当前位置： 首页»科研成果» 2013 The Global Land Surface Satellite (GLASS) Remote Sensing Data Processing System and Products 赵祥、梁顺林、刘强、程洁、张晓通、刘强、徐帅

 

Xiang Zhao ^1,2, Shunlin Liang ^1,2,3, Suhong Liu ^2,4, Wenping Yuan ¹, Zhiqiang Xiao ^2,4, Qiang Liu ^1,2, Jie Cheng ^1,2, Xiaotong Zhang ^1,2, Hairong Tang ⁵, Xin Zhang ², Qiang Liu ¹, Gongqi Zhou ², Shuai Xu ¹ and Kai Yu ⁵

 

¹ College of Global Change and Earth System Science, Beijing Normal University, No. 19, XinJieKouWai St., HaiDian District, Beijing 100875, China;

² State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing Applications, Chinese Academy of Sciences, No. 19, XinJieKouWai St., HaiDian District, Beijing 100875, China;

³ Department of Geographical Sciences, University of Maryland, 2181 Samuel J. LeFrak Hall, College Park, MD 20742, USA;

⁴ School of Geography, Beijing Normal University, No. 19, XinJieKouWai St., HaiDian District, Beijing 100875, China;

⁵ Institute of Electronics, Chinese Academy of Sciences, No. 19, North 4th Ring Road West, Haidian District, Beijing 100190, China.

 

ABSTRACT

Using remotely sensed satellite products is the most efficient way to monitor global land, water, and forest resource changes, which are believed to be the main factors for understanding global climate change and its impacts. A reliable remotely sensed product should be retrieved quantitatively through models or statistical methods. However, producing global products requires a complex computing system and massive volumes of multi-sensor and multi-temporal remotely sensed data. This manuscript describes the ground Global LAnd Surface Satellite (GLASS) product generation system that can be used to generate long-sequence time series of global land surface data products based on various remotely sensed data. To ensure stabilization and efficiency in running the system, we used the methods of task management, parallelization, and multi I/O channels. An array of GLASS remote sensing products related to global land surface parameters are currently being produced and distributed by the Center for Global Change Data Processing and Analysis at Beijing Normal University in Beijing, China. These products include Leaf Area Index (LAI), land surface albedo, and broadband emissivity (BBE) from the years 1981 to 2010, downward shortwave radiation (DSR) and photosynthetically active radiation (PAR) from the years 2008 to 2010.

 

KEY WORDS: remote sensing; satellite data; product generation system; GLASS products; high performance computing

 

PUBLISHED IN: REMOTE SENSING, 2013, 5 (5): 2436-2450.

 

SOURCE: http://www.mdpi.com/2072-4292/5/5/2436