# Assessing Ecosystem and Urban Services for Landscape Suitability Mapping
## 4 Conclusions
The elevation at which each species typically live was also considered to define each species' potential habitat better. Then, a buffer of 5 km around the potential service benefiting area was built [55] to select the landscape areas where the service can benefit the residents. The potential habitat areas of each edible species were selected between the many land uses included in the buffer. The service indicator was calculated as the sum of the species potentially present in each point of the study area. As nine edible species were assessed, the indicator value varies between 0 and 9. * Building density: It is used as an indicator for provisioning of nutrition goods, namely groundwater and surface water availability for drinking purposes (115 grdrin, 116 surdrin) and energy from fossil fuels (134 netener). This indicator can be considered a meaningful proxy of the quantity of these services, as, in Italy, they are associated by law with the construction of new buildings. The radius used for the Kernel Density Estimation is 200 m, which is the distance from the electricity cabin at which a typical local electricity service asks for a supplementary payment. It is calculated as follows: \(\bigcirc\) Data collection: a municipal database was used to extract buildings, their covered areas, and their number of floors; \(\bigcirc\) Calculation: Kernel density estimation (KDE) of the total floor area of buildings, obtained by multiplying the number of floors of a building by the building dimension. * Easiness of wells digging: It is used as an indicator of the service: provisioning of groundwater for the non-drinking purpose (intended as material for different production uses) (122 grnodrin). The indicator was calculated as follows: \(\bigcirc\) Data collection: A database from local public authorities reporting the wells registered across the territory was collected. This database also includes the wells' depth; \(\bigcirc\) Calculation: inverse distance weighting was applied to the difference between the maximum depth of a well (conventionally defined as 50 m) and the actual well depth. * Average water yield from rivers and water reservoirs was calculated to quantify the provisioning of surface water for non-drinking purposes (123 surndorin). The service was spatialized based on the following empirical observations: (1) a total amount of 2% of the average river flow can be used for industrial and agricultural uses; (2) about 40% of the total volume of reservoirs is available yearly. The indicator was calculated as follows: \(\bigcirc\) Data collection: a database of the water reservoirs, indicating the water volume capacity, and a database of the rivers and streams, indicating the average flow rate, were collected from local public authorities; \(\bigcirc\) Calculation: River flow rates and water reservoir volumes were multiplied by the percentages of availability observed empirically, resulting in the calculation of the average daily water availability. This value was distributed on a 50 m buffer area around each watercourse or reservoir. * Coppices: It has been used to estimate the provision of plant-based resources for energy (131 planres). The indicator was calculated as follows: \(\bigcirc\) Data collection: The forest map of Umbria was used as a dataset for the estimation of this indicator. It categorizes the forests with many attributes, such as accessibility of each forested land, which were assessed in the forest map, mainly based on slope; \(\bigcirc\) Calculation: the intensity of the service delivery was based on the levels of forest accessibility defined by the map: 1 = not sufficient, 2 = low, 3 = good. * Energy plants powered by livestock manure. It was used to map the provision of animal-based resources for energy (132 animres).