ORIGINAL PAPER
Suitability evaluation model for the land reclamation of coal mines in the northern foot of tianshan mountain, Xinjiang
1
Xinjiang University
2
School of Geological and Mining Engineering, Xinjiang University, Urumqi, Xinjiang, China
3
State Key Laboratory for Geomechanics and Deep Underground Engineering, Xinjiang University, Urumqi, Xinjiang, China
4
Xinjiang Intelligent Check for Security Environmental Protection Technology Co., Ltd, Urumqi, Xinjiang, China
5
The first regional geological survey brigade, Xinjiang Bureau of Geo-Exploration & Mineral Development , 466 North Tianjin road, Urumqi, Xinjiang, China
Submission date: 2022-05-01
Final revision date: 2022-06-11
Acceptance date: 2022-06-19
Publication date: 2022-06-28
Corresponding author
Zizhao Zhang
School of Geological and Mining Engineering, Xinjiang University, Urumqi, Xinjiang, China
School of Geological and Mining Engineering, Xinjiang University, Urumqi, Xinjiang, China
Gospodarka Surowcami Mineralnymi – Mineral Resources Management 2022;38(2):131-145
KEYWORDS
TOPICS
ABSTRACT
The ecological environment is significantly vulnerable to coal-mining activities in western China due to the cold and arid climate. The evaluation of land reclamation is therefore a key process that has to be known for the sustainable use of coal resources. A Bayes discriminant analysis method to evaluate the suitability level of land reclamation for coal mine lands in cold and arid regions of western China is presented. Ten factors influencing the suitability of land reclamation were selected as discriminant indexes in the suitability analysis. The data of eighty-four land reclamation units from sixteen coal-mining areas was used as training samples to develop a discriminant analysis model to evaluate the suitability level of land reclamation. The results show that the discriminant analysis model has high precision and the misdiscriminant ratio is 0.02 in the resubstitution process. The suitability levels of land reclamation for eleven sites in two coal mine lands were evaluated by using the model and the evaluation results are identical with that of the practical situation. Our method and findings are significant for decision makers in similar regions who want to prepare for possible strategies for land reclamation in the future.
METADATA IN OTHER LANGUAGES:
Polish
Model oceny przydatności do rekultywacji terenu kopalń węgla kamiennego w północnym podnóżu góry Tianshan, Xinjiang
rekultywacja gruntów, analiza dyskryminacyjna Bayesa, region zimny i suchy, poziom przydatności, indeksy
Środowisko ekologiczne jest bardzo wrażliwe na działalność wydobywczą węgla w zachodnich Chinach z powodu zimnego i suchego klimatu. Ocena rekultywacji gruntów jest zatem kluczowym procesem, który powinien być znany dla zrównoważonego wykorzystania zasobów węgla. W artykule przedstawiono metodę analizy dyskryminacyjnej Bayesa do oceny stopnia jej przydatności w rekultywacji gruntów kopalni węgla w zimnych i suchych regionach zachodnich Chin. Jako wskaźniki dyskryminacyjne w analizie przydatności wybrano dziesięć czynników wpływających na przydatność rekultywacji terenu. Dane z osiemdziesięciu czterech jednostek melioracyjnych z szesnastu obszarów górniczych wykorzystano jako próbki szkoleniowe do opracowania modelu analizy dyskryminacyjnej w celu oceny stopnia przydatności do rekultywacji terenu. Wyniki pokazują, że model analizy dyskryminacyjnej jest wysoko precyzyjny, a współczynnik błędnej dyskryminacji wynosi 0,02 w procesie resubstytucji. Poziomy przydatności rekultywacji dla jedenastu miejsc na dwóch terenach kopalni węgla zostały ocenione za pomocą modelu, a wyniki oceny są identyczne jak w praktyce. Model BDA ma wysoką precyzję i może być stosowany w praktyce inżynierskiej. W porównaniu z innymi metodami predykcji model BDA ma stabilną strukturę, a proces dyskryminacyjny jest prosty i wygodny. Jest to wstępna próba zastosowania teorii analizy dyskryminacyjnej Bayesa do oceny poziomu jej przydatności w rekultywacji gruntów, w szczególności w zachodnich Chinach, dla obszarów kopalń węgla. Wypracowania metoda i wyniki są istotne dla decydentów w podobnych regionach, którzy chcą przygotować się do możliwych strategii rekultywacji gruntów w przyszłości.
