Multi-Criteria GIS modelling for optimal alignment of roadway by-passes in the Tlokweng Planning Area, Botswana

Abstract

To find the optimal by-pass road alignment in the Tlokweng Planning Area in Botswana, a multi-criteria spatial-based model is developed using the GIS-MCE approach. In respect to the environmental impact assessment (EIA) approach, in this research a set of criteria is classified under 3 themes – economic, environmental and social. To determine the criterion and theme weights and perform their aggregation, the Analytical Hierarchy Process (AHP) and Weighted Sum (WS) are utilised. The least-cost path analysis is used to produce road alignments. The entire model is developed using ModeBuilder in the ArcGIS 10.5 environment. Depending on the theme’s preference, 4 road alignments are produced: economic, environmental, social and equal. Comparing GIS-produced alignments and the planned route proposed in the “Tlokweng Development Plan 2025” is carried out by applying an independent validation matrix using the DEFINTE software package.

The investigation into the robustness of the model is completed by examining the model output to identify criteria sensitive to weight changes. For this purpose, One-At-a-Time (OAT) sensitivity analysis and the statistical test for zero proportion are used. Sensitivity analysis results for criteria identified as sensitive are also presented spatially. To carry out the sensitivity analysis, a standalone Python script has been created which communicates with ArcGIS 10.5 through the ArcPy module.

This study has successfully investigated, developed and applied the MCE method for optimal planning of highway and road alignments together with a sensitivity analysis for the MCE method. The results show that the social alignment is the best of the 4 road alignments – economic, environmental, social and equal. The results further confirm that the planned alignment, not produced by applying the multi-criteria approach, substantially differs from the 4 mentioned routes produced in GIS. The results of the sensitivity analysis and statistical test for zero proportion reveal 6 criteria as sensitive. The criterion referring to land use/land cover displays the greatest difference in the results – the model becomes sensitive at -5% of this criterion weight change.

Further research is recommended to increase the robustness of the model. Some recommendations are further analyses regarding the assignment of criteria weights, standardisation of criteria and applying a “global” sensitivity approach in which more than one criterion weight is changed at a time.

Popular Abstract

Nowadays, a well-planned and efficient road infrastructure is one of the main prerequisites for the development and continued economic sustainability of communities and nations. Road infrastructure can affect communities in different ways. For example, if roads are not correctly planned, there can be negative consequences for ecology, the economy and humans health. For instance, traffic emissions can adversely affect the health of humans, animals and plants living nearby.

So when we want to build a road infrastructure, one of the main questions we need to ask is the following: How do we determine where the road should pass so that it affects our environment, economy and humans health in the least detrimental way? This is especially important for developing countries with greatly limited resources. In the search for an answer, we utilised the capabilities of Geographical Information Systems – GIS. We combined different environmental, economic and social criteria in a model which could help us find pratical solutions. To combine these criteria we applied a set of well-known methods from Multi-Criteria Evaluation analysis – MCE.

After building the model in GIS, we applied it in the Tlokweng Planning Area in Botswana. This location was chosen as a good example because of its limited sources and its planned rapid development in the near future. An important aspect of this development is building northern and southern by-pass roads around its urban area. Thus, the model is used to find a solution for these two by-pass routes. In addition, we want to propose how current road-planning practices in this community could be improved and used in future projects.

The applied model produced 4 different by-pass road alignments, based on four types of preference: economic, environmental, social and equal. When compared, the social road by-pass alignment was shown to be the most optimal. This is because protecting agricultural land within the Tlokweng Planning Area is a primary concern. Thus, the social solution will bring many benefits to the area’s inhabitants.

Finally, we wish to underline the importance of including different stakeholders throughout the entire process. In our investigation, we offer a set of solutions in which stakeholders were excluded. However, it is possible to use the model to obtain further solutions, which could be dependent on the preferences of others included during the entire road-planning process. Therefore, the proposed method could make the entire road-planning process more transparent as the opinions of others are both heard and considered, for example, the opinions of the public and those living in the by-pass area. This is important to keep in mind, because a good road-planning process should not bring benefits to only one group of people, but rather an entire community.

• author: Sekulic, Milan
• supervisor: Ali Mansourian; Ante Siljeg; Branko Cavric
• organization: Dept of Physical Geography and Ecosystem Science
• course: GISM01 20191
• year: 2019
• type: H2 - Master's Degree (Two Years)
• subject: Earth and Environmental Sciences
• keywords: GIS, Multi-criteria analysis, DEFINITE, Sensitivity Analysis, Python, AHP, Least-cost path, Dijkstra’s algorithm, ArcPy, Geography, model, road alignment
• publication/series: Master Thesis in Geographical Information Science
• report number: 102
• language: English
• additional info: External supervisors: Ante Siljeg, University of Zadar, Croatia and Branko Cavric, University of Botswana
• id: 8979335
• date added to LUP: 2019-06-04 13:45:46
• date last changed: 2019-06-04 13:45:46