Analysis-Ready Data Workshop 2021

makepath participated in this year’s Analysis-Ready Data (ARD21) conference. 

ARD21 is part of an annual Analysis-Ready Data Workshop series. This year’s focus was on satellite data interoperability.

The focus on data interoperability underscores the growing need for standardization of analysis-ready data, as data formats used often differs across industries.  

Below we highlight makepath’s participation as well as some noteworthy talks given during the conference, which can be watched here.  

Xarray-Spatial for Raster Analysis

[Timestamp 8:30]

makepath Co-Founder and Principal, Brendan Collins, shared how the Open Source GIS library, xarray-spatial, can be used for common raster analysis applications.

The xarray-spatial library includes core raster-analysis functions for geospatial developers that all work on top of xarray DataArrays and return xarray DataArrays.

The xarray-spatial Readme provides a matrix of supported inputs for the analysis functions.

xarray-spatial available tools

rioxarray: storing geospatial information on xarray datasets

[Timestamp 2:08]

Corteva Data Engineer, Alan Snow, explained how geospatial information can be easily stored on xarray datasets using rioxarray, an extension of xarray

rioxarray provides interoperability between data. This is an important feature for Corteva, an agriscience company, because sharing files that work for any purpose in their field is important. 

rioxarray stores spatial information in coordinates to limit the loss of metadata.

The multidimensional file format netCDF is supported, with other common spatial objects including Well Known Text and GeoTransform array supported as attributes. 

rioxarray attributes

Why I Wish I Could Delete Most Of The Code in stackstac

[Timestamp 15:34]

Gabe Joseph, Open-Source Engineer at Coiled, talked about how stackstac works to stack your STAC– your Spatio Temporal Asset Catalog.

Basically, you provide the metadata and stackstac converts that into a Daskbacked xarray DataArray.

This is all done with one function: stackstac.stack(stac_items)

stackstac main function

Geo-registered Xarrays in ODC

[Timestamp 28:40]

Dr. Kirill Kouzoubov, a Senior Software Engineer at the World Food Programme and Element 84, talked about how the Open Data Cube project deals with georegistration and xarray. 

The Open Data Cube (ODC) takes the “what, when, where, and how” of the data you want loaded and gives you back an xarray dataset with that data.

Open Data Cube dc.load

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