{"id":"https://openalex.org/W61401707","doi":null,"title":"AUTOMATIC EXTRACTION OF TREES FROM AERIAL IMAGES AND SURFACE MODELS","display_name":"AUTOMATIC EXTRACTION OF TREES FROM AERIAL IMAGES AND SURFACE MODELS","publication_year":2003,"publication_date":"2003-01-01","ids":{"openalex":"https://openalex.org/W61401707","mag":"61401707"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.126.4448","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.126.4448","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.commission3.isprs.org/pia/papers/pia03_s6p4.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/A5007191013","display_name":"Bernd-M. Straub","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I114112103","display_name":"Leibniz University Hannover","ror":"https://ror.org/0304hq317","country_code":"DE","type":"education","lineage":["https://openalex.org/I114112103"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Bernd-M. Straub","raw_affiliation_strings":["Leibniz University of Hanover"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Leibniz University of Hanover","institution_ids":["https://openalex.org/I114112103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5007191013"],"corresponding_institution_ids":["https://openalex.org/I114112103"],"apc_list":null,"apc_paid":null,"fwci":1.5446,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.83587162,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":96},"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":0.6021000146865845,"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":0.6021000146865845,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.1907999962568283,"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":0.031199999153614044,"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/tree-extraction","display_name":"tree extraction","score":0.8050000071525574},{"id":"https://openalex.org/keywords/surface-models","display_name":"surface models","score":0.9319999814033508},{"id":"https://openalex.org/keywords/linear-scale-space","display_name":"linear scale-space","score":0.8820000290870667},{"id":"https://openalex.org/keywords/multiscale-representation","display_name":"multi-scale representation","score":0.9380000233650208},{"id":"https://openalex.org/keywords/watershed-segmentation","display_name":"watershed segmentation","score":0.6830000281333923},{"id":"https://openalex.org/keywords/snakes","display_name":"snakes","score":0.9409999847412109},{"id":"https://openalex.org/keywords/laser-scanning","display_name":"laser scanning","score":0.6010000109672546},{"id":"https://openalex.org/keywords/image-matching","display_name":"image matching","score":0.9179999828338623},{"id":"https://openalex.org/keywords/forest-mapping","display_name":"forest mapping","score":0.3370000123977661}],"concepts":[{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5937498211860657},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.5828514099121094},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5638449788093567},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5406320691108704},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.523157000541687},{"id":"https://openalex.org/C82789328","wikidata":"https://www.wikidata.org/wiki/Q922585","display_name":"Orthophoto","level":2,"score":0.5198608040809631},{"id":"https://openalex.org/C99102927","wikidata":"https://www.wikidata.org/wiki/Q3058184","display_name":"Scale space","level":4,"score":0.5122553706169128},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5000855922698975},{"id":"https://openalex.org/C57489055","wikidata":"https://www.wikidata.org/wiki/Q190046","display_name":"Ellipsoid","level":2,"score":0.49554240703582764},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.4896896183490753},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4762168824672699},{"id":"https://openalex.org/C141349535","wikidata":"https://www.wikidata.org/wiki/Q1361664","display_name":"Laser