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Arrange Spatial Data
Published in Tamara Munzner, Visualization Analysis and Design, 2014
Cartographers have grappled with design choices for the visual representation of geographic spatial data for many hundreds of years. The term cartographic generalization is closely related to the term abstraction as used in this book: it refers to the set of choices about how to derive an appropriate geometry dataset from raw data so that it is suitable for the intended task of the map users. This concept includes considerations discussed in this book such as filtering, aggregation, and level of detail. For example, a city might be indicated with a point mark in a map drawn at the scale of an entire country, or as an area mark with detailed geometric information showing the shape of its boundaries in a map at the scale of a city and its surrounding suburbs. Cartographic data includes what this book classifies as nonspatial information: for example, population data in the form of a table could be used to size code the point marks representing cities by their population.
Airborne Laser Scanning (ALS) and Filtering Algorithms
Published in Ahmad Fikri Bin Abdullah, A Methodology for Processing Raw Lidar Data to Support Urban Flood Modelling Framework, 2020
Generalization is considered to have been performed well when the natural topography of an area may be optimally recovered from the limited information portrayed on the map. Cartographic generalization may involve the selection of objects to be omitted, the simplification of lines or features, the combination or summarization of objects, and/or the displacement of objects. Of course, some of these options may not be suitable for specific data types. In continuous data of equal types, the 'information trend' is conveyed to the map by the low frequencies in the data, while the majority of the information content is contained in the higher frequencies.
A procedural footprint enhancement of global topographic surface with multiple levels of detail
Published in International Journal of Digital Earth, 2020
The paging mechanism is usually linked with the spatial indexing technique. It is the indexing mechanism, which defines the spatial extent of current interest and mediates the LOD of the data to be fetched respectively. Coarser LODs are usually derived from the original source by means of feature- or shape-simplification methods or by the application of various generalization operators to distinct features or groups of features. Algorithms of cartographic generalization were deeply studied and many later served as a basis for further extensions within (3D) GIS. Currently, the Douglas and Peucker (1973) algorithm is probably the most used poly-line simplification method. The algorithm, however, can easily cause topological conflicts when applied to a set of neighboring poly-lines. Therefore, an solution was sought to overcome this imperfection. Dyken, Daehlen, and Sevaldrud (2009) and Meijers (2011a) discovered it by considering the complete set of poly-lines and all mutual topological relationships. Meijers (2011a) contributed to existing solutions using an unconnected graph of poly-lines and addressed the merge and split operations for map generalization, which often cause problems during simplification. Meijers (2011a) identifies poly-lines influenced by a given simplification with the help of an auxiliary kd-tree data structure, which facilitates fast access to the influenced poly-lines. In contrast, Dyken, Daehlen, and Sevaldrud (2009) avoid the overhead associated with the management of auxiliary data structures by encoding the poly-lines neighborhood relationships using unconstrained edges from the underlying triangulation.