期刊
FORESTS
卷 13, 期 4, 页码 -出版社
MDPI
DOI: 10.3390/f13040524
关键词
miombo forest; auxiliary data; road planning; spatial multi-criteria decision-making; analytical hierarchy process; miombo forest management
类别
资金
- Faculty of Forestry and Wood Sciences of the Czech University of Life Sciences in Prague (ZU Prague)
- Southern African Science Centre for Climate Change and Adaptive Land Management (SASSCAL)
This study focuses on the optimization of the existing road network in Huambo province, Angola, using analytic hierarchy process (AHP) and geographic information systems (GIS). The road suitability maps were developed based on various factors, such as flow accumulation, soil type, and geology. The findings suggest that these factors significantly impact road construction. The study provides important insights for planning road networks in Angola and lays the foundation for further research in developing a spatial decision support system (SDSS).
Angola's forests are abundant and highly productive with enormous potential to support local needs and exportation. The forests are well distributed across the country, but the existing road network is generally poor and, in some cases, inappropriate. Based on our previous work examining deforestation patterns and the modeling of primary tree attributes of vegetation types, we proposed forest management zones (MZ) for future planning in Huambo province in Angola. Herein, that same framework is applied for the detection of the existing road network in Huambo and the proposal of alternative routes inside the MZ. We used analytic hierarchy process (AHP) and geographic information systems (GIS) to optimize connectivity among the existing forest plantations and their distance to the closest major cities within the province. We developed road suitability maps based on AHP and GIS to ensure safer driving conditions and contribute to the forest planner's access to the current plantations. According to the suitability map created, 59.51% of the total area is suitable for road development and is counted in classes 4 and 5 in automatic classification. Parameters such as geology, slope, distance from roads to the railway, soil types, elevation, flow accumulation, and aspect were used. We provide a completed assessment of the state of existing roads and evaluate the safety of the observed road sections based on the AHP method. The calculated weights of the factors were all consistent with the model used (consistency ratio was 0.09 < 0.1). Finally, we proposed the best alternative routes to the existing cities, MZ in miombo woodlands, and forest plantations inside the province. Our findings indicated that flow accumulation, soil type, and geology were the most significant factors impacting road construction. Overall, our framework is an important starting point for further research activities towards developing a spatial decision support system (SDSS) for planning road networks in Angola.
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