IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i5p2015-d329109.html
   My bibliography  Save this article

Assessment of Land Reclamation Benefits in Mining Areas Using Fuzzy Comprehensive Evaluation

Author

Listed:
  • Xueyi Yu

    (School of Energy Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
    Key Laboratory of Western Mine Exploitation and Hazard Prevention with the Ministry of Education, Xi’an University of Science and Technology, Xi’an 710054, China)

  • Chi Mu

    (School of Energy Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
    Key Laboratory of Western Mine Exploitation and Hazard Prevention with the Ministry of Education, Xi’an University of Science and Technology, Xi’an 710054, China
    Shaanxi Provincial Land Engineering Construction Group, Xi’an 710054, China)

  • Dongdong Zhang

    (School of Energy Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
    Key Laboratory of Western Mine Exploitation and Hazard Prevention with the Ministry of Education, Xi’an University of Science and Technology, Xi’an 710054, China
    Shaanxi Provincial Land Engineering Construction Group, Xi’an 710054, China)

Abstract

Land reclamation plays a vital role in the ecological improvement and economic development of mining regions. This study aims to conduct a preliminary discussion on the evaluation content, evaluation methods, and evaluation indicators of land reclamation benefits in mining areas. Using fuzzy comprehensive evaluation (FCE) method, land reclamation was assessed. After compiling a model of the land reclamation influencing factors, an evaluation index of land reclamation benefit in the mining area was constructed using the land reclamation monitoring data for the northern part of the mining area over the last decade. In addition, an expert scoring method and a traditional evaluation model were used to estimate the comprehensive benefits of land reclamation at Hanjiawan coal mine in Shendong mining area. Land reclamation markedly improved the land type within the mining region and decreased the amount of damaged land, including subsided and occupied land. Moreover, land reclamation improved the available land area such as agricultural and construction land. The proposed model obtained an overall 63% increase in the land reclamation area. Different degrees of ecological, economic, and social benefits of Hanjiawan coal mine were observed; however, the ecological benefits were the most significant, with a growth rate of 56%. Based on the evaluation criteria, all benefits of the mining area after reclamation were good. Over time, land reclamation will offer greater comprehensive benefits to the mining area. Furthermore, this method can be used for precise evaluation of comprehensive benefits after land reclamation, and the assessment results will provide a reference basis for sustainable development of the mining area.

