The Methodology of Monitoring Crops with Remote Sensing at the National Scale

文献类型： 外文期刊

第一作者： Wu, Quan

作者： Wu, Quan;Sun, Li;He, Yajuan;Wang, Fei;Wang, Danqiong;Jiao, Weijie;Wang, Haijun;Han, Xue

作者机构：

关键词： Crop growth;Crop area;Crop yield;Agricultural condition;The system theory;Model;Operational work;National scale;RS

期刊名称：COMPUTER AND COMPUTING TECHNOLOGIES IN AGRICULTURE IX, CCTA 2015, PT I

ISSN： 1868-4238

年卷期： 2016 年 478 卷

页码：

收录情况： SCI

摘要： Monitoring crops with Remote Sensing (RS) at the national scale is usually an operational work acted as a normal business for the government needs to the crop field conditions. The crop information is main content of agricultural condition. It mainly includes crop growth, crop areas and crop yields, which can be named 3 factors for crop monitoring with RS. Diversification is the general feature of crop monitoring with RS, which reflects in 3 parts of labor objects, labor materials and labor process. Monitoring the 3 factors with RS has similar process summarized as 3 periods which are data acquisition and transmission, model development and application, producing products. Monitoring crops with RS at the national scale needs to found an organizational and technical system, using the System Theory according to the 3 factors, the 3 parts and the 3 periods, mentioned above. The operational work of monitoring the 3 factors have a common goal, which is that the monitoring result is more accurate, the monitoring process is faster, more economic and more convenient. In China, Remote Sensing Application Centre (RSAC) has been working on monitoring the main crops as an operational task and a research project based on its system for several years. The monitoring methods to the 3 factors are presented in this paper along with the cases coming from the monitoring products produced by RSAC in 2014.

分类号：

  • 相关文献

[1]Monitoring national food security using satellite remote sensing. Yang, BJ. 2004

[2]Study on Survey Methods for Crop Area Change Reasons at National Scale. Wu, Quan,Hu, Hualang,Wang, Danqiong,Jia, Lijuan,He, Yajuan,Liu, Yanxia,Duan, Xinyu. 2015

[3]A Method for Spatially Explicit Assessment of Potential Risks of Food Insecurity. Wu, Wenbin,Yang, Peng,Tang, Huajun,Zhou, Qingbo,Chen, Zhongxin,Wu, Wenbin,Yang, Peng,Tang, Huajun,Zhou, Qingbo,Chen, Zhongxin,Shibasaki, Ryosuke. 2010

[4]Global-scale assessment of potential future risks of food insecurity. Wu, Wenbin,Yang, Peng,Tang, Huajun,You, Liangzhi,Zhou, Qingbo,Chen, Zhongxin,Shibasaki, Ryosuke. 2011

[5]Modeling crop yield as affected by uniformity of sprinkler irrigation system. Li, JS. 1998

[6]Accuracy Assessment on the Crop Area Estimating Method Based on RS sampling at National Scale: a Case Study of China's Rice Area Estimation Assessment. Qian Yonglan,Li Xuan,Yang Bangjie,Jiao Xianfeng,Pei Zhiyuan. 2008

[7]Grey Comprehensive Evaluation Model of Wheat Medium- and Low-yield Zoning via Remote Sensing Monitoring Data. Guo Wei,Zhao Chunjiang,Huang Wenjiang,Gu Xiaohe,Yang Xiaodong,Wang Huifang,Guo Wei,Guo Wei,Liu Bin. 2012

[8]Exploring the Feasibility of Winter Wheat Freeze Injury by Integrating Grey System Model with RS and GIS. Wang Hui-fang,Guo Wei,Wang Ji-hua,Huang Wen-jiang,Gu Xiao-he,Dong Ying-ying,Xu Xin-gang,Wang Hui-fang,Wang Ji-hua,Dong Ying-ying. 2013

[9]An overview of spatial sampling procedures for crop area estimation. Wang Di,Dong Zhaoxia,Zhou Qingbo,Chen Zhongxin. 2016

[10]Estimating Crop Area at County Level on the North China Plain with an Indirect Sampling of Segments and an Adapted Regression Estimator. Dong, Qinghan,Liu, Jia,Wang, Limin,Chen, Zhongxin,Gallego, Javier. 2017

[11]The Quantificational Evaluation of a Sampling Unit Error Derived from Main Crop Area Monitorings at National Scale Based 3S in China. Wu, Quan,Sun, Li,Wang, Fei,Jia, Shaorong.

[12]Research on Key Technologies of Intelligent Agriculture based on Agricultural Big Data. Hao, Fengqi,Luo, Xuan,Mu, Chunhua. 2016

[13]Wheat Growth and Photosynthesis as Affected by Oxytetracycline as a Soil Contaminant. Li Zhao-Jun,Xie Xiao-Yu,Zhang Shu-Qing,Liang Yong-Chao.

[14]Long-term effective microorganisms application promote growth and increase yields and nutrition of wheat in China. Hu, Cheng,Qi, Yingchun. 2013

[15]Global sensitivity analysis and calibration of parameters for a physically-based agro-hydrological model. Xu, Xu,Huang, Guanhua,Xu, Xu,Huang, Guanhua,Sun, Chen,Mohanty, Binayak P.. 2016

[16]The growth and antioxidant defense responses of wheat seedlings to omethoate stress. Liang, Yongchao,Zhang, Bo,Chu, Guixin,Wei, Changzhou,Ye, Jun,Li, Zhiqiang,Zhang, Bo.

[17]Estimation of 305-day milk yield from test-day records of Chinese Holstein cattle. Kong, Ling-na,Li, Jian-bin,Li, Rong-ling,Huang, Jin-ming,Hou, Ming-hai,Zhong, Ji-feng,Kong, Ling-na,Sun, Shao-hua,Zhao, Xiu-xin,Ju, Zhi-hua,Ma, Ya-bin. 2017

[18]Data fusion for management of outdoor stored grain. Sun, L,Zhu, ZS. 2002

[19]Temperature-dependent development and oviposition behavior of Trichogramma ostriniae (Hymenoptera : Trichogrammatidae), a potential biological control agent for the European corn borer (Lepidoptera : Crambidae). Wang, BD,Ferro, DN,Wu, JW,Wang, SQ. 2004

[20]Correlation of resistance to Nilaparvata lugens Stal with secondary metabolites of rice plants. Liang, Guang-Wen,Zeng, Ling,Lin, Bing,Yang, Lang,Huang, Feng-Kuan. 2011

作者其他论文 更多>>

微信小程序