文献类型： 会议论文
第一作者： Ling Sun
作者： Ling Sun 1 ; Zesheng Zhu 2 ;
作者机构： 1.Resource Environment Institute JiangSu Academy of Agricultural Sciences Nanjing, 210014, China
2.Research Department Naval Command College Nanjing, 210016, China
关键词： weed disaster;monitoring;remote sensing;data;fusion
会议名称： International Conference on Biomedical Engineering and Biotechnology (iCBEB 2012)
主办单位：
页码： 1172-1175
摘要： This system essentially implements the information from RS and GIS associated with weed disaster modeling, and increases precision of weed disaster modeling by the information representing physical and logical fusion objects subject to weed disaster monitoring. This work focuses on the system architecture model and related design issues, including area and type estimation of weed disaster, whereas we use the model as a tool of data fusion to avoid the parameter estimation problems in complex environments..
分类号： R318-53
- 相关文献
[1]A RS/GIS-Based System for Monitoring Weed Disasters. Sun, Ling,Zhu, Zesheng. 2012
[2]Modeling and Monitoring Arable Land Use. Sun, Ling,Zhu, Zesheng. 2013
[3]Topdressing nitrogen recommendation for early rice with an active sensor in south China. Xue, Lihong,Yang, Linzhang,Xue, Lihong,Yang, Linzhang,Li, Ganghua,Qin, Xia,Zhang, Hailin. 2014
[4]Computing Hybrid Rotation Period of Cotton-rice and Cotton-others. Sun, Ling,Zhu, Zesheng. 2014
[5]Crop growth condition monitoring and analyzing in county scale by time series MODIS medium-resolution data. Yu, Kun,Wang, Zhiming,Sun, Ling,Shan, Jie,Mao, Liangjun. 2013
[6]An RS Image-Fusion Method of Farmland Fertility Remote Sensing. Sun, Ling,Zhu, Zesheng. 2012
[7]Algae blooms in the Yellow Sea between 2010 and 2012 from MODIS observations. Yu, Kun,Wang, Zhiming,Shan, Jie,Mao, Liangjun,Yu, Kun,Lu, Xiaoping,Bao, Guiye. 2013
[8]ANALYSIS OF SPATIAL AND TEMPORAL CHARACTERISTICS OF DROUGHT AND FLOOD BASED ON PRECIPITATION TEMPERATURE INDEX AT WINTER WHEAT GROWTH STAGES. Miao Tian,Jing Wang. 2019
[9]Regional rice yield estimation based on assimilation of remote sensing data and crop growth model with Ensemble Kalman method. Jing Wang,Kun Yu,Bihui Lu,MiaoTian. 2019
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