A QGIS pugin for GIS-based multicriteria decision analysis: An application of developing alternative future land-use scenarios in Ghana

Changjie Chen, Ziyi Guo and Jasmeet Judge

No x6tnj, SocArXiv from Center for Open Science

Abstract: In many West African countries, ongoing rapid urbanization urges reliable and proactive land use plans for sustainability purposes, which hinges on a complete assessment of land suitability. GIS-based multicriteria decision analysis (GIS-MCDA) is one of the most widely applied techniques in land use suitability analysis. It is pivotal that planners and analysts in the developing world have adequate support in conducting such analysis. To lower the financial and technological barriers, a new free and open-source software (FOSS) for GIS-MCDA is developed, called PyLUSATQ. It is designed as a QGIS plugin following a tight-coupling integration strategy, where analytic tools for GIS-based suitability analysis and MCDA are interconnected and seamlessly integrated into QGIS’s processing framework. With this implementation, users can create customized models with the PyLUSATQ tools using QGIS’s Graphical Modeler to automate the workflow for suitability analysis. PyLUSATQ is the first of its kind amongst all plugins published on the QGIS Python Plugin Repository, offering a range of tools for GIS-MCDA within the context of land use planning. To demonstrate its practical application, we created two 2050 future land-use scenarios in the Ashanti Region of Ghana. The first scenario depicts a "business-as-usual" model, whereas the second shows an "alternative" scenario if a higher development density was adopted. Comparisons of such scenarios provide evidential support for making informed decisions on land use policies. Additionally, the methodology introduced here is easily replicable for developing new QGIS plugins based on third-party Python libraries.

Date: 2023-08-11
New Economics Papers: this item is included in nep-afr
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Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:x6tnj

DOI: 10.31219/osf.io/x6tnj

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