Loading…

CLASSIFICATION OF DUAL-WAVELENGTH AIRBORNE LASER SCANNING POINT CLOUD BASED ON THE RADIOMETRIC PROPERTIES OF THE OBJECTS

Airborne laser scanning (ALS) is a well-known and willingly used technology. One of the advantages of this technology is primarily its fast and accurate data registration. In recent years ALS is continuously developed. One of the latest achievements is multispectral ALS, which consists in obtaining...

Full description

Saved in:
Bibliographic Details
Published in:International archives of the photogrammetry, remote sensing and spatial information sciences. remote sensing and spatial information sciences., 2018-05, Vol.XLII-2, p.901-907
Main Author: Pilarska, M.
Format: Article
Language:English
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-c3088-124ef95f8c6ac07320b32c8732e4bafda3e6d1d7dec6bdc647d0082858a0bbd13
cites
container_end_page 907
container_issue
container_start_page 901
container_title International archives of the photogrammetry, remote sensing and spatial information sciences.
container_volume XLII-2
creator Pilarska, M.
description Airborne laser scanning (ALS) is a well-known and willingly used technology. One of the advantages of this technology is primarily its fast and accurate data registration. In recent years ALS is continuously developed. One of the latest achievements is multispectral ALS, which consists in obtaining simultaneously the data in more than one laser wavelength. In this article the results of the dual-wavelength ALS data classification are presented. The data were acquired with RIEGL VQ-1560i sensor, which is equipped with two laser scanners operating in different wavelengths: 532 nm and 1064 nm. Two classification approaches are presented in the article: classification, which is based on geometric relationships between points and classification, which mostly relies on the radiometric properties of registered objects. The overall accuracy of the geometric classification was 86 %, whereas for the radiometric classification it was 81 %. As a result, it can be assumed that the radiometric features which are provided by the multispectral ALS have potential to be successfully used in ALS point cloud classification.
doi_str_mv 10.5194/isprs-archives-XLII-2-901-2018
format article
fullrecord <record><control><sourceid>doaj_cross</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_5d2da321cdc9437ca487d0170e9107e1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_5d2da321cdc9437ca487d0170e9107e1</doaj_id><sourcerecordid>oai_doaj_org_article_5d2da321cdc9437ca487d0170e9107e1</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3088-124ef95f8c6ac07320b32c8732e4bafda3e6d1d7dec6bdc647d0082858a0bbd13</originalsourceid><addsrcrecordid>eNpNkU1LwzAYgIsoOOb-Q07eokn6lV6Ersu2SG1G26m3kCapVpSNVkT_vemm4un9fnjh8bxLjK5CnATX3bDvB6h6_dx92AE-5pxDAhOEIUGYnngT4rZc7Qen__JzbzYMLwghHERRiMKJ95nlaVXxJc_SmosCiCVYbNMcPqT3LGfFql6DlJdzURYMuE1WgipLi4IXK7ARvKhBlovtAszdaAHcfb1moEwXXNyxuuQZ2JRiw8qas2pEj1Mxv2VZXV14Z616HezsJ0697ZLV2RrmYuWeyaH2EaUQk8C2SdhSHSmNYp-gxieausQGjWqN8m1ksImN1VFjdBTEBiFKaEgVahqD_anHj1yzUy9y33dvqv-SO9XJQ2PXP0nVv3f61crQEMcjWBudBH6sVUAdDcfIJhjFdmTdHFm63w1Db9s_HkZy1CIPWuSvFjlqkUQ6LXLU4n8DeMF9AA</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>CLASSIFICATION OF DUAL-WAVELENGTH AIRBORNE LASER SCANNING POINT CLOUD BASED ON THE RADIOMETRIC PROPERTIES OF THE OBJECTS</title><source>Free E-Journal (出版社公開部分のみ)</source><source>ProQuest - Publicly Available Content Database</source><creator>Pilarska, M.</creator><creatorcontrib>Pilarska, M.