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#landsat — Public Fediverse posts

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

  1. On-Demand Global Landsat Evapotranspiration Product - Development, Evaluation, And Dissemination
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    doi.org/10.1016/j.rse.2026.115 <-- shared paper
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    espa.cr.usgs.gov <-- shared (open data) USGS EROS Science Processing Architecture (ESPA) platform
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    etdata.org/ <-- OpenET SSEBop platform implementation (water management)
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    usgs.gov/landsat-missions/land <-- shared USGS Landsat Collection 2 Provisional Actual Evapotranspiration Science Product
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    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.)…”
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    “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

  2. Comparing DESIS Hyperspectral and Landsat 10 Simulated Superspectral Data for Crop Type Classification in California’s Central Valley
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    doi.org/10.3390/rs18142282 <-- shared paper
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    usgs.gov/publications/comparin <-- shared USGs publication page
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    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

  3. 🚀 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: usgs.gov/landsat-missions/news
    #EarthObservation #Landsat

  4. Enhancements To The USGS Landsat Level 2 Surface Temperature And Emissivity Product For Collection3 Reprocessing
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    doi.org/10.1016/j.rse.2026.115 <-- shared paper
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    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

  5. 🏙️ The Hellish Trade Zones
    (Ukrainian: “Торговельні пекельні зони”)

    An older piece from 2017 — but still relevant today.
    Using Landsat-8 thermal imagery, I explored how urban heat islands form in large commercial and industrial areas completely devoid of vegetation.

    These “hellish trade zones” show surface temperatures exceeding 45–50 °C, while nearby shelterbelts and green spaces remain much cooler.
    The visual storytelling approach — combining satellite data, maps, and simple explanations — helped raise public awareness about urban greening and environmental health in my city.

    📍 Location: Kryvyi Rih, Ukraine
    🛰️ Data: Landsat-8 (July 15, 2016), thermal band 10 + NDVI
    🔗 More: datastory.org.ua/%d1%82%d0%be%

    #UrbanHeatIsland #RemoteSensing #Landsat #UrbanEcology #ClimateChange #EnvironmentalData #UrbanGreening #Geospatial #GIScience #OpenScience #DataVisualization #Ukraine #Sustainability #KryvyiRih #UrbanHealth

  6. The Disappearance of Lac [Lake] Rouge [remote sensing]
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    earthobservatory.nasa.gov/imag <-- Shared NASA Earth Observatory Images Of The Day
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    cbc.ca/news/canada/north/lake- <-- shared media article
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    “A landscape in central Quebec transformed suddenly in spring 2025 when a lake burst its banks and drained. Members of the nearby community of Waswanipi who use the area for hunting, fishing, and trapping learned of the curious incident in early May, after reports of a washed-out road. Further air- and ground-based investigations revealed that land around the lake had collapsed and that Lac Rouge had emptied..."
    #GIS #spatial #mapping #spatiotemporal #water #hydrology #lake #LacRouge #Quebec #Canada #Waswanipi #Cree #FirstNation #wildfire #geomorphometry #outflow #OLI2 #Landsat #Landsat9 #earthobservation #remotesensing #wildlife #habitat #change #ecology #sediment # #snowmelt #rainfall

  7. Earth's Transformation In Satellite Images [video, Landsat, BBC]
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    bbc.com/reel/video/p0hrgnvl/ea <-- shared media article
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    “For over half-a-century, the Nasa and US Geological Survey's Landsat program has documented changes to the Earth's surface, making it the longest continuous space-based record of our planet's land ever.
    What has the program taught us about the Earth's transformation? And what's next for Landsat?...”
    #GIS #landsatnext #spatial #mapping #EROS #landsat #landsat9 #education #remotesensing #earthobservation #earth #monitoring #measuring #satellite #planet #history #future #plans
    @USGS @nasa @NASAEarthObservatory @EROS @Landsat

  8. Landsat Next – Satellites Offers Improved Data To Earth
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    doi.org/10.3133/fs20243005 <-- link to USGS fact sheet 2024-3005
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    landsat.gsfc.nasa.gov/satellit <-- NASA page
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    usgs.gov/landsat-missions/land <-- USGS page
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    youtu.be/339KeL29tig?si=kr9asL <-- NASA Goddard overview video
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    “With a trio of smaller satellites that can each detect 26 wavelengths of light, the Landsat Next mission is expected to look very different from its predecessors that have been observing Earth for 50 years. This new plan for Landsat Next, a joint mission of NASA and the U.S. Geological Survey, is designed to provide more frequent, and finer resolution, data of the changing surface of Earth…”
    #GIS #spatial #mapping #remotesensing #earthobservation #monitoring #satellite #Landsat #LandsatNext #planning #global #imagery #visualisation #spectral #usecase #appliedscience #economicimpact #economicvalue #value #costbenefit #multispectral #synoptic #natural #humanimpact
    @USGS @nasa @NASAGoddard @USGSEROS

  9. Outstanding radar image of the #Shiveluch #volcano.
    #Radar data is not affected by cloud cover or rain. It can be acquired day or night, and often penetrates snow down to bedrock, unlike optical data (e.g. #Sentinel2, #landsat ).
    Acquired on April 17, it shows the immense collapse of the crater, and potentially a growing lava lobe.
    Kudos to @RaphaelGrandin and Alina Shevchenko for their work in the area and Capella Space for providing the image.
    #geology #remotesensing #geophycis #geohazards