“HIGHLIGHTS
• ESPA platform allows access to on-demand, global, Landsat-based, ET products.
• SSEBop model has been used to create ET data since 1982 through ESPA.
• A quick estimation of field-scale crop consumptive water use can be achieved.
• Numerous orders reflect worldwide extensive interest and utilization of the data.
• Method, workflow, and performance of the actual ET data are presented in the study..."
#EROSScienceProcessingArchitecture #climate #global #Evapotranspiration #ET #GIS #spatial #mapping #remotesensing #earthobservation #water #hydrology #opendata #Landsat #OpenET #SSEBop #WaterManagement #Agriculture #USGS #EROS #datadelivery #food #foodsecurity #energy #water #watersecurity #model #modeling #ESPA #farming #cropland #wateruse #waterresources #workflow
@USGS @EROS

#erosscienceprocessingarchitecture #climate #global #evapotranspiration #et #gis

💧🌏 Greg Cocks @[email protected] · 2026-08-21 · 04:02 UTC

Comparing DESIS Hyperspectral and Landsat 10 Simulated Superspectral Data for Crop Type Classification in California’s Central Valley
--
https://doi.org/10.3390/rs18142282 <-- shared paper
--
https://www.usgs.gov/publications/comparing-desis-hyperspectral-and-landsat-10-simulated-superspectral-data-crop-type <-- 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

EOMasters @[email protected] · 2026-08-19 · 11:51 UTC

🚀 Thinking about building Landsat‑10 in your garage?
Better hurry — NASA’s RFP is out and the clock’s ticking. Early delivery even gets you a bonus.
Details: https://www.usgs.gov/landsat-missions/news/nasa-releases-landsat-10-spacecraft-request-proposal
#EarthObservation #Landsat

#earthobservation #landsat

Eugene @[email protected] · 2026-08-18 · 16:46 UTC

🔥 Mapping Calgary's Fuel Continuity: Where Can Wildfire Actually Spread?

In a baseline, unsuppressed fire scenario ("apocalyptic scenario"), surface fires can only sustain a continuous front where vegetation forms an unbroken canopy or grassland corridor.

Using my 2025 Calgary Land Cover Model (v6.0), I isolated all vegetated pixels and calculated the spatial continuity and total area of every single contiguous fuel patch across the city:
🌾 The Nose Hill Island (~1,100 ha): A massive grassland fuel bed right in the city's heart.
🌲 River Corridors (Fish Creek Provincial Park & Bow Valley, 500–1,500 ha): Linear fuel superclusters acting as natural conduits.
🏙️ Urban Built-up Fragmentation: Inside established communities, the continuous network of asphalt, concrete, and roofing fractures vegetation into micro-patches (< 1 ha).

#GIS #RemoteSensing #EarthObservation #Calgary #SpatialDataScience #LandCover #MachineLearning #GreennessOfCalgary #Rstats #UrbanTrees #TreeCanopy #UrbanHealth #Wildfire

#rstats #calgary #machinelearning #gis #earthobservation #wildfire

Eugene @[email protected] · 2026-08-17 · 20:52 UTC

🔥 Calgary Urban Heat: How the Solid-to-Tree Ratio drives an 8°C gap

My Summer 2025 ML satellite analysis reveals a direct relationship between a community's built-to-canopy footprint and surface temperature (LST):

🌳 Cooling Refuges (~29.5–31°C): Roxboro, Rideau Park, Discovery Ridge, Eau Claire (mature canopies + river valleys).
🔥 Northeast Heat Dome (~37–38°C): Marlborough, Rundle, Temple (dense low-rise footprint, minimal mature canopy).
🏗️ New Suburbs: Seton, Redstone, Rangeview (canopy lag: fully built out, but young saplings need years to mature).

🌲 Urban trees are not decorative landscaping — they are critical municipal climate infrastructure.

