SHIRE (**S**usceptibility **H**azard mapp**I**ng f**R**am**E**work) is a tool to facilitate and streamline landslide susceptibility and hazard mapping using a Random Forest classifier. It provides support for repetitive steps in landslide susceptibility and hazard mapping such as input dataset generation including data pre-processing.
It is a Python-based modular framework that can be complemented with individual modules necessary for answer individual mapping challenges due to the open-access nature of the code.
It is a Python-based modular framework that can be complemented with individual modules necessary for answering individual mapping challenges due to the open-access nature of the code.
Shire was developed as part of the [KISTE Project](https://kiste-project.de/)
Edrich A., Yildiz A., Kowalski J. (2024) Susceptibility and Hazard Mapping Framework SHIRE [Software]. DOI: https://git-ce.rwth-aachen.de/mbd/shire
Edrich A., Yildiz A., Kowalski J. (2024) Landslide Susceptibility and Hazard Mapping Framework SHIRE [Software]. https://git-ce.rwth-aachen.de/mbd/shire
@misc{shire,
author = {Edrich, Ann-Kathrin and Yildiz, Anil and Kowalski, Julia},
title = {{Landslide Susceptibility and Hazard Mapping Framework SHIRE [Software]}},
year = {2024},
note = {Access under \url{https://doi.org/10.6084/m9.figshare.24339643}},
}
Corresponding publications:
Edrich A., Yildiz A., Roscher R., Bast A., Graf F., Kowalski J. (2024) A modular framework for FAIR shallow landslide susceptibility mapping based on machine learning. Natural Hazards 120, 8953–8982. https://doi.org/10.1007/s11069-024-06563-8
@article{edrich2024modular,
title = {{A modular framework for FAIR shallow landslide susceptibility mapping based on machine learning}},
author = {Edrich, Ann-Kathrin and Yildiz, Anil and Roscher, Ribana and Kowalski, Julia},
journal = {Natural Hazards},
year = {2024},
doi = {https://doi.org/10.1007/s11069-024-06563-8}
