Construction of Comprehensive Drought Monitoring Model in Jing-Jin-Ji Region Based on Multisource Remote Sensing Data
文献类型：期刊论文
| 作者 | Yu, Haozhe1,2; Li, Lijuan1; Liu, Yang1,2; Li, Jiuyi1 |
| 刊名 | WATER
 |
| 出版日期 | 2019-05-01 |
| 卷号 | 11期号:5页码:17 |
| 关键词 | multisource remote sensing data synthesized drought monitoring model CDIR trend analysis Jing-Jin-Ji region China |
| ISSN号 | 2073-4441 |
| DOI | 10.3390/w11051077 |
| 通讯作者 | Li, Lijuan(lilijuan@igsnrr.ac.cn) |
| 英文摘要 | Drought is a complex hazard that has more adverse effects on agricultural production and economic development. Studying drought monitoring techniques and assessment methods can improve our ability to respond to natural disasters. Numerous drought indices deriving from meteorological or remote sensing data are focused mainly on monitoring single drought response factors such as soil or vegetation, and the ability to reflect comprehensive information on drought was poor. This study constructed a comprehensive drought-monitoring model considering the drought factors including precipitation, vegetation growth status, and soil moisture balance during the drought process for the Jing-Jin-Ji region, China. The comprehensive drought index of remote sensing (CDIR), a drought indicator deduced by the model, was composed of the vegetation condition index (VCI), the temperature condition index (TCI), and the precipitation condition index (PCI). The PCI was obtained from the Tropical Rainfall Measuring Mission (TRMM) satellite. The VCI and TCI were obtained from a moderate-resolution imaging spectroradiometer (MODIS). In this study, a heavy drought process was accurately explored using the CDIR in the Jing-Jin-Ji region in 2016. Finally, a three-month scales standardized precipitation index (SPI-3), drought affected crop area, and standardized unit yield of wheat were used as validation to evaluate the accuracy of this model. The results showed that the CDIR is closely related to the SPI-3, as well as variations in the drought-affected crop area and standardized unit yield of crop. The correlation coefficient of the CDIR with SPI-3 was between 0.45 and 0.85. The correlation coefficient between the CDIR and drought affected crop was between -0.81 and -0.86. Moreover, the CDIR was positively correlated with the standardized unit yield of crop. It showed that the CDIR index is a decent indicator that can be used for integrated drought monitoring and that it can synthetically reflect meteorological and agricultural drought information. |
| WOS关键词 | VEGETATION INDEX ; CHINA ; TEMPERATURE ; PRECIPITATION ; MODIS ; PROGRESS ; IMPACTS |
| 资助项目 | National Key Research and Development Plan: Factors Identification of Water Resources Carrying Risk and its Mechanism[2016YFC0401307] ; Demand Management of Water Resources and Development Layout in Beijing-Tianjin-Hebei Region[2016YFC0401402] |
| WOS研究方向 | Water Resources |
| 语种 | 英语 |
| WOS记录号 | WOS:000472680400207 |
| 出版者 | MDPI |
| 资助机构 | National Key Research and Development Plan: Factors Identification of Water Resources Carrying Risk and its Mechanism ; Demand Management of Water Resources and Development Layout in Beijing-Tianjin-Hebei Region |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/58343]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Li, Lijuan |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yu, Haozhe,Li, Lijuan,Liu, Yang,et al. Construction of Comprehensive Drought Monitoring Model in Jing-Jin-Ji Region Based on Multisource Remote Sensing Data[J]. WATER,2019,11(5):17. |
| APA | Yu, Haozhe,Li, Lijuan,Liu, Yang,&Li, Jiuyi.(2019).Construction of Comprehensive Drought Monitoring Model in Jing-Jin-Ji Region Based on Multisource Remote Sensing Data.WATER,11(5),17. |
| MLA | Yu, Haozhe,et al."Construction of Comprehensive Drought Monitoring Model in Jing-Jin-Ji Region Based on Multisource Remote Sensing Data".WATER 11.5(2019):17. |
入库方式： OAI收割
来源：地理科学与资源研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。