Fuzzy-based spatial modeling approach to predict island karst distribution: a conceptual model
Previous studies have shown that island karst could successfully indicate paleoclimate change in the Quaternary Period. However, because of the relative inaccessibility of carbonate islands and their rural settings, the exploration of island karst features has been limited. To enhance future researc...
Gespeichert in:
Veröffentlicht in: | Environmental earth sciences 2014-02, Vol.71 (3), p.1369-1377 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 1377 |
---|---|
container_issue | 3 |
container_start_page | 1369 |
container_title | Environmental earth sciences |
container_volume | 71 |
creator | Ho, Hung Chak Mylroie, John E Infante, Louis R Rodgers, John C., III |
description | Previous studies have shown that island karst could successfully indicate paleoclimate change in the Quaternary Period. However, because of the relative inaccessibility of carbonate islands and their rural settings, the exploration of island karst features has been limited. To enhance future research, remote sensing and geospatial modeling were used in this study to improve the island karst exploration record. The results showed that fuzzy-based spatial modeling could successfully predict the island karst distributions on a simple carbonate island. The accuracy of the model was above 90 %. This method could apply to other coastal karst regions and carbonate islands in the future. |
doi_str_mv | 10.1007/s12665-013-2543-4 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1642248171</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1642248171</sourcerecordid><originalsourceid>FETCH-LOGICAL-a459t-b8620863800b3f4646d6094947301c2fd2693399748f812c5b396578862043923</originalsourceid><addsrcrecordid>eNqFkU9LHTEUxYfSQsX6AbpqoAjdTHvzZzKJuyJqC4KL6taQyWSesfMmY25moZ_ePEZFuqh3kwv5ncO5nKr6TOE7BWh_IGVSNjVQXrNG8Fq8q_aokrKWTOv3L7uCj9UB4i2U4ZRrkHvV9eny8HBfdxZ9T3C2OdiRbGPvxzBtiJ3nFK27ITmSOfk-uEwCjnbqyV-bMJM-YE6hW3KI0xGxxMXJ-Tkvzyafqg-DHdEfPL371dXpyeXxr_r84uz38c_z2opG57pTkoGSXAF0fBBSyF6CFlq0HKhjQ8-k5lzrVqhBUeaajmvZtGonE1wzvl99W31L3rvFYzbbgM6PJaqPCxoqBWNC0Za-jTYguRQcdEG__oPexiVN5RBDRYlbMjMoFF0plyJi8oOZU9jadG8omF0_Zu3HlH7Mrh8jiubwydmis-OQ7OQCvgiZYi1ItfNmK4fla9r49CrBf8y_rKLBRmM3qRhf_WFABQCFRpTzHgEX_KVR</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1486320820</pqid></control><display><type>article</type><title>Fuzzy-based spatial modeling approach to predict island karst distribution: a conceptual model</title><source>Springer journals</source><creator>Ho, Hung Chak ; Mylroie, John E ; Infante, Louis R ; Rodgers, John C., III</creator><creatorcontrib>Ho, Hung Chak ; Mylroie, John E ; Infante, Louis R ; Rodgers, John C., III</creatorcontrib><description>Previous studies have shown that island karst could successfully indicate paleoclimate change in the Quaternary Period. However, because of the relative inaccessibility of carbonate islands and their rural settings, the exploration of island karst features has been limited. To enhance future research, remote sensing and geospatial modeling were used in this study to improve the island karst exploration record. The results showed that fuzzy-based spatial modeling could successfully predict the island karst distributions on a simple carbonate island. The accuracy of the model was above 90 %. This method could apply to other coastal karst regions and carbonate islands in the future.</description><identifier>ISSN: 1866-6280</identifier><identifier>EISSN: 1866-6299</identifier><identifier>DOI: 10.1007/s12665-013-2543-4</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer-Verlag</publisher><subject>Applied geophysics ; Areal geology ; Areal geology. Maps ; Biogeosciences ; Carbonates ; Coastal ; Earth and Environmental Science ; Earth Sciences ; Earth, ocean, space ; Environmental science ; Environmental Science and Engineering ; Exact sciences and technology ; Exploration ; Geochemistry ; Geographic information systems ; Geologic maps, cartography ; Geology ; Geomorphology ; Hydrology/Water Resources ; Internal geophysics ; Islands ; Karst ; karsts ; Marine and continental quaternary ; Mathematical models ; Original Article ; Paleoclimate ; Paleoclimate science ; Quaternary ; Remote sensing ; Rural ; Surficial geology ; Terrestrial Pollution</subject><ispartof>Environmental earth sciences, 2014-02, Vol.71 (3), p.1369-1377</ispartof><rights>Springer-Verlag Berlin Heidelberg 2013</rights><rights>2015 INIST-CNRS</rights><rights>Springer-Verlag Berlin Heidelberg 