Spatial Statistical Analysis refers to the method of analyzing and counting Geographic Spatial Data and exploring spatial relationships. Spatial Statistical Analysis generally considers that a certain geographical phenomenon or a certain attribute value on a regional unit is related to the same phenomenon or attribute value on a neighboring regional unit. Almost all Spatial Data have the feature of spatial dependency or Spatial Autocorrelation. Spatial Statistical Analysis establishes the statistical relationship between data through location, and uses statistical methods to find the law of spatial connection and spatial change.
Spatial Statistical Analysis includes Statistic Analysis of Spatial Data and Spatial Statistical Analysis of Data. The former focuses on the Statistic Analysis of the non-spatial characteristics of spatial objects and phenomena, and the central issue to be solved is: how to describe the process of spatial phenomena with mathematical statistical models; The latter starts directly from the spatial position and connection of spatial objects, and the analysis process has both randomness and structure, or spatial correlation and dependence, whose core is to recognize the spatial dependence, Spatial Association and Spatial Autocorrelation between data related to geographical location. The statistical relationship between data is established by spatial location.
Spatial Statistical Analysis provides a range of statistical functions for analyzing spatial distributions, patterns, processes, and relationships. The provided Spatial Data and related attributes can be analyzed to summarize the salient features of the spatial distribution (e. Mean Center or general directional trends), identify statistically significant spatial clusters (hot or cold spots) or spatial outliers, evaluate overall patterns of clustering or dispersion, determine appropriate scales of analysis, and explore spatial relationships.
SuperMap iDesktopX provides the following types of Spatial Statistical Analysis:
- Measuring Geographic Distributions: You can calculate various values that characterize the distribution, such as center, density, or direction, by measuring the distribution of a set of features. You can use this feature value to track changes in distribution over time or to compare the distribution of different features.
- Analysis Mode: It is used to evaluate the spatial distribution mode among the elements and judge whether the elements form a clustered spatial mode, a discrete spatial mode or a random spatial mode.
- Clustering Distribution: used to identify statistically significant hot spots, cold spots, or spatial outliers.
- Spatial Relationship Modeling: Build a data relationship model to mine the correlation between Feature Property factors.
Field of application
Spatial Statistical Analysis is widely used in resource management, urban construction, ecology, environmental assessment, regional economy and other fields.
Resource management: It is mainly used in agriculture and forestry to solve the distribution change and unification of various resources (such as land, forest, grassland, etc.) in agriculture and forestry Counting and other problems.
Urban construction: It is mainly used to analyze the development and changes of urban population, economy, construction, etc., to count the trend and law of change, and to select urban public facilities. Address.
Ecological and environmental assessment: regional ecological planning assessment, environmental status assessment, environmental impact assessment, pollutant distribution and flow direction, etc.
Regional economy: It is mainly used to analyze the change of GDP distribution in the region, and the relationship between GDP growth rate and some phenomena, population and infrastructure. Department.
Related topics
Measuring Geographic Distributions