#google-earth-engine — Public Fediverse posts

Hello Mastodon, an #introduction.
I'm a geospatial scientist with a PhD in Earth System and Geoinformation Science. I work in remote sensing and #GeoAI, mostly on drought, vegetation, and land — in Africa and the US Great Plains.
I'll mostly post maps, model results, and #GoogleEarthEngine and Python tutorials (#geopandas, #rasterio). I'm also building a national GIS data portal for #Cameroon.
#RemoteSensing #GIS #EarthObservation #Python

Hello Mastodon, an #introduction.
I'm a geospatial scientist with a PhD in Earth System and Geoinformation Science. I work in remote sensing and #GeoAI, mostly on drought, vegetation, and land — in Africa and the US Great Plains.
I'll mostly post maps, model results, and #GoogleEarthEngine and Python tutorials (#geopandas, #rasterio). I'm also building a national GIS data portal for #Cameroon.
#RemoteSensing #GIS #EarthObservation #Python

Ahora que están subiendo los precios de tokens en las IAgs (que tampoco se muy bien ni que IAgs, ni que tokAns xD), ha pasado algo por lo bajini pero que ha sido un golpe directo a las gónadas de la comunidad teledetectora (en la que me incluyo). Es decir, aquella que se dedica al estudio de la superficie del sistema tierra y su atmósfera mediante imágenes satelitales (principalmente).

Por ejemplo, no se si os suenan las misiones Landsat (EEUU) y Copérnicus (UE). En pocas palabras se dedican a lanzar satélites que echan fotos a la Tierra para que los usuarios nos las descarguemos. Y en este proceso de descarga aparece el todopoderoso Google. Yep.

Hasta la aparición de la plataforma Google Earth Engine, las imágenes tenías que descargarlas de una en una en cuadros que podían pesar, cada uno, unos 7GB. (Bueno no es tan así, se podía algoritmizar, pero la idea es que tardabas mucho). Con la aparición de Google, podías, no solo descargar la pequeña parte de la imagen que te interesaba, sino procesarla en sus servidores y, además, gratis. Como es lógico los teledetectores (y también otros), se mudaron a dicha plataforma donde realizaron todos sus análisis y solo descargaban el resultado final. Pero ha llegado la jugada maestra, como buen camello que ofrece la primera dosis gratis, Google ha decidido limitar lo que antes era gratis muchísimo, y una especie de tokens (EECU) han aparecido (quizás estaban pero no me había fijado, porque no los necesitaba).

Y, básicamente, ahora estamos todos rezando para que nuestra dosis de procesamiento no se acabe antes de tiempo. Y creando nuestras propias bases de datos por supuesto. Aunque, quizás, alguien (Europa guiño, guiño) debería ponerse las pilas y habilitar la descarga de solo la parte que nos interesa. Que por otra parte, como esto lo veía venir (al final es Google), solo la usaba para eso.

#Google #GoogleEarthEngine #Ciencia #Teledetección #Ecología #SistemaTierra #Europa #AnálisisDeDatos

Ahora que están subiendo los precios de tokens en las IAgs (que tampoco se muy bien ni que IAgs, ni que tokAns xD), ha pasado algo por lo bajini pero que ha sido un golpe directo a las gónadas de la comunidad teledetectora (en la que me incluyo). Es decir, aquella que se dedica al estudio de la superficie del sistema tierra y su atmósfera mediante imágenes satelitales (principalmente).

Por ejemplo, no se si os suenan las misiones Landsat (EEUU) y Copérnicus (UE). En pocas palabras se dedican a lanzar satélites que echan fotos a la Tierra para que los usuarios nos las descarguemos. Y en este proceso de descarga aparece el todopoderoso Google. Yep.

Hasta la aparición de la plataforma Google Earth Engine, las imágenes tenías que descargarlas de una en una en cuadros que podían pesar, cada uno, unos 7GB. (Bueno no es tan así, se podía algoritmizar, pero la idea es que tardabas mucho). Con la aparición de Google, podías, no solo descargar la pequeña parte de la imagen que te interesaba, sino procesarla en sus servidores y, además, gratis. Como es lógico los teledetectores (y también otros), se mudaron a dicha plataforma donde realizaron todos sus análisis y solo descargaban el resultado final. Pero ha llegado la jugada maestra, como buen camello que ofrece la primera dosis gratis, Google ha decidido limitar lo que antes era gratis muchísimo, y una especie de tokens (EECU) han aparecido (quizás estaban pero no me había fijado, porque no los necesitaba).

