Loading…

AUTOCORRELATION AND VISUAL MAP COMPLEXITY

One important element in the overall look of a quantitative map is the relationship between neighboring values as they appear on the map, i.e., the autocorrelation in the map based on the classes into which the values fall. Methods of calculating this relationship objectively include rank autocorrel...

Full description

Saved in:
Bibliographic Details
Published in:Annals of the Association of American Geographers 1975-06, Vol.65 (2), p.189-204
Main Author: OLSON, JUDY M.
Format: Article
Language:English
Subjects:
Citations: Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c4309-5542fd7de50bacd1386d5577d6859ad31c216e90857ce73189ed3e8731d513e73
cites
container_end_page 204
container_issue 2
container_start_page 189
container_title Annals of the Association of American Geographers
container_volume 65
creator OLSON, JUDY M.
description One important element in the overall look of a quantitative map is the relationship between neighboring values as they appear on the map, i.e., the autocorrelation in the map based on the classes into which the values fall. Methods of calculating this relationship objectively include rank autocorrelation; proportions of identical neighbors; average differences between neighboring values; number of clusters; and a weighted "proportion''value which includes a contribution from every neighboring pair, the amount of contribution varying inversely with the differences between the paired values. The first lag relationships appear to be most meaningful in terms of the visual appearance of hypothetical blocks of data ("maps"). Some of these measures are related to the way in which subjects order the blocks according to "spatial complexity,''although checkerboard patterns in particular introduce differences between measured and subjective sequences.
doi_str_mv 10.1111/j.1467-8306.1975.tb01030.x
format article
fullrecord <record><control><sourceid>jstor_proqu</sourceid><recordid>TN_cdi_proquest_journals_1296229323</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><jstor_id>2562081</jstor_id><sourcerecordid>2562081</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4309-5542fd7de50bacd1386d5577d6859ad31c216e90857ce73189ed3e8731d513e73</originalsourceid><addsrcrecordid>eNqVUEFPgzAYbYwmzuk_8ED05AFsKS3gxTSISsJgmczoqWG0JJBtzMKy7d9bwrKz9tJ-fd973_seAHcIWkifx9pCDnVND0NqId8lVreACGJo7c_A6ASdgxGE0DEJhd4luGrbWpcIU2cEHtg8S4N0NgtjlkVpYrDkxfiMPuYsNiZsagTpZBqHX1H2fQ0uynzZypvjPQbz1zAL3s04fYsCFpuFg6FvEuLYpXCFJHCRFwJhjwpCXFdQj_i5wKiwEZU-9IhbSBcjz5cCS0-_BEFY_4zB_aC7Uc3PVrYdr5utWuuRHNk-tW0f21h3PQ1dhWraVsmSb1S1ytWBI8j7aHjN-_15vz_vo-HHaPhek58H8q5aysM_mJwlCdOWtcLtoFC3XaNOCjahNvSQhsMBrtZlo1b5rlFLwbv8sGxUqfJ1UbUc_8HoLyL_hXA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1296229323</pqid></control><display><type>article</type><title>AUTOCORRELATION AND VISUAL MAP COMPLEXITY</title><source>JSTOR Archival Journals and Primary Sources Collection</source><creator>OLSON, JUDY M.</creator><creatorcontrib>OLSON, JUDY M.</creatorcontrib><description>One important element in the overall look of a quantitative map is the relationship between neighboring values as they appear on the map, i.e., the autocorrelation in the map based on the classes into which the values fall. Methods of calculating this relationship objectively include rank autocorrelation; proportions of identical neighbors; average differences between neighboring values; number of clusters; and a weighted "proportion''value which includes a contribution from every neighboring pair, the amount of contribution varying inversely with the differences between the paired values. The first lag relationships appear to be most meaningful in terms of the visual appearance of hypothetical blocks of data ("maps"). Some of these measures are related to the way in which subjects order the blocks according to "spatial complexity,''although checkerboard patterns in particular introduce differences between measured and subjective sequences.</description><identifier>ISSN: 0004-5608</identifier><identifier>EISSN: 1467-8306</identifier><identifier>DOI: 10.1111/j.1467-8306.1975.tb01030.x</identifier><language>eng</language><publisher>Oxford, UK: Taylor &amp; Francis Group</publisher><subject>Autocorrelation ; Checkerboards ; Complexity ; Correlations ; Geography ; Hypothetical maps ; Lag ; Map skills ; Mathematical sequences ; Musical intervals ; Neighborhoods ; Quantitative maps ; Testing of subjects ; Visual map complexity ; Zero</subject><ispartof>Annals of the Association of American Geographers, 1975-06, Vol.65 (2), p.189-204</ispartof><rights>Copyright Taylor &amp; Francis Group, LLC 1975</rights><rights>Copyright 1975 Association of American Geographers</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4309-5542fd7de50bacd1386d5577d6859ad31c216e90857ce73189ed3e8731d513e73</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/2562081$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/2562081$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>314,776,780,27898,27899,58210,58443</link.rule.ids></links><search><creatorcontrib>OLSON, JUDY M.