Abstract

At present, most remote sensing satellite data provide limited information sources, and there are many parameters such as surface and atmosphere that affect satellite sensor signal acquisition.The lack of information sources limits the processing of satellite remote sensing data and the accuracy of extracting multiple types of surface parameters. With the increase in the quantity and accuracy of remote sensing products produced by different satellite sensors, it is possible to provide prior knowledge for post-remote sensing data processing and information extraction to supplement effective information sources.However, there are three problems in the use of this technology: 1) How to achieve the conversion of spatial and spectral scales between different data sources? 2) If the remote sensing data acquired at different times is reduced or even eliminated, the influence of surface information changes on data processing and information extraction accuracy? 3) How to reduce or even avoid the error transmission of the prior product to the later data processing and information extraction? This lecture will take the cloud detection and aerosol inversion of satellite data as a case to discuss the supporting role of transcendental remote sensing products in satellite data processing and information extraction, and give the treatment methods for the above three problems.

Presenter Profile

Sun Lin is a professor at the School of Surveying and Mapping Science and Engineering of Shandong University of Science and Technology, director of the 3S Engineering Application Center of Shandong Province, winner of the Outstanding Youth Fund of Shandong Province, and a leading talent in innovation and entrepreneurship in Qingdao. In 2006, he obtained a doctorate in science from the Institute of Remote Sensing Applications of the Chinese Academy of Sciences. He has worked as a postdoctoral researcher in the Department of Geography at the University of Maryland (2012-2014).As the person in charge, he completed more than ten scientific research projects such as the National Natural Science Foundation, the National “863” Program Sub-project, the National Science and Technology Support Program Sub-topic, and other national and provincial level projects, and won 8 provincial and ministerial-level scientific and technological progress awards. He has published more than 50 academic papers in domestic and foreign journals, including 21 SCI papers in international authoritative journals such as JGR, ISPRS and AE as the first author (or correspondent author). His current research interests include cloud recognition of remote sensing satellite data, aerosol inversion in highly heterogeneous regions, and remote sensing information extraction based on deep learning.