Titlebook: Geographic Information Science; 9th International Co Jennifer A. Miller,David O‘Sullivan,Nancy Wiegand Conference proceedings 2016 Springer

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Conference proceedings 2016l, QC, Canada, in September 2016. The 21 full papers presented were carefully reviewed and selected from 63 submissions. The papers are organized in topical sections such as spatial algorithms; network analysis; spatial analysis; spatial methods; user-generated data and linked data; automated cartography and geovisualization..

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Partitioning Polygons via Graph Augmentationa minimal number of nonintersecting edges from . to bound the ratio between the graph-based distance and the Euclidean distance for all pairs of vertices described by .. Motivated by the problem of decomposing a polygon into natural subregions, we present an optimal linear-time algorithm for the cas

Abutment

Hierarchical Prism Trees for Scalable Time Geographic Analysisreal-time over multiple spatial and temporal scales are becoming the norm. At the same time, existing frameworks useful for understanding these dynamic spatio-temporal data, such as time geography, are unable to scale to the high volume, velocity, and variety of these emerging data sources. In this

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Distance-Constrained , Spatial Sub-Networks: A Summary of Results a distance constraint and maximize the number of spatial events covered by the sub-networks. The DCSSN problem is important for many societal applications, such as police patrol assignment and emergency response assignment. The problem is NP-hard; it is computationally challenging because of the la

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On Distortion of Raster-Based Least-Cost Corridorsa sequence of cells—connecting two terminuses such that its total accumulated cost is minimized. While it is widely known that raster-based least-cost paths are subject to three types of distortion, i.e., deviation, distortion, and proximity, little is known about potential distortion of their corri

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Model-Based Clustering of Social Vulnerability to Urban Extreme Heat Eventsards are known to exhibit biophysical variations (e.g., land cover and housing characteristics) and social variations (e.g., demographic and economic adaptations to heat mitigation). Geodemographic model-based classification permits a more extensive set of input variables, with richer attributions;