Y, básicamente, ahora estamos todos rezando para que nuestra dosis de procesamiento no se acabe antes de tiempo. Y creando nuestras propias bases de datos por supuesto. Aunque, quizás, alguien (Europa guiño, guiño) debería ponerse las pilas y habilitar la descarga de solo la parte que nos interesa. Que por otra parte, como esto lo veía venir (al final es Google), solo la usaba para eso.

#Google #GoogleEarthEngine #Ciencia #Teledetección #Ecología #SistemaTierra #Europa #AnálisisDeDatos

Integrated Data-Driven Multi-Criteria Analysis and Machine Learning Approaches for Assessment of Flood Susceptibility Mapping
--
https://doi.org/10.3390/w18070844 <-- shared paper
--
https://youtu.be/N7nyU1cMg5k?si=8WuXIaz4-JKPdCE0 <-- shared video, Mohmand Dam flooding
---
#FloodSusceptibility #FloodMapping #MachineLearning #GIS #RemoteSensing #Hydrology #Water #EnvironmentalResearch #AHP #FAHP #climatechange #extremeweather #GoogleEarthEngine #GIS #spatial #mapping #AI #model #modeling #MohmandDam #SwatRiver #Pakistan #machinelearning #AI #criteria #parameters #indices #rainfall #precipitation #LULC #soiltexture #planning #policy #water #hydrology #hydrography #riskmanagement #risk #hazard #flood #flooding #mitigation #watershed #watermanagement #resilence

Integrated Data-Driven Multi-Criteria Analysis and Machine Learning Approaches for Assessment of Flood Susceptibility Mapping
--
https://doi.org/10.3390/w18070844 <-- shared paper
--
https://youtu.be/N7nyU1cMg5k?si=8WuXIaz4-JKPdCE0 <-- shared video, Mohmand Dam flooding
---
#FloodSusceptibility #FloodMapping #MachineLearning #GIS #RemoteSensing #Hydrology #Water #EnvironmentalResearch #AHP #FAHP #climatechange #extremeweather #GoogleEarthEngine #GIS #spatial #mapping #AI #model #modeling #MohmandDam #SwatRiver #Pakistan #machinelearning #AI #criteria #parameters #indices #rainfall #precipitation #LULC #soiltexture #planning #policy #water #hydrology #hydrography #riskmanagement #risk #hazard #flood #flooding #mitigation #watershed #watermanagement #resilence

S2Coast-2023 - The First Global 10-Meter Resolution #Coastline Dataset Derived From Enhanced #Sentinel2 Composite #Imagery Using #GoogleEarthEngine
--
https://doi.org/10.1016/j.rse.2025.115186 <-- shared paper
--
https://zenodo.org/records/17092775 <-- shared data
--
“HIGHLIGHTS:
• Developed a GEE-based global coastline detection framework (S2Coast).
• HWLSentinel-2 serves as a unified and stable indicator for global coastline detection.
• The S2Coast-2023 coastline dataset is generated from annual Sentinel-2 imagery.
• Pixel-level accuracy compared with VHR-based OpenStreetMap coastlines..."
#GIS #spatial #mapping #RemoteSensing #CoastalResearch #ClimateChange #EarthObservation #Globalcoastlinemapping #Senitinel #googleearthengine #GEE #Compositing #coast #globe #global #model #modeling #detection #marine #terrestrial #ecosystems #knowledgebased #framework #spatialanalysis #spatiotemporal #QAQC

S2Coast-2023 - The First Global 10-Meter Resolution #Coastline Dataset Derived From Enhanced #Sentinel2 Composite #Imagery Using #GoogleEarthEngine
--
https://doi.org/10.1016/j.rse.2025.115186 <-- shared paper
--
https://zenodo.org/records/17092775 <-- shared data
--
“HIGHLIGHTS:
• Developed a GEE-based global coastline detection framework (S2Coast).
• HWLSentinel-2 serves as a unified and stable indicator for global coastline detection.
• The S2Coast-2023 coastline dataset is generated from annual Sentinel-2 imagery.
• Pixel-level accuracy compared with VHR-based OpenStreetMap coastlines..."
#GIS #spatial #mapping #RemoteSensing #CoastalResearch #ClimateChange #EarthObservation #Globalcoastlinemapping #Senitinel #googleearthengine #GEE #Compositing #coast #globe #global #model #modeling #detection #marine #terrestrial #ecosystems #knowledgebased #framework #spatialanalysis #spatiotemporal #QAQC