scanning","level":3,"score":0.4652149975299835},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.4573374390602112},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45647627115249634},{"id":"https://openalex.org/C117455697","wikidata":"https://www.wikidata.org/wiki/Q190149","display_name":"Photogrammetry","level":2,"score":0.4462526738643646},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4437383711338043},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3806380033493042},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2500254809856415},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.2389160692691803},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.19316968321800232},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.15418586134910583},{"id":"https://openalex.org/C520434653","wikidata":"https://www.wikidata.org/wiki/Q38867","display_name":"Laser","level":2,"score":0.08767154812812805},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.08573752641677856},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0835425853729248},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.08033031225204468},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.126.4448","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.126.4448","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.commission3.isprs.org/pia/papers/pia03_s6p4.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.505.553","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.505.553","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ipi.uni-hannover.de/uploads/tx_tkpublikationen/straub-pia_red.pdf","raw_type":"text"},{"id":"mag:61401707","doi":null,"is_oa":false,"landing_page_url":"https://www.isprs.org/proceedings/XXXIV/3-W8/papers/pia03_s6p4.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":23,"referenced_works":["https://openalex.org/W571981728","https://openalex.org/W1523554224","https://openalex.org/W1561442812","https://openalex.org/W1636819276","https://openalex.org/W1701745718","https://openalex.org/W1978683887","https://openalex.org/W2005073772","https://openalex.org/W2012080718","https://openalex.org/W2014590262","https://openalex.org/W2022735534","https://openalex.org/W2046428581","https://openalex.org/W2061274743","https://openalex.org/W2086921140","https://openalex.org/W2104095591","https://openalex.org/W2112328181","https://openalex.org/W2128147491","https://openalex.org/W2131172512","https://openalex.org/W2152660071","https://openalex.org/W2252347002","https://openalex.org/W2312997001","https://openalex.org/W2912565176","https://openalex.org/W3211330693","https://openalex.org/W7165773520"],"related_works":["https://openalex.org/W7095427473","https://openalex.org/W2135679817","https://openalex.org/W7095121793","https://openalex.org/W1978683887","https://openalex.org/W119129722","https://openalex.org/W2184045687","https://openalex.org/W2391092731","https://openalex.org/W2316194814","https://openalex.org/W2061274743","https://openalex.org/W2363224849"],"abstract_inverted_index":{"In":[0],"this":[1,96,116],"paper":[2,197],"we":[3],"present":[4],"an":[5,29,62,84],"approach":[6,21,43,166,192],"for":[7,134],"the":[8,14,17,42,46,50,56,69,73,78,88,92,106,110,131,145,151,191,196],"automatic":[9],"extraction":[10],"of":[11,16,28,41,49,58,72,87,91,109,115,125,144,156,172,190],"trees":[12],"and":[13,31,77,128,177,180,185,198],"boundaries":[15],"tree\u2019s":[18],"crowns.":[19],"The":[20,39,112,142,154,165],"is":[22,44,66,75,81,99,103,119,148,159,193],"based":[23],"on":[24],"a":[25,32,59,122,135],"multi-scale":[26,89],"representation":[27,90],"orthoimage":[30],"surface":[33,93,146,170],"model":[34,147],"in":[35,83,195],"Linear":[36],"Scale":[37],"Space.":[38],"idea":[40],"that":[45],"coarse":[47,79],"structure":[48,71,80],"crown":[51,74,136,158],"can":[52],"be":[53],"approximated":[54],"with":[55,105,161,169],"help":[57],"sphere":[60],"or":[61],"ellipsoid.":[63],"This":[64],"assumption":[65],"true,":[67],"if":[68],"fine":[70],"ignored":[76],"revealed":[82],"appropriate":[85],"level":[86,98],"model.":[94],"But":[95],"scale":[97,126,140],"unknown,":[100],"because":[101],"it":[102],"correlated":[104],"unknown":[107],"diameter":[108],"crown.":[111],"proposed":[113],"solution":[114],"chicken-and-egg":[117],"problem":[118],"to":[120,129],"investigate":[121],"wide":[123],"range":[124],"levels,":[127],"select":[130],"best":[132],"hypothesis":[133],"from":[137],"all":[138],"these":[139],"levels.":[141],"segmentation":[143],"performed":[149],"using":[150],"watershed":[152],"transformation.":[153],"boundary":[155],"every":[157],"measured":[160],"Active":[162],"Contours":[163],"(Snakes).":[164],"was":[167],"tested":[168],"models":[171],"different":[173,181],"resolutions":[174],"(0.25":[175],"m":[176],"1":[178],"m)":[179],"sensors,":[182],"laser":[183],"scanner":[184],"image":[186],"matching.":[187],"An":[188],"overview":[189],"given":[194],"important":[199],"points":[200],"are":[201],"discussed.":[202],"1.":[203]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2016-06-24T00:00:00"}