REFERENCES (40)
1.
Amiri, F. and Shariff, A.R.B.M. 2012. Application of geographic information systems in land-use suitability evaluation for beekeeping: A case study of Vahregan watershed (Iran). African Journal of Agricultural Research 7(1), pp. 89–97.
2.
Amirshenava, S. and Osanloo, M. 2022. Strategic planning of post-mining land uses: A semi-quantitative approach based on the SWOT analysis and IE matrix. Resources Policy 76, DOI: 10.1016/j.resourpol.2022.102585.
3.
Bagheri et al. 2013 – Bagheri, M., Sulaiman, W.N.A. and Vaghefi, N. 2013. Application of geographic information system technique and analytical hierarchy process model for land-use suitability analysis on coastal area. Journal of Coastal Conservation 17(1), pp. 1–10, DOI: 10.1007/s11852-012-0213-4.
4.
Cengiz, T. and Akbulak, C. 2009. Application of analytical hierarchy process and geographic information systems in land-use suitability evaluation: a case study of Dümrek village (Çanakkale, Turkey). International Journal of Sustainable Development & World Ecology 16(44), pp. 286–294, DOI: 10.1080/13504500903106634.
5.
Chen et al. 2020 – Chen, L., Yu, L., Ou, J.C., Zhou, Y.B., Wei, J.W. and Wang, F. 2020. Prediction of coal and gas outburst risk at driving working face based on Bayes discriminant analysis model. Earthquakes & Structures 18(1), pp. 73–82, DOI: 10.12989/eas.2020.18.1.073.
6.
Chen et al. 2015 – Chen, L.M., Stehouwer, R., Tong, X.G., Kost, D., Bigham, J.M. and Dick, W.A. 2015. Surface coal mine land reclamation using a dry flue gas desulfurization product: Short-term and long-term water responses. Chemosphere 134 , pp. 459–465, DOI: 10.1016/j.chemosphere.2015.05.014.
7.
Cheng et al. 2017 – Cheng, L.L., Hu, Z.Q. and Lou, S. 2017. Improved methods for fuzzy comprehensive evaluation of the reclamation suitability of abandoned mine lands. International Journal of Mining. Reclamation and Environment 31(3), pp. 212–229 (in Chinese).
8.
Du, H.Y. and Li, J. 2001. Agricultural land suitability evaluation. Model and system implementation-a case study of Panzhihua. Resources Science 5, pp. 41–45 (in Chinese).
9.
Dučinskas et al. 2012 – Dučinskas, K., Stabingien, L. and Stabingis, G. 2012. Application of Bayes linear discriminant functions in image classification. Pattern Recognition Letters 33(3), pp. 278–282, DOI: 10.1016/j.patrec.2011.10.020.
10.
Efthymia, N. and Panos, N. 2020. Sex estimation: a comparison of techniques based on binary logistic, probit and cumulative probit regression, linear and quadratic discriminant analysis, neural networks, and nave Bayes classification using ordinal variables. International journal of legal medicine 134(3), pp. 1213–1225, DOI: 10.1007/s00414-019-02148-4.
11.
Elaalem et al. 2011 – Elaalem, M., Comber, A. and Fisher, P. 2011. A comparison of fuzzy AHP and ideal point methods for evaluating land suitability. Transactions in Gis 3, pp. 329–346, DOI: 10.1111/j.1467-9671.2011.01260.x.
12.
