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

机译:由可再生能源装置和土建工程改造的景观的随机评估

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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.
机译:就可持续性而言,可再生能源(RE)装置和土建工程是有益的,但是为了利用这种能源,景观中需要大量空间。在当代环境理论中,景观被视为环境参数,可再生能源工程对景观的改造已引起科学界和受影响社会的越来越多的关注。这项研究开发了一种新颖的计算随机工具2D高程图(2D-C),该工具可以分析和比较由RE作品生成的原始图像和经过转换的景观图像。这是通过2D图像灰度强度的可变性表征来实现的。对艺术绘画进行基准分析,以便评估用于图像分析的2D-C的属性以及图像之间的可变性变化。对可再生能源工程改造后的景观进行了广泛的应用。结果表明2D-C能够量化图像特征变化的变化,这可能在大型工程工作的景观影响评估中很有用。

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