Google rolls out WeatherNext 2 for sharper forecasts

https://web.brid.gy/r/https://nerds.xyz/2025/11/google-weathernext-2-ai-model/

„Wirtualny satelita” od Google. AlphaEarth Foundations widzi więcej i dokładniej niż kiedykolwiek

Google DeepMind oraz Google Earth Engine zaprezentowały AlphaEarth Foundations – nowy, fundamentalny model sztucznej inteligencji, który ma zrewolucjonizować sposób, w jaki monitorujemy i analizujemy zmiany na powierzchni Ziemi.

Narzędzie działa jak „wirtualny satelita”, łącząc dane z wielu źródeł, aby stworzyć spójny i niezwykle szczegółowy obraz naszej planety.

Nowy model AI rozwiązuje dwa kluczowe problemy w obserwacji Ziemi: przeciążenie danymi oraz niespójność informacji pochodzących z różnych satelitów. AlphaEarth Foundations integruje petabajty danych – od optycznych zdjęć satelitarnych, przez radar, po symulacje klimatyczne – w jedną, zunifikowaną cyfrową reprezentację. Analizuje całą powierzchnię lądową i wody przybrzeżne Ziemi z precyzją do kwadratów o boku 10 metrów.

Kluczową innowacją jest tworzenie bardzo kompaktowych podsumowań danych, które wymagają 16 razy mniej miejsca na dysku niż w przypadku innych testowanych systemów AI. Jak podaje Google, w testach porównawczych model AlphaEarth Foundations był stale najdokładniejszy, osiągając średnio o 24% niższy wskaźnik błędu niż inne testowane modele.

Our new AI model AlphaEarth Foundations is mapping the planet in astonishing detail. 🌏🔍

Scientists will now be able to track the impact of deforestation, monitoring crop health, and more – significantly faster, thanks to our new datasets. 🧵 pic.twitter.com/rbojUifykg

— Google DeepMind (@GoogleDeepMind) July 30, 2025

Dane dostępne dla wszystkich

Aby przyspieszyć badania i umożliwić nowe zastosowania, Google udostępnia roczne zbiory danych wygenerowane przez model w ramach publicznego zestawu „Satellite Embedding dataset” w Google Earth Engine. Dzięki temu naukowcy, rządy i organizacje pozarządowe mogą prowadzić zaawansowane analizy, często przy użyciu zaledwie kilku linijek kodu.

Z danych korzysta już ponad 50 organizacji na całym świecie, w tym Organizacja Narodów Zjednoczonych do spraw Wyżywienia i Rolnictwa (FAO), Group on Earth Observations (GEO) oraz czołowe uniwersytety, jak Stanford czy Oregon State University.

„Zestaw danych Satellite Embedding rewolucjonizuje naszą pracę, pomagając krajom w mapowaniu niezbadanych dotąd ekosystemów – jest to kluczowe dla ustalenia priorytetów w działaniach na rzecz ochrony przyrody” – mówi Nick Murray, dyrektor Global Ecology Lab na James Cook University i lider projektu Global Ecosystems Atlas.

Innym przykładem jest organizacja MapBiomas, która wykorzystuje dane AlphaEarth do mapowania brazylijskich ekosystemów i analizowania zmian w rolnictwie. „Ten zestaw danych może odmienić sposób, w jaki pracuje nasz zespół – mamy teraz nowe możliwości tworzenia map, które są dokładniejsze, precyzyjniejsze i szybsze w produkcji” – powiedział Tasso Azevedo, założyciel MapBiomas. Google opublikowało również wideo (załączone powyżej z postu na X), na którym można zobaczyć, jak model radzi sobie z „widzeniem” przez chmury w Ekwadorze czy mapowaniem złożonej powierzchni Antarktydy.