Fang et al. 2012 – Fang, D.C., Liu, G.L., Wang, F. and Zhang, L.P. 2012. The Research on the GIS-based land suitability evaluation model (LSEM). Geomatics & Spatial Information Technology 1, pp. 35–36 (in Chinese).
13.
Gustavo de Araújo Carvalho et al. 2019 – Gustavo de Araújo Carvalho, Minnett, P.J., Paes, E.T., de Miranda, F.P. and Landau, L. 2019. Oil-Slick Category Discrimination (Seeps vs. Spills): A Linear Discriminant Analysis Using RADARSAT-2 Backscatter Coefficients in Campeche Bay (Gulf of Mexico). Remote Sensing 11(14), pp. 1652, DOI: 10.3390/rs11141652.
14.
Hamsici, O.C. and Martinez, A.M. 2008. Bayes optimality in linear discriminant analysis. IEEE Transactions on Pattern Analysis & Machine Intelligence 30(4), pp. 647–657, DOI: 10.1109/TPAMI.2007.70717.
15.
Ioannis et al. 2017 – Ioannis, P., Michael, G., Christos, R. and Francis, P. 2017. Selection of optimal land uses for the reclamation of surface mines by using evolutionary algorithms. International Journal of Mining Science and Technology 27(3), pp. 491–498, DOI: 10.1016/j.ijmst.2017.03.008.
16.
Irhamah et al. 2019 – Irhamah, I., Rahimatin, S.M., Kuswanto, H. and Wulandari, L. 2019. Classification of pneumonia patients risk using hybrid genetic algorithm-discriminant analysis and Nave Bayes. Journal of Theoretical and Applied Information Technology 97(6), pp. 1845–1855.
17.
Jafari, S. and Zaredar, N. 2010. Land suitability analysis using multi attribute decision making approach. International journal of environmental science and development 1(5), pp. 441–445, DOI: 10.7763/IJESD.2010.V1.85.
18.
Kalogirou, S. 2002. Expert systems and GIS: an application of land suitability evaluation. Computers, environment and urban systems 26(2), pp. 89–112, DOI: 10.1016/S0198-9715(01)00031-X.
19.
Kim et al. 2012 – Kim, S.M., Choi, Y., Suh, J., Oh, S., Park, H.D., Yoon, S.H. and Go, W.R. 2012. ArcMine: a GIS extension to support mine reclamation planning. Computers and Geosciences 46, pp. 84–95, DOI: 10.1016/j.cageo.2012.04.007.
20.
Kim et al. 2015 – Kim, S.M., Suh, J., Oh, S., Son, J., Hyun, C.U., Park, H.D., Shin, S.H. and Choi, Y. 2015. Assessing and prioritizing environmental hazards associated with abandoned mines in Gangwon-do, South Korea: the Total Mine Hazards Index. Environmental Earth Sciences 75(5), pp. 1–14, DOI: 10.1007/s12665-016-5283-4.
21.
Kubit et al. 2015 – Kubit, O.E., Pluhar, C.J. and DeGraff, J.V. 2015. A model for prioritizing sites and reclamation methods at abandoned mines. Environmental Earth Sciences 73(12), pp. 7915–7931, DOI: 10.1007/s12665-014-3949-3.
22.
Lottermoser et al. 2009 – Lottermoser, B.G., Munksgaard, N.C. and Daniell, M. 2009. Trace Element Uptake by Mitchell Grasses Grown on Mine Wastes, Cannington Ag-Pb-Zn Mine, Australia: Implications for Mined Land Reclamation. Water Air and Soil Pollution 203(1–4), pp. 243–259, DOI: 10.1007/s11270-009-0007-y.
23.
Moosavirad, SM. and Behnia, B. 2017. Suitability evaluation for land reclamation in mining areas: Gol-e-Gohar Iron Ore Mine of Sirjan, Kerman, Iran. International Journal of Mining, Reclamation & Environment 31(1), pp. 38–51, DOI: 10.1080/17480930.2015.1105650.
24.
