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Summary of Proposal LAN0563

TitleCrop identification using multi-frequency SAR data
Investigator Wu, Bingfang - Institute of Remote Sensing Applications, Chinese Academy of Science, Lab for Agriculture and Environment
Team Member
Dr. Li, Qiangzi - Institute of Remote Sensing Applications, Chinese Academy of Science, Lab for Agriculture & Environment
Dr. Du, Xin - Institute of Remote Sensing Applications, Chinese Academy of Science, Lab for Agriculture & Environment
Dr. Jia, Kun - Institute of Remote Sensing Applications, Chinese Academy of Science, Lab for Agriculture & Environment
SummaryThe research objective of this proposal focus on developing a new crop identification method based on multi-frequency SAR data, including X-, C- and L-band. For crop identification, our proposal is aiming to retrieve crop canopy structure parameters, such as crop height and LAI, using multi-frequency SAR data, and then use these parameters to distinguish crop types based on the canopy characters of different crops. In this proposal, we want to construct water-cloud model with different frequency SAR data, integrated with the field observation data. Here we use water-cloud model to simulate crop canopy structure parameters, such as crop height and LAI. And then, we will use the constructed models to retrieve crop parameters. If this model can not realize our research objective, we will investigate some other scattering models to retrieve crop parameters, and finally to identify different crop types. To reach our objective, we will collect supporting data in the study areas, such as crop maps, ground observation data, as well as the discriminative characters of different crops. For study area selection, we choose two experiment areas. One is Yucheng in Shandong province, the other is Yongchang in Gansu province. Our study is requesting a total of 24 images over two years and two sites. The images include StripMode dual polarization, and a limited number of full polarimetric images and ScanSAR images. The research team also expect to access Radarsat-2, ALOS PalSAR and Envisat ASAR over the same study sites described in this proposal, as well as some optical images, such as QuickBird and Spot-5. This research will produce a preliminary and final report on research findings and the contribution of TerraSAR-X for crop identification, as well as conference papers, presentations and journal publications. Our study has been funded from two approved research projects, one funded by the National Natural Science Foundation of China (Grant NO.40801144), and the other is the Dragon-2 project which can provide Envisat data for our study.

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DLR 2004-2016