By Daniel A. Griffith, Yongwan Chun, Denis J. Dean
This booklet includes refereed papers from the thirteenth foreign convention on GeoComputation held on the college of Texas, Dallas, may possibly 20-23, 2015. due to the fact that 1996, the contributors of the GeoComputation (the paintings and technological know-how of fixing complicated spatial issues of desktops) group have joined jointly to advance a sequence of meetings within the uk, New Zealand, Australia, eire and the USA of the USA. The convention encourages assorted issues concerning novel methodologies and applied sciences to counterpoint the long run improvement of GeoComputation research.
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Additional resources for Advances in Geocomputation: Geocomputation 2015--The 13th International Conference
2 The Gen-2 Disaggregation Method Population maps produced by our Gen-1 method oﬀer an eﬃcient means of improving upon the SEDAC grids (see the comparison in Sect. 3). However, because SEDAC has no population grids for 2010, and because SEDAC grids for 1990 and 2000 contain some inconsistencies, we decided to change our disaggregation algorithm to a direct disaggregation from census blocks. This approach requires larger hardware resources and is less computationally eﬃcient, but the outcome justiﬁes the extra eﬀort.
For each component, we also identify the main challenges from a computing perspective. Acknowledgements This material is based upon work supported by the National Science Foundation under Grant No. S. DoD under Grant No. HM1582-08-1-0017, HM0210-13-1-0005, and University of Minnesota via U-Spatial. We would like to thank Kim Koffolt and the members of the University of Minnesota Spatial Computing Research Group for their comments. References Andrews-Speed P, Bleischwitz B, Boersma T, Johnson C, Kemp G, VanDeveer S (2014) Want, waste or war?
2009). This product provides compatible land cover classiﬁcations for 1992 and 2001, but at the cost of reducing the number of land cover categories to only eight classes that constitute Level I of the Anderson classiﬁcation scheme (Anderson et al. 1976). We further reclassify the eight-class land cover data into just three classes: urban, vegetation, and uninhabited area. The Gen-1 dasymetric model uses these three-classes of land cover as its ancillary data. For details of Gen-1 disaggregation, see Dmowska and Stepinski (2014).