#AI #AlphaEarthFoundations #Google #GoogleDeepMind #GoogleEarthEngine #MapBiomas #mapowanie #news #obserwacjaZiemi #sztucznaInteligencja #zmianyKlimatu

High Spatial-Resolution Satellite Mapping Of Suspended Particulate Matter In Global Coastal Waters Using Particle Composition-Adaptive Algorithms
--
https://doi.org/10.1016/j.rse.2025.114745 <-- shared paper
--
https://tssmapping.projects.earthengine.app/view/sscmap <-- shared SedXplorer: Global Coastal Suspended Sediment Explorer (web mapping tool)
--
#GIS #spatial #mapping #remotesensing #coastal #coast #sediment #dynamics #suspendedparticulatematter #particlecomposition #watertype #classification #Landsat #GoogleEarth #GoogleEarthEngine #GEE #opendata #spatialanalysis #spatiotemporal #sedimentology #SPM #earthobservation #model #modeling #marine #estaurine #water #hydrology #geomorphology #global #river #erosion #waterquality #turbidity

High Spatial-Resolution Satellite Mapping Of Suspended Particulate Matter In Global Coastal Waters Using Particle Composition-Adaptive Algorithms
--
https://doi.org/10.1016/j.rse.2025.114745 <-- shared paper
--
https://tssmapping.projects.earthengine.app/view/sscmap <-- shared SedXplorer: Global Coastal Suspended Sediment Explorer (web mapping tool)
--
#GIS #spatial #mapping #remotesensing #coastal #coast #sediment #dynamics #suspendedparticulatematter #particlecomposition #watertype #classification #Landsat #GoogleEarth #GoogleEarthEngine #GEE #opendata #spatialanalysis #spatiotemporal #sedimentology #SPM #earthobservation #model #modeling #marine #estaurine #water #hydrology #geomorphology #global #river #erosion #waterquality #turbidity

So it seems from the lack of responses to my previous post https://fediscience.org/@jgomezdans/114427792187001051 that no one is using the #Copernicus #DataSpace via #STAC. I guess most academic #geo peeps use #GoogleEarthEngine or just download the data files directly? Is STAC only really used by commercial #satellite "bros"?

So it seems from the lack of responses to my previous post https://fediscience.org/@jgomezdans/114427792187001051 that no one is using the #Copernicus #DataSpace via #STAC. I guess most academic #geo peeps use #GoogleEarthEngine or just download the data files directly? Is STAC only really used by commercial #satellite "bros"?

Striking Satellite Images Reveal Antarctica Is 10 Times Greener Than 35 Years Ago
--
https://www.sciencealert.com/striking-satellite-images-reveal-antarctica-is-10-times-greener-than-35-years-ago <-- shared technical article
--
https://doi.org/10.1038/s41561-024-01564-5 <-- shared paper
--
#GIS #spatial #mapping #remotesensing #landsat #change #Antarctic #AntarcticPeninsula #spatialanalysis #spatiotemporal #climatechange #greening #vegetation #change #warming #satellite #browning #cryosphere #anthropogenic #warming #moss #terrestrial #ecosystems #GoogleEarthEngine #NDVI #TCG #icefree #model #modeling

Striking Satellite Images Reveal Antarctica Is 10 Times Greener Than 35 Years Ago
--
https://www.sciencealert.com/striking-satellite-images-reveal-antarctica-is-10-times-greener-than-35-years-ago <-- shared technical article
--
https://doi.org/10.1038/s41561-024-01564-5 <-- shared paper
--
#GIS #spatial #mapping #remotesensing #landsat #change #Antarctic #AntarcticPeninsula #spatialanalysis #spatiotemporal #climatechange #greening #vegetation #change #warming #satellite #browning #cryosphere #anthropogenic #warming #moss #terrestrial #ecosystems #GoogleEarthEngine #NDVI #TCG #icefree #model #modeling

New [2018] 30 Metre Resolution Global Shoreline Vector And Associated Global Islands Database For The Development Of Standardized Ecological Coastal Units
--
https://doi.org/10.1080/1755876X.2018.1529714 <-- shared 2018 paper
--
#GIS #spatial #mapping #coast #coastline #global #shoreline #landsat #remotesensing #spatialanalysis #extraction #AI #machinelearning #GSV #GSHSS #ecology #terrestrial #marine #ECU #waters #GEO #GoogleEarthEngine #MBON #BluePlanet #water #hydrography #hydrospatial #GroupOnEarthObservations
@GroupOnEarthObservations #islands @GEOSEC2025

