首页    期刊浏览 2024年07月05日 星期五
登录注册

文章基本信息

  • 标题:Monitoring Broadleaf Forest Pest Based on L-Band SAR Tomography
  • 本地全文:下载
  • 作者:Kunkun Cao ; Kunkun Cao ; Weixian Tan
  • 期刊名称:IOP Conference Series: Earth and Environmental Science
  • 印刷版ISSN:1755-1307
  • 电子版ISSN:1755-1315
  • 出版年度:2019
  • 卷号:237
  • 期号:5
  • 页码:052004
  • DOI:10.1088/1755-1315/237/5/052004
  • 出版社:IOP Publishing
  • 摘要:Synthetic aperture radar tomography (TomoSAR) has been proved to be able to reconstruct 3D reflectance of volumetric targets, such as vegetation. It gives us an opportunity and a possibility to monitor forest pest through extracting 3D structural information of the forest. In this paper, TomoSAR echo data of normal and pest forest are simulated with PolSAR Pro at L-band before and after the pest respectively, after analysing physical geometry and backscattering properties of forest pest and disease. Then, a method used for extracting 3D structure information of the forest is presented and discussed. Finally, differences between the normal and pest forest are demonstrated and analyzed with the TomoSAR imaging results.
国家哲学社会科学文献中心版权所有