Optimising a landscape visual quality protocol. A Method for reducing respondent fatigue and obtaining site-specific indicators.

Evaluation of landscape visual quality is crucial for policymaking and planning but is still challenging. A wide range of visual assessment protocols is available, but there is still no consensus on appropriate indicators or approaches. Also, evaluation protocols can encompass many indicators, being exhaustive and complex and making the evaluation lengthy. Furthermore, protocols tend to be catered to a particular type of landscape or site-specific, and it can be tricky to ensure the protocol developed is adequate for the landscape under study. This paper proposes a methodology to optimise the selection of indicators for landscape visual assessments. There are two main goals: i) reduce the evaluation time to avoid respondent fatigue, and ii) make the protocol site-specific, choosing indicators that perform better and avoiding redundant indicators. •The presented method optimises the selection of indicators in expert visual assessments;•Indicators are rated in situ on a 5-point scale and go through a performance and redundancy test;•It helps to adapt complex evaluation protocols to the study landscape and to choose robust indicators in a supported and scientific way.

Application of electroencephalographic techniques to the study of visual impact of renewable energies.

Much is currently being studied on the negative visual impact associated to the installation of large wind turbines or photovoltaic farms. However, methodologies for quantitatively assessing landscape impact are scarce. In this work we used electroencephalographic (EEG) recordings to investigate the brain activity of 14 human volunteers when looking at the same landscapes with and without wind turbines, solar panels and nuclear power plants. Our results showed no significant differences for landscapes with solar power systems or without them, and the same happened for wind turbines, what was in agreement with their subjective scores. However, there were clear and significant differences when looking at landscapes with and without nuclear power plants. These differences were more pronounced around a time window of 376-407 msec and showed a clear right lateralization for the pictures containing nuclear power plants. Although more studies are still needed, these results suggest that EEG recordings can be a useful procedure for measuring visual impact.