ABSTRACT
The final objective of most users of satellite remote sensing (RS) is to combine their results with other geographic variables for different purposes: forest inventory, agricultural suitability, natural hazard assessment, analysis of climate patterns, etc. In this regard, image interpretation is not the final goal of the user but just a source of input information in the framework of an integrated spatial analysis. This integration is carried out with geographical information systems (GIS) technologies. GIS can be defined as a set of programs that store, manage, manipulate, and represent data with some kind of spatial component (Bolstad 2008; Burrough and McDonell 1998; Longley et al. 2005). This geographically referenced information includes maps, statistics, or climatic data (Figure 9.1). With a common location, all these variables can be mutually related in diverse ways. Since the information is stored in digital format, a GIS takes advantage of a very diverse range of computer analytical capabilities, facilitating multiple operations that are impossible to perform by conventional means: cartographic generalization, path analysis, variable overlaying, slope, aspect, or visibility calculations, neighbor analysis, etc.
