# Visibility Assessment of New Photovoltaic Power Plants in Areas with Special Landscape Value
## 5 Conclusions  
The construction of new PV plants contributes to the reduction of CO2 emissions but does not have the support of all the parties involved. In areas that have a high landscape value or in tourist areas, this type of facility can be opposed by the population due to its visual impact. This work has presented a methodology, based on GIS, to determine the places where future PV facilities will have a greater or lesser visibility for a set of potential observers in movement, and its application to geographical areas with special landscape or cultural protection. The methodology is based on an objective measure: the accumulated perception time for all the potential observers. The perception that observers have of this type of facility is estimated by means of a variable called Accumulated Perception Time, \(APT_{i,k}\). This variable represents the cumulative value of the possible hours per year in which the proposed PV plant, located in cell \(i\), can be seen by observers travelling along all the observation points of route \(k\). In order to make a more appropriate assessment of observability, two factors have been included in the calculation of \(APT_{i,k}\): the factor \(fhw_{i,n}\), which considers the visible part of the PV facility placed in the cell \(i\), from observation point \(n\), and the skyline index, \(1 sk_{i,n}\), which takes into account the part of the facility that can be see above the horizon. This makes it possible to present a greater degree of visibility to facilities that can be seen partially or totally above the horizon. Figure 4: _GAPT_ map, in hours/year, of the study area. By calculating the values obtained for the \(APT_{i,k}\) variables of each route \(k\) in the area studied, the \(GAPT_{i}\) variable is evaluated. This variable represents the global cumulative value of hours per year in which the future PV plant, placed in the cell \(i\), can be seen by all observers travelling along all routes \(k\) in the area under study. It is possible to generate maps that graphically represent the value of the \(GAPT\) variable, by means of the use of GIS tools. With these maps, the agents involved in the construction of PV plants can easily identify those locations in the study area with lower \(GAPT\) values and which will therefore be more suitable for the installation of PV plants, based objectively on their observability. As a case study, we have applied this methodology to one of the most famous pilgrimage routes. Specifically, the study area is the section of the Way of Saint James that crosses the region of La Rioja in northern Spain. The observers that have been considered correspond to the pilgrims that walk along all routes of the Way in this region. The result is a raster dataset that represents the value of the \(GAPT\) variable, in which it is possible to identify those places which have lower values and which, therefore, will be more suitable for the installation of PV plants based on their low observability from the Way of Saint James. Some of the limitations of the proposed methodology, that will be addressed in future works, focus on the following issues:  
* A high computational effort is required to achieve detailed results. Each visibility analysis for different heights of the PV facility produces a raster map. * All the nodes of the routes have been considered as waypoints for the observers. In a more detailed analysis, a special treatment could be considered for some of these nodes corresponding to places on the Way of St. James where pilgrims usually stop on their way: viewpoints, fountains or rest areas. The \(APT_{i,n}\) value for these nodes should be proportional to the average stopping time of pilgrims at such locations. * The visual impact caused by glares from PV panels has not been taken into account. The methodology described here is easily applicable to different routes, observers with different characteristics, and photovoltaic facilities with different dimensions, etc.