Why Spatial Analysis

Spatial analysis is how we understand our world—mapping where things are, how they relate, what it all means, and what actions to take.

From computational analysis of geographic patterns to finding optimum routes, site selection, and advanced predictive modeling, spatial analysis is at the very heart of geographic information system (GIS) technology.

The process of examining the location, attributes and relationships of features in spatial data through analytical techniques. It extracts or creates new information from spatial data.

Besides the visual perception of the spatial distribution of the phenomenon, it is very useful to translate the existing patterns into objective and measurable considerations, like in the following cases:

01Epidemiologists collect data about the occurrence of diseases. Does the distribution of cases of a disease form a pattern in space? Is there any association with any source of pollution? Is there any evidence of contagion? Did it vary with time ?

02We want to investigate if there is any spatial concentration in the distribution of theft. Are thefts that occur in certain areas correlated to socio-economic characteristics of these areas?

03Geologists desire to estimate, from some samples, the extension of a mineral deposit in a region. Can those samples be used to estimate the mineral distribution in that region?

04We want to analyze a region for agricultural zoning purposes. How to choose the independent variables – soil, vegetation or geomorphology and determine what the contribution of each one of them is to define where each type of crop is more adequate?

All of these problems are part of spatial analysis of geographical data. The emphasis of Spatial Analysis is to measure properties and relationships, taking into account the spatial localization of the phenomenon under study in a direct way. That is, the central idea is to incorporate space into the analysis to be made. This book presents a set of tools that try to address these issues. It is intended to help those interested to study, explore and model processes that express themselves through a distribution in space, here called geographic phenomena.