  Desktop GIS applications, such as ArcGIS and QGIS, provide tools essential
for conducting suitability analysis, an activity that is central in formulating
a land-use plan. But, when it comes to building complicated land-use
suitability models, these applications have several limitations, including
operating system-dependence, lack of dedicated modules, insufficient
reproducibility, and difficult, if not impossible, deployment on a computing
cluster. To address the challenges, this paper introduces PyLUSAT: Python for
Land Use Suitability Analysis Tools. PyLUSAT is an open-source software package
that provides a series of tools (functions) to conduct various tasks in a
suitability modeling workflow. These tools were evaluated against comparable
tools in ArcMap 10.4 with respect to both accuracy and computational
efficiency. Results showed that PyLUSAT functions were two to ten times more
efficient depending on the job's complexity, while generating outputs with
similar accuracy compared to the ArcMap tools. PyLUSAT also features
extensibility and cross-platform compatibility. It has been used to develop
fourteen QGIS Processing Algorithms and implemented on a high-performance
computational cluster (HiPerGator at the University of Florida) to expedite the
process of suitability analysis. All these properties make PyLUSAT a
competitive alternative solution for urban planners/researchers to customize
and automate suitability analysis as well as integrate the technique into a
larger analytical framework.
