Advances in Geocomputation: Geocomputation 2015--The 13th by Daniel A. Griffith, Yongwan Chun, Denis J. Dean

By Daniel A. Griffith, Yongwan Chun, Denis J. Dean

This booklet comprises refereed papers from the thirteenth foreign convention on GeoComputation held on the collage of Texas, Dallas, may possibly 20-23, 2015. because 1996, the contributors of the GeoComputation (the paintings and technological know-how of fixing complicated spatial issues of desktops) neighborhood have joined jointly to enhance a chain of meetings within the uk, New Zealand, Australia, eire and the us of the USA. The convention encourages diversified subject matters concerning novel methodologies and applied sciences to counterpoint the long run improvement of GeoComputation research.

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Using dasymetric modeling on such a large scale is a technically demanding task due to its needs to handle very large datasets and to develop computationally efficient algorithms. Recognizing a need for broad-coverage population data at a high spatial resolution, population grids have been produced for countries within the European Union, Africa, South America, and Asia (see Table 1). edu). U. pop. gridb S. America, Africa, Asia Europe 100 m Australian pop. worldpop. eea. ciesin. edu/ et al. (2007), Linard et al.

Consequently, maps showing the A. F. edu A. A. Griffith et al. 1007/978-3-319-22786-3_4 35 36 A. F. Stepinski spatial distribution of population are in vector form, resulting in an unrealistic level of homogeneity (lack of spatial resolution) in the population distribution. , a metropolitan area that stretches over two or more states). Given the limitations of areal units-based population data, the focus of investigation has shifted to populations grids that are capable of depicting the population distribution at a higher resolution.

Our Gen-1 grid (Fig. 1f) offers a significant improvement over the SEDAC 250 m grid. The river and the industrial transportation corridor are well delineated and parks and green spaces are distinguished from built-up areas. Comparing the Gen-1 grid with the block-based map, however, reveals that some industrial, uninhabited areas are shown as inhabited because some NLCD classes contain residential and non-residential buildings. Also, the resolution of our Gen-1 map in the downtown area is not as good as it is in the block-based map.

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