Natural Hazard Susceptibility Assessment for Road Planning Using Spatial Multi-Criteria Analysis

Abstract

Inadequate infrastructural networks can be detrimental to society if transport between locations becomes hindered or delayed, especially due to natural hazards which are difficult to control. Thus determining natural hazard susceptible areas and incorporating them in the initial planning process, may reduce infrastructural damages in the long run. The objective of this study was to evaluate the usefulness of expert judgments for assessing natural hazard susceptibility through a spatial multi-criteria analysis approach using hydrological, geological, and land use factors. To utilize spatial multi-criteria analysis for decision support, an analytic hierarchy process was adopted where expert judgments were evaluated individually and in an aggregated manner. The estimates of susceptible areas were then compared with the methods weighted linear combination using equal weights and factor interaction method. Results showed that inundation received the highest susceptibility. Using expert judgment showed to perform almost the same as equal weighting where the difference in susceptibility between the two for inundation was around 4%. The results also showed that downscaling could negatively affect the susceptibility assessment and be highly misleading. Susceptibility assessment through spatial multi-criteria analysis is useful for decision support in early road planning despite its limitation to the selection and use of decision rules and criteria. A natural hazard spatial multi-criteria analysis could be used to indicate areas where more investigations need to be undertaken from a natural hazard point of view, and to identify areas thought to have higher susceptibility along existing roads where mitigation measures could be targeted after in-situ investigations.

GIS-Based Site Selection for Check Dams in Watersheds: Considering Geomorphometric and Topo-Hydrological Factors

“…Such characteristic factors may include slope, terrain ruggedness index (TRI), topographic position index (TPI), drainage density (DD), stream order (SO), stream power index (SPI), topographic wetness index (TWI), and sediment transport index (STI). However, carrying out this process with commercial software for multi-criteria decision analysis (MCDA) and GIS may still be resource and time consuming [31] and, most importantly, not readily evaluated in terms of efficiency and accuracy of site selection results (e.g., [23,24]).…”

A Method for Urban Flood Risk Assessment and Zoning Considering Road Environments and Terrain

“…Good traffic conditions are key to promoting economic growth [7], thus traffic delays and road network damage caused by urban flooding have a serious impact on society [2]. The traffic capacity and service levels of roads vary in cities, and roads also suffer different kinds of damage by floods.…”

“…The traffic capacity and service levels of roads vary in cities, and roads also suffer different kinds of damage by floods. Therefore, it is important to identify the risk points of road networks in flood risk assessment [7,22].…”

“…Meanwhile, impervious surfaces, which are largely adopted in urban areas, have made cities suffer severely in flood disasters [6]. As a kind of impervious surface, roads are not only important infrastructures of cities, but also key elements contributing to the urban economy [7]. However, roads are extremely vulnerable to floods, and damaged road sections have a huge impact on cities [2,8].…”

Landslide susceptibility mapping of SE Serbia using GIS

“…There is numerous methods for landslide susceptibility analysis such as fuzzy logic (SAboYA et al, 2006), analytic hierarchy process (AHP), analytic network process (YALCIn, 2008), weighted linear combination (AYALEW et al, 2004), logistic regression (AkGun & buLuT, 2007) and multivariate statistical approach (vAn WESTEn et al, 1997). many researches use AHP for comparing the factors (kARLSSon et al, 2017;mAnSouRI DAnESHvAR, 2014;AYALEW et al, 2005;PELLICAnI et al, 2014;mA et al, 2013;PouR -GHASEmI et al, 2012) because it is simple decision making method. In Serbia there are a few examples of use AHP for susceptibility (mARIjAnovIć et al, 2013) and for landfill site selection (DjokAnovIć et al, 2016).…”