# Assessing Ecosystem and Urban Services for Landscape Suitability Mapping
## 4 Conclusions  
This research developed an S-MCDA model, called SUSAM, for the spatial quantification of landscape suitability, intended as the landscape ability to provide services with common features as preferred by specific groups of stakeholders. This application showed that SUSAM could effectively produce a spatial index of suitability, highlighting areas with different provision degrees of a defined group of services, producing informative indicators for landscape policy makers. Figure 8: Average ratios between suitability indices of economic activities’ scenarios calculated using different weights for each landscape class (w9/w7: 9 on 7, w7/w5: 7 on 5, w5/w4: 5 on 3, w3/base: 3 on the baseline). (**A,B**): FARM scenario; (**C,D**): HOUS scenario; (**E,F**): COMM scenario. (**A,C,E**): supply-based suitability; (**B,D,F**): demand-based suitability; Descriptions of the landscape classes’ codes are reported in Table 1, scenarios’ codes in Table 2.  
The sensitivity analysis applied on SUSAM showed that the relative importance of services (services ranking) heavily influences the results, demonstrating that the method is highly sensitive to the change in scenarios, and therefore very helpful for supporting landscape analysis for policy making. The service relative weights only secondarily influence the results, especially if the weights used in the comparison are lower than seven. This evidence suggests an uncertainty reduction in the suitability assessment, since the weight can be more complex to define than the ranking of services. The service indicators' values are highly influential on the SUSAM results, meaning that the choice of the indicators and the methodology for their normalization should be carefully evaluated for an effective SUSAM application. The following are available online at [[https://www.mdpi.com/article/10.3390/app11178232/s1](https://www.mdpi.com/article/10.3390/app11178232/s1)]([https://www.mdpi.com/article/10.3390/app11178232/s1](https://www.mdpi.com/article/10.3390/app11178232/s1)), Table S1: SUSAM service list in MS Excel format, including the correspondent spatial indicators' details, and the service codes. Conceptualization, S.A., M.V. ; methodology S.A., M.V. ; investigation, S.A.; data curation, S.A.; writing--original draft preparation, S.A., M.V. ; writing--review and editing, S.A., M.V. ; visualization, S.A.; supervision, M.V. All authors have read and agreed to the published version of the manuscript. This research was developed within the framework of the Towards Rural Synergies and Trade-offs between Economic Development and Ecosystem Services (TRUSTEE) project funded by the RURAGRI ERA-NET Consortium (project number 235175), which includes the Italian Ministry of Agricultural, Food and Forestry Policies. Not applicable. Data Availability Statement: Data are available, upon any reasonable request, from the authors. The authors wish to thank [PERSON]. [PERSON] of the Environmental Geography Group, Institute for Environmental Studies, Vrije Universiteit Amsterdam, for her valuable collaboration during all the research steps. The authors declare no conflict of interest. Additional spatial indicators developed in this research for quantifying specific services or group of services (the indicator codes reported in Table S1 are indicated in parenthesis):  
* Habitat suitability for the most common edible species. It quantifies the provisioning of nutrition goods \"wild plants, algae and their outputs\" (112 wildpl) as suggested by [64]. The indicator was calculated as follows:  
* Data collection: Data from Global Biodiversity Information Facility (GBIF) database were collected for each edible plant and fungi species localized in the study area. Information about edible species was retrieved from actaplantarum.org (accessed on 15 April 2020). A geobotanic map was used as a database of the land use of the area;
* Calculation: The potential habitats of each different species were listed and, then, identified on the geobotanic map.