</creatorcontrib><title>AUTOCORRELATION AND VISUAL MAP COMPLEXITY</title><title>Annals of the Association of American Geographers</title><description>One important element in the overall look of a quantitative map is the relationship between neighboring values as they appear on the map, i.e., the autocorrelation in the map based on the classes into which the values fall. Methods of calculating this relationship objectively include rank autocorrelation; proportions of identical neighbors; average differences between neighboring values; number of clusters; and a weighted "proportion''value which includes a contribution from every neighboring pair, the amount of contribution varying inversely with the differences between the paired values. The first lag relationships appear to be most meaningful in terms of the visual appearance of hypothetical blocks of data ("maps"). Some of these measures are related to the way in which subjects order the blocks according to "spatial complexity,''although checkerboard patterns in particular introduce differences between measured and subjective sequences.</description><subject>Autocorrelation</subject><subject>Checkerboards</subject><subject>Complexity</subject><subject>Correlations</subject><subject>Geography</subject><subject>Hypothetical maps</subject><subject>Lag</subject><subject>Map skills</subject><subject>Mathematical sequences</subject><subject>Musical intervals</subject><subject>Neighborhoods</subject><subject>Quantitative maps</subject><subject>Testing of subjects</subject><subject>Visual map complexity</subject><subject>Zero</subject><issn>0004-5608</issn><issn>1467-8306</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1975</creationdate><recordtype>article</recordtype><recordid>eNqVUEFPgzAYbYwmzuk_8ED05AFsKS3gxTSISsJgmczoqWG0JJBtzMKy7d9bwrKz9tJ-fd973_seAHcIWkifx9pCDnVND0NqId8lVreACGJo7c_A6ASdgxGE0DEJhd4luGrbWpcIU2cEHtg8S4N0NgtjlkVpYrDkxfiMPuYsNiZsagTpZBqHX1H2fQ0uynzZypvjPQbz1zAL3s04fYsCFpuFg6FvEuLYpXCFJHCRFwJhjwpCXFdQj_i5wKiwEZU-9IhbSBcjz5cCS0-_BEFY_4zB_aC7Uc3PVrYdr5utWuuRHNk-tW0f21h3PQ1dhWraVsmSb1S1ytWBI8j7aHjN-_15vz_vo-HHaPhek58H8q5aysM_mJwlCdOWtcLtoFC3XaNOCjahNvSQhsMBrtZlo1b5rlFLwbv8sGxUqfJ1UbUc_8HoLyL_hXA</recordid><startdate>197506</startdate><enddate>197506</enddate><creator>OLSON, JUDY M.</creator><general>Taylor &amp; Francis Group</general><general>Association of American Geographers</general><general>Blackwell Publishing Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>FIXVA</scope><scope>FKUCP</scope><scope>IBDFT</scope><scope>K30</scope><scope>PAAUG</scope><scope>PAWHS</scope><scope>PAWZZ</scope><scope>PAXOH</scope><scope>PBHAV</scope><scope>PBQSW</scope><scope>PBYQZ</scope><scope>PCIWU</scope><scope>PCMID</scope><scope>PCZJX</scope><scope>PDGRG</scope><scope>PDWWI</scope><scope>PETMR</scope><scope>PFVGT</scope><scope>PGXDX</scope><scope>PIHIL</scope><scope>PISVA</scope><scope>PJCTQ</scope><scope>PJTMS</scope><scope>PLCHJ</scope><scope>PMHAD</scope><scope>PNQDJ</scope><scope>POUND</scope><scope>PPLAD</scope><scope>PQAPC</scope><scope>PQCAN</scope><scope>PQCMW</scope><scope>PQEME</scope><scope>PQHKH</scope><scope>PQMID</scope><scope>PQNCT</scope><scope>PQNET</scope><scope>PQSCT</scope><scope>PQSET</scope><scope>PSVJG</scope><scope>PVMQY</scope><scope>PZGFC</scope></search><sort><creationdate>197506</creationdate><title>AUTOCORRELATION AND VISUAL MAP COMPLEXITY</title><author>OLSON, JUDY M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4309-5542fd7de50bacd1386d5577d6859ad31c216e90857ce73189ed3e8731d513e73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1975</creationdate><topic>Autocorrelation</topic><topic>Checkerboards</topic><topic>Complexity</topic><topic>Correlations</topic><topic>Geography</topic><topic>Hypothetical maps</topic><topic>Lag</topic><topic>Map skills</topic><topic>Mathematical sequences</topic><topic>Musical intervals</topic><topic>Neighborhoods</topic><topic>Quantitative maps</topic><topic>Testing of subjects</topic><topic>Visual map complexity</topic><topic>Zero</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>OLSON, JUDY M.</creatorcontrib><collection>CrossRef</collection><collection>Periodicals Index Online Segment 03</collection><collection>Periodicals Index Online Segment 04</collection><collection>Periodicals Index Online Segment 27</collection><collection>Periodicals Index Online</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - West</collection><collection>Primary Sources Access (Plan D) - International</collection><collection>Primary Sources Access &amp; Build (Plan A) - MEA</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Midwest</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Northeast</collection><collection>Primary Sources Access (Plan D) - Southeast</collection><collection>Primary Sources Access (Plan D) - North