To calculate the overall image classification accuracy, we use the following formula:
\[
\text{Overall Accuracy} = \frac{\text{Sum of the diagonal elements}}{\text{Sum of all elements}} \times 100.
\]
From the error matrix:
\[
\begin{array}{|c|c|c|c|c|}
\hline
\text{Thematic Map Classes} & \text{SOIL} & \text{WATER} & \text{CROP} & \text{Total}
\hline
\text{Ground Truth Classes} & \text{SOIL} & 40 & 1 & 4 & 45
\text{WATER} & 7 & 25 & 3 & 35
\text{CROP} & 1 & 2 & 17 & 20
\hline
\text{Total} & 48 & 28 & 24 & 100
\hline
\end{array}
\]
The diagonal elements are 40 (SOIL), 25 (WATER), and 17 (CROP). The sum of these diagonal elements is:
\[
\text{Sum of diagonal elements} = 40 + 25 + 17 = 82.
\]
The total number of elements in the matrix is:
\[
\text{Sum of all elements} = 48 + 28 + 24 = 100.
\]
Thus, the overall accuracy is:
\[
\text{Overall Accuracy} = \frac{82}{100} \times 100 = 82%.
\]
Hence, the overall classification accuracy is 82.