Suggested Citation

  • Xueyi Yu & Chi Mu & Dongdong Zhang, 2020. "Assessment of Land Reclamation Benefits in Mining Areas Using Fuzzy Comprehensive Evaluation," Sustainability, MDPI, vol. 12(5), pages 1-20, March.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:5:p:2015-:d:329109
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/5/2015/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/12/5/2015/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Enjun Ma & Xiangzheng Deng & Qian Zhang & Anping Liu, 2014. "Spatial Variation of Surface Energy Fluxes Due to Land Use Changes across China," Energies, MDPI, vol. 7(4), pages 1-13, April.
    2. Nicola, Francesca de & De Pace, Pierangelo & Hernandez, Manuel A., 2016. "Co-movement of major energy, agricultural, and food commodity price returns: A time-series assessment," Energy Economics, Elsevier, vol. 57(C), pages 28-41.
    3. Lima, Ana T. & Mitchell, Kristen & O’Connell, David W. & Verhoeven, Jos & Van Cappellen, Philippe, 2016. "The legacy of surface mining: Remediation, restoration, reclamation and rehabilitation," Environmental Science & Policy, Elsevier, vol. 66(C), pages 227-233.
    4. Huiru Zhao & Nana Li, 2016. "Optimal Siting of Charging Stations for Electric Vehicles Based on Fuzzy Delphi and Hybrid Multi-Criteria Decision Making Approaches from an Extended Sustainability Perspective," Energies, MDPI, vol. 9(4), pages 1-22, April.
    5. Dongjing Xu & Suping Peng & Shiyao Xiang & Yunlan He, 2017. "A Novel Caving Model of Overburden Strata Movement Induced by Coal Mining," Energies, MDPI, vol. 10(4), pages 1-13, April.
    6. Ji, Qiang & Bouri, Elie & Roubaud, David & Shahzad, Syed Jawad Hussain, 2018. "Risk spillover between energy and agricultural commodity markets: A dependence-switching CoVaR-copula model," Energy Economics, Elsevier, vol. 75(C), pages 14-27.
    7. Qingxiang Huang & Yanpeng He & Jian Cao, 2019. "Experimental Investigation on Crack Development Characteristics in Shallow Coal Seam Mining in China," Energies, MDPI, vol. 12(7), pages 1-16, April.
    8. Xiaoli Hu & Ling Lu & Xin Li & Jianhua Wang & Xuegang Lu, 2015. "Ejin Oasis Land Use and Vegetation Change between 2000 and 2011: The Role of the Ecological Water Diversion Project," Energies, MDPI, vol. 8(7), pages 1-18, July.
    9. Yong-Zhi Chang & Suo-Cheng Dong, 2016. "Evaluation of Sustainable Development of Resources-Based Cities in Shanxi Province Based on Unascertained Measure," Sustainability, MDPI, vol. 8(6), pages 1-18, June.
    10. Xiangzheng Deng & Chunhong Zhao & Yingzhi Lin & Tao Zhang & Yi Qu & Fan Zhang & Zhan Wang & Feng Wu, 2014. "Downscaling the Impacts of Large-Scale LUCC on Surface Temperature along with IPCC RCPs: A Global Perspective," Energies, MDPI, vol. 7(4), pages 1-20, April.
    11. Wei Zhang & Dong-Sheng Zhang & Li-Xin Wu & Hong-Zhi Wang, 2014. "On-Site Radon Detection of Mining-induced Fractures from Overlying Strata to the Surface: A Case Study of the Baoshan Coal Mine in China," Energies, MDPI, vol. 7(12), pages 1-25, December.
    12. Yu Zhang & Xiaojiao Zou & Caifen Xu & Qingshan Yang, 2018. "Decoupling Greenhouse Gas Emissions from Crop Production: A Case Study in the Heilongjiang Land Reclamation Area, China," Energies, MDPI, vol. 11(6), pages 1-13, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fan Wang & Yao Lu & Jin Li & Juan Ni, 2021. "Evaluating Environmentally Sustainable Development Based on the PSR Framework and Variable Weigh Analytic Hierarchy Process," IJERPH, MDPI, vol. 18(6), pages 1-16, March.
    2. Rui Zhao & Kening Wu & Xiaoliang Li & Nan Gao & Mingming Yu, 2021. "Discussion on the Unified Survey and Evaluation of Cultivated Land Quality at County Scale for China’s 3rd National Land Survey: A Case Study of Wen County, Henan Province," Sustainability, MDPI, vol. 13(5), pages 1-26, February.
    3. Pratiwi & Budi H. Narendra & Chairil A. Siregar & Maman Turjaman & Asep Hidayat & Henti H. Rachmat & Budi Mulyanto & Suwardi & Iskandar & Rizki Maharani & Yaya Rayadin & Retno Prayudyaningsih & Tri Wi, 2021. "Managing and Reforesting Degraded Post-Mining Landscape in Indonesia: A Review," Land, MDPI, vol. 10(6), pages 1-29, June.
    4. Chenyang Wu & Yichen Zhang & Jiquan Zhang & Yanan Chen & Chenyu Duan & Jiawei Qi & Zhongshuai Cheng & Zengkai Pan, 2022. "Comprehensive Evaluation of the Eco-Geological Environment in the Concentrated Mining Area of Mineral Resources," Sustainability, MDPI, vol. 14(11), pages 1-19, June.
    5. Xi Lu & Jiaqing Lu & Xinzheng Yang & Xumei Chen, 2022. "Assessment of Urban Mobility via a Pressure-State-Response (PSR) Model with the IVIF-AHP and FCE Methods: A Case Study of Beijing, China," Sustainability, MDPI, vol. 14(5), pages 1-23, March.
    6. Baoquan Cheng & Jianchang Li & Jingfang Tao & Jianling Huang & Huihua Chen, 2023. "Assessing the Land Reclamation Suitability of Beam Fabrication and Storage Yard in Railway Construction: An AHP-MEA Method," IJERPH, MDPI, vol. 20(5), pages 1-20, February.
    7. Amirshenava, Sina & Osanloo, Morteza, 2022. "Strategic planning of post-mining land uses: A semi-quantitative approach based on the SWOT analysis and IE matrix," Resources Policy, Elsevier, vol. 76(C).
