{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T10:18:11Z","timestamp":1742984291780,"version":"3.40.3"},"publisher-location":"Cham","reference-count":15,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030490751"},{"type":"electronic","value":"9783030490768"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-49076-8_17","type":"book-chapter","created":{"date-parts":[[2020,6,16]],"date-time":"2020-06-16T23:04:52Z","timestamp":1592348692000},"page":"172-182","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Structured Pointcloud Segmentation for Individual Mangrove Tree Modeling"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7091-4372","authenticated-orcid":false,"given":"Jos\u00e9 L.","family":"Silv\u00e1n-C\u00e1rdenas","sequence":"first","affiliation":[]},{"given":"Jos\u00e9 A.","family":"Gallardo-Cruz","sequence":"additional","affiliation":[]},{"given":"Laura M.","family":"Hern\u00e1ndez-Huerta","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,6,17]]},"reference":[{"key":"17_CR1","doi-asserted-by":"crossref","unstructured":"Bucksch, A., Lindenbergh, R., Menenti, M., Rahman, M.Z.: Skeleton-based botanic tree diameter estimation from dense lidar data. In: Lidar Remote Sensing for Environmental Monitoring X. vol. 7460, p. 746007. International Society for Optics and Photonics (2009)","DOI":"10.1117\/12.825997"},{"issue":"5","key":"17_CR2","doi-asserted-by":"publisher","first-page":"1067","DOI":"10.1016\/j.rse.2009.01.017","volume":"113","author":"JF C\u00f4t\u00e9","year":"2009","unstructured":"C\u00f4t\u00e9, J.F., Widlowski, J.L., Fournier, R.A., Verstraete, M.M.: The structural and radiative consistency of three-dimensional tree reconstructions from terrestrial lidar. Remote Sens. Environ. 113(5), 1067\u20131081 (2009)","journal-title":"Remote Sens. Environ."},{"issue":"5","key":"17_CR3","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1038\/ngeo1123","volume":"4","author":"DC Donato","year":"2011","unstructured":"Donato, D.C., Kauffman, J.B., Murdiyarso, D., Kurnianto, S., Stidham, M., Kanninen, M.: Mangroves among the most carbon-rich forests in the tropics. Nat. Geosci. 4(5), 293 (2011)","journal-title":"Nat. Geosci."},{"issue":"6","key":"17_CR4","doi-asserted-by":"publisher","first-page":"1148","DOI":"10.1016\/j.rse.2009.02.010","volume":"113","author":"A Kato","year":"2009","unstructured":"Kato, A., Moskal, L.M., Schiess, P., Swanson, M.E., Calhoun, D., Stuetzle, W.: Capturing tree crown formation through implicit surface reconstruction using airborne lidar data. Remote Sens. Environ. 113(6), 1148\u20131162 (2009)","journal-title":"Remote Sens. Environ."},{"issue":"1","key":"17_CR5","doi-asserted-by":"publisher","first-page":"75","DOI":"10.14358\/PERS.78.1.75","volume":"78","author":"W Li","year":"2012","unstructured":"Li, W., Guo, Q., Jakubowski, M.K., Kelly, M.: A new method for segmenting individual trees from the lidar point cloud. Photogramm. Eng. Remote Sensing 78(1), 75\u201384 (2012)","journal-title":"Photogramm. Eng. Remote Sensing"},{"issue":"8","key":"17_CR6","doi-asserted-by":"publisher","first-page":"1076","DOI":"10.1016\/j.cageo.2006.11.012","volume":"33","author":"G Miliaresis","year":"2007","unstructured":"Miliaresis, G., Kokkas, N.: Segmentation and object-based classification for the extraction of the building class from lidar dems. Comput. Geosci. 33(8), 1076\u20131087 (2007)","journal-title":"Comput. Geosci."},{"issue":"3","key":"17_CR7","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1016\/j.rse.2004.05.013","volume":"92","author":"F Morsdorf","year":"2004","unstructured":"Morsdorf, F., Meier, E., K\u00f6tz, B., Itten, K.I., Dobbertin, M., Allg\u00f6wer, B.: Lidar-based geometric reconstruction of boreal type forest stands at single tree level for forest and wildland fire management. Remote Sens. Environ. 92(3), 353\u2013362 (2004)","journal-title":"Remote Sens. Environ."},{"issue":"4","key":"17_CR8","doi-asserted-by":"publisher","first-page":"1980","DOI":"10.1109\/TIP.2018.2881836","volume":"28","author":"JL Silv\u00e1n-C\u00e1rdenas","year":"2019","unstructured":"Silv\u00e1n-C\u00e1rdenas, J.L., Salazar-Garibay, A.: Local geometric deformations in the dht domain with applications. IEEE Trans. Image Process. 