Stochastic Evaluation of Landscapes Transformed by Renewable Energy Installations and Civil Works

G.-Fivos Sargentis, Panayiotis Dimitriadis, Romanos Ioannidis, Theano Iliopoulou and Demetris Koutsoyiannis
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G.-Fivos Sargentis: School of Civil Engineering, Laboratory of Hydrology and Water Resources Development, National Technical University of Athens, Heroon Polytechneiou 9, Zographou 157 80, Greece
Panayiotis Dimitriadis: School of Civil Engineering, Laboratory of Hydrology and Water Resources Development, National Technical University of Athens, Heroon Polytechneiou 9, Zographou 157 80, Greece
Romanos Ioannidis: School of Civil Engineering, Laboratory of Hydrology and Water Resources Development, National Technical University of Athens, Heroon Polytechneiou 9, Zographou 157 80, Greece
Theano Iliopoulou: School of Civil Engineering, Laboratory of Hydrology and Water Resources Development, National Technical University of Athens, Heroon Polytechneiou 9, Zographou 157 80, Greece
Demetris Koutsoyiannis: School of Civil Engineering, Laboratory of Hydrology and Water Resources Development, National Technical University of Athens, Heroon Polytechneiou 9, Zographou 157 80, Greece

Energies, 2019, vol. 12, issue 14, 1-13

Abstract: 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.

Keywords: renewable energy; stochastic analysis of images; landscapes transformation; landscape visual impact assessment; optimizing landscape architecture (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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