{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,1,20]],"date-time":"2025-01-20T12:40:05Z","timestamp":1737376805744,"version":"3.33.0"},"reference-count":35,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2017,3,4]],"date-time":"2017-03-04T00:00:00Z","timestamp":1488585600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004543","name":"China Scholarship Council","doi-asserted-by":"publisher","award":["201504910261"],"id":[{"id":"10.13039\/501100004543","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41301390"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the National Science and Technology Major Project","award":["2014AA06A511"]},{"name":"the Major State Basic Research Development Program of China","award":["2013CB733405, 2010CB950603"]},{"name":"the National Science and Technology Major Project of China"},{"name":"he Youth Innovation Promotion Association CAS","award":["2017089"]},{"name":"the Hundred Talents Program CAS","award":["Y6YR0700QM"]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"Orthomosics and digital surface models (DSM) derived from aerial imagery, acquired by consumer-grade cameras, have the potential for crop type mapping. In this study, a novel method was proposed for extracting the crop height from DSM and for evaluating the orthomosics and crop height for the identification of crop types (mainly corn, cotton, and sorghum). The crop height was extracted by subtracting the DSM derived during the crop growing season from that derived after the crops were harvested. Then, the crops were identified from four-band aerial imagery (blue, green, red, and near-infrared) and the crop height, using an object-based classification method and a maximum likelihood method. The results showed that the extracted crop height had a very high linear correlation with the field measured crop height, with an R-squared value of 0.98. For the object-based method, crops could be identified from the four-band airborne imagery and crop height, with an overall accuracy of 97.50% and a kappa coefficient of 0.95, which were 2.52% and 0.04 higher than those without crop height, respectively. When considering the maximum likelihood, crops could be mapped from the four-band airborne imagery and crop height with an overall accuracy of 78.52% and a kappa coefficient of 0.67, which were 2.63% and 0.04 higher than those without crop height, respectively.<\/jats:p>","DOI":"10.3390\/rs9030239","type":"journal-article","created":{"date-parts":[[2017,3,9]],"date-time":"2017-03-09T11:56:43Z","timestamp":1489060603000},"page":"239","source":"Crossref","is-referenced-by-count":22,"title":["Evaluation of Orthomosics and Digital Surface Models Derived from Aerial Imagery for Crop Type Mapping"],"prefix":"10.3390","volume":"9","author":[{"given":"Mingquan","family":"Wu","sequence":"first","affiliation":[{"name":"The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, P.O. Box 9718, 20 Datun Road, Chaoyang, Beijing 100101, China"},{"name":"USDA-Agricultural Research Service, Aerial Application Technology Research Unit, 3103 F & B Road, College Station, TX 77845, USA"}]},{"given":"Chenghai","family":"Yang","sequence":"additional","affiliation":[{"name":"USDA-Agricultural Research Service, Aerial Application Technology Research Unit, 3103 F & B Road, College Station, TX 77845, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0294-5705","authenticated-orcid":false,"given":"Xiaoyu","family":"Song","sequence":"additional","affiliation":[{"name":"USDA-Agricultural Research Service, Aerial Application Technology Research Unit, 3103 F & B Road, College Station, TX 77845, USA"},{"name":"Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China"}]},{"given":"Wesley","family":"Hoffmann","sequence":"additional","affiliation":[{"name":"USDA-Agricultural Research Service, Aerial Application Technology Research Unit, 3103 F & B Road, College Station, TX 77845, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1710-8301","authenticated-orcid":false,"given":"Wenjiang","family":"Huang","sequence":"additional","affiliation":[{"name":"Laboratory of Digital Earth Sciences, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5959-9351","authenticated-orcid":false,"given":"Zheng","family":"Niu","sequence":"additional","affiliation":[{"name":"The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, P.O. Box 9718, 20 Datun Road, Chaoyang, Beijing 100101, China"}]},{"given":"Changyao","family":"Wang","sequence":"additional","affiliation":[{"name":"The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, P.O. Box 9718, 20 Datun Road, Chaoyang, Beijing 100101, China"}]},{"given":"Wang","family":"Li","sequence":"additional","affiliation":[{"name":"The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, P.O. Box 9718, 20 Datun Road, Chaoyang, Beijing 100101, China"}]}],"member":"1968","published-online":{"date-parts":[[2017,3,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"5257","DOI":"10.3390\/rs6065257","article-title":"An airborne multispectral imaging system based on two consumer-grade cameras for agricultural remote sensing","volume":"6","author":"Yang","year":"2014","journal-title":"Remote Sens."},{"key":"ref_2","first-page":"1207","article-title":"The photogrammetric potential of low-cost UAVs in forestry and agriculture","volume":"31","author":"Engel","year":"2008","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. 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