FOSS4G 2022 general tracks

Matthew Hanson

Matthew Hanson is the Geospatial Engineering Lead at Element 84. Matthew is active in the open-source geospatial community helping to develop standards supporting the interoperability of remote sensing data and is author and contributor to multiple open-source projects. At Element 84, Matthew collaborates with the small-sat industry and government satellite programs to develop open standards and software to support scalable, open science.

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Sessions

08-24
12:00
30min
The State of Cloud-Native Geospatial
Matthew Hanson

The vision of “Cloud-Native Geospatial” is a new paradigm of performing efficient computing and data access in the cloud in an interoperable way in order to achieve scalable and repeatable analysis of geospatial data. The last few years have seen major developments in open standards and open software that are helping make this vision possible, supporting full end to end interoperable workflows on remote sensing data, from data discovery to publishing of interoperable derived products.

This talk will present the current state of the Spatio Temporal Asset Catalog (STAC) specifications (stac-spec and stac-api-spec), updates in the published STAC extensions, and the latest community developments around Analysis Ready Data (ARD). We will cover the landscape of current recommended cloud-optimized file formats, for raster, vector, and point-cloud data formats (COG, Zarr, GeoParquet, COPC). Finally, we will provide recommendations for open-source client software to use to take advantage of the emerging geospatial clouds.

State of software
Room Onice
08-25
15:35
5min
Analysis Ready (Meta)Data
Matthew Hanson

The term Analysis Ready Data started as a way to describe a Landsat product that would efficiently allow time-series based analysis by providing a consistent, grid and pixel-aligned product corrected to surface-based measurements. Since then it has come to mean a wide range of things, but without a clear set of standards on how to characterize ARD there is little to no interoperability among datasets that call themselves ARD.

The Analysis Ready Metadata initiative uses the SpatioTemporal Asset Catalog (STAC) spec as the vehicle for describing well-characterized data. This goes beyond the basic geospatial and temporal characteristics captured in the core STAC spec and into detail about the processing level of the data, corrections that have been applied, as well as spatial and measurement uncertainties. Having well-characterized data through it’s STAC metadata enables discovery of usable data, automated processing using interoperable workflows, and tracking of data provenance of derived products.

The CEOS ARD (previously CARD4L) specifications require certain metadata and processing to be done for it to be compliant and can use this STAC metadata to automatically assess the potential for a dataset to be compliant with the needed requirements. This talk will cover elements of STAC, ARD, and the CARD4L family product specifications.

Open Data
Modulo 0
08-24
11:00
30min
STAC Best Practices and Tools
Matthew Hanson, Pete Gadomski

The SpatioTemporal Asset Catalog (STAC) specification is a common language for describing geospatial information that is flexible enough to extend across domains and use cases. In this talk, we walk through best practices for building STAC catalogs and using STAC extensions, using real world examples. These best practices are informed by documentation, conversations with STAC contributors, and discussions within the wider community. We survey the ecosystem of open-source STAC software, which includes libraries and tools written in Python, Node.js, and more. We show examples of reading, modifying, and writing STAC catalogs with a selection of software, including PySTAC and stactools, and we show which metadata to include in your STAC objects to ensure interoperability with powerful tools like xarray and pandas. Whether you are new to the STAC ecosystem or an experienced contributor, this talk will provide you with the context and tools you need to build your best STAC!

State of software
Room Onice