**5. Hot spot mapping**

A hot spot map was produced to demonstrate locations with high, moderate, and low potentials for installing an EV charging station for the study area (**Figure 4**). High suitable areas were highlighted in red on the map. The areas have an index demand score of 50 or greater, and contain the highest mixture of input demand factors. These are driving public frequently visited areas and are ideal for installing EV charging

stations. Downtown business districts, shopping districts, employment hubs, public facilities, health care centers, park and ride lots, parking garages, and major roads and intersections, attractions, recreational areas etc., are all hot spots for EV charging stations. The yellow areas represented moderate suitable areas. This class displayed an uneven mixture of input demand factors. Moderate demand areas are secondary choices for charging station when prime areas cannot be located in surrounding areas.

**Figure 4.** *Optimal locations to install EV charging stations.*


*Using Geospatial Analysis to Assist with Clean Vehicle Infrastructure DOI: http://dx.doi.org/10.5772/intechopen.110864*

#### **Table 3.**

*Influence of the demand factors.*

Examples are small business parks near larger residential neighborhoods, and areas that are seeing population and employment growth. Low suitability areas were colored green, where showed a low mixture of influential factors and surrounded by low suitability factors such as residential neighborhoods, open space, and agricultural areas.

The multi-factor modeling system developed in this research classifies the hierarchical importance of each input demand factor, and identifies suitability of locations for installing EV charging stations. The ranking for each input demand factor was tested against the total number of input grids. The testing showed that the majority of the input demand factors had an average influential percentage of 80%, as listed in **Table 3**, indicating the model's ability to produce reliable results [29].
