Research Article Intuitionistic Fuzzy Hamacher Generalized Shapley Choquet Integral Operators Based Decision-Making Model for Feature Extraction and Automatic Material Classification in Mining Area Using Satellite Data Seema Khanum , 1 M. Gunasekaran , 2 S. V. Rajiga , 1 A. Firos , 3 and Kafui Tsoeke Agbevanu 4 1 Department of Computer Science, Government Arts College, Salem 636007, India 2 Department of Computer Science, Government Arts College, Dharmapuri 636705, India 3 Department of Computer Science and Engineering, Rajiv Gandhi University, Doimukh 791112, India 4 Department of Computer Science, Ho Technical University, P. O. Box HP 217, Ho, Ghana Correspondence should be addressed to A. Firos; firosabd@gmail.com and Kafui Tsoeke Agbevanu; kagbevanu@htu.edu.gh Received 24 March 2022; Revised 19 April 2022; Accepted 22 April 2022; Published 30 May 2022 Academic Editor: Samson Jerold Samuel Chelladurai Copyright © 2022 Seema Khanum et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. e normal methods for monitoring environmental pollution with image data have many false positives. erefore, this study is proposing a single-valued neutrosophic set (SVNS) (a variant of NS)-based method as a decision-making model using intui- tionistic fuzzy Hamacher generalized Shapley Choquet integral operators for feature extraction and automatic material clas- sification in mining area using satellite data. e experimental results show that this decision-making model using intuitionistic fuzzy Hamacher generalized Shapley Choquet integral operators for feature extraction and automatic material classification can better predict the presence of four heavy metals, i.e., vanadium(V), iron (Fe), copper (Cu), and nickel (Ni) in the study area than other methods. For vanadium metal, the determination accuracies, namely, producer accuracy, user accuracy, overall accuracy, and Kappa were 94.5%, 94.1%, 93.88%, and 0.93%, respectively. It was found that the estimated results and the distribution trend of heavy metals are almost the same as in actual ground measurements. 1. Introduction e environmental pollution due to heavy metal mining is increasing day by day [1]. Geological Survey of India data say that India is consuming 4% of vanadium produced in the world, that is, about 85000 metric tons. In this arena, China is the largest player, who consumes 44% of this metal and they are producing 57% of globe’s vanadium. e vanadium metal is noted for its toxicity [25]. e symptoms associated with vanadium poisoning are cough with spu- tum, wheezing, sore throat, headache, and rhinitis. e studies have shown that vanadate acts directly on the smooth muscle of the bronchi. It promotes the release of Ca 2+ in the cells by a mechanism involving the production of inositol triphosphate and inhibition of ATPase [6]. Vanadium has “insulin-like” action [7, 8], and this effect explains the observed hypoglycemia. In remote sensing technology, we acquire information or data about the Earth’s surface without actually being in contact with it [9]. e best example of remote sensing are our eyes. Human beings observe many things through the eyes without touching these things. However, our eyes are not sensitive to all parts of the electromagnetic spectrum. Our eyes are only sensitive to the visible part of the elec- tromagnetic spectrum. erefore, we as humans use a very small window of the electromagnetic spectrum. But there are some animals and birds which are more sensitive in other parts of the electromagnetic spectrum. For instance, the mammal bat has got a different kind of remote sensing technology. at means, it sends the echo pulses and records Hindawi Advances in Materials Science and Engineering Volume 2022, Article ID 2890996, 15 pages https://doi.org/10.1155/2022/2890996