Explain how interpolation is sensitive to input sample data, such as when data points are missing, or insufficiently dense.
Gridding is the act of taking a field of measurements and discretizing it into a regular tessellation, often either a lattice of squares or hexagons. Gridding can either discretize continuous phenomena or aggregate discrete instances; in either case, gridding serves conceptually to assist analysis, for example in finding local minima or maxima (i.e., "hotspots"). The process of gridding often involves interpolation, which is the rational estimation of unknown data values within the bounds of known values. Contouring refers to the creation of isolines throughout a data surface, often one represented by a grid. This section describes gridding, interpolation, and contouring, highlighting a few example methods by which interpolation is frequently done in the geospatial analysis.