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Esophageal cancer spatial and correlation analyses: Water pollution, mortality rates, and safe buffer distances in China SCI/SSCI论文
2014
Authors:  Zhang X. Y.;  Zhuang D. F.;  Ma X.;  Jiang D.
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Esophageal Cancer  Water Pollution  Environment  Gis  Spatial Analysis  Gis  
Spatial-temporal variation of marginal land suitable for energy plants from 1990 to 2010 in China 期刊论文
SCIENTIFIC REPORTS, 2014, 卷号: 4
Authors:  Jiang, Dong;  Hao, Mengmeng(郝蒙蒙);  Fu, Jingying;  Zhuang, Dafang;  Huang, Yaohuan
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Assessment of debris flow hazards using a Bayesian Network SCI/SSCI论文
2012
Authors:  Liang W. J.;  Zhuang D. F.;  Jiang D.;  Pan J. J.;  Ren H. Y.
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Debris Flow Hazard  Bayesian Network  Hazard Assessment  Chinese  Mainland  Shallow Landslide Susceptibility  Artificial Neural-networks  Hong-kong  Natural Slopes  Lantau Island  Water-quality  Gis  Prediction  Mountains  Inventory  
Advances in Multi-Sensor Data Fusion: Algorithms and Applications 期刊论文
With the development of satellite and remote sensing techniques, more and more image data from airborne/satellite sensors have become available. Multi-sensor image fusion seeks to combine information from different images to obtain more inferences than can be derived from a single sensor. In image-based application fields, image fusion has emerged as a promising research area since the end of the last century. The paper presents an overview of recent advances in multi-sensor satellite image fusion. Firstly, the most popular existing fusion algorithms are introduced, with emphasis on their recent improvements. Advances in main applications fields in remote sensing, including object identification, classification, change detection and maneuvering targets tracking, are described. Both advantages and limitations of those applications are then discussed. Recommendations are addressed, including: (1) Improvements of fusion algorithms; (2) Development of, 2009, 卷号: 9, 期号: 10, 页码: 7771-7784
Authors:  Dong, Jiang;  Zhuang, Dafang(庄大方);  Huang, Yaohuan;  Fu, Jingying
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Multi-sensor  Data Fusion  Remote Sensing