| 基于HJ-CCD数据的水稻洪涝灾情诊断分析及长势监测 |
| |
| 引用本文： | 王慧芳,霍治国,周广胜,吴立,冯海宽,黄大鹏.基于HJ-CCD数据的水稻洪涝灾情诊断分析及长势监测[J].农业工程学报,2015,31(Z2):107-111. |
| |
| 作者姓名： | 王慧芳 霍治国 周广胜 吴立 冯海宽 黄大鹏 |
| |
| 作者单位： | 中国气象科学研究院,北京 100081;北京农业信息技术研究中心,北京 100097,中国气象科学研究院,北京 100081,中国气象科学研究院,北京 100081,中国气象科学研究院,北京 100081,北京农业信息技术研究中心,北京 100097,国家气候中心,北京 100081 |
| |
| 基金项目： | the National Natural Science Foundation of China(41401415).the National Science-technology Support Plan Projects(2012BAD20B02). |
| |
| 摘 要： |
|
| 关 键 词： | remote sensing vegetation models rice flood disaster LAI Beer—Lambert laws HJ-CCD data |
| 收稿时间： | 2015/10/1 0:00:00 |
Rice flooding disaster diagnosis analysis and growth monitoring based on HJ-CCD data |
| |
| Wang Huifang,Huo Zhiguo,Zhou Guangsheng,Wu Li,Feng Haikuan and Huang Dapeng.Rice flooding disaster diagnosis analysis and growth monitoring based on HJ-CCD data[J].Transactions of the Chinese Society of Agricultural Engineering,2015,31(Z2):107-111. |
| |
| Authors: | Wang Huifang Huo Zhiguo Zhou Guangsheng Wu Li Feng Haikuan and Huang Dapeng |
| |
| Institution: | Chinese Academy of Meteorological Sciences, Beijing 100081, China;Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China,Chinese Academy of Meteorological Sciences, Beijing 100081, China,Chinese Academy of Meteorological Sciences, Beijing 100081, China,Chinese Academy of Meteorological Sciences, Beijing 100081, China,Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China and National Climate Centre, Beijing 100081, China |
| |
| Abstract: | It has great significance to study quick monitoring of rice flood disaster and applying timely remedial measures in the disaster area.LAI is a very important physiological parameter in crop growth characterization index, which can reflect the crop growing information objectively.The existing methods of flood monitoring using remote sensing technology rarely consider the damage and the post disaster growth of rice.The HJ-CCD data take advantage of high temporal resolution and high spatial resolution remote sensing image, which can be used for gathering rice growing information during the critical period.The growth situation after rice flood disaster in Anhui Province was monitored using 3 screens HJ-CCD data as the data source on 16th July, 19th August, 26th August, 2009, respectively.The semi-empirical function model based on Beer-Lambert laws was constructed for this inversion LAI.And LAI were acquired in each stage after flood disaster, the trend of growth diagnosis dynamic change was analyzed and assessed by rice flood disaster evaluation indicator.At the same time, the 40 field investigate data were used to verify the model and the R2=0.4251, RMSE=2.053.The results show that LAI can be well evaluated the degree of rice flood disaster growth based on HJ-CCD data, and it is effective for monitoring and diagnosing rice flood disaster.The results provide a theoretical basis for rice flood disaster research, post disaster rehabilitation and recovery, and provide a theoretical basis for the implementation of targeted remedial measures at the same time. |
| |
| Keywords: | |
|
| 点击此处可从《农业工程学报》浏览原始摘要信息 |
| 点击此处可从《农业工程学报》下载免费的PDF全文 |
|
