## 3 Results  
### Land Use-Land Cover (LULC) Classification and Accuracy Assessment  
The spatiotemporal distribution of different LULC features, namely Vegetation, Mining, Water body, and Others, is presented in Figure 3a-d for the study years 1990, 2000, 2010, and 2020, respectively. Before analyzing and assessing the LULC transformation, it was essential to evaluate the accuracy of classified LULC maps. The confusion matrix table (Table 2) revealed that the LULC maps were classified with considerable classification accuracy, wherein the overall classification accuracy was observed as \(\sim\)94%, 95%, 93.50%, and 95.50% for the years 1990, 2000, 2010, and 2020, respectively. The kappa coefficient for these years was found to be 0.92, 0.93, 0.91, and 0.94, respectively. Besides, the user'saccuracy of mining and vegetation class was found considerable for further use (84-90% for mining and 94-96% for vegetation). The details of the accuracy assessment using the confusion matrix are provided in Table 2.  
The LULC maps of the Rajmahal Hills during 1990-2020 showed that vegetation coverage significantly decreased (Figure 3). On the other hand, a significant increment in the mining area was noted (zoomed regions in Figure 3). Especially from 2010-2020, a drastic rise in the mining areas was seen, which caused a loss in vegetation cover over the Rajmahal Hills. The top northern, eastern, western, and lower regions of the Rajmahal Hills were found to have notable stone and coal mining clusters (Figure 3, Zoomed regions). Before 2000, the stone mining patches were less, while they remarkably increased in the last two decades (from 2010), as shown in Figure 3 (Z1, Z2, Z4, Z5).  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{6}{c}{Year—1990} \\ \hline LULC Classes & Waterbody & Mining & Vegetation & Others & Total & User’s Accuracy \\ \hline Waterbody & 49 & 0 & 0 & 1 & 50 & 98 \\ Mining & 0 & 43 & 1 & 6 & 50 & 86 \\ Vegetation & 0 & 0 & 48 & 2 & 50 & 96 \\ Others & 0 & 2 & 0 & 48 & 50 & 96 \\ Total & 49 & 45 & 49 & 57 & 200 & \\ Producers accuracy & 100 & 95.56 & 97.95 & 84.21 & & \\ \hline Overall accuracy & & & & & & 94 \\ \hline \hline \multicolumn{6}{c}{Year—2000} \\ \hline LULC classes & Waterbody & Mining & Vegetation & Others & Total & User’s accuracy \\ \hline Waterbody & 49 & 0 & 0 & 1 & 50 & 98 \\ Mining & 0 & 44 & 1 & 5 & 50 & 88 \\ Vegetation & 0 & 0 & 47 & 3 & 50 & 94 \\ Others & 0 & 0 & 0 & 50 & 50 & 100 \\ Total & 49 & 44 & 48 & 59 & 200 & \\ Producers accuracy & 100 & 100 & 97.92 & 84.75 & & \\ \hline \hline \multicolumn{6}{c}{Overall accuracy} \\ \hline \hline \multicolumn{6}{c}{Year—2010} \\ \hline LULC classes & Waterbody & Mining & Vegetation & Others & Total & User’s accuracy \\ \hline Waterbody & 48 & 0 & 1 & 1 & 50 & 96 \\ Mining & 0 & 42 & 1 & 7 & 50 & 84 \\ Vegetation & 0 & 0 & 47 & 3 & 50 & 94 \\ Others & 0 & 0 & 0 & 50 & 50 & 100 \\ Total & 48 & 42 & 49 & 61 & 200 & \\ Producers accuracy & 100 & 100 & 96 & 81.96 & & \\ \hline \multicolumn{6}{c}{Overall accuracy} \\ \hline \hline \multicolumn{6}{c}{Year—2020} \\ \hline LULC classes & Waterbody & Mining & Vegetation & Others & Total & User’s accuracy \\ \hline Waterbody & 50 & 0 & 0 & 0 & 50 & 100 \\ Mining & 0 & 45 & 0 & 5 & 50 & 90 \\ Vegetation & 0 & 0 & 48 & 2 & 50 & 96 \\ Others & 0 & 0 & 2 & 48 & 50 & 96 \\ Total & 50 & 45 & 50 & 55 & 200 & \\ Producers accuracy & 100 & 100 & 96 & 87.27 & & \\ \hline \multicolumn{6}{c}{Overall accuracy} \\ \hline \hline \end{tabular}
\end{table}
Table 2: Confusion matrix of classified LULC maps at 10 years interval. User’s accuracy, producer’s accuracy, and overall accuracy are in percentage (%).