CISS 2023

Presentation Title：

Recent research progress in agricultural crop classification with PolSAR data

Abstract：

Agricultural crop-type classification is one of the most significant applications in polarimetric synthetic aperture radar (PolSAR) images. As a remote sensing technique, PolSAR has been proved to have the ability to provide high-resolution information of illustrated objects. However, single-temporal PolSAR data are restricted to provide sufficient information for crop identification due to the complicated condition of varying morphology within various growing stages. With an increasing number of spaceborne PolSAR systems launched, a large amount of real PolSAR data are being generated and used to provide great opportunities for multitemporal analysis. This presentation discusses the recent research progress in crop classification with PolSAR data.

Biography：Jiao Guo is currently an associate professor and a doctoral supervisor with the College of Mechanical and Electronic Engineering, Northwest A&F University, Xianyang, China. He is also the youth editorial board member of the Journal of Remote Sensing and the associate technical director of high-tech enterprise in Jiangsu Province. He received the B.S. and Ph.D. degree in information and communication engineering from Xidian University, in 2006 and 2011, respectively. From 2015 to 2016, he was a visiting scholar at CSIRO Data61, Floreat, WA, Australia. His main research interests include radar signal processing and remote sensing, polarimetric synthetic aperture radar (PolSAR), SAR interferometry and agricultural remote sensing, etc.