New [2018] 30 Metre Resolution Global Shoreline Vector And Associated Global Islands Database For The Development Of Standardized Ecological Coastal Units
--
https://doi.org/10.1080/1755876X.2018.1529714 <-- shared 2018 paper
--
#GIS #spatial #mapping #coast #coastline #global #shoreline #landsat #remotesensing #spatialanalysis #extraction #AI #machinelearning #GSV #GSHSS #ecology #terrestrial #marine #ECU #waters #GEO #GoogleEarthEngine #MBON #BluePlanet #water #hydrography #hydrospatial #GroupOnEarthObservations
@GroupOnEarthObservations #islands @GEOSEC2025

Cropland Abandonment Between 1986 And 2018 Across The United States - Spatiotemporal Patterns And Current Land Uses
--
https://doi.org/10.1088/1748-9326/ad2d12 <-- shared paper
--
https://www.agdaily.com/crops/study-30-million-acres-cropland-abandoned-since-1980s <-- shared media article
--
#GIS #spatial #mapping #spatiotemporal #USA #spatialanalysis #crops #cropland #abandoned #remotesensing #landsat #imagery #CONUS #AI #USDA #OgallalaAquifer #GoogleEarthEngine #CNN #machinelearning #irrigation #ConservationReserveProgram #landuse #landcover #planning #management #economics

Cropland Abandonment Between 1986 And 2018 Across The United States - Spatiotemporal Patterns And Current Land Uses
--
https://doi.org/10.1088/1748-9326/ad2d12 <-- shared paper
--
https://www.agdaily.com/crops/study-30-million-acres-cropland-abandoned-since-1980s <-- shared media article
--
#GIS #spatial #mapping #spatiotemporal #USA #spatialanalysis #crops #cropland #abandoned #remotesensing #landsat #imagery #CONUS #AI #USDA #OgallalaAquifer #GoogleEarthEngine #CNN #machinelearning #irrigation #ConservationReserveProgram #landuse #landcover #planning #management #economics

#30DayMapChallenge Day 23: Memory
This map by Noel Gorelick, co-founder of #GoogleEarthEngine & newest Kontur team member, combines Hansen Global Tree Cover/Loss dataset & 80+ workshop locations (from memory) that helped Earth Engine "map" its impact 🌲🌍.
#30DayMapChallenge2024

This has been a long time coming, and not the end of it either. The slow squeeze of Google Earth Engine has started.

First came the commercial offerings, now they are pushing people by default to Google Cloud (i.e. have your credit card on the ready).

For those on the free tier, you will see less capacity (stronger quota). And, you will be squeezed, again and again. The market uptake is high enough, so the free ride is over.

#GoogleEarthEngine #GEE #Google #enshitification

This has been a long time coming, and not the end of it either. The slow squeeze of Google Earth Engine has started.

First came the commercial offerings, now they are pushing people by default to Google Cloud (i.e. have your credit card on the ready).

For those on the free tier, you will see less capacity (stronger quota). And, you will be squeezed, again and again. The market uptake is high enough, so the free ride is over.

#GoogleEarthEngine #GEE #Google #enshitification

This composite is created by my #GoogleEarthEngine app, which provides a very simple interface for creating Sentinel-1-based multitemporal composites. The open-access app can be used by anyone interested in exploring this technique's capabilities.

Find the app here 👉 https://niklasjordan.users.earthengine.app/view/multitempviewer

[🧵 3/3]

@sonaguliyeva et al. (2023) applied #machinelearning algorithms in mapping #croptypes using high resolution #Azersky imagery & demonstrated the value of #opensource platforms like #GoogleEarthEngine in the #classification of crops #LoLManuscriptMonday https://bit.ly/Guliyeva_2023

Shout out to Sona's co-authors & affiliated organizations #Azercosmos #NationalAviationAcademy #Azerbaijan #EOChat #GISChat

@sonaguliyeva et al. (2023) applied #machinelearning algorithms in mapping #croptypes using high resolution #Azersky imagery & demonstrated the value of #opensource platforms like #GoogleEarthEngine in the #classification of crops #LoLManuscriptMonday https://bit.ly/Guliyeva_2023