</creatorcontrib><description>Airborne laser scanning (ALS) is a well-known and willingly used technology. One of the advantages of this technology is primarily its fast and accurate data registration. In recent years ALS is continuously developed. One of the latest achievements is multispectral ALS, which consists in obtaining simultaneously the data in more than one laser wavelength. In this article the results of the dual-wavelength ALS data classification are presented. The data were acquired with RIEGL VQ-1560i sensor, which is equipped with two laser scanners operating in different wavelengths: 532 nm and 1064 nm. Two classification approaches are presented in the article: classification, which is based on geometric relationships between points and classification, which mostly relies on the radiometric properties of registered objects. The overall accuracy of the geometric classification was 86 %, whereas for the radiometric classification it was 81 %. As a result, it can be assumed that the radiometric features which are provided by the multispectral ALS have potential to be successfully used in ALS point cloud classification.</description><identifier>ISSN: 2194-9034</identifier><identifier>ISSN: 1682-1750</identifier><identifier>EISSN: 2194-9034</identifier><identifier>DOI: 10.5194/isprs-archives-XLII-2-901-2018</identifier><language>eng</language><publisher>Copernicus Publications</publisher><ispartof>International archives of the photogrammetry, remote sensing and spatial information sciences., 2018-05, Vol.XLII-2, p.901-907</ispartof><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3088-124ef95f8c6ac07320b32c8732e4bafda3e6d1d7dec6bdc647d0082858a0bbd13</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27923,27924</link.rule.ids></links><search><creatorcontrib>Pilarska, M.</creatorcontrib><title>CLASSIFICATION OF DUAL-WAVELENGTH AIRBORNE LASER SCANNING POINT CLOUD BASED ON THE RADIOMETRIC PROPERTIES OF THE OBJECTS</title><title>International archives of the photogrammetry, remote sensing and spatial information sciences.</title><description>Airborne laser scanning (ALS) is a well-known and willingly used technology. One of the advantages of this technology is primarily its fast and accurate data registration. In recent years ALS is continuously developed. One of the latest achievements is multispectral ALS, which consists in obtaining simultaneously the data in more than one laser wavelength. In this article the results of the dual-wavelength ALS data classification are presented. The data were acquired with RIEGL VQ-1560i sensor, which is equipped with two laser scanners operating in different wavelengths: 532 nm and 1064 nm. Two classification approaches are presented in the article: classification, which is based on geometric relationships between points and classification, which mostly relies on the radiometric properties of registered objects. The overall accuracy of the geometric classification was 86 %, whereas for the radiometric classification it was 81 %. As a result, it can be assumed that the radiometric features which are provided by the multispectral ALS have potential to be successfully used in ALS point cloud classification.</description><issn>2194-9034</issn><issn>1682-1750</issn><issn>2194-9034</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNpNkU1LwzAYgIsoOOb-Q07eokn6lV6Ersu2SG1G26m3kCapVpSNVkT_vemm4un9fnjh8bxLjK5CnATX3bDvB6h6_dx92AE-5pxDAhOEIUGYnngT4rZc7Qen__JzbzYMLwghHERRiMKJ95nlaVXxJc_SmosCiCVYbNMcPqT3LGfFql6DlJdzURYMuE1WgipLi4IXK7ARvKhBlovtAszdaAHcfb1moEwXXNyxuuQZ2JRiw8qas2pEj1Mxv2VZXV14Z616HezsJ0697ZLV2RrmYuWeyaH2EaUQk8C2SdhSHSmNYp-gxieausQGjWqN8m1ksImN1VFjdBTEBiFKaEgVahqD_anHj1yzUy9y33dvqv-SO9XJQ2PXP0nVv3f61crQEMcjWBudBH6sVUAdDcfIJhjFdmTdHFm63w1Db9s_HkZy1CIPWuSvFjlqkUQ6LXLU4n8DeMF9AA</recordid><startdate>20180530</startdate><enddate>20180530</enddate><creator>Pilarska, M.