What is the primary purpose of surface interpolation in GIS?

The primary purpose of surface interpolation in GIS is to estimate values at unknown locations based on known values, which is precisely what the selected answer reflects. This technique involves using a set of data points with known values (e.g., elevation, temperature, or pollution levels) to create a continuous surface that predicts values at locations where no measurements exist.

Through various interpolation methods—such as inverse distance weighting, kriging, or spline—GIS can generate a smooth and coherent representation of spatial phenomena. This is particularly valuable in fields like meteorology, environmental science, and urban planning, where understanding gradients or changes across a landscape is crucial. In practice, surface interpolation allows GIS professionals to analyze trends, identify patterns, and make decisions based on derived data rather than just discrete measurements.

While options like creating new map layers, analyzing network efficiencies, or providing graphical representations of data involve aspects of GIS, these are not the fundamental aim of surface interpolation. Rather, they support different functionalities within the GIS ecosystem, illustrating the breadth of tools and methodologies used in geographic analysis.