Journal of Geo-information Science ›› 2016, Vol. 18 ›› Issue (5): 578-589.doi: 10.3724/SP.J.1047.2016.00578

• Orginal Article •     Next Articles

The Theory and Calculation of Spatial-spectral Cognition of Remote Sensing

LUO Jiancheng1(), WU Tianjun2,*(), XIA Liegang3   

  1. 1. State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
    2. Department of Mathematics and Information Science, College of Science, Chang’an University, Xi’an 710064
    3. College of Computer science and Technology, Zhejiang University of Technology, Hangzhou 310026
  • Received:2016-01-04 Revised:2016-03-11 Online:2016-05-10 Published:2016-05-10
  • Contact: WU Tianjun E-mail:luojc@radi.ac.cn;wutianjun1986@163.com

Abstract:

In recent years, with the rapid development of earth observation technologies, remote sensing using the satellites has gradually entered the era of big data. Facing the current demands and characteristics of remote sensing applications, it is feasible and necessary to explore the theories and methods of high-spatial-resolution remote sensing cognition with the cooperation of visual cognition. In this context, we are inspired by Geo-informatic-Tupu and intend to study the spatial-spectral cognition of remote sensing. This paper systematically presents the theory and calculation methodology for the spatial-spectral cognition of remote sensing, and expects to standardize the processes of remote sensing information extraction, as a result to further build a sophisticated, quantitative, intelligent and integrated model for the remote sensing information interpretation. The whole methodology contains two directions' cognitive calculation, namely horizontal "bottom-up hierarchical abstraction" and longitudinal "top-down knowledge transfer". These two steps are corresponded with three principal Spatial-Spectral transformation processes, which are summarized as "extracting spatial maps based on clustering pixels' spectrum", "coordinating spatial-spectral features" and "understanding attributes through the recognition of known diagram". Our study focuses on the analysis of the involved concepts, the basic idea, the key technologies and their existing difficulties, and emphasizes on the utilization of big data and gradually the application of integrated knowledge to achieve different levels of remote sensing cognition. Through these approaches, we expect to provide a new perspective for the remote sensing interpretation with the adoption of big data resources.

Key words: spatial-spectral cognition of remote sensing, extracting spatial maps based on clustering pixels' spectrum, coordinating spatial-spectral features, understanding attributes through the recognition of known diagram, bottom-up hierarchical abstraction, top-down knowledge transfer