{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T21:08:59Z","timestamp":1762376939154,"version":"build-2065373602"},"reference-count":44,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2021,6,10]],"date-time":"2021-06-10T00:00:00Z","timestamp":1623283200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41571323"],"award-info":[{"award-number":["41571323"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100017616","name":"Beijing Talents Fund","doi-asserted-by":"publisher","award":["2020A58"],"award-info":[{"award-number":["2020A58"]}],"id":[{"id":"10.13039\/501100017616","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Lodging is one of the main problems in maize production. Assessing the self-recovery ability of maize plants after lodging at different growth stages is of great significance for yield loss assessment and agricultural insurance claims. The objective of this study was to quantitatively analyse the effects of different growth stages and lodging severity on the self-recovery ability of maize plants using UAV-LiDAR data. The multi-temporal point cloud data obtained by the RIEGL VUX-1 laser scanner were used to construct the canopy height model of the lodging maize. Then the estimated canopy heights of the maize at different growth stages and lodging severity were obtained. The measured values were used to verify the accuracy of the canopy height estimation and to invert the corresponding lodging angle. After verifying the accuracy of the canopy height, the accuracy parameter of the tasselling stage was R2 = 0.9824, root mean square error (RMSE) = 0.0613 m, and nRMSE = 3.745%. That of the filling stage was R2 = 0.9470, RMSE = 0.1294 m, and nRMSE = 9.889%, which showed that the UAV-LiDAR could accurately estimate the height of the maize canopy. By comparing the yield, canopy height, and lodging angle of maize, it was found that the self-recovery ability of maize at the tasselling stage was stronger than that at the filling stage, but the yield reduction rate was 14.16~26.37% higher than that at the filling stage. The more serious the damage of the lodging is to the roots and support structure of the maize plant, the weaker is the self-recovery ability. Therefore, the self-recovery ability of the stem tilt was the strongest, while that of root lodging and root stem folding was the weakest. The results showed that the UAV-LiDAR could effectively assess the self-recovery ability of maize after lodging.<\/jats:p>","DOI":"10.3390\/rs13122270","type":"journal-article","created":{"date-parts":[[2021,6,10]],"date-time":"2021-06-10T21:34:38Z","timestamp":1623360878000},"page":"2270","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Assessing the Self-Recovery Ability of Maize after Lodging Using UAV-LiDAR Data"],"prefix":"10.3390","volume":"13","author":[{"given":"Xueqian","family":"Hu","sequence":"first","affiliation":[{"name":"National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China"},{"name":"College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China"}]},{"given":"Lin","family":"Sun","sequence":"additional","affiliation":[{"name":"College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China"}]},{"given":"Xiaohe","family":"Gu","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China"}]},{"given":"Qian","family":"Sun","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China"},{"name":"College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China"}]},{"given":"Zhonghui","family":"Wei","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China"},{"name":"School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China"}]},{"given":"Yuchun","family":"Pan","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China"}]},{"given":"Liping","family":"Chen","sequence":"additional","affiliation":[{"name":"National Research Center for Intelligent Agricultural Equipment, Beijing 100097, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,10]]},"reference":[{"key":"ref_1","unstructured":"National Bureau of Statistics of China (2020, December 10). 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