Interpolation

Interpolation is a core spatial analysis technique used in Geographic Information Systems (GIS), remote sensing, and geospatial analysis to estimate values at locations where direct measurements are unavailable. It works by analyzing the spatial relationships among known data points and predicting values for unsampled areas based on the characteristics of nearby observations. The result is a continuous surface that accurately represents the distribution and variation of geographic phenomena such as elevation, temperature, rainfall, air quality, soil moisture, groundwater levels, and vegetation. Interpolation transforms scattered or discrete datasets into detailed and meaningful maps, making it easier to visualize spatial patterns, identify trends, and fill data gaps. It plays a vital role in environmental monitoring, agriculture, hydrology, meteorology, urban planning, disaster management, and natural resource management. By providing reliable estimates for unknown locations, interpolation supports informed decision-making, improves spatial analysis accuracy, and enables researchers and planners to better understand and manage geographic processes.