Loading…

Object-oriented per-parcel land use classification of very high resolution images

The traditional method to gain information on land use in urban areas is based on the visual interpretation of very high resolution aerial photographs; a process which is both time consuming and expensive. Very high resolution satellite data are an alternative for updating and maintaining cartograph...

Full description

Saved in:
Bibliographic Details
Main Authors: Kressler, F.P., Bauer, T.B., Steinnocher, K.T.
Format: Conference Proceeding
Language:English
Subjects:
Citations: Items that cite this one
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c219t-b96631341615163902a946bd059562553b3cd255b752ee327c0cdfa49c1d35493
cites
container_end_page 167
container_issue
container_start_page 164
container_title
container_volume
creator Kressler, F.P.
Bauer, T.B.
Steinnocher, K.T.
description The traditional method to gain information on land use in urban areas is based on the visual interpretation of very high resolution aerial photographs; a process which is both time consuming and expensive. Very high resolution satellite data are an alternative for updating and maintaining cartographic and geographic data bases. If the full potential of the new image data is to be realized for urban land use mapping, new inferential remote-sensing analysis tools need to be applied. This is because urban land use is an abstract concept which is defined in terms of function rather than form. This paper investigates the potential of an object-oriented classification approach to discriminate between different urban land use categories from panchromatic and multispectral IKONOS-2 data, covering parts of the City of Vienna. In order to validate the results, the classification was compared with a land use data set created by the City Council of Vienna (MA-41) on the basis of orthophotos.
doi_str_mv 10.1109/DFUA.2001.985866
format conference_proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_985866</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>985866</ieee_id><sourcerecordid>985866</sourcerecordid><originalsourceid>FETCH-LOGICAL-c219t-b96631341615163902a946bd059562553b3cd255b752ee327c0cdfa49c1d35493</originalsourceid><addsrcrecordid>eNotT91KwzAYDYigzN6LV3mB1iRfkjaXYzoVBkNw1yNNvm4ZsS1JJ-ztLc7DgQPn4vwQ8shZxTkzzy_r3bISjPHKNKrR-oYUpm7YTKiZMnBHipxPbIZUEmp-Tz637QndVA4pYD-hpyOmcrTJYaTR9p6eM1IXbc6hC85OYejp0NEfTBd6DIcjTZiHeP7zw7c9YH4gt52NGYt_XZDd-vVr9V5utm8fq-WmdIKbqWyN1sBBcs0V12CYsEbq1s8zlRZKQQvOz9rWSiCCqB1zvrPSOO5BSQML8nTNDYi4H9Pcni7762_4BbAhTTc</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Object-oriented per-parcel land use classification of very high resolution images</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Kressler, F.P. ; Bauer, T.B. ; Steinnocher, K.T.</creator><creatorcontrib>Kressler, F.P. ; Bauer, T.B. ; Steinnocher, K.T.</creatorcontrib><description>The traditional method to gain information on land use in urban areas is based on the visual interpretation of very high resolution aerial photographs; a process which is both time consuming and expensive. Very high resolution satellite data are an alternative for updating and maintaining cartographic and geographic data bases. If the full potential of the new image data is to be realized for urban land use mapping, new inferential remote-sensing analysis tools need to be applied. This is because urban land use is an abstract concept which is defined in terms of function rather than form. This paper investigates the potential of an object-oriented classification approach to discriminate between different urban land use categories from panchromatic and multispectral IKONOS-2 data, covering parts of the City of Vienna. In order to validate the results, the classification was compared with a land use data set created by the City Council of Vienna (MA-41) on the basis of orthophotos.</description><identifier>ISBN: 9780780370593</identifier><identifier>ISBN: 0780370597</identifier><identifier>DOI: 10.1109/DFUA.2001.985866</identifier><language>eng</language><publisher>IEEE</publisher><subject>Cities and towns ; Councils ; Image analysis ; Image resolution ; Multispectral imaging ; Object recognition ; Remote sensing ; Satellites ; Spatial resolution ; Urban areas</subject><ispartof>IEEE/ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas (Cat. No.01EX482), 2001, p.164-167</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c219t-b96631341615163902a946bd059562553b3cd255b752ee327c0cdfa49c1d35493</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/985866$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2056,4047,4048,27923,54918</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/985866$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Kressler, F.P.</creatorcontrib><creatorcontrib>Bauer, T.B.</creatorcontrib><creatorcontrib>Steinnocher, K.T.