In GIS, spatial analysis refers to the process of statistics, analysis and prediction of spatial data using GIS technology and spatial data. The following are common methods of spatial analysis in GIS:
1. Spatial query:
In GIS, spatial query is one of the most basic and commonly used spatial analysis methods. It retrieves data through spatial location and spatial relationships, such as searching for all points, lines, or polygons within an area, or finding features adjacent to a location or feature. Spatial queries in GIS include point queries, line queries, area queries, buffer queries, etc.
2. Spatial statistics:
Through statistical analysis of GIS data, the spatial distribution characteristics and laws of geographical phenomena are revealed. For example, you can calculate the quantity, density, distribution, etc. of a certain element in a certain area. Spatial statistical methods in GIS include point density analysis, line density analysis, area analysis, interaction analysis, etc.
3. Spatial interpolation:
In GIS, spatial interpolation is a method that uses the attribute values of known points to estimate the attribute values of unknown locations. For example, the temperature in a certain location can be estimated from known weather station data, or the population density in a certain area can be estimated from known census data. Spatial interpolation methods in GIS include inverse distance weighting method, Crimson method, spline interpolation method, etc.
4. Spatial model:
In GIS, the spatial model is a statistical model based on spatial data, used to analyze the correlation, similarity and variability of spatial phenomena. For example, the relationship between population density and city size can be studied through spatial regression models. Spatial models in GIS include spatial autocorrelation models, spatial error models, spatial lag models, etc.
5. Spatial decision support:
In GIS, spatial decision support refers to the use of GIS technology and spatial analysis methods to support decision makers in making decisions in complex spatial environments. For example, GIS technology can be used in urban planning to simulate the effects of different planning options and make decisions based on the simulation results.
Spatial decision support methods in GIS include multi-criteria decision analysis, spatial decision trees, simulations, etc.
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