access mosaiks

We have worked to develop multiple ways to access MOSAIKS features:

• Global Administrative Units (Planet imagery) You can download features aggregated to country, province, or municipality (ADM0/ADM1/ADM2 boundaries), as described in Sherman et al. (2023). These features are based on Planet imagery. These files are relatively small in size and can be used at these resolutions or to downscale administrative data. To download them, register at api.mosaiks.org and access them via the “Precomputed Files” tab.

• USA grid from Rolf et al (Google basemap imagery) You can download features for a set of locations across the United States, as described in Rolf et al. (Nature Communications, 2021). These features are based on imagery from the Google Earth base map. You can download the features from the Code Ocean Capsule associated with that manuscript (the capsule will also allow you to replicate the analysis of that paper on a remote machine). The Github repository for that analysis is here.

• Global 0.01 x 0.01 degree grid (Planet imagery) You can download features for a complete and dense grid of global land areas via our API. These features are based on on quarterly mosaics from Planet’s Surface Reflectance Basemaps produce from 2019 Q3. Because the complete data set is large (multiple TB), you will need to request custom subsamples of the imagery. To download them, register at api.mosaiks.org and access them via the “Map Query” tool or by uploading a list of locations via the “File Query” tool.

• Recompute MOSAIKS features (Landsat & Sentinel imagery) You can recompute MOSAIKS features yourself using Microsoft’s Planetary Computer (Github repo which currently supports Gaussian random convolutional features). This approach will not provide the benefit of pre-computed features, since you will recompute features on-the-fly every time, but the massive compute power of the Planetary Computer makes this relatively fast and cheap for users.

We have put together a Resource Page for MOSAIKS users here (registration required), which includes example Python and R notebooks for using the pipeline.

Don’t forget to see our Tutorial Page here, which has an example Python notebook that we walk through in the video.

If you are looking for new data sets that we create using MOSAIKS (not features), we will be posting those here.