For the purpose of developing solutions, it is crucial to monitor how the planet changes in reaction to fires, floods, and other environmental disturbances exacerbated by climate change or human activities (deforestation and urban development). With Dynamic World , Google is now making data more accessible by utilizing its AI Platform and Earth Engine.

In the past, it has been challenging to obtain comprehensive, current data on land cover, which shows how much of a region is covered by various land and water types, including wetlands, forests, agricultural crops, trees, and urban growth.

Dynamic World provides global, ten-meter-resolution land cover data in aa2 with the World Resources Institute (WRI). A pixel (about 1,100 square feet of land) of satellite imagery is analyzed to determine whether it has water, flooded vegetation, built-up areas, trees, crops, bare ground, grass, shrub/scrub, or snow/ice.

With the use of this knowledge, experts like scientists and decision-makers can keep an eye on the environment and gain a better understanding of its ecosystems, allowing them to forecast future events more precisely and devise practical solutions to save the world.

With data as recent as two days ago, Dynamic World specifically uses photographs from the Copernicus Sentinel-2 to produce 5,000 images per day. In contrast:

Current global land cover maps typically only give land cover data on a monthly or annual basis and might take months to compile.

While a peer-reviewed study on Nature Scientific Data has been released, Google is providing Dynamic World as an open and free dataset.

We are under pressure to create better, more effective, and more sustainable methods to use land because of the worldwide land shortage. We require dependable, almost real-time monitoring of every hectare of the planet if we are to generate what is required from the land, safeguard the remaining natural resources, and partially restore what has been lost.

Vice President of Food, Forests, Water, and the Ocean at WRI Craig Hanson
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