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.Google DeepMind is powering a new agricultural landscape understanding layer in Google Earth for portions of the Asia-Pacific region to bring powerful data to our iconic imagery. Leveraging machine learning and satellite imagery, this data layer is able to visualize the ""atomic units"" of agriculture: individual field boundaries. This...

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Google Earth

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231,640 Aufrufe • vor 8 Monaten •via X (Twitter)

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22 Kommentare

Profilbild von DaCon
DaConvor 8 Monaten

@GoogleDeepMind You could put a solar yield sim on top. Simulating average or point in time solar irradiance. Seasonal and daily light distribution mapping is key for crop planing and yield. As this varies through a solar cycle, you can also plan crop and soil rest cycles, or grazing rotation.

Profilbild von Shami
Shamivor 8 Monaten

@GoogleDeepMind I've used it and it's amazing 🤩

Profilbild von Sebastian Buzdugan
Sebastian Buzduganvor 8 Monaten

@GoogleDeepMind that land cover segmentation must be seriously complex

Profilbild von Techificial.ai
Techificial.aivor 8 Monaten

@GoogleDeepMind @googleearth & @GoogleDeepMind, this initiative is mind-blowing! Utilising AI to improve agricultural insights will empower farmers and improve resource management. I'm really excited to see the impact it will have in the region.

Profilbild von @Mforja
@Mforjavor 8 Monaten

@GoogleDeepMind Defining agriculture in “atomic units” feels like the right abstraction for applying AI to real land management. This is where geospatial ML starts becoming infrastructure, not just visualization.

Profilbild von Luke
Lukevor 8 Monaten

@GoogleDeepMind Been putting code and AI into the insights of the family farm productions. My mom has rain precipitation, production, prices and other data points for the last 7 years of production.

Profilbild von CosmicNomad
CosmicNomadvor 8 Monaten

@GoogleDeepMind Why just Asia-pacific? Can’t we have this everywhere?

Profilbild von Wessel van Keulen
Wessel van Keulenvor 8 Monaten

@GoogleDeepMind Good progress. What’s next?

Profilbild von Ram
Ramvor 8 Monaten

@GoogleDeepMind Does it also integrated with local weather forecast? Like rainy days?

Profilbild von Yeppi
Yeppivor 8 Monaten

@GoogleDeepMind google earth is build with flutter, right?

Profilbild von suiscats（ゆらゆら）
suiscats（ゆらゆら）vor 8 Monaten

@GoogleDeepMind @grok これは耕作、維持管理を判別できる？

Profilbild von J Dominique A.
J Dominique A.vor 8 Monaten

@GoogleDeepMind All satellite image process: training site, groundtruething, image classification, etc should be

Profilbild von 3DTOPO
3DTOPOvor 8 Monaten

@GoogleDeepMind @yohaniddawela

Profilbild von Amit
Amitvor 8 Monaten

@GoogleDeepMind Modeling agricultural landscapes from satellite imagery is harder than people think. You get radiance, clouds, seasonal artifacts, and messy ground truth. The real progress is in harmonizing temporal sequences into actionable, high-granularity crop maps.

Profilbild von I Have Many Names
I Have Many Namesvor 8 Monaten

@GoogleDeepMind 🚀

Profilbild von Vitucho.
Vitucho.vor 8 Monaten

@GoogleDeepMind Brutal !

Profilbild von 🔻🍉🇰🇼 🇸🇦
🔻🍉🇰🇼 🇸🇦vor 8 Monaten

@GoogleDeepMind It has been two years almost and my area image isn’t updated, is this intended?

Profilbild von Shreya
Shreyavor 8 Monaten

@GoogleDeepMind Oh

Profilbild von Tobe Duru
Tobe Duruvor 8 Monaten

@GoogleDeepMind to provide real-time insights on crop health and land use

Profilbild von Rahul Raghav
Rahul Raghavvor 8 Monaten

@GoogleDeepMind curious how this will impact crop yield predictions and resource allocation in the region

Profilbild von #INTERNETofAGENTS
#INTERNETofAGENTSvor 8 Monaten

@GoogleDeepMind Refinement! 👌

Profilbild von Sachin 1990 Sacbin G
Sachin 1990 Sacbin Gvor 8 Monaten

@GoogleDeepMind flustered

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