LSAPy Documentation

Description

LSAPy (Land Suitability Analysis in Python) is a highly customizable, open-source Python library designed to streamline and enhance Land Suitability Analysis (LSA) workflows. Its objective is to make conducting LSA in Python easier and more accessible to users. The package implements a fuzzy-logic approach and provides a set of objects that work together to deliver a flexible and user-defined LSA framework.

By relying on `xarray`_ objects for computation, LSAPy is specifically designed to facilitate LSA under climate change projections. Moreover, the use of `xarray`_ allows for seamless integration with the broader Python ecosystem, such as `dask`_ for efficient parallel processing and `matplotlib`_ for data visualisation. The modular design of LSAPy addresses some limitations of existing LSA tools by offering greater flexibility, reproducibility, and scalability for research and practical applications.

Table of Contents:

• About
  • Quick Install
  • Land Suitability Analysis (LSA)
  • Contributing
  • How to cite LSAPy
  • Credits
• Getting Started
  • Installation
  • Land Suitability Analysis (LSA)
• User Guide
  • Suitability Criteria
  • Land Suitability Analysis
• API Reference
  • Standardization Functions
  • SuitabilityCriteria
  • LandSuitabilityAnalysis
  • Statistical Summary
  • Utils
• Community

• Changelog
• Bibliography