This is especially important for organizations like national government resource agencies that use this data to define land-planning priorities and determine budget allocations. With planned annual releases, users have the option to make year-over-year comparisons in global land cover today and into the future. “We are constantly updating our land-cover map with new data and features, and this latest improvement ensures that anyone viewing temporal change can be confident what they are seeing represents the natural world.” “Users are working with maps that will accurately reflect events and earth processes that are happening in reality,” said Sean Breyer, Esri program manager for ArcGIS Living Atlas of the World. The result is a higher confidence that changes detected represent meaningful real-world changes. The AI model performing the global classification has been optimized to reduce model insufficiency, class ambiguity, and sensitivity to seasonal variability. Year-over-year changes detected in the LULC time series maps can be key indicators for analysts and decision-makers.
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