Relief Visualization Toolbox (RVT) was produced to help scientists visualize raster elevation model datasets. We have narrowed down the selection to include techniques that have proven to be effective for identification of small scale features. The default settings therefore assume working with high resolution digital elevation models derived from airborne laser scanning missions (lidar), however RVT methods can also be used for other purposes.
Sky-view factor, for example, can be efficiently used in numerous studies where digital elevation model visualizations and automatic feature extraction techniques are indispensable, e.g. in geography, archaeology, geomorphology, cartography, hydrology, glaciology, forestry and disaster management. It can even be used in engineering applications, such as predicting the availability of the GPS signal in urban areas.
Methods currently implemented are:
- hillshading,
- hillshading from multiple directions,
- slope gradient,
- simple local relief model,
- multi-scale relief model,
- sky illumination,
- sky-view factor (as developed by our team),
- anisotropic sky-view factor,
- positive and negative openness,
- local dominance,
- multi-scale topographic position.
The rvt Python package contains three modules:
-
rvt.visfor computing visualizations -
rvt.blendfor blending visualizations together -
rvt.defaultfor defining default parameters with methods to compute and save visualization functions using set parameters
When using the tools, please cite:
- Kokalj, Ž., Somrak, M. 2019. Why Not a Single Image? Combining Visualizations to Facilitate Fieldwork and On-Screen Mapping. Remote Sensing 11(7): 747.
- Zakšek, K., Oštir, K., Kokalj, Ž. 2011. Sky-View Factor as a Relief Visualization Technique. Remote Sensing 3: 398-415.
The RVT Python package can be installed using Conda or PyPI, and can be used in Python scripts, Jupyter Notebooks and ArcGIS Pro.
RVT can also be installed as a set of custom raster functions for ArcGIS, and a plugin for QGIS.
You can also clone the repository.
The rvt package is available from the Anaconda Cloud repository. Using Conda to install the rvt package will include all required libraries.
To use this method, first install Anaconda and Conda.
Then open Anaconda Prompt (Windows) or Terminal (MacOS) and run:
conda install -c rvtpy rvt_py
Another option is to install the rvt-py package and required libraries using the Python Package Index (PyPI).
PyPI usually has problems installing gdal, so install gdal first to use this method.
Then open Command Prompt (Windows) or Terminal (MacOS) and run:
pip install rvt-py
Required libraries (specified versions have been tested, other versions may also work):
- numpy 1.19.2
- scipy 1.5.2
- gdal 3.0.2
We recommend using Python 3.6 or higher and a Conda environment (this works best with gdal).
Documentation of the package and its use is available at Relief Visualization Toolbox in Python documentation.
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change. Please report any bugs and suggestions for improvements.
Development of RVT Python scripts was part financed by the Slovenian Research Agency core funding No. P2-0406, and by research project No. J6-9395.
This project is licensed under the terms of the Apache License.
RVT Python library by Žiga Kokalj, Žiga Maroh, Krištof Oštir, Klemen Zakšek and Nejc Čož, 2022.
It is developed in collaboration between ZRC SAZU and University of Ljubljana.