@ARTICLE{Hao_Ruihua_Suitability_2022,
 author={Hao, Ruihua and Zhang, Zizhao and Guo, Xiaoli and Huang, Xuebang and Guo, Zezhou and Liu, Tianchao},
 volume={vol. 38},
 number={No 2},
 journal={Gospodarka Surowcami Mineralnymi - Mineral Resources Management},
 pages={131-145},
 howpublished={online},
 year={2022},
 publisher={Komitet Zrównoważonej Gospodarki Surowcami Mineralnymi PAN},
 publisher={Instytut Gospodarki Surowcami Mineralnymi i Energią PAN},
 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.},
 type={Article},
 title={Suitability evaluation model for the land reclamation of coal mines in the northern foot of tianshan mountain, Xinjiang},
 URL={http://www.czasopisma.pan.pl/Content/123717/PDF-MASTER/Hao%20i%20inni.pdf},
 doi={10.24425/gsm.2022.141669},
 keywords={land reclamation, Bayes discriminant analysis, cold and arid region, suitability level, indexes},
}