</creator><general>Copernicus Publications</general><scope>AAYXX</scope><scope>CITATION</scope><scope>DOA</scope></search><sort><creationdate>20180530</creationdate><title>CLASSIFICATION OF DUAL-WAVELENGTH AIRBORNE LASER SCANNING POINT CLOUD BASED ON THE RADIOMETRIC PROPERTIES OF THE OBJECTS</title><author>Pilarska, M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3088-124ef95f8c6ac07320b32c8732e4bafda3e6d1d7dec6bdc647d0082858a0bbd13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pilarska, M.</creatorcontrib><collection>CrossRef</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>International archives of the photogrammetry, remote sensing and spatial information sciences.</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pilarska, M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>CLASSIFICATION OF DUAL-WAVELENGTH AIRBORNE LASER SCANNING POINT CLOUD BASED ON THE RADIOMETRIC PROPERTIES OF THE OBJECTS</atitle><jtitle>International archives of the photogrammetry, remote sensing and spatial information sciences.</jtitle><date>2018-05-30</date><risdate>2018</risdate><volume>XLII-2</volume><spage>901</spage><epage>907</epage><pages>901-907</pages><issn>2194-9034</issn><issn>1682-1750</issn><eissn>2194-9034</eissn><abstract>Airborne laser scanning (ALS) is a well-known and willingly used technology. One of the advantages of this technology is primarily its fast and accurate data registration. In recent years ALS is continuously developed. One of the latest achievements is multispectral ALS, which consists in obtaining simultaneously the data in more than one laser wavelength. In this article the results of the dual-wavelength ALS data classification are presented. The data were acquired with RIEGL VQ-1560i sensor, which is equipped with two laser scanners operating in different wavelengths: 532 nm and 1064 nm. Two classification approaches are presented in the article: classification, which is based on geometric relationships between points and classification, which mostly relies on the radiometric properties of registered objects. The overall accuracy of the geometric classification was 86 %, whereas for the radiometric classification it was 81 %. As a result, it can be assumed that the radiometric features which are provided by the multispectral ALS have potential to be successfully used in ALS point cloud classification.</abstract><pub>Copernicus Publications</pub><doi>10.5194/isprs-archives-XLII-2-901-2018</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2194-9034
ispartof International archives of the photogrammetry, remote sensing and spatial information sciences., 2018-05, Vol.XLII-2, p.901-907
issn 2194-9034
1682-1750
2194-9034
language eng
recordid cdi_doaj_primary_oai_doaj_org_article_5d2da321cdc9437ca487d0170e9107e1
source Free E-Journal (出版社公開部分のみ); ProQuest - Publicly Available Content Database
title CLASSIFICATION OF DUAL-WAVELENGTH AIRBORNE LASER SCANNING POINT CLOUD BASED ON THE RADIOMETRIC PROPERTIES OF THE OBJECTS
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-08T09%3A00%3A12IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-doaj_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=CLASSIFICATION%20OF%20DUAL-WAVELENGTH%20AIRBORNE%20LASER%20SCANNING%20POINT%20CLOUD%20BASED%20ON%20THE%20RADIOMETRIC%20PROPERTIES%20OF%20THE%20OBJECTS&rft.jtitle=International%20archives%20of%20the%20photogrammetry,%20remote%20sensing%20and%20spatial%20information%20sciences.&rft.au=Pilarska,%20M.&rft.date=2018-05-30&rft.volume=XLII-2&rft.spage=901&rft.epage=907&rft.pages=901-907&rft.issn=2194-9034&rft.eissn=2194-9034&rft_id=info:doi/10.5194/isprs-archives-XLII-2-901-2018&rft_dat=%3Cdoaj_cross%3Eoai_doaj_org_article_5d2da321cdc9437ca487d0170e9107e1%3C/doaj_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c3088-124ef95f8c6ac07320b32c8732e4bafda3e6d1d7dec6bdc647d0082858a0bbd13%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true