Published May 17, 2021 | Version v2
Dataset Open

Dynamic World Test Tiles

Authors/Creators

  • 1. Google
  • 2. National Geographic Society
  • 3. World Resources Institute
  • 4. Boston University

Description

From the Dynamic World dataset, DOI: PENDING DYNAMICWORLD DOI

Description:

These data comprise the Dynamic World estimated probabilities, Dynamic World Top-1 label, and expert consensus set of GeoTIFF test tiles used for validating Dynamic World and other LULC maps.

  • A metadata CSV is included to enable cross-walking between these tiles and the Sentinel-2 L2A used to annotate the tile.
  • The label_* images contain bands 'lulc' and 'label' corresponding to the annotated, and Top-1 predicted label respectively. The 'lulc' band is 1s-indexed, with 0 corresponding to "no markup."
  • The probs_* images contain the estimated probabilities.

The Dynamic World abstract:

We developed a new automated approach for globally consistent, high resolution, near real-time (NRT) land use land cover (LULC) mapping leveraging deep learning on 10m Sentinel-2 imagery. When compared to other global LULC datasets, our data exceeded the next best global product agreement with an expert consensus test set by 7.5%. We utilize a highly scalable cloud based system for generating LULC maps and provide an open, continuous feed of LULC in parallel with Sentinel-2 acquisitions. This NRT product accommodates a variety of user needs ranging from extremely up-to-date LULC data to annual global maps. Furthermore, the continuous nature of the product's outputs enables refinement, extension, and even redefinition of the LULC classification. In combination, these unique attributes enable unprecedented flexibility for a diverse community of users across a variety of disciplines.

Files

dw_test.zip

Files (3.9 GB)

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