Climate change analyzing remote sensing data with Python
summary
Claims a working workflow that lets scientists skip downloads and run reproducible analysis in Jupyter notebooks against hosted remote sensing archives, and shows it actually scales to large files. Demonstrations use xray and dask for out‑of‑core arrays, ipyleaflet maps for interactive selection, Landsat stacks to derive Landsat velocities and consolidated lidar to compute volume change from icebridge HDFi granules; queries hit PostGIS and cloud hosts and the notebook examples complete within minutes.
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chapters (8)
- 0:00Climate change intro
- 3:20Climate change consequences
- 8:17Remote sensing basics
- 12:28Python for geospatial
- 19:15Glacier velocity with Landsat
- 23:20Ice flow and lidar processing
- 30:073D visualization and projections
- 33:23Future plans and Pangeo
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