Monitoring land use and land cover change near a nuclear power plant construction site: Akkuyu case, Turkey

被引:0
作者
Muzaffer Can Iban
Ezgi Sahin
机构
[1] Mersin University,Department of Geomatics Engineering
[2] Mersin University,Department of Geographic Information Systems and Remote Sensing
来源
Environmental Monitoring and Assessment | 2022年 / 194卷
关键词
Google earth engine; Land use land cover; Nuclear power plants; Random forest; Remote sensing;
D O I
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中图分类号
学科分类号
摘要
Land use and land cover (LULC) change analysis of the construction site and its surroundings of the Akkuyu Nuclear Power Plant project in southern Turkey was undertaken in this case study, which was supported by remotely sensed Landsat 8 image composites. The composite images compiled in 2017 and 2021 were prepared on the Google Earth Engine platform. The Random Forest algorithm was used as the classifier model. A high classification performance was obtained for both images (kappa > 0.88, overall accuracy > 90%). After the classification process, LULC maps for both years were generated, and statistical calculations for the LULC change were computed for both the entire study area (15 × 25 km) and a buffer zone with a radius of 1 km around the power plant. In the whole study area, artificial surfaces significantly increased (78.46%), whereas forests (− 8.31%) and barren lands experienced a considerable decrease (− 6.11%). In the 1 km buffer, artificial surfaces predominantly increased (113.94%), while forests and barren lands decreased dramatically (− 69.13% and − 74.28%, respectively). The agricultural areas in the study area were changed into other LULC classes: 9.1% to artificial surfaces, 27.6% to barren lands, and 21.7% to forest. The rise in the area of artificial surfaces was especially noticeable within the 1 km buffer zone: construction activities converted 36.1% of agricultural fields, 54.1% of forests, and 23.2% of barren lands into artificial surfaces. The filling activities on the seashore resulted in a loss of water bodies of up to 26.5%. The study provides an overview of how the LULC classes have evolved on the construction site and in the region. In the end, the study discusses how the current land use preferences in the region contradict the issues and concerns mentioned in the existing body of literature.
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  • [61] Yazdi AM(2018)The acquisition of impervious surface area from LANDSAT 8 satellite sensor data using urban indices: A comparative analysis Environmental Monitoring and Assessment 153 337-undefined
  • [62] Alimohammadi A(2015)Satellite-based detection of evacuation-induced land cover changes following the Fukushima Daiichi nuclear disaster Remote Sensing Letters 70 989-undefined
  • [63] Ekmekçioglu M(2009)Monitoring the changing position of coastlines using aerial and satellite image data: An example from the eastern coast of Trabzon Turkey. Environmental Monitoring and Assessment 5 61-undefined
  • [64] Can Kutlu A(2012)Comparison of support vector machine, neural network, and CART algorithms for the land-cover classification using limited training data points ISPRS Journal of Photogrammetry and Remote Sensing 197 639-undefined
  • [65] Kahraman C(2017)Exploring Google Earth Engine platform for big data processing: Classification of multi-temporal satellite imagery for crop mapping Frontiers in Earth Science 81 152-undefined
  • [66] Erdoğan M(2021)Bird rookery nutrient over-enrichment as a potential accelerant of mangrove cay decline in Belize Oecologia 10 3776-undefined
  • [67] Kaya İ(2002)Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages Remote Sensing of Environment 25 236-undefined
  • [68] Fallati L(1989)Digital change detection techniques using remotely-sensed data International Journal of Remote Sensing 560 5-undefined
  • [69] Savini A(1997)Monitoring the impact of coal mining and thermal power industry on land use pattern in and around Singrauli Coalfield using remote sensing data and GIS Journal of the Indian Society of Remote Sensing 164 20666-undefined
  • [70] Sterlacchini S(2018)Global land change from 1982 to 2016 Nature 12 1871-undefined