{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,2]],"date-time":"2025-10-02T00:12:27Z","timestamp":1759363947813,"version":"build-2065373602"},"publisher-location":"Cham","reference-count":28,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032001368","type":"print"},{"value":"9783032001375","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"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":[[2026]]},"DOI":"10.1007\/978-3-032-00137-5_19","type":"book-chapter","created":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T23:56:44Z","timestamp":1759276604000},"page":"272-285","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Deep Learning Approach for\u00a0Average Height Estimation in\u00a0Oak Colony Using RGB Images"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-3271-3709","authenticated-orcid":false,"given":"Raphael Duarte","family":"Britto","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0979-8314","authenticated-orcid":false,"given":"Jo\u00e3o","family":"Mendes","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0004-4099-2566","authenticated-orcid":false,"given":"Vinicius","family":"Grilo","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0647-8892","authenticated-orcid":false,"given":"Jo\u00e3o P.","family":"Castro","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6568-1121","authenticated-orcid":false,"given":"Murillo Ferreira","family":"dos Santos","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6368-8098","authenticated-orcid":false,"given":"Marina","family":"Castro","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3803-2043","authenticated-orcid":false,"given":"Ana I.","family":"Pereira","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7902-1207","authenticated-orcid":false,"given":"Jos\u00e9","family":"Lima","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,10,1]]},"reference":[{"issue":"7521","key":"19_CR1","doi-asserted-by":"publisher","first-page":"903","DOI":"10.1136\/bmj.331.7521.903","volume":"331","author":"DG Altman","year":"2005","unstructured":"Altman, D.G., Bland, J.M.: Standard deviations and standard errors. BMJ 331(7521), 903 (2005)","journal-title":"BMJ"},{"key":"19_CR2","unstructured":"Instituto Portugu\u00eas do\u00a0Mar e\u00a0da Atmosfera\u00a0(IPMA): IPMA - Clima Normais (2025). https:\/\/www.ipma.pt\/opencms\/en\/oclima\/normais.clima\/1971-2000\/"},{"issue":"10","key":"19_CR3","doi-asserted-by":"publisher","first-page":"582","DOI":"10.3390\/f9100582","volume":"9","author":"L Chen","year":"2018","unstructured":"Chen, L., Ren, C., Zhang, B., Wang, Z., Xi, Y.: Estimation of forest above-ground biomass by geographically weighted regression and machine learning with sentinel imagery. Forests 9(10), 582 (2018)","journal-title":"Forests"},{"key":"19_CR4","doi-asserted-by":"publisher","first-page":"105815","DOI":"10.1016\/j.compag.2020.105815","volume":"179","author":"AP Dalla Corte","year":"2020","unstructured":"Dalla Corte, A.P., et al.: Forest inventory with high-density UAV-lidar: machine learning approaches for predicting individual tree attributes. Comput. Electron. Agricult. 179, 105815 (2020)","journal-title":"Comput. Electron. Agricult."},{"key":"19_CR5","unstructured":"DJI: Matrice 300 RTK Product Sheet (2020). https:\/\/www.dji.com\/matrice-300\/downloads"},{"key":"19_CR6","unstructured":"DJI: Zenmuse L1 Product Sheet (2021). https:\/\/www.dji.com\/zenmuse-l1\/downloads"},{"issue":"1","key":"19_CR7","doi-asserted-by":"publisher","first-page":"12","DOI":"10.33904\/ejfe.938067","volume":"7","author":"R Eker","year":"2021","unstructured":"Eker, R., Alkan, E., Ayd\u0131n, A.: A comparative analysis of UAV-RTK and UAV-PPK methods in mapping different surface types. Euro. J. Forest Eng. 7(1), 12\u201325 (2021)","journal-title":"Euro. J. Forest Eng."},{"key":"19_CR8","unstructured":"Hagl\u00f6f Sweden AB: Vertex IV product sheet, technical specification document for the Vertex IV ultrasound hypsometer. Includes Details on Features, Specifications, and Usage in Forestry Applications (2016)"},{"issue":"1","key":"19_CR9","doi-asserted-by":"publisher","first-page":"17","DOI":"10.3390\/rs12010017","volume":"12","author":"J Harkel","year":"2019","unstructured":"Harkel, J., Bartholomeus, H., Kooistra, L.: Biomass and crop height estimation of different crops using UAV-based lidar. Remote Sens. 12(1), 17 (2019)","journal-title":"Remote Sens."