您好，欢迎访问北京市农林科学院 机构知识库！
北京市农林科学院机构知识库

全部

  • 全部
  • 标题
  • 学者
  • 机构
  • 关键词

Evaluation of Orthomosics and Digital Surface Models Derived from Aerial Imagery for Crop Type Mapping

文献类型： 外文期刊

作者： Wu, Mingquan 1 ; Yang, Chenghai 2 ; Song, Xiaoyu 2 ; Hoffmann, Wesley Clint 2 ; Huang, Wenjiang 4 ; Niu, Zheng 1 ; Wan 1 ;

作者机构： 1.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, POB 9718,20 Datun Rd, Beijing 100101, Peoples R China

2.USDA ARS, Aerial Applicat Technol Res Unit, 3103 F&B Rd, College Stn, TX 77845 USA

3.Beijing Acad Agr & Forestry Sci, Beijing Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

4.Chinese

关键词： aerial imagery;crop mapping;consumer-grade cameras;crop height;object-based classification

期刊名称：REMOTE SENSING （ 影响因子：4.848； 五年影响因子：5.353 ）

ISSN： 2072-4292

年卷期： 2017 年 9 卷 3 期

页码：

收录情况： SCI

摘要： 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.

  • 相关文献

[1]Estimation of Winter Wheat Above-Ground Biomass Using Unmanned Aerial Vehicle-Based Snapshot Hyperspectral Sensor and Crop Height Improved Models. Yue, Jibo,Yang, Guijun,Li, Zhenhai,Wang, Yanjie,Feng, Haikuan,Xu, Bo,Yue, Jibo,Yue, Jibo,Li, Changchun,Wang, Yanjie,Yang, Guijun,Li, Zhenhai,Wang, Yanjie,Feng, Haikuan,Xu, Bo,Yang, Guijun,Li, Zhenhai,Xu, Bo. 2017

[2]An Object-Based Method for Urban Land Cover Classification Using Airborne Lidar Data. Chen, Ziyue,Chen, Ziyue,Gao, Bingbo. 2014

作者其他论文 更多>>
置顶
购物车
反馈

© 京ICP备09089781号-29 主办单位：北京市农林科学院

学术资源： 中国农业科学院 农业专业知识服务系统 农科联盟资源共建共享平台 中国农业科技文献与信息服务平台 中国农业期刊集成服务平台