{"id":"https://openalex.org/W175105586","doi":null,"title":"Least-Squares Matching with Airborne Laserscanning Data in a TIN Structure","display_name":"Least-Squares Matching with Airborne Laserscanning Data in a TIN Structure","publication_year":2000,"publication_date":"2000-01-01","ids":{"openalex":"https://openalex.org/W175105586","mag":"175105586"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.454.3308","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.454.3308","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.isprs.org/proceedings/XXXIII/congress/part3/548_XXXIII-part3.pdf","raw_type":"text"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5055212602","display_name":"Hans\u2010Gerd Maas","orcid":"https://orcid.org/0000-0001-9034-3469","observed_orcids":["https://orcid.org/0000-0001-9034-3469"]},"institutions":[{"id":"https://openalex.org/I78650965","display_name":"Technische Universit\u00e4t Dresden","ror":"https://ror.org/042aqky30","country_code":"DE","type":"education","lineage":["https://openalex.org/I78650965"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Hans\u2010Gerd Maas","raw_affiliation_strings":["Dresden Univ. of Technol"],"raw_orcid":"https://orcid.org/0000-0001-9034-3469","affiliations":[{"raw_affiliation_string":"Dresden Univ. of Technol","institution_ids":["https://openalex.org/I78650965"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5055212602"],"corresponding_institution_ids":["https://openalex.org/I78650965"],"apc_list":null,"apc_paid":null,"fwci":10.6212,"has_fulltext":false,"cited_by_count":75,"citation_normalized_percentile":{"value":0.97449664,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":98},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.7031000256538391,"subfield":{"id":"https://openalex.org/subfields/1107","display_name":"Forestry"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.7031000256538391,"subfield":{"id":"https://openalex.org/subfields/1107","display_name":"Forestry"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12983","display_name":"Satellite Image Processing and Photogrammetry","score":0.14489999413490295,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.1054999977350235,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/airborne-lidar","display_name":"airborne laser scanning","score":0.8759999871253967},{"id":"https://openalex.org/keywords/least-squares-matching","display_name":"least squares matching","score":0.8820000290870667},{"id":"https://openalex.org/keywords/triangulated-irregular-network","display_name":"triangulated irregular network","score":0.9860000014305115},{"id":"https://openalex.org/keywords/point-cloud-matching","display_name":"point cloud matching","score":0.6949999928474426},{"id":"https://openalex.org/keywords/partial-occlusion","display_name":"partial occlusion","score":0.7099999785423279},{"id":"https://openalex.org/keywords/precision-estimation","display_name":"precision estimation","score":0.492000013589859},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"covariance matrix","score":0.3919999897480011}],"concepts":[{"id":"https://openalex.org/C200925200","wikidata":"https://www.wikidata.org/wiki/Q7624170","display_name":"STRIPS","level":2,"score":0.6290870308876038},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.59427809715271},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.5836207866668701},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5482984185218811},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.5397874116897583},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5221703052520752},{"id":"https://openalex.org/C15627037","wikidata":"https://www.wikidata.org/wiki/Q541961","display_name":"Classification of discontinuities","level":2,"score":0.49473926424980164},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4427313208580017},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.41027557849884033},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36055654287338257},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2780206799507141},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.18532449007034302},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.454.3308","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.454.3308","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.isprs.org/proceedings/XXXIII/congress/part3/548_XXXIII-part3.pdf","raw_type":"text"},{"id":"mag:175105586","doi":null,"is_oa":false,"landing_page_url":"https://www.isprs.org/proceedings/XXXIII/congress/part3/548_XXXIII-part3.