# An Online Multicriteria--Spatial Decision Support System for Public Services Planning
## 3 Requirements and Methodology
### Concept and Methods  
In the following, we present a decision process valid for the application, which integrates most elements of the framework for MCDA according to [PERSON] [12] (shown in Figure 2). Due to the complexity of the MCDA process for a user, the online tool handles the elements in separate steps. In the illustration, we have added the steps in which the frame elements are edited in the online tool (user interface in Section 4). In Figure 3, we describe the process from the user's perspective (blue) and refer to the analysis process that takes place in the backend (yellow). In order to meet the aforementioned user requirements and offer a high degree of flexibility in parameterisation, we need a clear and standardised process in the user interface and a methodical/analytical process flow in the backend of our application. To offer an appealing user interface that fulfils our technical requirements, we have chosen the MasterPortal [37] as a platform. It is a responsive and modular application based on Vue.js, which already contains OpenLayers for map functions. It mainly provides functionalities for map integration, but additional components for more complex custom implementations are also possible. Figure 1: Schematic representation distance decay with the planner’s parameter decision (**right**) and the exemplary effect in space (**left**) for a given infrastructure (blue dot). The distance in the supply status can be set individually. In the following, we explain the analysis process step by step and the corresponding parameterisation by the user in a slightly simplified manner. We also name the used methods and describe the technical components:  
After the user has received introductory information in _step 1_, the user defines the analysis area in _step 2_. This is used to clip the _population grid_ to the area of interest. In _step 3_, the user selects the infrastructure types relevant for the analysis purposes via a checkbox for each infrastructure type. The following _step 4_ allows for selection of the specific _population age groups_ to be considered. On the one hand, this can be the entire population. However, it is also possible to consider only selected age groups. This expands the analysis options as, for example, only the younger age groups can be considered when evaluating the supply situation for early childhood education, while the older age groups could be taken into account for the supply analysis of geriatric infrastructure. In the background, the desired age groups are used according to the user selection from the population grid and, if necessary, summed. _Step 5_: The criteria map is created at this point. Thanks to the user's individual parameterisations, it contains the spatial weighting [17]. Simplified: According to the definition by the user, distant locations are less important for the supply. The innovation here is that the user themselves decides how and where the threshold values for this run. We use the midvalue method introduced by [38] as a stepwise distance decay function. The user defines which threshold values apply for accessibility in order to map the supply situation for each infrastructure. These _travel-time parameters_ provide the basis for the  
Figure 2: Framework for spatial MCDA (according to [12]). For an overview, the framework elements are linked with the corresponding process steps of the workflow of our online tool. distance-decay calculations_ over a street network dataset. The calculation is performed by an instance of the _open-route service_ (ORS). This is a freely available software for routing and catchment area calculation by the Heidelberg Institute for Geoinformation Technology [39]. The following basic data and input parameters are required to calculate the _distance decay_: The _infrastructure locations_ for the types selected in step 3, a _network dataset_ for routing between the given infrastructure locations, and the _populations grid_ cells from step 2 and 4 (calculate distances and catchment areas).