Introduction¶
UW Geospatial Data Analysis
CEE498/CEWA599
David Shean
Overview¶
This week, we are going to cover raster basics. We will introduce and use gdal and rasterio to process, analyze and visualize Landsat-8 satellite images over Washington state.
Reading and Tutorials¶
Please review the following material (especially if you have limited GIS or remote sensing experience), and come to lecture/lab with questions on topics that are unclear, so we can discuss together. There is some overlap in content, but different presentation of the essential material, so hopefully one or more will work for you:
Raster basics¶
ESRI Documentation (~15 min)
Data Carpentry Introduction to Raster Data (~15 min)
Multispectral Image and Landsat background¶
EarthLab Section 5: https://www.earthdatascience.org/courses/use-data-open-source-python/multispectral-remote-sensing/
Suggested (can skim/read, no need for interactive):
Chapter 7: Introduction to Multispectral Remote Sensing Data in Python
Chapter 9: Work with Landsat Remote Sensing Data in Python
Chapter 11: Calculate Vegetation Indices in Python
Optional:
Chapter 8
Chapter 10
Rasterio¶
GDAL¶
Parts 1, 2 and 4 of Rob Simmons’ “A Gentle Introduction to GDAL”:
Optional
Other resources¶
GeoHackWeek: https://geohackweek.github.io/raster/
EarthLab Section 3: https://www.earthdatascience.org/courses/use-data-open-source-python/intro-raster-data-python/fundamentals-raster-data/
Note: The EarthLab material recently migrated from
rasteriotorioxarray. We will start withrasterio, then come back toxarrayandrioxarraylater in the quarter.