Skip to content

Work with DEM data using Python from Simple to Complicated. Many python packages will be touched such as GDAL, numpy, xarray, rasterio, folium, cartopy, geopandas etc.

License

Notifications You must be signed in to change notification settings

monocilindro/Work-with-DEM-data-using-Python-from-Simple-to-Complicated

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

34 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Work-with-DEM-data-using-Python-from-Simple-to-Complicated

Work with DEM data using Python from Simple to Complicated. Many python packages will be touched such as GDAL, numpy, xarray, rasterio, folium, cartopy, geopandas etc.

  1. Visualize Elevation Contours from DEM data

  2. Histograms of DEM Values

  3. Deal with DEM in ASCIIGRID Format

  4. Clip GeoTIFF Data With a Shapefile

  5. Reproject DEM

  6. Hillshade from a Digital Elevation Model (DEM)

  7. Watershed Delineation from DEM

  8. Exploratory Flood Inundation Model with Flood Fill Algorithm

  9. Inundation Estimation with RFSM

  10. Visualize DEM in An Interactive Map

  11. Reclassify DEM

  12. Merge Overlapping Rasters Using R and Terra

  13. Merge Overlapping Rasters Using python and rioxarray

  14. Merge Overlapping Rasters Using Python and GDAL VRT Pixel Functions

  15. Vectorize - Extract Raster Boundry to GeoDataFrame

Sup01-Quickly Visualize DEM Attributes with Datashader

Sup02-DEM, DTM, DSM and Canopy Height Model

Sup03-Ridgelines Map of DEM

To simiplify data reading and prepocessing, xarray (backended with rasterio) is used as possible as I can. Hope these tutorials are a little bit helpful to you.

Being a data scientist (maybe the only one in your company), sometimes, you will feel very bored, and the best way to get rid of it is to keep coding with python :).

Many thanks to those people who develop and maintian python packages involved in this tutorial.

About

Work with DEM data using Python from Simple to Complicated. Many python packages will be touched such as GDAL, numpy, xarray, rasterio, folium, cartopy, geopandas etc.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 99.6%
  • HTML 0.4%