Mapping uncertain geographical attributes: incorporating robustness into choropleth classification design-Reference-Cited by-同舟云学术

Mapping uncertain geographical attributes: incorporating robustness into choropleth classification design

Published:2020-02-16 Issue:11 Volume:34 Page:2204-2224
ISSN:1365-8816
Container-title:International Journal of Geographical Information Science
language:en
Short-container-title:International Journal of Geographical Information Science

Author:

Mu Wangshu¹^ORCID,Tong Daoqin¹^ORCID

Affiliation:

1. School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ, USA

Funder

National Science Foundation

Publisher

Informa UK Limited

Subject

Library and Information Sciences,Geography, Planning and Development,Information Systems

Link

https://www.tandfonline.com/doi/pdf/10.1080/13658816.2020.1726921

Reference37 articles.

1. ACS. 2018. Using American Community Survey (ACS) Estimates and Margins of Error [online]. Available from: https://www.census.gov/programs-surveys/acs/guidance/training-presentations/acs-moe.html Accessed 31 July 2019.

2. Local Indicators of Spatial Association-LISA

3. Retrospective Deconstruction of Statistical Maps: A Choropleth Case Study

4. The Price of Robustness

5. Evaluation of Methods for Classifying Epidemiological Data on Choropleth Maps in Series

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