License: 
Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.GISCIENCE.2018.58
URN: urn:nbn:de:0030-drops-93860
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2018/9386/
Sims, Kelly ;
Thakur, Gautam ;
Sparks, Kevin ;
Urban, Marie ;
Rose, Amy ;
Stewart, Robert
Dynamically-Spaced Geo-Grid Segmentation for Weighted Point Sampling on a Polygon Map Layer (Short Paper)
Abstract
Geo-grid algorithms divide a large polygon area into several smaller polygons, which are important for studying or executing a set of operations on underlying topological features of a map. The current geo-grid algorithms divide a large polygon in to a set of smaller but equal size polygons only (e.g. is ArcMaps Fishnet). The time to create a geo-grid is typically proportional to number of smaller polygons created. This raises two problems - (i) They cannot skip unwanted areas (such as water bodies, given about 71% percent of the Earth's surface is water-covered); (ii) They are incognizant to any underlying feature set that requires more deliberation. In this work, we propose a novel dynamically spaced geo-grid segmentation algorithm that overcomes these challenges and provides a computationally optimal output for borderline cases of an uneven polygon. Our method uses an underlying topological feature of population distributions, from the LandScan Global 2016 dataset, for creating grids as a function of these weighted features. We benchmark our results against available algorithms and found our approach improves geo-grid creation. Later on, we demonstrate the proposed approach is more effective in harvesting Points of Interest data from a crowd-sourced platform.
BibTeX - Entry
@InProceedings{sims_et_al:LIPIcs:2018:9386,
author = {Kelly Sims and Gautam Thakur and Kevin Sparks and Marie Urban and Amy Rose and Robert Stewart},
title = {{Dynamically-Spaced Geo-Grid Segmentation for Weighted Point Sampling on a Polygon Map Layer (Short Paper)}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {58:1--58:7},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-083-5},
ISSN = {1868-8969},
year = {2018},
volume = {114},
editor = {Stephan Winter and Amy Griffin and Monika Sester},
publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
address = {Dagstuhl, Germany},
URL = {http://drops.dagstuhl.de/opus/volltexte/2018/9386},
URN = {urn:nbn:de:0030-drops-93860},
doi = {10.4230/LIPIcs.GISCIENCE.2018.58},
annote = {Keywords: geofence, geo-grid, quadtree, points of interest (POI), volunteered geographic information (VGI)}
}
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Keywords: |
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geofence, geo-grid, quadtree, points of interest (POI), volunteered geographic information (VGI) |
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Collection: |
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10th International Conference on Geographic Information Science (GIScience 2018) |
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Issue Date: |
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2018 |
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Date of publication: |
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02.08.2018 |