2014</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a459t-b8620863800b3f4646d6094947301c2fd2693399748f812c5b396578862043923</citedby><cites>FETCH-LOGICAL-a459t-b8620863800b3f4646d6094947301c2fd2693399748f812c5b396578862043923</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s12665-013-2543-4$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s12665-013-2543-4$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27922,27923,41486,42555,51317</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=28270680$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Ho, Hung Chak</creatorcontrib><creatorcontrib>Mylroie, John E</creatorcontrib><creatorcontrib>Infante, Louis R</creatorcontrib><creatorcontrib>Rodgers, John C., III</creatorcontrib><title>Fuzzy-based spatial modeling approach to predict island karst distribution: a conceptual model</title><title>Environmental earth sciences</title><addtitle>Environ Earth Sci</addtitle><description>Previous studies have shown that island karst could successfully indicate paleoclimate change in the Quaternary Period. However, because of the relative inaccessibility of carbonate islands and their rural settings, the exploration of island karst features has been limited. To enhance future research, remote sensing and geospatial modeling were used in this study to improve the island karst exploration record. The results showed that fuzzy-based spatial modeling could successfully predict the island karst distributions on a simple carbonate island. The accuracy of the model was above 90 %. This method could apply to other coastal karst regions and carbonate islands in the future.</description><subject>Applied geophysics</subject><subject>Areal geology</subject><subject>Areal geology. Maps</subject><subject>Biogeosciences</subject><subject>Carbonates</subject><subject>Coastal</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Earth, ocean, space</subject><subject>Environmental science</subject><subject>Environmental Science and Engineering</subject><subject>Exact sciences and technology</subject><subject>Exploration</subject><subject>Geochemistry</subject><subject>Geographic information systems</subject><subject>Geologic maps, cartography</subject><subject>Geology</subject><subject>Geomorphology</subject><subject>Hydrology/Water Resources</subject><subject>Internal geophysics</subject><subject>Islands</subject><subject>Karst</subject><subject>karsts</subject><subject>Marine and continental quaternary</subject><subject>Mathematical models</subject><subject>Original Article</subject><subject>Paleoclimate</subject><subject>Paleoclimate science</subject><subject>Quaternary</subject><subject>Remote sensing</subject><subject>Rural</subject><subject>Surficial geology</subject><subject>Terrestrial Pollution</subject><issn>1866-6280</issn><issn>1866-6299</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqFkU9LHTEUxYfSQsX6AbpqoAjdTHvzZzKJuyJqC4KL6taQyWSesfMmY25moZ_ePEZFuqh3kwv5ncO5nKr6TOE7BWh_IGVSNjVQXrNG8Fq8q_aokrKWTOv3L7uCj9UB4i2U4ZRrkHvV9eny8HBfdxZ9T3C2OdiRbGPvxzBtiJ3nFK27ITmSOfk-uEwCjnbqyV-bMJM-YE6hW3KI0xGxxMXJ-Tkvzyafqg-DHdEfPL371dXpyeXxr_r84uz38c_z2opG57pTkoGSXAF0fBBSyF6CFlq0HKhjQ8-k5lzrVqhBUeaajmvZtGonE1wzvl99W31L3rvFYzbbgM6PJaqPCxoqBWNC0Za-jTYguRQcdEG__oPexiVN5RBDRYlbMjMoFF0plyJi8oOZU9jadG8omF0_Zu3HlH7Mrh8jiubwydmis-OQ7OQCvgiZYi1ItfNmK4fla9r49CrBf8y_rKLBRmM3qRhf_WFABQCFRpTzHgEX_KVR</recordid><startdate>20140201</startdate><enddate>20140201</enddate><creator>Ho, Hung Chak</creator><creator>Mylroie, John E</creator><creator>Infante, Louis R</creator><creator>Rodgers, John C., III</creator><general>Springer-Verlag</general><general>Springer Berlin Heidelberg</general><general>Springer</general><general>Springer Nature B.V</general><scope>FBQ</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7ST</scope><scope>7TG</scope><scope>7UA</scope><scope>7XB</scope><scope>88I</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>GNUQQ</scope><scope>H96</scope><scope>HCIFZ</scope><scope>KL.