28(4), 1980\u20131992 (2019)","journal-title":"IEEE Trans. Image Process."},{"key":"17_CR9","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1007\/978-3-642-31149-9_7","volume-title":"Pattern Recognition","author":"JL Silv\u00e1n-C\u00e1rdenas","year":"2012","unstructured":"Silv\u00e1n-C\u00e1rdenas, J.L.: A segmentation method for tree crown detection and modelling from LiDAR measurements. In: Carrasco-Ochoa, J.A., Mart\u00ednez-Trinidad, J.F., Olvera L\u00f3pez, J.A., Boyer, K.L. (eds.) MCPR 2012. LNCS, vol. 7329, pp. 65\u201374. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-31149-9_7"},{"key":"17_CR10","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1016\/j.isprsjprs.2015.01.018","volume":"104","author":"VF Str\u00eembu","year":"2015","unstructured":"Str\u00eembu, V.F., Str\u00eembu, B.M.: A graph-based segmentation algorithm for tree crown extraction using airborne lidar data. ISPRS J. Photogramm. Remote Sensing 104, 30\u201343 (2015)","journal-title":"ISPRS J. Photogramm. Remote Sensing"},{"key":"17_CR11","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1016\/j.isprsjprs.2015.01.011","volume":"104","author":"AV Vo","year":"2015","unstructured":"Vo, A.V., Truong-Hong, L., Laefer, D.F., Bertolotto, M.: Octree-based region growing for point cloud segmentation. ISPRS J. Photogramm. Remote Sensing 104, 88\u2013100 (2015)","journal-title":"ISPRS J. Photogramm. Remote Sensing"},{"key":"17_CR12","first-page":"3","volume":"34","author":"G Vosselman","year":"2003","unstructured":"Vosselman, G.: 3D reconstruction of roads and trees for city modelling. Int. Arch. Photogramm. Remot Sensing Spat. Inf. Sci. 34, 3 (2003)","journal-title":"Int. Arch. Photogramm. Remot Sensing Spat. Inf. Sci."},{"issue":"8","key":"17_CR13","first-page":"33","volume":"46","author":"G Vosselman","year":"2004","unstructured":"Vosselman, G., Gorte, B.G., Sithole, G., Rabbani, T.: Recognising structure in laser scanner point clouds. Int. Arch. Photogramm. Remot Sensing Spat. Inf. Sci. 46(8), 33\u201338 (2004)","journal-title":"Int. Arch. Photogramm. Remot Sensing Spat. Inf. Sci."},{"issue":"6","key":"17_CR14","doi-asserted-by":"publisher","first-page":"3938","DOI":"10.3390\/s8063938","volume":"8","author":"Y Wang","year":"2008","unstructured":"Wang, Y., Weinacker, H., Koch, B.: A lidar point cloud based procedure for vertical canopy structure analysis and 3D single tree modelling in forest. Sensors 8(6), 3938\u20133951 (2008)","journal-title":"Sensors"},{"issue":"6","key":"17_CR15","doi-asserted-by":"publisher","first-page":"3309","DOI":"10.1109\/TGRS.2016.2514508","volume":"54","author":"Z Zhang","year":"2016","unstructured":"Zhang, Z., et al.: A multilevel point-cluster-based discriminative feature for ALS point cloud classification. IEEE Trans. Geosci. Remote Sens. 54(6), 3309\u20133321 (2016)","journal-title":"IEEE Trans. Geosci. Remote Sens."}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-49076-8_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,16]],"date-time":"2024-06-16T23:04:21Z","timestamp":1718579061000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-49076-8_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030490751","9783030490768"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-49076-8_17","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"17 June 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MCPR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Mexican Conference on Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Morelia","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Mexico","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 June 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 June 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"mcpr22020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/ccc.inaoep.mx\/~mcpr2020\/index.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"67","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"31","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"46% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.05","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.79","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"The conference was held virtually due to the COVID-19 pandemic.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}