Semantic Representation of Raster Spatial Data

when people think spatially, they do not usually consider geographic coordinates nor projections. facing questions having a spatial sense, people do not answer with maps or coordinates, but use some references whose spatial location is "well known". for instance, the answer of a conventional geographic information system to the question "where is the cic?" would be "in coordinates 19.50314°n, 99.14759°w". in contrast, a person would answer "in zacatenco" or "near to eje central". the semantic processing attempts to enrich an abstraction level similar to the one that people use commonly. this processing, applied to spatial data, does not depend on scales, resolutions, projections or others that are fundamental in conventional systems. we assume that the first step for making semantic processing is the semantic description of "raw" spatial data. such description is the identification of the objects contained in data and the location of such objects within a conceptual framework, where they get a meaning. in this work, we present a methodology for making this semantic description using as a case study the digital elevation models. the methodology is build up of three stages: conceptualization, to define the conceptual framework of the description; synthesis, to process "raw" spatial data and to obtain the spatial objects contained in data; and description, to generate the representation of results from the synthesis according to the conceptual framework.