Pereira, J.M. and Duckstein, L. 1993. A multiple criteria decision-making approach to GIS-based land suitability evaluation International Journal of Geographical Information Systems 7(5), pp. 407–424, DOI: 10.1080/02693799308901971.
25.
Reshmidevi et al. 2009 – Reshmidevi, T.V., Eldho, T.I. and Jana, R. 2009. A GIS-integrated fuzzy rule-based inference system for land suitability evaluation in agricultural watersheds. Agricultural systems 101(1), pp. 101–109, DOI: 10.1016/j.agsy.2009.04.001.
26.
Shi, D. 2013. Land reclamation suitability evaluation based on the limit method. Sustainable Development Of Urban Infrastructure 253–255, pp. 1–3.
27.
TD/T 1007-2003 Standards of surveying and evaluating reserved land resource for cultivation. Beijing: Ministry of Land and Resources of the People’s Republic of China.
28.
TD/T 1031-2011 Regulation on compiling land reclamation plan. Beijing: Ministry of Land and Resources of the People’s Republic of China.
29.
TD/T 1036-2013 Completion standards on land reclamation quality. Beijing: Ministry of Land and Resources of the People’s Republic of China.
30.
Tian et al. 2012 – Tian, X.S., Zhou, C.R., Zheng, J.B. and Tan, X.L. 2014. Research on suitability evaluation of the gas temporary land based on the index method. Environmental Engineering 32(s1), pp. 856–859 (in Chinese).
31.
Wang et al. 2015 – Wang, G.L., Zhang, W.C., Song, K.S., Hu, Q.F. and Luo, H.C. 2015. Suitability evaluation for land reclamation in coal mining subsidence area based on extenics. Chinese Journal of Underground Space & Engineering 11(1), pp. 222–228 (in Chinese).
32.
Wang, LB. and Gu, GT. 2010. Multivate Statistical Analysis: Models, Case Study and Application of SPSS. Economic Science Press (in Chinese).
33.
Wang et al. 2012 – Wang, S.D., Guo, Z., Chen, Q.J. and Zhang, H.B. 2012. Study and application of suitability evaluation of land reclamation based on comprehensive extreme condition method. J. Science of Surveying and Mapping 37(01), pp. 66–70 (in Chinese).
34.
Yang et al. 2012 – Yang, D.B., Zhang, W.X. and Yao, Q. 2012. Research of mining subsided land reclamation system based on GIS. Mechanical And Electronics Engineering III(10), pp. 130–134 (in Chinese).
35.
Yao, C. and Cheng, G. 2016. Approximative Bayes optimality linear discriminant analysis for Chinese handwriting character recognition. Neurocomputing 207(2), pp. 346–353, DOI: 10.1016/j.neucom.2016.05.017.
36.
Ye, B.Y. 2012. Integrating MCE with GIS for suitability evaluation of the reclamation land in Antaibao open pit coal mine. [In:] World Automation Congress (WAC), pp. 1–5.
37.
Yu et al. 2012 – Yu, H.L., Li, X.Q., Deng, C.X. and Lu, N. 2012. The reclaimed land suitability evaluation and reclamation mode of coal mine area in five mountains Mountain. Journal of Agriculture 2(06), pp.59–64+77 (in Chinese).
38.
Zhang, A. and Zhang, H.S. 2011. GIS-based coal mining land reclamation suitability evaluation assessment. 19th International Conference on Geoinformatics (Geoinformatics 2011) (in Chinese).
39.
Zhang et al. 2016 – Zhang, H.Y., Sun, T., Shao, D.D. and Yang, W. 2016. Fuzzy logic method for evaluating habitat suitability in an estuary affected by land reclamation. Wetlands 36(1), pp. 19–30 (in Chinese).
40.
Zhang, Q.J. and Lu, J.N. 2014. Suitability Evaluation on Land Reclamation in Hebei Fanshan Phosphate Mine. Advanced Materials Research, pp. 1291–1296 (in Chinese).
| eISSN: | 2299-2324 |
| ISSN: | 0860-0953 |
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
