For multiple industries, the element of geography plays a vital role in contributing to their successful operations. Particularly for corporate giants operational in the oil industry, GIS (Geographical information systems) are implemented frequently. Given this increase in their application, the use of spacial analysis is now also increasing. The use of spatial analysis shall render GIS data manipulation tools to be more sophisticated and advanced. Before embarking upon the relationship of spatial analysis and GIS, it is important to detail upon the concept of spatial analysis alone.
Defining Spatial Analysis
In simple terms, spatial analysis may be defined as process in which demographic and other forms of data are analyzed for determining geographical patterns and ascertaining the relationship amongst them (Clarke, Graham and John, 2004). This process may vary from a simple map to more complex models that are able to combine a series of data layers. A spatial analysis goes beyond the realms of space and physical geographical locations to incorporate social and perceptual factors. These maybe included in the form of social or economic distance (Anselin, 2000). While it is difficult to fit general spaces into the GIS models, spatial analysis allows for manipulation and visualization of these objects in the correct form. It is perhaps unfair to limit the definition of space to the geographic realm.
Spatial analysis finds application when it comes to delivery of accurate information and data. This data is used exclusively when it comes to human and financial resources. Spatial analysis in combination with GIS finds massive application in our society these days be it for crime investigation or for transportation (Boots, 2000). The key benefit of spatial analysis is that it is able to provide an edge to real world scenarios and processes based on the current situation, the specific features of the locality or other factors.
Understanding Spatial Data
Given the multiple arithmetic and logical models involved in spatial analysis, it would be safe to state that this procedure has evolved largely from quantitative methods advancement and particular application in the field of geography (Unwin, 1996). Spatial analysis thus has been able to take GIS a step ahead from a restricted realm of limited representational forms to a more clear understanding of our geographical dimensions. GIS on the other hand is able to provide the supportive environment that is much needed for the manipulation of data in a spatial analysis.
While there are numerous other quantitative techniques present for data analysis, spatial analysis as the name indicates is limited exclusively to spatial data - data form that is of crucial importance in modern times (Getis, 2000). As the given data sets of this data type are exceptionally large, the use of this form of analysis is crucial (Goodchild and Haining, 2003). It is worth mentioning however that the data is typically independent in this case and the attribute values recorded tend to be directly related to their recorded location or distances. This key property has been the basis of several ...