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

Sargentis, G.-Fivos; Dimitriadis, Panayiotis; Ioannidis, Romanos; Iliopoulou, Theano; Koutsoyiannis, Demetris

doi:10.3390/en12142817

Submit to this Journal Review for this Journal Edit a Special Issue

Article Menu

...

Open AccessArticle

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

G.-Fivos Sargentis

Panayiotis Dimitriadis

Romanos Ioannidis

Theano Iliopoulou

and

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

Author to whom correspondence should be addressed.

Energies 2019, 12(14), 2817; https://doi.org/10.3390/en12142817

Received: 11 June 2019 / Revised: 4 July 2019 / Accepted: 14 July 2019 / Published: 22 July 2019

(This article belongs to the Section B: Energy and Environment)

View Full-Text Download PDF

Browse Figures

Citation Export

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. View Full-Text

Keywords: renewable energy; stochastic analysis of images; landscapes transformation; landscape visual impact assessment; optimizing landscape architecture

▼ Show Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Supplementary Material

Supplementary File 1:
PDF-Document (PDF, 1987 KiB)

Share and Cite

MDPI and ACS Style

Sargentis, G.-F.; Dimitriadis, P.; Ioannidis, R.; Iliopoulou, T.; Koutsoyiannis, D. Stochastic Evaluation of Landscapes Transformed by Renewable Energy Installations and Civil Works. Energies 2019, 12, 2817. https://doi.org/10.3390/en12142817

AMA Style

Sargentis G-F, Dimitriadis P, Ioannidis R, Iliopoulou T, Koutsoyiannis D. Stochastic Evaluation of Landscapes Transformed by Renewable Energy Installations and Civil Works. Energies. 2019; 12(14):2817. https://doi.org/10.3390/en12142817

Chicago/Turabian Style

Sargentis, G.-Fivos, Panayiotis Dimitriadis, Romanos Ioannidis, Theano Iliopoulou, and Demetris Koutsoyiannis. 2019. "Stochastic Evaluation of Landscapes Transformed by Renewable Energy Installations and Civil Works" Energies 12, no. 14: 2817. https://doi.org/10.3390/en12142817

Find Other Styles

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Metrics

Abstract views Pdf views Html views

Article Menu

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

Abstract

Supplementary Material

Share and Cite

Article Metrics

Article Access Statistics

Article Access Map by Country/Region

Further Information

Guidelines

MDPI Initiatives

Follow MDPI