Shout out to Sona's co-authors & affiliated organizations #Azercosmos #NationalAviationAcademy #Azerbaijan #EOChat #GISChat

Area Estimation of Mango and Coconut Crops using Machine Learning in Hesaraghatta Hobli of Bengaluru Urban District, Karnataka [India]
--
https://doi.org/10.58825/jog.2023.17.1.75 <-- shared paper
--
#GIS #spatial #mapping #spatialanalysis #Mango #Coconut #Areaestimation #Machinelearning #ConvolutionalNeuralNetwork #CNN #RandomForest #RF #agricultural #agriculture #farming #estimates #Karnataka #India #acreage #production #horticulture #commodities #export #remotesensing #satellite #GoogleEarthEngine #GEE #Copernicus #Sentinel2 #algorithms #learning #google #ml

Area Estimation of Mango and Coconut Crops using Machine Learning in Hesaraghatta Hobli of Bengaluru Urban District, Karnataka [India]
--
https://doi.org/10.58825/jog.2023.17.1.75 <-- shared paper
--
#GIS #spatial #mapping #spatialanalysis #Mango #Coconut #Areaestimation #Machinelearning #ConvolutionalNeuralNetwork #CNN #RandomForest #RF #agricultural #agriculture #farming #estimates #Karnataka #India #acreage #production #horticulture #commodities #export #remotesensing #satellite #GoogleEarthEngine #GEE #Copernicus #Sentinel2 #algorithms #learning #google #ml

Our newest episode of #SceneFromAbove with special guest @sabrinaszeto has launched TODAY! 🚀✨

Tune in to hear about Sabrina's work with #GoogleEarthEngine & #EarthEngineUserMeetup, advocacy through Women+ in Geospatial, & more! 🎉🛰️ #EOChat #gischat

⭐ S13E5 link ⭐ :
https://scenefromabove.podbean.com/e/s13e5-empowering-geospatial-innovation-with-sabrina-szeto/

Thanks to Sabrina for joining us! And thanks to @rafaelatiengo, @morganahcrowley & @flaviamendes for your efforts this episode! 🛰️

✨Season 13 of #SceneFromAbove is brought to you by Geoawesomeness and UP42 ✨

Our newest episode of #SceneFromAbove with special guest @sabrinaszeto has launched TODAY! 🚀✨

Tune in to hear about Sabrina's work with #GoogleEarthEngine & #EarthEngineUserMeetup, advocacy through Women+ in Geospatial, & more! 🎉🛰️ #EOChat #gischat

⭐ S13E5 link ⭐ :
https://scenefromabove.podbean.com/e/s13e5-empowering-geospatial-innovation-with-sabrina-szeto/

Thanks to Sabrina for joining us! And thanks to @rafaelatiengo, @morganahcrowley & @flaviamendes for your efforts this episode! 🛰️

✨Season 13 of #SceneFromAbove is brought to you by Geoawesomeness and UP42 ✨

.@IleanaCallejas et al. (2021) analyze imagery from #MODIS #Aqua from #GoogleEarthEngine with marine traffic & precipitation data to establish an improvement in water quality in Belize Coastal Lagoon during the #COVID19 anthropause. #LoLManuscriptMonday https://bit.ly/Callejas_2021

.@IleanaCallejas et al. (2021) analyze imagery from #MODIS #Aqua from #GoogleEarthEngine with marine traffic & precipitation data to establish an improvement in water quality in Belize Coastal Lagoon during the #COVID19 anthropause. #LoLManuscriptMonday https://bit.ly/Callejas_2021

Hey #GoogleEarthEngine enthusiasts! #eemont v0.3.6 has been released! 🚀😉

Check it here: https://github.com/davemlz/eemont

🆕 #AwesomeSpectralIndices v0.3.0 🛰️🌿
🆕 #Radar indices computation support for #Sentinel1 and #Palsar2!

#EOchat #GISchat #EarthEngine #Geospatial #Geopython

Hey #GoogleEarthEngine enthusiasts! #eemont v0.3.6 has been released! 🚀😉

Check it here: https://github.com/davemlz/eemont

🆕 #AwesomeSpectralIndices v0.3.0 🛰️🌿
🆕 #Radar indices computation support for #Sentinel1 and #Palsar2!

