The best method of interpolation of contours is computation.

Interpolation of contours is a technique used to estimate the values of points within a given set of contour lines. It is commonly used in various fields such as geography, geology, and engineering to create smooth and continuous representations of spatial data.

There are several methods of interpolation, including estimation, graphical means, and computation. Let's discuss each method in detail to understand why computation is considered the best.

1. Estimation:
- Estimation involves making educated guesses or approximations based on available data.
- While estimation can be useful in some cases, it may not provide accurate results, especially when dealing with complex data or irregularly spaced contour lines.
- Estimation is subjective and depends on the individual's judgment, which can lead to inconsistencies and inaccuracies.

2. Graphical means:
- Graphical means involve visually interpreting contour lines and manually drawing additional lines to fill in the gaps.
- This method can be time-consuming and prone to human errors.
- It may also be difficult to determine the exact values of points between contour lines, resulting in a less precise representation of the data.

3. Computation:
- Computation involves using mathematical algorithms to calculate the values of points within the given set of contour lines.
- This method utilizes the available data points and applies interpolation techniques, such as linear or polynomial interpolation, to estimate values at intermediate points.
- Computation provides a more accurate and objective approach to interpolate contours since it is based on mathematical calculations rather than subjective judgments.
- It can handle complex datasets and irregularly spaced contour lines more effectively, resulting in smoother and more reliable representations of the data.

In conclusion, while estimation and graphical means have their uses, computation is considered the best method of interpolation for contours due to its accuracy, objectivity, and ability to handle complex datasets.