{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T09:28:03Z","timestamp":1768814883922,"version":"3.49.0"},"reference-count":66,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2022,12,24]],"date-time":"2022-12-24T00:00:00Z","timestamp":1671840000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["U1809208"],"award-info":[{"award-number":["U1809208"]}]},{"name":"National Natural Science Foundation of China","award":["32171785"],"award-info":[{"award-number":["32171785"]}]},{"name":"National Natural Science Foundation of China","award":["32201553"],"award-info":[{"award-number":["32201553"]}]},{"name":"National Natural Science Foundation of China","award":["2023C02035"],"award-info":[{"award-number":["2023C02035"]}]},{"name":"Leading Goose Project of Science Technology Department of Zhejiang Province","award":["U1809208"],"award-info":[{"award-number":["U1809208"]}]},{"name":"Leading Goose Project of Science Technology Department of Zhejiang Province","award":["32171785"],"award-info":[{"award-number":["32171785"]}]},{"name":"Leading Goose Project of Science Technology Department of Zhejiang Province","award":["32201553"],"award-info":[{"award-number":["32201553"]}]},{"name":"Leading Goose Project of Science Technology Department of Zhejiang Province","award":["2023C02035"],"award-info":[{"award-number":["2023C02035"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In this paper, a method for extracting the height of urban forest trees based on a smartphone was proposed to efficiently and accurately determine tree heights. First, a smartphone was used to obtain person\u2013tree images, LabelImg was used to label the images, and a dataset was constructed. Secondly, based on a deep learning method called You Only Look Once v5 (YOLOv5) and the small-hole imaging and scale principles, a person\u2013tree scale height measurement model was constructed. This approach supports recognition and mark functions based on the characteristics of a person and a tree in a single image. Finally, tree height measurements were obtained. By using this method, the heights of three species in the validation set were extracted; the range of the absolute error was 0.02 m\u20130.98 m, and the range of the relative error was 0.20\u201310.33%, with the RMSE below 0.43 m, the rRMSE below 4.96%, and the R2 above 0.93. The person\u2013tree scale height measurement model proposed in this paper greatly improves the efficiency of tree height measurement while ensuring sufficient accuracy and provides a new method for the dynamic monitoring and investigation of urban forest resources.<\/jats:p>","DOI":"10.3390\/rs15010097","type":"journal-article","created":{"date-parts":[[2022,12,27]],"date-time":"2022-12-27T07:31:56Z","timestamp":1672126316000},"page":"97","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Intelligent Estimating the Tree Height in Urban Forests Based on Deep Learning Combined with a Smartphone and a Comparison with UAV-LiDAR"],"prefix":"10.3390","volume":"15","author":[{"given":"Jie","family":"Xuan","sequence":"first","affiliation":[{"name":"State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"Key Laboratory of Carbon Cycling in Forest Ecosystems and 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