Demcompare, a DEM comparison tool

[](https://www.python.org/downloads/release/python-380/) [](https://demcompare.readthedocs.io/en/latest/developer_guide/contributing.html) [](https://opensource.org/licenses/Apache-2.0/) [](https://demcompare.readthedocs.io/)

Overview • Install • Usage • Documentation •

Overview

Demcompare is a python software that aims at comparing two DEMs together.

A DEM is a 3D computer graphics representation of elevation data to represent terrain.

Demcompare has several characteristics:

• Works whether or not the two DEMs share common format projection system, planimetric resolution, and altimetric unit.
• Performs the coregistration based on the Nuth & Kääb universal coregistration method.
• Offers two coregistration modes to choose which of both DEMs is to be adapted during coregistration.
• Provides a wide variety of standard metrics which can be classified.
• Classifies the stats by slope ranges by default, but one can provide any other data to classify the stats.

Install

Only Linux Plaforms are supported (virtualenv or bare machine) with Python >= 3.8 installed.

Demcompare is available on Pypi and can be typically installed through a virtualenv:

python3 -m venv venv
source venv/bin/activate
pip install --upgrade pip
pip install demcompare

Usage

Download the data samples and run the python script demcompare with sample configuration:

# download data samples
wget https://raw.githubusercontent.com/CNES/demcompare/master/data_samples/srtm_blurred_and_shifted.tif
wget https://raw.githubusercontent.com/CNES/demcompare/master/data_samples/srtm_ref.tif

# download demcompare predefined configuration
wget https://raw.githubusercontent.com/CNES/demcompare/master/data_samples/sample_config.json

# run demcompare
demcompare sample_config.json

A report can be observed with:

firefox test_output/report/published_report/html/index.html

Documentation

Please consult our online documentation.

Licensing

Demcompare software is distributed under the Apache Software License (ASL) v2.0.

See LICENSE file or http://www.apache.org/licenses/LICENSE-2.0 for details.

Copyrights and authoring can be found in NOTICE file.

Related tools

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Pandora - CNES Stereo Matching framework