Explore efficient methods for handling large-scale geospatial data in this 26-minute PyCon US talk. Learn about various data formats like GeoJSON, Parquet, Shapefiles, and GeoTIFF, and discover techniques to convert and analyze them effectively. Delve into the challenges of working with petabytes of data and uncover solutions using tools such as the xarray-spatial library for raster-based analysis, RTXpy for GPU-powered spatial processing, and Microsoft Planetary Computer for geospatial data handling. Gain insights into vertical scaling, vector and raster data management, and practical applications through examples from MakePath's blog and team members' experiences. Master concepts like Dask, GeoPandas, data shaders, and hotspots to enhance your geospatial data wrangling skills at scale.
Who Said Wrangling Geospatial Data at Scale was Easy?
Overview
Syllabus
Introduction
Vertical Scaling Example
Brendan Collins Introduction
About MakePath
MakePath Blog
Sophia Yang
Natalie Odell
Data Formats
Vector Data
DasGeopandas
Raster Data
No Labels
Xray Spatial
Data Shader
Dasc
Kupai
Hotspots
Planetary Computer
Taught by
PyCon US
