## 2 Materials and Methods
### Description of the Proposed Decision-Support Tool
#### 2.2.1 GIS Geodatabase and Basic Criteria Definition  
The integrated collection of various types of data and geodata that is expertly organized in separate thematic layers and managed into a GIS geodatabase as a single cohesive unit constitutes an essential step in such complex spatial multi-criteria applications. This step enables seamless data retrieval and facilitates efficient decision-making processes. Shapefiles and GeoTIFF have been a popular source of data for GIS, while in cases where digital data is unavailable, existing analog maps are scanned and digitized. After collecting and storing the necessary geodata, an overlay analysis is conducted by combining the characteristics of the different geodata layers. Overlay analysis constitutes a spatial operation in which two or more different layers of geodata, which are registered to a common coordinate system, are superimposed to virtually represent the spatial relationships between features that occupy the same geographic space. This process results in a composite map, which is commonly used to find locations that are suitable for a particular use or are susceptible to some risk, and consequently, areas, patterns, and trends are effectively identified. It is noted that overlay analysis can be accomplished with any data type (raster or vector). In general, there are two methods for performing overlay analysis: feature overlay (overlaying points, lines, or polygons) and raster overlay. In the context of optimum routing, a feature overlay has been initially carried out to provide stakeholders and experts with a rapid and detailed digital overview of the area under consideration and empower them to make well-informed decisions. However, after converting all vector geodata into raster format, raster overlay analysis is utilized to derive the desired raster cost (i.e., weighted) surface, which is essential for the LCPA (i.e., routing analysis) to handle areas with multiple overlapping geohazards and other hazards. To ensure that the computational tool produces accurate and reliable results that can be used confidently in decision-making processes, the utilized geodata has been reclassified and resampled. Reclassification constitutes an attribute generalization technique provided by GIS software that can be applied to both vector and raster data. Specifically, during the reclassification process, the classes of a geodata layer change without altering its geometry, thereby allowing consistent comparisons and analysis across different datasets. In spatial multi-criteria applications, such as the one presented in the sequence, reclassification is crucial for the \"criteria standardization\" process, where each geodata layer is converted to a thematic layer. On the other hand, geodata resampling involves changing the spatial resolution of a raster dataset. Reprojecting an image to a different coordinate system is another important process that creates an image pixel grid on an alignment other than that of the original image. The value of each pixel in the new image must be computed by sampling or interpolating over a neighborhood of pixels from the corresponding position in the original image. Resampling and reprojecting geodata with different resolutions  
Figure 2: Flowchart describing the methodology of the proposed decision-support tool. and mapping projections to a common resolution and projection constitute essential steps before combining and analyzing raster datasets. Herein, all the utilized geodata has been resampled and reprojected to have a uniform spatial resolution and coordinate system, thus eliminating any potential biases or errors [55]. Selecting the optimal route of a CI in real case studies constitutes a demanding decision-making procedure that typically takes into account various design criteria based on the project requirements and constraints, such as budget, accessibility, and environmental issues.