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W430276750","https://openalex.org/W1596936506","https://openalex.org/W1980980087","https://openalex.org/W2071859106","https://openalex.org/W2130722170","https://openalex.org/W2146733066","https://openalex.org/W2152151173","https://openalex.org/W2574149607"],"related_works":["https://openalex.org/W166499580","https://openalex.org/W2188547322","https://openalex.org/W430276750","https://openalex.org/W154591559","https://openalex.org/W7097739964","https://openalex.org/W1971710819","https://openalex.org/W7100022195","https://openalex.org/W2100961934","https://openalex.org/W2030304790","https://openalex.org/W2183637516"],"abstract_inverted_index":{"A":[0,245],"number":[1,143],"of":[2,10,58,111,118,127,144,154,168,185,192,248,265,275,291],"tasks":[3,27],"in":[4,68,86,115,157,211,222,272,278,284],"airborne":[5,159],"laserscanning":[6],"require":[7],"the":[8,53,64,80,112,116,125,152,177,183,186,190,212,216,219,249,262,266,273,292],"establishment":[9],"correspondences":[11],"between":[12,20],"point":[13,21,165,294],"data":[14,66,106,213],"from":[15,179,228],"neighbouring":[16],"strips,":[17],"or":[18],"referencing":[19],"clouds":[22],"and":[23,46,141,149,189,214,252,281],"object":[24],"models.":[25],"These":[26,270],"may":[28],"be":[29,98,203],"solved":[30],"by":[31,79,208,215],"interpolating":[32],"laserscanner":[33,105,197],"data,":[34],"which":[35],"are":[36,240,271],"usually":[37,241],"irregularly":[38],"distributed":[39],"21/2-D":[40],"points,":[41],"to":[42,104,135,151,196,202,205,236,256,288],"a":[43,56,69,128,142],"regular":[44],"grid":[45],"applying":[47,101],"standard":[48,263],"photo-grammetric":[49],"matching":[50,61,102,193,225],"techniques.":[51],"Instead,":[52],"paper":[54,175],"presents":[55],"formulation":[57,123],"least":[59,223],"squares":[60,224],"based":[62],"on":[63,124],"original":[65],"points":[67],"triangulated":[70],"irregular":[71],"network":[72],"structure,":[73],"thus":[74],"avoiding":[75],"degrading":[76],"effects":[77],"caused":[78,207],"interpo-lation.":[81],"The":[82,121,139,174,233],"technique":[83,140,188],"determines":[84],"shifts":[85],"all":[87],"three":[88],"coordinate":[89],"directions":[90],"together":[91],"with":[92,163,230],"their":[93],"covariance":[94],"matrix.":[95],"It":[96],"can":[97],"shown":[99],"that":[100,218,239],"techniques":[103,194],"causes":[107],"large":[108],"systematic":[109],"errors":[110,156],"shift":[113,268],"parameters":[114],"case":[117],"partial":[119],"occlusions.":[120],"presented":[122,187],"basis":[126],"TIN":[129],"structure":[130],"allows":[131],"for":[132,261],"manifold":[133],"extensions":[134,145],"solve":[136],"this":[137,180],"problem.":[138],"have":[146],"been":[147],"implemented":[148],"applied":[150,195],"measurement":[153],"strip":[155],"an":[158],"laser":[160],"scanner":[161],"dataset":[162],"moderate":[164],"density,":[166],"consisting":[167],"20":[169],"strips":[170],"including":[171],"crossing":[172],"strips.":[173],"shows":[176],"results":[178],"test,":[181],"discusses":[182],"advantages":[184],"limitations":[191],"data.":[198],"Special":[199],"attention":[200],"has":[201],"paid":[204],"problems":[206],"height":[209,279],"discontinuities":[210],"fact":[217],"design":[220,250],"matrix":[221,251],"is":[226],"derived":[227],"observations":[229],"stochastic":[231],"properties.":[232],"latter":[234],"leads":[235],"precision":[237,259],"figures":[238,260],"much":[242],"too":[243],"optimistic.":[244],"detailed":[246],"analysis":[247],"extensive":[253],"testing":[254],"lead":[255],"better":[257],"funded":[258],"deviation":[264],"obtained":[267],"parameters.":[269],"order":[274],"one":[276,282],"centimeter":[277],"direction":[280],"decimeter":[283],"horizontal":[285],"direction,":[286],"corresponding":[287],"about":[289],"1/20th":[290],"average":[293],"spacing.":[295]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":4},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":6}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2016-06-24T00:00:00"}