Loecher, M and Ropkins, K (2015) RgoogleMaps and loa: unleashing R graphics power on map tiles. Journal of Statistical Software, 63 (4). ISSN 1548-7660
Abstract
The RgoogleMaps package provides (1) an R interface to query the Google and the OpenStreetMap servers for static maps in the form of PNGs, and (2) enables the user to overlay plots on those maps within R. The loa package provides dedicated panel functions to integrate RgoogleMaps within the lattice plotting environment. In addition to solving the generic task of plotting on a map background in R, we introduce several specific algorithms to detect and visualize spatio-temporal clusters. This task can often be reduced to detecting over-densities in space relative to a background density. The relative density estimation is framed as a binary classification problem. An integrated hotspot visualizer is presented which allows the efficient identification and visualization of clusters in one environment. Competing clustering methods such as the scan statistic and the density scan other higher detection power at a much larger computational cost. Such clustering method can then be extended using the lattice trellis framework to provide further insight into the relationship between clusters and potentially influential parameters. While there are other options for such map `mashups' we believe that the integration of RgoogleMaps and lattice using loa can in certain circumstances be advantageous, e.g., by providing a highly intuitive working environment for multivariate analysis and flexible testbed for the rapid development of novel data visualizations.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | (c) 2015, The Authors. This is an open access article under the terms of the Creative Commons Attribution License, CC BY 3.0 |
Keywords: | scan statistic; RgoogleMaps; loa; hotspots; supervised learning; PRIM; lattice; conditional clusters |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Environment (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 17 Mar 2015 16:19 |
Last Modified: | 21 Feb 2024 13:54 |
Published Version: | http://www.jstatsoft.org/v63/i04 |
Status: | Published |
Publisher: | University of California, Los Angeles |
Identification Number: | 10.18637/jss.v063.i04 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:83465 |