A historical and future impact assessment of mining activities on surface biophysical characteristics change: A remote sensing-based approach. (March 2021)

• Record Type: Journal Article
• Authors: Firozjaei, Mohammad Karimi; Sedighi, Amir; Firozjaei, Hamzeh Karimi; Kiavarz, Majid; Homaee, Mehdi; Arsanjani, Jamal Jokar; Makki, Mohsen; Naimi, Babak; Alavipanah, Seyed Kazem
• Is Part Of: Ecological indicators. Volume 122(2021)
• Publication Date: 2021-03
• Subjects: Mining -- LULC change -- Forest -- LST -- NDVI -- Earth observation -- CA-Markov; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2020.107264
• Languages: English
• ISSNs: 1470-160X

Abstract

Highlights: A new method was used for impact assessment of mining activities on environment change. A remote sensing-based approach was used to predict the LST and NDVI maps. We applied our method on five mine over worldwide. The forest cover was reduced due to the increasing mining activities. A significant and negative impact of the mine activities will continue in future. Abstract: Mining activities and associated actions cause land-use/land-cover (LULC) changes across the world. The objective of this study were to evaluate the historical impacts of mining activities on surface biophysical characteristics, and for the first time, to predict the future changes in pattern of vegetation cover and land surface temperature (LST). In terms of the utilized data, satellite images of Landsat, and meteorological data of Sungun mine in Iran, Athabasca oil sands in Canada, Singrauli coalfield in India and Hambach mine in Germany, were used over the period of 1989–2019. In the first step, the spectral bands of Landsat images were employed to extract historical LULC changes in the study areas based on the homogeneity distance classification algorithm (HDCA). Thereafter, a CA-Markov model was used to predict the future of LULC changes based on the historical changes. In addition, LST and vegetation cover maps were calculated using the single channel algorithm, and the normalized difference vegetation index (NDVI), respectively. In the second step, the trends of LST and NDVI variations in different LULC change types and over different time periods were investigated. Finally, a CA-Markov model was used to predict the LST and NDVI maps and the trend of their variations in future. The results indicated that the forest and green space cover was reduced from 9.95 in 1989 to 5.9 Km 2 in 2019 for Sungun mine, from 42.14 in 1999 to 33.09 Km 2 in 2019 for Athabasca oil sands, from 231.46 in 1996 to 263.95 Km 2 in 2016 for Singrauli coalfield, and from 180.38 in 1989 to 133.99 Km 2 in 2017 for Hambach mine, as a result of expansion and development of of mineral activities. Our findings about Sungun revealed that the areal coverage of forest and green space will decrease to 15% of the total study area by 2039, resulting in reduction of the mean NDVI by almost 0.06 and increase of mean standardized LST from 0.52 in 2019 to 0.61 in 2039. our results further indicate that for Athabasca oil sands (Singrauli coalfield, Hambach mine), the mean values of standardized LST and NDVI will change from 0.5 (0.44 and 0.4) and 0.38 (0.38, 0.35) in 2019 (2016, 2017) to 0.57 (0.5, 0.47) and 0.33 (0.32, 0.28), in 2039 (2036, 2035), respectively. This can be mainly attributed to the increasing mining activities in the past as well as future years. The discussion and conclusions presented in this study can be of interest to local planners, policy makers, and environmentalists in order to observe the damages brought to the environment and the society in a larger picture.