</creatorcontrib><title>Object-oriented per-parcel land use classification of very high resolution images</title><title>IEEE/ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas (Cat. No.01EX482)</title><addtitle>DFUA</addtitle><description>The traditional method to gain information on land use in urban areas is based on the visual interpretation of very high resolution aerial photographs; a process which is both time consuming and expensive. Very high resolution satellite data are an alternative for updating and maintaining cartographic and geographic data bases. If the full potential of the new image data is to be realized for urban land use mapping, new inferential remote-sensing analysis tools need to be applied. This is because urban land use is an abstract concept which is defined in terms of function rather than form. This paper investigates the potential of an object-oriented classification approach to discriminate between different urban land use categories from panchromatic and multispectral IKONOS-2 data, covering parts of the City of Vienna. In order to validate the results, the classification was compared with a land use data set created by the City Council of Vienna (MA-41) on the basis of orthophotos.</description><subject>Cities and towns</subject><subject>Councils</subject><subject>Image analysis</subject><subject>Image resolution</subject><subject>Multispectral imaging</subject><subject>Object recognition</subject><subject>Remote sensing</subject><subject>Satellites</subject><subject>Spatial resolution</subject><subject>Urban areas</subject><isbn>9780780370593</isbn><isbn>0780370597</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2001</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotT91KwzAYDYigzN6LV3mB1iRfkjaXYzoVBkNw1yNNvm4ZsS1JJ-ztLc7DgQPn4vwQ8shZxTkzzy_r3bISjPHKNKrR-oYUpm7YTKiZMnBHipxPbIZUEmp-Tz637QndVA4pYD-hpyOmcrTJYaTR9p6eM1IXbc6hC85OYejp0NEfTBd6DIcjTZiHeP7zw7c9YH4gt52NGYt_XZDd-vVr9V5utm8fq-WmdIKbqWyN1sBBcs0V12CYsEbq1s8zlRZKQQvOz9rWSiCCqB1zvrPSOO5BSQML8nTNDYi4H9Pcni7762_4BbAhTTc</recordid><startdate>2001</startdate><enddate>2001</enddate><creator>Kressler, F.P.</creator><creator>Bauer, T.B.</creator><creator>Steinnocher, K.T.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2001</creationdate><title>Object-oriented per-parcel land use classification of very high resolution images</title><author>Kressler, F.P. ; Bauer, T.B. ; Steinnocher, K.T.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c219t-b96631341615163902a946bd059562553b3cd255b752ee327c0cdfa49c1d35493</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2001</creationdate><topic>Cities and towns</topic><topic>Councils</topic><topic>Image analysis</topic><topic>Image resolution</topic><topic>Multispectral imaging</topic><topic>Object recognition</topic><topic>Remote sensing</topic><topic>Satellites</topic><topic>Spatial resolution</topic><topic>Urban areas</topic><toplevel>online_resources</toplevel><creatorcontrib>Kressler, F.P.</creatorcontrib><creatorcontrib>Bauer, T.B.</creatorcontrib><creatorcontrib>Steinnocher, K.T.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore Digital Library</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Kressler, F.P.</au><au>Bauer, T.B.</au><au>Steinnocher, K.T.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Object-oriented per-parcel land use classification of very high resolution images</atitle><btitle>IEEE/ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas (Cat. No.01EX482)</btitle><stitle>DFUA</stitle><date>2001</date><risdate>2001</risdate><spage>164</spage><epage>167</epage><pages>164-167</pages><isbn>9780780370593</isbn><isbn>0780370597</isbn><abstract>The traditional method to gain information on land use in urban areas is based on the visual interpretation of very high resolution aerial photographs; a process which is both time consuming and expensive. Very high resolution satellite data are an alternative for updating and maintaining cartographic and geographic data bases. If the full potential of the new image data is to be realized for urban land use mapping, new inferential remote-sensing analysis tools need to be applied. This is because urban land use is an abstract concept which is defined in terms of function rather than form. This paper investigates the potential of an object-oriented classification approach to discriminate between different urban land use categories from panchromatic and multispectral IKONOS-2 data, covering parts of the City of Vienna. In order to validate the results, the classification was compared with a land use data set created by the City Council of Vienna (MA-41) on the basis of orthophotos.</abstract><pub>IEEE</pub><doi>10.1109/DFUA.2001.985866</doi><tpages>4</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISBN: 9780780370593
ispartof IEEE/ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas (Cat. No.01EX482), 2001, p.164-167
issn
language eng
recordid cdi_ieee_primary_985866
source IEEE Electronic Library (IEL) Conference Proceedings
subjects Cities and towns
Councils
Image analysis
Image resolution
Multispectral imaging
Object recognition
Remote sensing
Satellites
Spatial resolution
Urban areas
title Object-oriented per-parcel land use classification of very high resolution images
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-14T12%3A06%3A04IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Object-oriented%20per-parcel%20land%20use%20classification%20of%20very%20high%20resolution%20images&rft.btitle=IEEE/ISPRS%20Joint%20Workshop%20on%20Remote%20Sensing%20and%20Data%20Fusion%20over%20Urban%20Areas%20(Cat.%20No.01EX482)&rft.au=Kressler,%20F.P.&rft.date=2001&rft.spage=164&rft.epage=167&rft.pages=164-167&rft.isbn=9780780370593&rft.isbn_list=0780370597&rft_id=info:doi/10.1109/DFUA.2001.985866&rft_dat=%3Cieee_6IE%3E985866%3C/ieee_6IE%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c219t-b96631341615163902a946bd059562553b3cd255b752ee327c0cdfa49c1d35493%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=985866&rfr_iscdi=true