Development of airborne remote sensing data assimilation system

35th International Symposium on Remote Sensing of Environment

地球科学;生态环境科学

Gudu, B.R.^1,3 ; Bi, H.Y.^2,3 ; Wang, H.Y.^2 ; Qin, S.X.^2,3 ; Ma, J.W.^2

Institute of Remote Sensing Application, Chinese Academy of Sciences, Beijing, China^1

Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, Beijing, China^2

University of Chinese Academy of Sciences, Beijing, China^3

关键词: Airborne remote sensing;    Data assimilation algorithms;    Data assimilation systems;    Dimensional variations;    Ensemble Kalman Filter;    Particle filter algorithms;    Variable infiltration capacities;    Vegetation parameters;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/17/1/012189/pdf
DOI  :  10.1088/1755-1315/17/1/012189

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

In this paper, an airborne remote sensing data assimilation system for China Airborne Remote Sensing System is introduced. This data assimilation system is composed of a land surface model, data assimilation algorithms, observation data and fundamental parameters forcing the land surface model. In this data assimilation system, Variable Infiltration Capacity hydrologic model is selected as the land surface model, which also serves as the main framework of the system. Three-dimensional variation algorithm, four-dimensional variation algorithms, ensemble Kalman filter and Particle filter algorithms are integrated in this system. Observation data includes ground observations and remotely sensed data. The fundamental forcing parameters include soil parameters, vegetation parameters and the meteorological data.