Google announced on Thursday the availability of a new dataset that depicts Earth's surface properties in near-real-time. When using Dynamic World, a high-resolution land cover map may be created by combining deep learning algorithms with satellite photos.
Land cover maps often take a long time to generate, and there are large gaps between when photos are collected and when the data is made available to the general population. When it comes to landscape classification, they typically don't have a precise breakdown of what's on the ground in any area—a city might be labeled as "built-up," even if there are large portions of parkland.
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How Does It Work?
For every 1,100 square feet, Google says Dynamic World assesses the land cover type. Sections are likely to be covered by water, vegetation, built-up areas, trees, crops, barren terrain, or by one of nine other forms of cover: grass, shrub/scrub, or even snow or ice. In a report published in Nature's Scientific Data, Google described the technique built with the World Resources Institute.
For example, as seen in the accompanying snapshot of New York City, the majority of the region is densely populated (red). However, the city's biggest parks include swaths of grass (green) and shrub/scrub (yellow).
Over 5,000 photos are generated daily by the Dynamic World model, and the land cover data is updated in real-time. Researchers and politicians may now more easily assess disasters like wildfires and hurricanes, allowing quicker and more effective responses to such events.
Google said, "if the world is to create what is required from land, safeguard the nature that remains, and restore some of what has been lost, we need reliable, near real-time monitoring of every hectare of the earth."
Featured image: Google Earth
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