By Geoffrey H. Dutton
Whilst spatial facts is digitized to be used in geographic info platforms and different software program, information regarding its unique scale, solution and accuracy is often misplaced. hence, utilizing such details at various scales and mixing it with info from different assets could be tough. Mapping vector facts at smaller than the unique scale calls for its generalization, that's frequently dealt with by way of post-processing in ways in which are just weakly supported through databases. The types and techniques defined during this ebook triumph over many such difficulties through offering a multi-resolution information illustration that enables retrieval of map information at a hierarchy of scales, in addition to documenting the accuracy of each spatial coordinate.
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While spatial info is digitized to be used in geographic details structures and different software program, information regarding its unique scale, answer and accuracy is usually misplaced. therefore, utilizing such details at assorted scales and mixing it with info from different assets might be tough. Mapping vector information at smaller than the unique scale calls for its generalization, that's often dealt with by means of post-processing in ways in which are just weakly supported via databases.
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Additional info for A Hierarchical Coordinate System for Geoprocessing and Cartography (Lecture Notes in Earth Sciences)
GEM's high degree of data compression was based on the implicit ordering of facets in complete sub-hierarchies; the bits in a GEM archive indicated changes in elevation by their values, and identified facets by their ordering, as do elevation grids, only pyrarnidally. To retrieve elevations across a region, elevations for its quadrants would need to be recursively evaluated (adding and subtracting the delta codes) by traversing the DEPTH pyramid to evaluate the polynomial for each leaf node at the desired level of detail.
But they directly denote position, and do so at multiple, nested resolutions. 3 These properties are achieved through the use of a geometric computational model that, starting with an octahedron we imagine to be embedded in the Earth, subdivides its eight faces into four each, proceeding to recursively subdivide each of the 32 resulting triangular facets (also called quadrants) into four children. 3. While all facets can be subdivided in the same way, in practice this is not done everywhere, but only where one has point positions to encode.
Like Fekete's work at Goddard, HSDS research at UCSB focused on encoding and manipulating data in the multilevel triangular raster defined by the QTM grid. Twelve- and 15-neighbor triangular raster chain encoding methods (further explained in Goodchild et al 1991) were used to identify connected components and enable intersection and dilation of HSDS facets at any hierarchical level. The UCSB team also created Motif-based visualization software that let users at workstations to orient a globe and zoom in to regions at specified levels of detail.
A Hierarchical Coordinate System for Geoprocessing and Cartography (Lecture Notes in Earth Sciences) by Geoffrey H. Dutton