#GIS #RemoteSensing #YYC #EarthObservation #Calgary #SpatialDataScience #LandCover #MachineLearning #Geoscience #GreennessOfCalgary #Rstats #UrbanTrees #TreeCanopy #UrbanHealth

#rstats #yyc #calgary #machinelearning #gis #earthobservation

💧🌏 Greg Cocks @[email protected] · 2026-08-14 · 03:26 UTC

Impact Of Urbanization Driven Land Use And Land Cover Change On Ecological Environmental Quality In Rupandehi Nepal Assessed Using The Remote Sensing Ecological Index
--
https://doi.org/10.1007/s44288-026-00650-y <-- shared paper
--
https://kathmandupost.com/money/2026/02/18/rupandehi-s-continued-urban-sprawl-comes-at-a-cost-for-agriculture-in-the-periphery <-- 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

💧🌏 Greg Cocks @[email protected] · 2026-08-05 · 04:59 UTC

Enhancements To The USGS Landsat Level 2 Surface Temperature And Emissivity Product For Collection3 Reprocessing
--
https://doi.org/10.1016/j.rse.2026.115563 <-- 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

Datacom Industry Association @[email protected] · 2026-07-27 · 12:42 UTC

Satellites, HAPS, and aircraft are quietly becoming something more than relays. They're turning into compute nodes.

The Datacom Industry Association Aerospace #WorkingGroup just released a whitepaper on this shift: "Aerospace-enabled Services — The Edge-Cloud Continuum Beyond the Atmosphere."

📄 Read the whitepaper now: https://datacom-ia.eu/2026/07/24/aerospace-wg-releases-whitepaper-on-edge-cloud-continuum-beyond-the-atmosphere/

#Aerospace #EdgeComputing #NTN #EarthObservation #HAPS #Satellite #DigitalInfrastructure #DIA

#workinggroup #aerospace #edgecomputing #ntn #earthobservation #haps

SpaceNews: The space industry's source [Unofficial] @[email protected] · 2026-07-24 · 10:00 UTC

EU delays release of Copernicus imagery over Gulf of Oman

https://fed.brid.gy/r/https://spacenews.com/eu-delays-release-of-copernicus-imagery-over-gulf-of-oman/

#news #policypolitics #copernicus #earthobservation #europe #iran

💧🌏 Greg Cocks @[email protected] · 2026-07-10 · 04:56 UTC

A Scale-Invariance-Based Algorithm Application For Land Surface Temperature Downscaling In Denmark
--
https://doi.org/10.3390/rs18132263 <-- shared paper
--
https://zenodo.org/records/20863040 <-- shared open data for downscaled LST dataset for Copenhagen
--
H/T @CLIM4cities
#urbanclimate #downscaling #landsurfacetemperature #LST #AI #machinelearning #scaleinvariance #residualcorrection #Sentinel #Landsat #satellite #remotesensing #earthobservation #CLIM4cities #UrbanClimate #ClimateServices #MachineLearning #ClimateAdaptation #heatwave #temperature #ontheground #Copenhagen #Denmark #impervioussurface #asphalt #roof #concrete #albedo #heatabsorption #mitigation #urban #urbancentre #treecover #vegetation #urbanheatisland #planning #design #hotspots #monitoring #spatialanalysis #spatiotemporal #model #modeling #usecase #operational #climatechange #extremeweather #evidencebased #adapation #sustainability #urbanplanning #climateresilience #EssentialClimateVariable #ECV
@+ATLANTIC | @Danish Meteorological Institute | @ESA Φ-lab Collaborative Innovation Network | @CLIM4cities

#urbanclimate #downscaling #landsurfacetemperature #lst #ai #machinelearning

geo-spatial.org @[email protected] · 2026-07-01 · 07:22 UTC

☀️ Good morning from #FOSS4GE2026 !

A new day has started in Timișoara, with sessions on ☁️ Cloud GIS , #QGIS 🧭, #MapLibre 🗺️, #GeoServer 🛠️, 🛰️ Earth Observation, 🤖 AI, 🌆Digital Twins, and much more.

