research-article

Embedding and extending GIS for exploratory analysis of large-scale species distribution data

Authors:

Jianting Zhang,

Le GruenwaldAuthors Info & Claims

GIS '08: Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems

Article No.: 28, Pages 1 - 10

https://doi.org/10.1145/1463434.1463470

Published: 05 November 2008 Publication History

Abstract

Exploratory analysis of large-scale species distribution data is essential to gain information and knowledge, stimulating hypotheses and seeking possible explanations of species distribution patterns. Geographical Information System (GIS) has played an important role in modeling and visualizing species distribution patterns for a single or a limited number of species. However, traditional GIS models do not take taxonomic components of species distribution data into consideration and are neither effective nor efficient in managing large-scale species distribution data.

In this study, we propose to embed and extend GIS for large scale species distribution data analysis. We provide an integrated data model that seamlessly links geographical, taxonomic and environmental data related to species distribution data analysis. We then present LEEASP (a Linked Environment for Exploratory Analysis of large-scale Species Distribution data), a prototype that has been developed based on the integrated data model. LEEASP utilizes the state-of-the-art advanced visualization techniques and multiple view coordination techniques to visualize different data sources that are relevant to species distribution data analysis. The North America tree species distribution data and other related data are used as an example to demonstrate the feasibility of the realization of the proposed integrated data model and how LEEASP can help users explore the geographical-taxonomic-environmental relationships

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Cited By

El Meseery MHoeber O(2018)Geo-Coordinated Parallel Coordinates (GCPC): Field trial studies of environmental data analysisVisual Informatics10.1016/j.visinf.2018.02.0012:2(111-124)Online publication date: Jun-2018
https://doi.org/10.1016/j.visinf.2018.02.001
Zhang JYou SGruenwald L(2017)Towards GPU-Accelerated Web-GIS for Query-Driven Visual ExplorationWeb and Wireless Geographical Information Systems10.1007/978-3-319-55998-8_8(119-136)Online publication date: 22-Mar-2017
https://doi.org/10.1007/978-3-319-55998-8_8
Zhang JYou SGruenwald L(2015)Efficient Parallel Zonal Statistics on Large-Scale Global Biodiversity Data on GPUsProceedings of the 4th International ACM SIGSPATIAL Workshop on Analytics for Big Geospatial Data10.1145/2835185.2835187(35-44)Online publication date: 3-Nov-2015
https://dl.acm.org/doi/10.1145/2835185.2835187
Show More Cited By

Index Terms

Embedding and extending GIS for exploratory analysis of large-scale species distribution data
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms
      1. Graphical user interfaces
  2. Visualization
    1. Visualization application domains
      1. Geographic visualization
2. Information systems
  1. Information systems applications
    1. Spatial-temporal systems

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cover image ACM Conferences

GIS '08: Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems

November 2008

559 pages

ISBN:9781605583235

DOI:10.1145/1463434

Program Chairs:
Walid G. Aref
Purdue University
,
Mohamed F. Mokbel
University of Minnesota
,
Markus Schneider
University of Florida

Copyright © 2008 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Microsoft: Microsoft
SIGSPATIAL: ACM Special Interest Group on Spatial Information

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Published: 05 November 2008

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GIS '08: 16th International Symposium on Advances in Geographic Information Systems

November 5 - 7, 2008

California, Irvine

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Overall Acceptance Rate 257 of 1,238 submissions, 21%

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Cited By

El Meseery MHoeber O(2018)Geo-Coordinated Parallel Coordinates (GCPC): Field trial studies of environmental data analysisVisual Informatics10.1016/j.visinf.2018.02.0012:2(111-124)Online publication date: Jun-2018
https://doi.org/10.1016/j.visinf.2018.02.001
Zhang JYou SGruenwald L(2017)Towards GPU-Accelerated Web-GIS for Query-Driven Visual ExplorationWeb and Wireless Geographical Information Systems10.1007/978-3-319-55998-8_8(119-136)Online publication date: 22-Mar-2017
https://doi.org/10.1007/978-3-319-55998-8_8
Zhang JYou SGruenwald L(2015)Efficient Parallel Zonal Statistics on Large-Scale Global Biodiversity Data on GPUsProceedings of the 4th International ACM SIGSPATIAL Workshop on Analytics for Big Geospatial Data10.1145/2835185.2835187(35-44)Online publication date: 3-Nov-2015
https://dl.acm.org/doi/10.1145/2835185.2835187
Das RPatra MRoutray MHADDAWY PYi HPARDO T(2010)Integrating WebGIS with service oriented rural information gridProceedings of the 4th International Conference on Theory and Practice of Electronic Governance10.1145/1930321.1930355(161-166)Online publication date: 25-Oct-2010
https://dl.acm.org/doi/10.1145/1930321.1930355
Zhang JGertz MGruenwald LWolfson OAgrawal DLu C(2009)Efficiently managing large-scale raster species distribution data in PostgreSQLProceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems10.1145/1653771.1653815(316-325)Online publication date: 4-Nov-2009
https://dl.acm.org/doi/10.1145/1653771.1653815
Jianting Zhang (2009)Efficient managing large scale species range maps in a spatial database environment2009 17th International Conference on Geoinformatics10.1109/GEOINFORMATICS.2009.5293395(1-6)Online publication date: Aug-2009
https://doi.org/10.1109/GEOINFORMATICS.2009.5293395

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