Exploring the Data Commons, One Dataset at a Time

Let's deep dive into datasets that build our GEE Community Catalog. Our journey begins with Canada's stand-level satellite-based forest inventory (SBFI) with over 25+ million inventory polygons/stands

This week let’s talk about Canada’s stand-level satellite-based forest inventory the strategic, satellite-based forest inventory for Canada’s 650-Mha,forest-dominated ecosystems. Think of this as a multivariate inventory of contiguous features into stands or polygons. This builds on some amazing datasets from tree species to forest structure, and age of forest to name just a few.

With over 25 million polygons this allows for a partitioned and yet consistent forest inventory and classification across all of Canada’s forest ecosystems. You can download the dataset here and read the paper here. This dataset is extremely rich in attributes with over 120+ attributes attached to each of these polygons allowing varied use across different applications.

Getting to the data

The original dataset was stored in an ESRI geodatabase format that can be difficult to access without specialized software. However, the creators helpfully exported the component layers as Earth Engine assets. These assets were combined, flattened, and converted into a single geospatial feature collection for easier use.

To visualize the data, a random color palette was applied based on the "Max_Age" attribute rather than trying to reproduce the original lyr color scheme. This simplified the process while still allowing tree stand ages to be distinguished.

The Awesome GEE Community Catalog

The Awesome Google Earth Engine Community catalog at this moment has been accessed across almost every single country with over 300k requests per month. With over 350+ TB of community-curated datasets and over 1680+ datasets. This dataset is now part of the Awesome GEE Community Catalog and can be accessed here. The attribute table is included for users to scroll through and use the different attributes to cluster, filter, or perform secondary analysis using this inventory.

Try the sample code that runs on Earth Engine here

The resulting feature collection contains a wealth of attributes about each forest stand thanks to the satellite imagery analysis. This robust information provides valuable insights into the status and dynamics of Canada's forest resources at a local level. If you want to find out more about the community catalog and want to be involved find me on Linkedin and Github, reach out, and have a conversation. Share your data ideas.

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Next up is a Global Land Cover dataset over 30+ years.

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