Contextual Line Simplification (CLS) for ArcGIS

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A map or visualization of the earth's surface represents geographic features in a smaller scale. Hence, the information it contains must be restricted to what can graphically be presented at map scale and fit in the map medium. This adjustment process is called generalization. One fundamental generalization process in cartography is simplification, which applies to linear features. Simplification of a line involves removal of high density vertices, based on a given criterion (e.g., minimize line distortion by controlling the offset of the generalized line from the original; Douglas-Peucker algorithm) to reduce complexity or redundancy in a dataset. Lately, with the rapid developments in mobile positioning technologies, a series of new applications (e.g., fleet management systems, location based services) have emerged, which produce vast amounts of spatiotemporal (mobility) data. Raw mobility data typically include the spatio-temporal locations (triplets: x, y, t) of either concrete objects or abstract concepts (e.g., spreading diseases) that form trajectories to describe the movement of individual objects. To handle the massive collections of mobility data there is usually a need to reduce its size. The trajectory generalization (also referred as trajectory simplification or compression) has been considered in the past and a series of solutions have been proposed. A representative algorithm extends the Douglas-Peucker algorithm with the notion of Synchronous Euclidean Distance (SED). The simplification of a static or dynamic line (trajectory) may result in a target line that violates the spatial relations (topological, direction or distance) that apply between the source line and some other objects in space. For example, the generalization of a sea vessel trajectory may result into a target trajectory that intersects an island. The proposed methodology resolves this problem by introducing a contextual simplification of both static and dynamic linear features considering other layers as contextual constraints. This method will be integrated into ArcGIS - the leading Geographic Information System software package - toolset to support a contextual simplification of linear features for the benefit of the GIS user community.