{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T18:03:21Z","timestamp":1783620201490,"version":"3.55.0"},"reference-count":41,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2019,5,6]],"date-time":"2019-05-06T00:00:00Z","timestamp":1557100800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2017YFE0122500"],"award-info":[{"award-number":["2017YFE0122500"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004826","name":"Beijing Natural Science Foundation","doi-asserted-by":"publisher","award":["6182011"],"award-info":[{"award-number":["6182011"]}],"id":[{"id":"10.13039\/501100004826","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61661136003"],"award-info":[{"award-number":["61661136003"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Special Funds for Technology innovation capacity building sponsored by the Beijing Academy of Agriculture and Forestry Sciences","award":["KJCX20170423"],"award-info":[{"award-number":["KJCX20170423"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The leaf area index (LAI) is a key parameter for describing crop canopy structure, and is of great importance for early nutrition diagnosis and breeding research. Light detection and ranging (LiDAR) is an active remote sensing technology that can detect the vertical distribution of a crop canopy. To quantitatively analyze the influence of the occlusion effect, three flights of multi-route high-density LiDAR dataset were acquired at two time points, using an Unmanned Aerial Vehicle (UAV)-mounted RIEGL VUX-1 laser scanner at an altitude of 15 m, to evaluate the validity of LAI estimation, in different layers, under different planting densities. The result revealed that normalized root-mean-square error (NRMSE) for the upper, middle, and lower layers were 10.8%, 12.4%, 42.8%, for 27,495 plants\/ha, respectively. The relationship between the route direction and ridge direction was compared, and found that the direction of flight perpendicular to the maize planting ridge was better than that parallel to the maize planting ridge. The voxel-based method was used to invert the LAI, and we concluded that the optimal voxel size were concentrated on 0.040 m to 0.055 m, which was approximately 1.7 to 2.3 times of the average ground point distance. The detection of the occlusion effect in different layers under different planting densities, the relationship between the route and ridge directions, and the optimal voxel size could provide a guideline for UAV\u2013LiDAR application in the crop canopy structure analysis.<\/jats:p>","DOI":"10.3390\/rs11091067","type":"journal-article","created":{"date-parts":[[2019,5,9]],"date-time":"2019-05-09T08:19:59Z","timestamp":1557389999000},"page":"1067","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":42,"title":["Effect of Leaf Occlusion on Leaf Area Index Inversion of Maize Using UAV\u2013LiDAR Data"],"prefix":"10.3390","volume":"11","author":[{"given":"Lei","family":"Lei","sequence":"first","affiliation":[{"name":"Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture, Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China"},{"name":"College of Surveying and Mapping Science and Technology, Xi\u2019an University of Science and Technology, Xi\u2019an 710054, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunxia","family":"Qiu","sequence":"additional","affiliation":[{"name":"College of Surveying and Mapping Science and Technology, Xi\u2019an University of Science and Technology, Xi\u2019an 710054, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9878-3274","authenticated-orcid":false,"given":"Zhenhai","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture, Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dong","family":"Han","sequence":"additional","affiliation":[{"name":"Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture, Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China"},{"name":"College of Surveying and Mapping Science and Technology, Xi\u2019an University of Science and Technology, Xi\u2019an 710054, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liang","family":"Han","sequence":"additional","affiliation":[{"name":"College of Architecture and Geomatics Engineering, Shanxi Datong University, Datong 037003, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yaohui","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4257-2288","authenticated-orcid":false,"given":"Jintao","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Anhui University, Hefei 230601, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bo","family":"Xu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture, Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haikuan","family":"Feng","sequence":"additional","affiliation":[{"name":"Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture, Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao","family":"Yang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture, Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guijun","family":"Yang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture, Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,5,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/j.rse.2015.09.002","article-title":"Estimation of Leaf Area Index (LAI) in corn and soybeans using multi-polarization C- and L-band radar data","volume":"170","author":"Hosseini","year":"2015","journal-title":"Remote Sens. 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