Land & Carbon Lab
Dynamic World
Near-real-time (NRT) land use/land cover (LULC) dataset at 10 meter resolution that includes nine classes, pixel-level class probabilities, and labeling information.
Created
Oct 10, 2024
Last Updated
Oct 10, 2024
Caution:
- Dynamic World data is intended to be used through Google Earth Engine given the rapid update frequency and large number of Sentinel-2 scenes collected and processed daily.
- To select only pixels that confidently belong to a Dynamic World class, it is recommended to mask Dynamic World outputs by thresholding the estimated "probability" of the top-1 prediction.
- Performance varies spatially and temporally as a function of both the quality of S2 cloud masking and variability in land cover and condition.
- Dynamic World tends to perform most strongly in temperate and tree-dominated biomes. Arid shrublands and rangelands were observed to present the greatest source of confusion specifically between crops and shrubs.
- Single-date classifications are highly dependent on accurate cloud and cloud shadow masking. Though the authors implemented a fairly conservative masking process that includes several existing products and algorithms, missed clouds are typically misclassified as Snow & Ice and missed shadows as Water.
WRI Data
0 Data Files
No data files found
Didn't find what you were looking for?
STAY UP TO DATE WITH THE NEWS
Powered by Portal.js from