</scope><scope>L.G</scope><scope>M2P</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>SOI</scope><scope>7QH</scope><scope>7SC</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20140201</creationdate><title>Fuzzy-based spatial modeling approach to predict island karst distribution: a conceptual model</title><author>Ho, Hung Chak ; Mylroie, John E ; Infante, Louis R ; Rodgers, John C., III</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a459t-b8620863800b3f4646d6094947301c2fd2693399748f812c5b396578862043923</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Applied geophysics</topic><topic>Areal geology</topic><topic>Areal geology. Maps</topic><topic>Biogeosciences</topic><topic>Carbonates</topic><topic>Coastal</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Earth, ocean, space</topic><topic>Environmental science</topic><topic>Environmental Science and Engineering</topic><topic>Exact sciences and technology</topic><topic>Exploration</topic><topic>Geochemistry</topic><topic>Geographic information systems</topic><topic>Geologic maps, cartography</topic><topic>Geology</topic><topic>Geomorphology</topic><topic>Hydrology/Water Resources</topic><topic>Internal geophysics</topic><topic>Islands</topic><topic>Karst</topic><topic>karsts</topic><topic>Marine and continental quaternary</topic><topic>Mathematical models</topic><topic>Original Article</topic><topic>Paleoclimate</topic><topic>Paleoclimate science</topic><topic>Quaternary</topic><topic>Remote sensing</topic><topic>Rural</topic><topic>Surficial geology</topic><topic>Terrestrial Pollution</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ho, Hung Chak</creatorcontrib><creatorcontrib>Mylroie, John E</creatorcontrib><creatorcontrib>Infante, Louis R</creatorcontrib><creatorcontrib>Rodgers, John C., III</creatorcontrib><collection>AGRIS</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Environment Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>ProQuest Central Student</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>ProQuest Science Journals</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>Environment Abstracts</collection><collection>Aqualine</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Environmental earth sciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ho, Hung Chak</au><au>Mylroie, John E</au><au>Infante, Louis R</au><au>Rodgers, John C., III</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Fuzzy-based spatial modeling approach to predict island karst distribution: a conceptual model</atitle><jtitle>Environmental earth sciences</jtitle><stitle>Environ Earth Sci</stitle><date>2014-02-01</date><risdate>2014</risdate><volume>71</volume><issue>3</issue><spage>1369</spage><epage>1377</epage><pages>1369-1377</pages><issn>1866-6280</issn><eissn>1866-6299</eissn><abstract>Previous studies have shown that island karst could successfully indicate paleoclimate change in the Quaternary Period. However, because of the relative inaccessibility of carbonate islands and their rural settings, the exploration of island karst features has been limited. To enhance future research, remote sensing and geospatial modeling were used in this study to improve the island karst exploration record. The results showed that fuzzy-based spatial modeling could successfully predict the island karst distributions on a simple carbonate island. The accuracy of the model was above 90 %. This method could apply to other coastal karst regions and carbonate islands in the future.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer-Verlag</pub><doi>10.1007/s12665-013-2543-4</doi><tpages>9</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1866-6280 |
ispartof | Environmental earth sciences, 2014-02, Vol.71 (3), p.1369-1377 |
issn | 1866-6280 1866-6299 |
language | eng |
recordid | cdi_proquest_miscellaneous_1642248171 |
source | Springer journals |
subjects | Applied geophysics Areal geology Areal geology. Maps Biogeosciences Carbonates Coastal Earth and Environmental Science Earth Sciences Earth, ocean, space Environmental science Environmental Science and Engineering Exact sciences and technology Exploration Geochemistry Geographic information systems Geologic maps, cartography Geology Geomorphology Hydrology/Water Resources Internal geophysics Islands Karst karsts Marine and continental quaternary Mathematical models Original Article Paleoclimate Paleoclimate science Quaternary Remote sensing Rural Surficial geology Terrestrial Pollution |
title | Fuzzy-based spatial modeling approach to predict island karst distribution: a conceptual model |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-10T00%3A04%3A45IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Fuzzy-based%20spatial%20modeling%20approach%20to%20predict%20island%20karst%20distribution:%20a%20conceptual%20model&rft.jtitle=Environmental%20earth%20sciences&rft.au=Ho,%20Hung%20Chak&rft.date=2014-02-01&rft.volume=71&rft.issue=3&rft.spage=1369&rft.epage=1377&rft.pages=1369-1377&rft.issn=1866-6280&rft.eissn=1866-6299&rft_id=info:doi/10.1007/s12665-013-2543-4&rft_dat=%3Cproquest_cross%3E1642248171%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1486320820&rft_id=info:pmid/&rfr_iscdi=true |