We look forward to inspiring discussions, live demonstrations, and interesting conversations with the open geospatial community. See you around! 🌍

#OpenSource #Geospatial #GIS #EarthObservation #digitaltwins

#foss4ge2026 #qgis #maplibre #geoserver #opensource #geospatial

💧🌏 Greg Cocks @[email protected] · 2026-06-11 · 05:05 UTC

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)
--
https://www.ecoticias.com/en/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/33120/ <-- shared technical article
--
https://news.exeter.ac.uk/faculty-of-environment-science-and-economy/earth-and-environmental-science/plants-growing-higher-across-himalaya-as-climate-warms/ <-- shared technical newsitem
--
https://doi.org/10.1002/ecog.08259 <-- shared (2026) paper
--
https://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

💧🌏 Greg Cocks @[email protected] · 2026-06-10 · 03:45 UTC

[G]lobal Decline In Endorheic Basin Water Storages
--
https://doi.org/10.1038/s41561-018-0265-7 <-- shared paper
--
https://en.wikipedia.org/wiki/Endorheic_basin <-- shared Wikipedia page
--
“Endorheic (hydrologically landlocked) basins spatially concur with arid/semi-arid climates. Given limited precipitation but high potential evaporation, their water storage is vulnerable to subtle flux perturbations, which are exacerbated by global warming and human activities. Increasing regional evidence suggests a probably recent net decline in endorheic water storage, but this remains unquantified at a global scale. By integrating satellite observations and hydrological modelling, [they] reveal[ed] that during 2002–2016 the global endorheic system experienced a widespread water loss of about 106.3 Gt/yr, attributed to comparable losses in surface water, soil moisture and groundwater. This decadal decline, disparate from water storage fluctuations in exorheic basins, appears less sensitive to El Niño–Southern Oscillation-driven climate variability, which implies a possible response to longer-term climate conditions and human water management. In the mass-conserved hydrosphere, such an endorheic water loss not only exacerbates local water stress, but also imposes excess water on exorheic basins, leading to a potential sea level rise that matches the contribution of nearly half of the land glacier retreat (excluding Greenland and Antarctica). Given these dual ramifications, [they] suggest the necessity for long-term monitoring of water storage variation in the global endorheic system and the inclusion of its net contribution to future sea level budgeting…”
#water #hydrology #hydrography #global #waterresources #waterstorage #Endorheic #Basin #watersecurity #arid #semiarid #rainfall #precipitation #spatialanalysis #spatiotemporal #globalwarming #climatechange #humanimpacts #anthropogenic #regional #remotesensing #GIS #spatial #mapping #earthobservation #surfacewater #groundwater #soilmoisture #exorheic #watermanagement #hydrosphere #waterstress #SLR #sealevelrise #monitoring #waterbudgets

#water #hydrology #hydrography #global #waterresources #waterstorage

SpaceNews: The space industry's source [Unofficial] @[email protected] · 2026-05-29 · 12:00 UTC

Spatial data has become a weapon of war in the US-Iran war

https://fed.brid.gy/r/https://spacenews.com/spatial-data-has-become-a-weapon-of-war-in-the-us-iran-war/

#military #opinion #dualusetechnology #earthobservation #iran #sn

Fiona Gregory @[email protected] · 2026-05-27 · 20:18 UTC

#Mexico City is sinking #earthobservation #subsidence #radar #SAR #NISAR https://www.nasa.gov/missions/nisar/us-indian-space-mission-maps-extreme-subsidence-in-mexico-city/

#mexico #earthobservation #subsidence #radar #sar #nisar

earthling @[email protected] · 2026-05-25 · 14:25 UTC

@coreyspowell
10/
In short: It’s not an apocalypse; it’s a data corrective. It proves that the engine room of our planet is a highly active, rapidly changing environment, and it took a constellation of advanced satellites sixteen years of data-crunching to finally reveal what happened right under our feet.

#Geophysics
#Geomagnetism
#EarthsCore
#Geodynamics
#OuterCore
#Geodynamo
#ESASwarm
#CryoSat
#SatelliteData
#EarthObservation
#GeomagneticField
#WorldMagneticModel
#WMM