},{"key":"19_CR10","unstructured":"Jardim Bot\u00e2nico UTAD: Ficha t\u00e9cnica quercus pyrenaica (nd), informa\u00e7\u00f5es compiladas pela equipa do Jardim Bot\u00e2nico UTAD. A utiliza\u00e7\u00e3o est\u00e1 regida pelos termos e condi\u00e7\u00f5es gerais de utiliza\u00e7\u00e3o da Flora Digital de Portugal. http:\/\/jb.utad.pt"},{"key":"19_CR11","doi-asserted-by":"publisher","first-page":"100014","DOI":"10.1016\/j.bioeco.2021.100014","volume":"1","author":"C Johnson","year":"2021","unstructured":"Johnson, C., et al.: The bio-based industries joint undertaking as a catalyst for a green transition in Europe under the European green deal. EFB Bioecon. J. 1, 100014 (2021)","journal-title":"EFB Bioecon. J."},{"issue":"3","key":"19_CR12","doi-asserted-by":"publisher","first-page":"220","DOI":"10.4097\/kjae.2015.68.3.220","volume":"68","author":"DK Lee","year":"2015","unstructured":"Lee, D.K., In, J., Lee, S.: Standard deviation and standard error of the mean. Korean J. Anesthesiol. 68(3), 220\u2013223 (2015)","journal-title":"Korean J. Anesthesiol."},{"issue":"52","key":"19_CR13","doi-asserted-by":"publisher","first-page":"2106475","DOI":"10.1002\/adfm.202106475","volume":"31","author":"G Lee","year":"2021","unstructured":"Lee, G., Wei, Q., Zhu, Y.: Emerging wearable sensors for plant health monitoring. Adv. Func. Mater. 31(52), 2106475 (2021)","journal-title":"Adv. Func. Mater."},{"key":"19_CR14","doi-asserted-by":"publisher","first-page":"637","DOI":"10.1016\/j.ecolind.2016.03.036","volume":"67","author":"W Li","year":"2016","unstructured":"Li, W., Niu, Z., Chen, H., Li, D., Wu, M., Zhao, W.: Remote estimation of canopy height and aboveground biomass of maize using high-resolution stereo images from a low-cost unmanned aerial vehicle system. Ecol. Ind. 67, 637\u2013648 (2016)","journal-title":"Ecol. Ind."},{"key":"19_CR15","doi-asserted-by":"crossref","unstructured":"Maesano, M., Santopuoli, G., Moresi, F.V., Matteucci, G., Lasserre, B., Scarascia\u00a0Mugnozza, G.: Above ground biomass estimation from UAV high resolution RGB images and lidar data in a pine forest in southern Italy. iForest-Biogeosci. Forestry 15(6), 451 (2022)","DOI":"10.3832\/ifor3781-015"},{"key":"19_CR16","doi-asserted-by":"publisher","first-page":"107494","DOI":"10.1016\/j.ecolind.2021.107494","volume":"125","author":"P Mao","year":"2021","unstructured":"Mao, P., et al.: An improved approach to estimate above-ground volume and biomass of desert shrub communities based on UAV RGB images. Ecol. Ind. 125, 107494 (2021)","journal-title":"Ecol. Ind."},{"key":"19_CR17","doi-asserted-by":"crossref","unstructured":"Matiza, C., Mutanga, O., Peerbhay, K., Odindi, J., Lottering, R.: Assessing above-ground biomass in reforested urban landscapes using machine learning and remotely sensed data. J. Spatial Sci., 1\u201328 (2024)","DOI":"10.1080\/14498596.2024.2343764"},{"issue":"3","key":"19_CR18","doi-asserted-by":"publisher","first-page":"352","DOI":"10.3390\/rs13030352","volume":"13","author":"R Neuville","year":"2021","unstructured":"Neuville, R., Bates, J.S., Jonard, F.: Estimating forest structure from UAV-mounted lidar point cloud using machine learning. Remote Sens. 13(3), 352 (2021)","journal-title":"Remote Sens."},{"key":"19_CR19","doi-asserted-by":"publisher","first-page":"120209","DOI":"10.1016\/j.foreco.2022.120209","volume":"514","author":"MS Patr\u00edcio","year":"2022","unstructured":"Patr\u00edcio, M.S., Dias, C.R., Nunes, L.: Mixed-effects generalized height-diameter model: a tool for forestry management of young sweet chestnut stands. For. Ecol. Manage. 514, 120209 (2022)","journal-title":"For. Ecol. Manage."},{"issue":"4","key":"19_CR20","doi-asserted-by":"publisher","first-page":"253","DOI":"10.3126\/ijasbt.v1i4.9154","volume":"1","author":"S Ranjitkar","year":"2013","unstructured":"Ranjitkar, S.: Effect of elevation and latitude on spring phenology of Rhododendron at Kanchenjunga conservation area, East Nepal. Int. J. Appl. Sci. Biotechnol. 