Spatial statistical analysis refers to the statistical method of analyzing geospatial data and researching spatial relatioships. Spatial statistical analysis usually considers that a certain geographical phenomenon or attribute value on a regional unit is related to the same phenomenon or attribute value in the adjacent area unit. Almost all spatial data has spatial dependence or spatial autocorrelation. Spatial statistical analysis establishes statistical relation between data through location, and uses statistical methods to find the laws of spatial relationship and spatial variation.

Spatial statistical analysis includes statistical analysis of spatial data and spatial statistical analysis of data. The former focuses on the statistical analysis of the non-spatial characteristics of space objects and phenomena, and the central topic of settlement is: how to describe space phenomena in mathematical statistical models. The latter directly from the spatial location of space objects, contact, study both random and structural, or natural phenomenon with spatial correlation and dependence, its core is the understanding between data associated with the geographical position of spatial dependence, spatial correlation and spatial autocorrelation, build a statistical relationship between data by space position.

Spatial statistical analysis provides a series of statistical functions for analyzing spatial distribution, pattern, process and relationship.To analyze the spatial data and related properties, characteristics of spatial distribution of significant aggregated (for example, to determine the average center or the overall direction trend), identify statistically significant spatial clustering (hot or cold spots) or clustering or discrete spatial outliers, assessment of the overall pattern, determine appropriate analysis scale and to explore the spatial relations.

SuperMap iDesktop provides the following types of spatial statistical analysis:

**Measuring Geographic Analysis**:Measures the distribution of a set of features allows you to calculate a value that represents a characteristic of the distribution, such as the center, compactness, or orientation. You can use this value to track changes in the distribution over time or compare distributions of different features.**Analyzing Patterns**:Evaluate the spatial distribution pattern of the elements, and the determining factor is to form a clustering space mode, discrete space mode or random spatial pattern.**Cluster Analysis**:Identify hot spots, cold spots, or spatial outliers with statistical significance.**Modeling Spatial Relationships**:Construct a data relational model to explore the correlation between factor attribute factors.

### Application Fields

Spatial statistical analysis is widely used in resource management, urban construction, ecological and environmental assessment, regional economy and other fields.

**Resource management**: Mainly applied to agriculture and forestry, to solve the problems of the distribution of various resources (such as land, forest, grassland, etc.) in agriculture and forestry.**Urban construction**: Mainly used to analyze urban population, economy, construction and other development changes, statistical change trend and change law, the location of urban public facilities.**Ecological and environmental assessment**: Assessment of regional ecological planning, assessment of environmental status, environmental impact assessment, pollutant distribution and flow direction, etc.**Regional economy**: Mainly applied to the distribution of GDP in the analysis area, and the GDP growth rate is related to some phenomena, population and infrastructure.