LSAPy: Land Suitability Analysis in Python

LSAPy is a highly customizable Python library designed to streamline and enhance Land Suitability Analysis (LSA) workflows. The package implements a fuzzy-logic approach and provides two core objects – SuitabilityCriteria and LandSuitabilityAnalysis – and one module (lsapy.standardize) that work together to deliver a flexible and user-defined LSA framework. By relying on xarray objects for computation (Hoyer and Hamman, 2017), LSAPy seamlessly integrates with the broader Python ecosystem, such as dask for efficient parallel processing and matplotlib for data visualisation. Its modular design addresses some limitations of existing LSA tools by offering greater flexibility, reproducibility, and scalability for research and practical applications.