How can you perform "Data Interpolation" in ArcGIS Pro?

Data interpolation in ArcGIS Pro involves estimating unknown values at certain locations based on known values from surrounding areas. This process is crucial for various applications, such as environmental modeling, resource management, and geographic mapping.

Using tools like Kriging or Inverse Distance Weighting is a sophisticated and standardized approach to perform interpolation. Kriging is a geostatistical method that not only considers the distance between known data points but also factors in their spatial correlations, providing a more statistically robust estimate of values in areas without measurement. Inverse Distance Weighting, on the other hand, is a simpler, yet effective technique that gives more weight to nearby known values than to those further away, essentially averaging the influence of surrounding data points to estimate the unknown values.

These methods are built into ArcGIS Pro and are designed to generate surface models based on the spatial distribution of points. They leverage the mathematical principles of interpolation to create smooth and continuous spatial data, which can be visualized and analyzed further.

The other choices, such as manually estimating data values or conducting statistical sampling, do not utilize the structured and systematic approach that established interpolation techniques provide. Similarly, comparing similar datasets doesn't involve generating estimations based on spatial relationships but rather focuses on making assessments between existing datasets. Therefore, employing