    8. Yao, Yue & Sun, Deqiang & Xu, Jin-Hua & Wang, Bin & Peng, Guohong & Sun, Bingmei, 2023. "Evaluation of enhanced oil recovery methods for mature continental heavy oil fields in China based on geology, technology and sustainability criteria," Energy, Elsevier, vol. 278(PB).
    9. Hui Zou & Xiaohua Ma, 2021. "Identifying resource and environmental carrying capacity in the Yangtze River Economic Belt, China: the perspectives of spatial differences and sustainable development," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(10), pages 14775-14798, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yip, Pick Schen & Brooks, Robert & Do, Hung Xuan & Nguyen, Duc Khuong, 2020. "Dynamic volatility spillover effects between oil and agricultural products," International Review of Financial Analysis, Elsevier, vol. 69(C).
    2. Le, Trung H. & Pham, Linh & Do, Hung X., 2023. "Price risk transmissions in the water-energy-food nexus: Impacts of climate risks and portfolio implications," Energy Economics, Elsevier, vol. 124(C).
    3. Chen, Peng & He, Limin & Yang, Xuan, 2021. "On interdependence structure of China's commodity market," Resources Policy, Elsevier, vol. 74(C).
    4. Caporin, Massimiliano & Naeem, Muhammad Abubakr & Arif, Muhammad & Hasan, Mudassar & Vo, Xuan Vinh & Hussain Shahzad, Syed Jawad, 2021. "Asymmetric and time-frequency spillovers among commodities using high-frequency data," Resources Policy, Elsevier, vol. 70(C).
    5. Sun, Yunpeng & Gao, Pengpeng & Raza, Syed Ali & Shah, Nida & Sharif, Arshian, 2023. "The asymmetric effects of oil price shocks on the world food prices: Fresh evidence from quantile-on-quantile regression approach," Energy, Elsevier, vol. 270(C).
    6. Khalfaoui, Rabeh & Baumöhl, Eduard & Sarwar, Suleman & Výrost, Tomáš, 2021. "Connectedness between energy and nonenergy commodity markets: Evidence from quantile coherency networks," Resources Policy, Elsevier, vol. 74(C).
    7. Morelli, Giacomo, 2023. "Stochastic ordering of systemic risk in commodity markets," Energy Economics, Elsevier, vol. 117(C).
    8. Xinyu Yuan & Jiechen Tang & Wing-Keung Wong & Songsak Sriboonchitta, 2020. "Modeling Co-Movement among Different Agricultural Commodity Markets: A Copula-GARCH Approach," Sustainability, MDPI, vol. 12(1), pages 1-17, January.
    9. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Adewuyi, Adeolu O. & Lee, Chien-Chiang, 2022. "Quantile risk spillovers between energy and agricultural commodity markets: Evidence from pre and during COVID-19 outbreak," Energy Economics, Elsevier, vol. 113(C).
    10. Hardik A. Marfatia & Qiang Ji & Jiawen Luo, 2022. "Forecasting the volatility of agricultural commodity futures: The role of co‐volatility and oil volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 383-404, March.
    11. Eissa, Mohamad Abdelaziz & Al Refai, Hisham, 2019. "Modelling the symmetric and asymmetric relationships between oil prices and those of corn, barley, and rapeseed oil," Resources Policy, Elsevier, vol. 64(C).
    12. Raza, Syed Ali & Guesmi, Khaled & Belaid, Fateh & Shah, Nida, 2022. "Time-frequency causality and connectedness between oil price shocks and the world food prices," Research in International Business and Finance, Elsevier, vol. 62(C).
    13. Satish Kumar & Aviral Kumar Tiwari & I. D. Raheem & Qiang Ji, 2020. "Dependence risk analysis in energy, agricultural and precious metals commodities: a pair vine copula approach," Applied Economics, Taylor & Francis Journals, vol. 52(28), pages 3055-3072, June.
    14. Liu, Chang & Sun, Xiaolei & Wang, Jun & Li, Jianping & Chen, Jianming, 2021. "Multiscale information transmission between commodity markets: An EMD-Based transfer entropy network," Research in International Business and Finance, Elsevier, vol. 55(C).
    15. Albulescu, Claudiu Tiberiu & Tiwari, Aviral Kumar & Ji, Qiang, 2020. "Copula-based local dependence among energy, agriculture and metal commodities markets," Energy, Elsevier, vol. 202(C).
    16. Khalfaoui, Rabeh & Shahzad, Umer & Ghaemi Asl, Mahdi & Ben Jabeur, Sami, 2023. "Investigating the spillovers between energy, food, and agricultural commodity markets: New insights from the quantile coherency approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 63-80.
    17. Karel Janda & Ladislav Kristoufek, 2019. "The relationship between fuel and food prices: Methods, outcomes, and lessons for commodity price risk management," CAMA Working Papers 2019-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    18. Shahzad, Farrukh & Bouri, Elie & Mokni, Khaled & Ajmi, Ahdi Noomen, 2021. "Energy, agriculture, and precious metals: Evidence from time-varying Granger causal relationships for both return and volatility," Resources Policy, Elsevier, vol. 74(C).
    19. Rangan Gupta & Christian Pierdzioch, 2024. "Multi-Task Forecasting of the Realized Volatilities of Agricultural Commodity Prices," Working Papers 202423, University of Pretoria, Department of Economics.
    20. Luo, Jiawen & Ji, Qiang, 2018. "High-frequency volatility connectedness between the US crude oil market and China's agricultural commodity markets," Energy Economics, Elsevier, vol. 76(C), pages 424-438.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:12:y:2020:i:5:p:2015-:d:329109. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.