Introduction to Spatial Analysis

Spatial analysis is a set of techniques for analyzing spatial data. The results of spatial analysis are dependent on the locations of the objects being analyzed.

The emphasis of the spatial analysis is to measure properties and relationships, taking into account the spatial location of the phenomenon under study.

Spatial statistics extends traditional statistics to support the analysis of geographic data. It provides techniques to describe the distribution of data in the geographic space (descriptive spatial statistics), analyze the spatial patterns of the data (spatial pattern analysis), identify and measure spatial relationships (spatial regression), and create a surface from sampled data (spatial interpolation, usually categorized as geostatistics).

The Attribute Fill contains some features that allow different modes of populating layers data based on others layers.

The Cellular Spaces is a tool that allows the creation of a cellular dataset that can be used in various ways.

The spatial analysis process

The spatial analysis is composed by a set of chained procedures whose aim is to choose an inferential model that explicitly considers the spatial relationship present in the phenomenon.

The initial procedures of analysis include the set of generic methods of exploratory analysis and the visualization of data, in general through maps.

These techniques permit the description of the distribution of the variables of study, the identification of observations that are outliers not only in relation to the type of distribution but also in relation to its neighbors, and to look for the existence of patterns in the spatial distribution.

Through these procedures it is possible to propose hypothesis about the observations, in a way of selecting the best inferential model supported by the data.