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Renewable energy (RE) installations and civil works are beneficial in terms of sustainability, but a considerable amount of space in the landscape is required in order to harness this energy. In contemporary environmental theory the landscape is considered an environmental parameter and the transformation of the landscape by RE works has received increasing attention by the scientific community and affected societies. This research develops a novel computational stochastic tool the 2D Climacogram (2D-C) that allows the analysis and comparison of images of landscapes, both original and transformed by RE works. This is achieved by a variability characterization of the grayscale intensity of 2D images. A benchmark analysis is performed for art paintings in order to evaluate the properties of the 2D-C for image analysis, and the change in variability among images. Extensive applications are performed for landscapes transformed by RE works. Results show that the 2D-C is able to quantify the changes in variability of the image features, which may prove useful in the landscape impact assessment of large-scale engineering works.

Modern organized societies require robust infrastructures, among which hydraulic projects, such as water supply and drainage systems, are most important, particularly in water-scarce areas. Athens is a unique example because it is a big city (population 3.7 million) located in a very dry area. In order to support the development of the city, large hydraulic projects had to be constructed during its history and, as a result, Athens currently has one of the largest water supply systems in the world. Could Athenians choose smaller scale infrastructures instead? Analyzing social, technical and economical historical data, we can see that large capital investments were required. In order to evaluate these investments this paper presents a technical summary of the development. An economic analysis displays historical values of these investments in present monetary values. The cost of existing infrastructure is compared to the cost of constructing smaller reservoirs and a model is created to correlate the price of water and the cost of water storage with the size of reservoirs. In particular, if more and smaller reservoirs were built instead of the large existing ones, the cost of the water would significantly increase, as illustrated by modelling the cost using local data.

<p>Wind turbines are large-scale engineering infrastructures that may cause significant social reactions, due to the anticipated aesthetic nuisance. On the other hand, aesthetics is a highly subjective issue, thus any attempt towards its quantification requires accounting for the uncertainty induced from subjectivity. In this work, taking as example the Aegean island of Tinos, Cyclades, Greece, we present a stochastic-based methodology for evaluating the feasibility of developing wind parks in terms of their aesthetic impacts. At first, a field analysis is been conducted along with photographic surveying, 3D representation and the opinion of the target population regarding the development of wind parks across the island. Subsequently, the landscape transformations that will be caused from the wind turbines are assessed according to the theory of aesthetics, which are depicted by using suitable spatial analysis tools in GIS environment. The 3D representation images along with the maps are finally assessed through stochastic analysis, in order to quantify the visual impacts to the landscape and the nuisance to local community.</p>

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Even though landscape quality is largely a subjective issue, the integration of infrastructure into landscapes has been identified as a key element of sustainability. In a spatial planning context, the landscape impacts that are generated by infrastructures are commonly quantified through visibility analysis. In this study, we develop a new method of visibility analysis and apply it in a case study of a reservoir (Plastiras dam in Greece). The methodology combines common visibility analysis with a stochastic tool for visual-impacts evaluation; points that generate high visual contrasts in landscapes are considered Focus Points (FPs) and their clustering in landscapes is analyzed trying to answer two questions: (1) How does the clustering of Focus Points (FPs) impact the aesthetic value of the landscape? (2) How can the visual impacts of these FPs be evaluated? Visual clustering is calculated utilizing a stochastic analysis of generated Zones of Theoretical Visibility. Based on the results, we argue that if the visual effect of groups of FPs is positive, then the optimal sitting of FPs should be in the direction of faint clustering, whereas if the effect is negative, the optimal sitting of FPs should be directed to intense clustering. In order to optimize the landscape integration of infrastructure, this method could be a useful analytical tool for environmental impact assessment or a monitoring tool for a project’s managing authorities. This is demonstrated through the case study of Plastiras’ reservoir, where the clustering of positively perceived FPs is found to be an overlooked attribute of its perception as a highly sustainable infrastructure project.

<p>This research uses a stochastic computational tool (2D-C) for characterizing images in order to examine similarities and differences among artworks. 2D-C is measures the degree of variability (change in variability vs. scale) in images using stochastic analysis.</p><p>Apparently, beauty is not easy to quantify, even with stochastic measures. The meaning of beauty is linked to the evolution of human civilization and the analysis of the connection between the observer and the beauty (art, nature) has always been of high interest in both philosophy and science. Even though this analysis has mostly been considered part of the so-called social studies and humanities, mathematicians have also been involved. Mathematicians are generally not specialized to contribute, through their expertise, in sociopolitical analysis of messages and motivations of art but have been consistently applying mathematical knowledge, which is their expertise, in trying to explain aesthetics. In most of these analyses, the question at hand is if what is pleasing to the eye or not can be explained though mathematics.</p><p>Historically, it is known that from the time of the ancient Egyptian civilization a mathematic rule of the analogies of human body as models of beauty had been developed, and later in ancient Greece, the mathematicians Pythagoras and Euclid were the first known to have searched for a common rule (canon) existing in shapes that are perceived as beautiful. Euclid's Elements (c. 300 BC), for example, contains the first known definition of the “golden ratio”.</p><p>The opinions of later philosophers on this pursuit of mathematicians in the analysis of aesthetics were more varied. Leibniz, for example, believed that there is a norm behind every aesthetic feeling which we simply don’t know how to measure. On the contrary, Descartes supports that instead of regarding the aesthetic quality as an inherent quality of a physical object, the distinction of mind and nature have allowed humans to incorporate their own subjective feelings in determining their aesthetic preferences.</p><p>Thus many artists knew and apply math and geometry in their artwork, many philosophers tried to connect math and arts. Hence, it might be interesting to examine art work through a stochastic view. Stochastic analyses of the examined artworks are presented using climacograms and through stochastic evaluation with 2D-C we try to quantify some aspects of the artists’ expression. </p>