Preprocessing Dischma Snowdepth Timeseries

This repository contains all necessary code and data to harmonize and standardize the snow depth maps from the ADS and the UltraCam sensor systems for the Dischma catchment.
The workflow establishes a high-resolution (2m) spatial continuous timeseries of snow depth maps over 10 years.

Table of Contents

• Repository Files
• Installation & Usage
• Dataset Download

Repository Files

• preprocessing.py: Main script for preprocessing the snow depth maps.
• preprocessing_base/: Library of functions used for preprocessing.
• preprocessing_config.yaml: Configuration file for processing settings (edit this to match your setup).
• env/environment.yml: Conda environment specification for dependencies.
• reference_raster_mask_2m.tif: Reference raster file for spatial alignment and matching.

These files together enable harmonization and standardization of snow depth maps from different sensor systems for the Dischma catchment.

Installation & Usage

This guide assumes you have a Mamba/Conda installation. For a minimal, open-source setup, we recommend installing Miniforge from the official repository.
Miniforge comes with mamba, a fast, parallel replacement for conda.

Steps:

1. Clone the repository & navigate into its directory

   git clone "https://github.com/ChristianGoehrig/Dischma-Snowdepth-Timeseries" Dischma_Snowdepth_Timeseries
   cd Dischma_Snowdepth_Timeseries

2. Create and activate the environment with Mamba (or Conda)

   mamba env create -f env/environment.yml
   conda activate Dischma_Snowdepth_Timeseries

3. Download required datasets and configuration:

   • Download both UltraCam and ADS datasets and save them in a common directory (see Dataset Download).

4. Set up the configuration file

   • Edit preprocessing_config.yaml to adjust processing settings according to your data and needs.

5. Run the preprocessing script

   python preprocessing.py

   • Ensure all dependencies are installed. If any are missing, install them as needed (see environment.yml).

6. Retrieve harmonized output

   • The harmonized files will be generated in your configured output_folder.

Note: Because 2018 is of much smaller coverage, consider not integrating this year to gain larger spatial coverage.

Dataset Download

Snow depth maps of each dataset can be downloaded from Envidat.

• UltraCam Dataset
• ADS Dataset

Limitation: No acquisitions exist for 2011.