Central</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Southeast</collection><collection>Primary Sources Access (Plan D) - South Central</collection><collection>Primary Sources Access &amp; Build (Plan A) - UK / I</collection><collection>Primary Sources Access (Plan D) - Canada</collection><collection>Primary Sources Access (Plan D) - EMEALA</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - North Central</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - South Central</collection><collection>Primary Sources Access &amp; Build (Plan A) - International</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - International</collection><collection>Primary Sources Access (Plan D) - West</collection><collection>Periodicals Index Online Segments 1-50</collection><collection>Primary Sources Access (Plan D) - APAC</collection><collection>Primary Sources Access (Plan D) - Midwest</collection><collection>Primary Sources Access (Plan D) - MEA</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Canada</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - UK / I</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - EMEALA</collection><collection>Primary Sources Access &amp; Build (Plan A) - APAC</collection><collection>Primary Sources Access &amp; Build (Plan A) - Canada</collection><collection>Primary Sources Access &amp; Build (Plan A) - West</collection><collection>Primary Sources Access &amp; Build (Plan A) - EMEALA</collection><collection>Primary Sources Access (Plan D) - Northeast</collection><collection>Primary Sources Access &amp; Build (Plan A) - Midwest</collection><collection>Primary Sources Access &amp; Build (Plan A) - North Central</collection><collection>Primary Sources Access &amp; Build (Plan A) - Northeast</collection><collection>Primary Sources Access &amp; Build (Plan A) - South Central</collection><collection>Primary Sources Access &amp; Build (Plan A) - Southeast</collection><collection>Primary Sources Access (Plan D) - UK / I</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - APAC</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - MEA</collection><jtitle>Annals of the Association of American Geographers</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>OLSON, JUDY M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>AUTOCORRELATION AND VISUAL MAP COMPLEXITY</atitle><jtitle>Annals of the Association of American Geographers</jtitle><date>1975-06</date><risdate>1975</risdate><volume>65</volume><issue>2</issue><spage>189</spage><epage>204</epage><pages>189-204</pages><issn>0004-5608</issn><eissn>1467-8306</eissn><abstract>One important element in the overall look of a quantitative map is the relationship between neighboring values as they appear on the map, i.e., the autocorrelation in the map based on the classes into which the values fall. Methods of calculating this relationship objectively include rank autocorrelation; proportions of identical neighbors; average differences between neighboring values; number of clusters; and a weighted "proportion''value which includes a contribution from every neighboring pair, the amount of contribution varying inversely with the differences between the paired values. The first lag relationships appear to be most meaningful in terms of the visual appearance of hypothetical blocks of data ("maps"). Some of these measures are related to the way in which subjects order the blocks according to "spatial complexity,''although checkerboard patterns in particular introduce differences between measured and subjective sequences.</abstract><cop>Oxford, UK</cop><pub>Taylor &amp; Francis Group</pub><doi>10.1111/j.1467-8306.1975.tb01030.x</doi><tpages>16</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0004-5608
ispartof Annals of the Association of American Geographers, 1975-06, Vol.65 (2), p.189-204
issn 0004-5608
1467-8306
language eng
recordid cdi_proquest_journals_1296229323
source JSTOR Archival Journals and Primary Sources Collection
subjects Autocorrelation
Checkerboards
Complexity
Correlations
Geography
Hypothetical maps
Lag
Map skills
Mathematical sequences
Musical intervals
Neighborhoods
Quantitative maps
Testing of subjects
Visual map complexity
Zero
title AUTOCORRELATION AND VISUAL MAP COMPLEXITY
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-27T09%3A55%3A52IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-jstor_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=AUTOCORRELATION%20AND%20VISUAL%20MAP%20COMPLEXITY&rft.jtitle=Annals%20of%20the%20Association%20of%20American%20Geographers&rft.au=OLSON,%20JUDY%20M.&rft.date=1975-06&rft.volume=65&rft.issue=2&rft.spage=189&rft.epage=204&rft.pages=189-204&rft.issn=0004-5608&rft.eissn=1467-8306&rft_id=info:doi/10.1111/j.1467-8306.1975.tb01030.x&rft_dat=%3Cjstor_proqu%3E2562081%3C/jstor_proqu%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c4309-5542fd7de50bacd1386d5577d6859ad31c216e90857ce73189ed3e8731d513e73%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1296229323&rft_id=info:pmid/&rft_jstor_id=2562081&rfr_iscdi=true