Earth observation big data for climate change research

被引:94
作者
Guo Hua-Dong [1 ,2 ]
Zhang Li [1 ,2 ]
Zhu Lan-Wei [1 ,2 ]
机构
[1] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China
[2] Hainan Key Lab Earth Observat, Beijing 572029, Hainan, Peoples R China
基金
中国国家自然科学基金;
关键词
Earth observation big data; Climate change; Information and simulation systems; Sensitive factors; Synchronous satellite-aerial-ground observation experiments;
D O I
10.1016/j.accre.2015.09.007
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Earth observation technology has provided highly useful information in global climate change research over the past few decades and greatly promoted its development, especially through providing biological, physical, and chemical parameters on a global scale. Earth observation data has the 4V features (volume, variety, veracity, and velocity) of big data that are suitable for climate change research. Moreover, the large amount of data available from scientific satellites plays an important role. This study reviews the advances of climate change studies based on Earth observation big data and provides examples of case studies that utilize Earth observation big data in climate change research, such as synchronous satellite-aerial-ground observation experiments, which provide extremely large and abundant datasets; Earth observational sensitive factors (e.g., glaciers, lakes, vegetation, radiation, and urbanization); and global environmental change information and simulation systems. With the era of global environment change dawning, Earth observation big data will underpin the Future Earth program with a huge volume of various types of data and will play an important role in academia and decisionmaking. Inevitably, Earth observation big data will encounter opportunities and challenges brought about by global climate change.
引用
收藏
页码:108 / 117
页数:10
相关论文
共 36 条
[1]   THE ANALYSIS OF OBSERVED CHAOTIC DATA IN PHYSICAL SYSTEMS [J].
ABARBANEL, HDI ;
BROWN, R ;
SIDOROWICH, JJ ;
TSIMRING, LS .
REVIEWS OF MODERN PHYSICS, 1993, 65 (04) :1331-1392
[2]  
Brown CW, 2005, RE S D I PR, V7, P21, DOI 10.1007/1-4020-3100-9_2
[3]  
CEOS (Committee on Earth Observation Satellites), 2007, SAT OBS CLIM SYST CE
[4]  
CEOS (Committee on Earth Observation Satellites), 2006, SAT OBS CLIM SYST CO
[5]   Vertical accuracy assessment of freely available digital elevation models over low-lying coastal plains [J].
Du, Xiaoping ;
Guo, Huadong ;
Fan, Xiangtao ;
Zhu, Junjie ;
Yan, Zhenzhen ;
Zhan, Qin .
INTERNATIONAL JOURNAL OF DIGITAL EARTH, 2016, 9 (03) :252-271
[6]  
FAO (Food and Agriculture Organization), 2011, 163 FAO
[7]   Impact of Anthropogenic Heat Release on Regional Climate in Three Vast Urban Agglomerations in China [J].
Feng Jinming ;
Wang Jun ;
Yan Zhongwei .
ADVANCES IN ATMOSPHERIC SCIENCES, 2014, 31 (02) :363-373
[8]  
Gantz J, 2012, IDC IVIEW IDC ANALYZ, V2007, P1
[9]   Monitoring the distribution of C3 and C4 grasses in a temperate grassland in northern China using moderate resolution imaging spectroradiometer normalized difference vegetation index trajectories [J].
Guan, Linlin ;
Liu, Liangyun ;
Peng, Dailiang ;
Hu, Yong ;
Jiao, Quanjun ;
Liu, Lingling .
JOURNAL OF APPLIED REMOTE SENSING, 2012, 6
[10]  
Guo H, 2013, B CHINESE ACAD SCI, P525