1(4), 253\u2013257 (2013)","journal-title":"Int. J. Appl. Sci. Biotechnol."},{"issue":"24","key":"19_CR21","doi-asserted-by":"publisher","first-page":"9899","DOI":"10.1073\/pnas.1019576108","volume":"108","author":"SS Saatchi","year":"2011","unstructured":"Saatchi, S.S., et al.: Benchmark map of forest carbon stocks in tropical regions across three continents. Proc. Natl. Acad. Sci. 108(24), 9899\u20139904 (2011)","journal-title":"Proc. Natl. Acad. Sci."},{"key":"19_CR22","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 (2015)"},{"issue":"6","key":"19_CR23","doi-asserted-by":"publisher","first-page":"1704","DOI":"10.1073\/pnas.0812721106","volume":"106","author":"S Solomon","year":"2009","unstructured":"Solomon, S., Plattner, G.K., Knutti, R., Friedlingstein, P.: Irreversible climate change due to carbon dioxide emissions. Proc. Natl. Acad. Sci. 106(6), 1704\u20131709 (2009)","journal-title":"Proc. Natl. Acad. Sci."},{"issue":"1","key":"19_CR24","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1093\/treephys\/tps127","volume":"33","author":"A Sumida","year":"2013","unstructured":"Sumida, A., Miyaura, T., Torii, H.: Relationships of tree height and diameter at breast height revisited: analyses of stem growth using 20-year data of an even-aged Chamaecyparis obtusa stand. Tree Physiol. 33(1), 106\u2013118 (2013)","journal-title":"Tree Physiol."},{"key":"19_CR25","first-page":"2007","volume":"3","author":"M Tom\u00e9","year":"2007","unstructured":"Tom\u00e9, M., Meyer, A., Ramos, T., Barreiro, S., Faias, S., Corti\u00e7ada, A.: Rela\u00e7\u00f5es hipsom\u00e9tricas e equa\u00e7\u00f5es de di\u00e2metro da copa desenvolvidas no \u00e2mbito do tratamento dos dados do invent\u00e1rio florestal nacional 2005\u20132006. Publica\u00e7\u00f5es GIMREF. RT 3, 2007 (2007)","journal-title":"Publica\u00e7\u00f5es GIMREF. RT"},{"key":"19_CR26","unstructured":"Tom\u00e9, M., Barreiro, S., Paulo, J.A., Faias, S.P.: Selec\u00e7\u00e3o de equa\u00e7\u00f5es para estima\u00e7\u00e3o de vari\u00e1veis da \u00e1rvore em invent\u00e1rios florestais a realizar em portugal. Publica\u00e7\u00f5es FORCHANGE PT 9 (2007)"},{"key":"19_CR27","unstructured":"Vasconcellos, J.D.C., Franco, J.D.A.: Carvalhos de portugal. Anais do Instituto Superior de Agronomia, vol. 21 (1954)"},{"key":"19_CR28","doi-asserted-by":"publisher","first-page":"170778","DOI":"10.1016\/j.scitotenv.2024.170778","volume":"922","author":"L Zhang","year":"2024","unstructured":"Zhang, L., Heuvelink, G.B., Mulder, V.L., Chen, S., Deng, X., Yang, L.: Using process-oriented model output to enhance machine learning-based soil organic carbon prediction in space and time. Sci. Total Environ. 922, 170778 (2024)","journal-title":"Sci. Total Environ."}],"container-title":["Communications in Computer and Information Science","Optimization, Learning Algorithms and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-00137-5_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T23:56:48Z","timestamp":1759276608000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-00137-5_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,1]]},"ISBN":["9783032001368","9783032001375"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-00137-5_19","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"value":"1865-0929","type":"print"},{"value":"1865-0937","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,1]]},"assertion":[{"value":"1 October 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare relevant to this article\u2019s content.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"OL2A","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Optimization, Learning Algorithms and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Sesti Levante","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 April 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 April 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ol2a2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/ol2a.ipb.pt","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}