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Python/Bash Beginner's guide to demcoreg

The demcoreg README.md provides a basic overview of installation and usage for users with basic Python, bash, and git/github proficiency. This document is intended to provide additional support for new users of these tools, who often need to co-register two DEMs for a relatively limited application, without all of the advanced options.

Operating System

  • The intructions below are for a *nix machine (Linux or Mac OS X).
  • For Windows, we reccomend that you install Ubuntu subsystem for Windows and then follow the instructions below. Since you're using a linux subsystem, you want to use miniconda for linux in the first installation step (not Windows).

Installation

  1. Install conda. Managing python packages is best done using conda. You can download miniconda for your OS/architecture here: https://docs.conda.io/en/latest/miniconda.html
  2. Open a terminal/shell
  3. Create and activate a Python environment called demcoreg_env with necessary packages installed:
  • Run this command to create an environment: conda create -c conda-forge -n demcoreg_env python gdal rasterio geopandas requests matplotlib
  • After this completes, the new environment must be "activated". You can do this with: conda activate demcoreg_env
    • Note: you will need to activate each time you start a new terminal session
  1. Prepare to install software from github (this needs to be done only once)
  • Create a directory to store code from github repositories. One option is ~/src which creates a new subdirectory src in your home directory, usually /Users/loginname (shorthand ~). In the terminal, run: mkdir ~/src
  • Navigate to the new subdirectory: cd ~/src
  1. Clone github repositories:
  • git clone https://github.com/dshean/pygeotools.git
  • git clone https://github.com/dshean/demcoreg.git
  • git clone https://github.com/dshean/imview.git
  1. Install these packages, so you can use them with your conda Python:
  • pip install -e pygeotools/
  • pip install -e demcoreg/
  • pip install -e imview/
  1. In addition to Python modules, these packages also contain some command-line scripts. While you can always run these scripts from the terminal using a full path (e.g., ~/src/demcoreg/demcoreg/dem_align.py), it's convenient to run them using only dem_align.py. To accomplish this, you can add the directory to the ~/.bashrc (or ~/.bash_profile) file in your home directory.
  • To get the full path name realpath demcoreg/demcoreg
  • Open ~/.bashrc (or ~/.bash_profile) in a text editor of your choice, and add this line to the end of the file: export PATH="~/src/pygeotools/pygeotools:~/src/demcoreg/demcoreg:~/src/imview/imview:$PATH"
    • Navigate to your home directory using cd ~
    • Type ls -al in the command line to view a list of files (including hidden files) in the home directory
    • Determine if you have ~/.bashrc (or ~/.bash_profile)
      • If neither exists, you can create with touch ~/.bashrc
    • Edit the corresponding file with a text editor
      • On OS X, can run open ~/.bashrc (or open ~/.bash_profile) to open the file with TextEdit.app
      • On most platforms, can edit directly using nano, vim, emacs or other text editor
  • Run source ~/.bashrc in your current terminal session (won't need to do this in the future)
  1. You may need to reactivate the demcoreg envionment if you ran source ~/.bashrc. As in step 3, do so with: conda activate demcoreg_env
  2. In your terminal, run dem_align.py -h. You should see the usage statement starting with:
usage: dem_align.py [-h] [-mode {ncc,sad,nuth,none}]
                    [-mask_list {toa,snodas,modscag,bareground,glaciers,nlcd,none} [{toa,snodas,modscag,bareground,glaciers,nlcd,none} ...]]
                    [-tiltcorr] [-polyorder POLYORDER] [-tol TOL]
                    [-max_offset MAX_OFFSET] [-max_dz MAX_DZ]
                    [-res {min,max,mean,common_scale_factor}]
                    [-slope_lim SLOPE_LIM SLOPE_LIM] [-max_iter MAX_ITER]
                    [-outdir OUTDIR]
                    ref_fn src_fn

Basic command-line usage

  • If the above sequence of commands are followed, you have all the command-line tools and python libraries in demcoreg, pygeotools and imview at your disposal (Look at their corresponding readmes for more details).
  • dem_align.py is the workhorse here which can be used to align two rasters. This is probably the most desirable operation for new users who install this package for aligning/co-registering two DEMs.
  • To align two DEMs named dem1.tif and dem2.tif, run the following command: dem_align.py -mode nuth dem1.tif dem2.tif
    Note: When run for the first time, demcoreg will download glacier polygons from the rgi website which might take some time.
    • If you have no already downloaded the rgi glacier polygons, you will be prompt to run get_rgi.sh
    • In order to run get_rgi.sh, you will need to install wget if it is not already installed on your computer. You can do so using conda forge or brew: conda install wget or brew install wget
  • This will co-register dem2.tif to dem1.tif, and will store the results in a subdirectory (see the log output). The folders contain the aligned dem2.tif (filename ending with *_align.tif), final elevation difference map (filename ending with *_align_diff.tif) and the elevation difference map over static surfaces used during alignment (*_align_diff_filt.tif).
  • You can open these GeoTiff files in GIS software like QGIS/ArcGIS to analyse the above mentioned files. The output folder also contains a .png file (ending with *_align.png). This contains figures of input DEMs, surfaces used for co-registration, elevation difference maps and histograms/stats before and after co-registration (see sample png figure in demcoreg README).

Advanced command-line usage

  • Run the command as dem_align.py -h to get extended usage, explanations of options and default values.
  • By default, dem_align.py will exclude DEM pixels over glaciers during co-registration. To use all pixels in the input DEMs, use the option -mask_list none.
  • One can limit co-registration to DEM pixels over bare ground or snow-free areas. Two options for landcover classification are available - the National LandCover Dataset (NLCD) for the United States, and a global bareground dataset. To limit co-registration over these surfaces, use options -mask_list nlcd or -mask_list bareground. Two or more masking options can be combined with a comma-seperated string: -mask_list glaciers,nlcd
  • To remove residual elevation differences after co-registration, dem_align.py uses polynomial fits of arbitrary order -tiltcorr. By default this will use a first-order polynomial (planar fit), though the user can specified higher order fits (e.g., -tiltcorr 3 for cubic fit)
  • Users can also change the slope (-slope_lim) and maximum absolute elevation difference (-max_dz) filters. By default, these filters exclude surface slopes outside of 0.1° to 40° and any pixels with absolute elevation difference greater than 100 m.

Python API: using demcoreg in a python script/notebook

  • Most of the demcoreg code contains modular functions that are called by executables like dem_align.py. These can also be called directly from a Python script or interactive session (like Jupyter notebook)
  • For example, to access the get_icemask function in dem_mask.py:
    • Add from demcoreg import dem_mask near the top of your Python script or notebook
    • Call the function dem_mask.get_icemask(GDAL_DataSet) for your input GDAL DataSet object (e.g., output from gdal.Open(dem1.tif))
    • (ice_mask_example).

Additional help

  • The source code contains additional notes and documentation. Users can file a Github Issue if the encounter errors or bugs. We hope to improve documentation and simplify the installation process in the future, so could use help if you have the time!