#EOchat #GISchat #EarthEngine #Geospatial #Geopython

I recently made a useful addition to my #GEE code which allows me to see when it was last run in local time while ingesting data in the community catalog

You can try it yourself. I am channeling @Keiko_geo #EarthEngine tips series 😀

https://code.earthengine.google.com/79a474f67640936683b47f1989cf3ece

#GoogleEarthEngine #gischat

I just found out there is people creating YouTube video tutorials about #AwesomeSpectralIndices and #GoogleEarthEngine ❤️

Here is one about #spectral by @ksabmagar7. Keep up the nice work!

Link: https://www.youtube.com/watch?v=GJuoBp6B3fU&ab_channel=ktmagar%27sYT

I just found out there is people creating YouTube video tutorials about #AwesomeSpectralIndices and #GoogleEarthEngine ❤️

Here is one about #spectral by @ksabmagar7. Keep up the nice work!

Link: https://www.youtube.com/watch?v=GJuoBp6B3fU&ab_channel=ktmagar%27sYT

RT @YellowstoneNPS: To analyze the current extent of aspen in northern Yellowstone, the @NASA_DEVELOP team refined ecological models in #GoogleEarthEngine using @NASA_Landsat and @CopernicusEU imagery to classify aspen stands. #DEVELOPinthePark

🐦🔗: https://n.respublicae.eu/CopernicusEU/status/1601542280036642816

RT @YellowstoneNPS: To analyze the current extent of aspen in northern Yellowstone, the @NASA_DEVELOP team refined ecological models in #GoogleEarthEngine using @NASA_Landsat and @CopernicusEU imagery to classify aspen stands. #DEVELOPinthePark

🐦🔗: https://n.respublicae.eu/CopernicusEU/status/1601542280036642816

Hey #GoogleEarthEngine enthusiasts! #spectral 0.3.0 has been released! Now you have access to the new version of #AwesomeSpectralIndices in the Code Editor 😉 ⬇️

🏅 228 Spectral Indices! 🛰️ 🌿

Repo: https://github.com/awesome-spectral-indices/spectral

#EarthEngine #GISchat #EOchat #JavaScript #RemoteSensing

Hey #GoogleEarthEngine enthusiasts! #spectral 0.3.0 has been released! Now you have access to the new version of #AwesomeSpectralIndices in the Code Editor 😉 ⬇️

🏅 228 Spectral Indices! 🛰️ 🌿

Repo: https://github.com/awesome-spectral-indices/spectral

#EarthEngine #GISchat #EOchat #JavaScript #RemoteSensing

Animated gif with leafmap #geospatial #GoogleEarthEngine

https://leafmap.org/notebooks/61_vector_to_gif/

Animated gif with leafmap #geospatial #GoogleEarthEngine

https://leafmap.org/notebooks/61_vector_to_gif/

#GoogleEarthEngine is perfect for deriving and visualising big remote sensing data in 5 minutes for #30DayMapChallenge! @[email protected] mapped colour hue diversity of #Estonia using the sliding window method for the #Landsat8 summertime 2019 mosaic. Code: https://code.earthengine.google.com/1fcba5553cad9a17b8ee698913639423?noload=true

May I introduce to you the - #EarthEngine App Finder - a new #streamlit application to
+ find #GoogleEarthEngine apps by their location
+ filter by zoom level
+ open the app directly in browser

#EOchat #GEE 🎬🌎🛰️🎁
https://share.streamlit.io/philippgaertner/ee-appshot-streamlit-map/main

May I introduce to you the - #EarthEngine App Finder - a new #streamlit application to
+ find #GoogleEarthEngine apps by their location
+ filter by zoom level
+ open the app directly in browser

#EOchat #GEE 🎬🌎🛰️🎁
https://share.streamlit.io/philippgaertner/ee-appshot-streamlit-map/main

Tweet deAntony.Barja (@antony_barja), a las 27 abr. 7:17 a. m. - Hello, #GoogleEarthEngine enthusiasts! 🌎🌍🌏🚀
I'm glad to share two cheatsheets for rgee, it was a challenge for me and @csaybar, it's our first release.
Comming soon in #rstudio #rgee #rspatial
Download: https://t.co/B0v0ACef18
Discussion: https://t.co/uisZsqFA5o https://t.co/GrA7VEp8ZK

https://twitter.com/antony_barja/status/1519289702444060677