Guidance: Spatial analysis originated from the quantitative revolution in geography and regional science during the 1960s. In its early stages, it primarily involved applying quantitative (mainly statistical) methods to analyze spatial distribution patterns of points, lines, and areas. Later, greater emphasis was placed on the characteristics of geographic space itself, spatial decision-making processes, and the spatio-temporal evolution of complex spatial systems. In reality, since the advent of maps, people have consistently engaged in various forms of spatial analysis, whether consciously or unconsciously. For example, measuring distances, directions, and areas of geographic features on maps, or even using maps for tactical analysis and strategic decision-making, are all instances of spatial analysis conducted by people. The latter, in particular, represents a higher level of spatial analysis.
GIS integrates the latest multi-disciplinary technologies, such as relational database management, efficient graphics algorithms, interpolation, zoning and network analysis, providing powerful tools for spatial analysis, making advanced spatial analysis tasks difficult and complex in the past. Most GIS software currently has spatial analysis capabilities. Spatial analysis has long been one of the core functions of geographic information systems, which unique extraction, representation and transmission functions of geographic information (especially implicit information) are the main functional features of GIS that are different from general information systems.
Spatial analysis is a collective term for techniques related to analyzing spatial data. Depending on the nature of the data involved, it can be divided into: (1) analytical operations based on spatial graphical data; (2) data operations based on non-spatial attributes; and (3) integrated operations combining both spatial and non-spatial data.
The foundation of spatial analysis relies on geospatial databases, employing various mathematical methods including geometric and logical operations, statistical analysis, and algebraic computations. The ultimate objectives are to address practical problems related to geographic spaces encountered by people, extract and communicate geospatial information, particularly implicit information to support decision-making.
This chapter introduces the fundamental functions of spatial analysis in GIS, including spatial query and measurement, buffer analysis, overlay analysis, network analysis, spatial interpolation, statistical classification analysis, etc. It also describes the associated algorithms and their computational formulas.