The assessment of drought relief by typhoon Saomai based on MODIS remote sensing data in Shanghai, China

被引:0
|
作者
Yuanshu Jing
Jian Li
Yongyuan Weng
Jing Wang
机构
[1] Nanjing University of Information Science and Technology,Jiangsu Key Lab of Agricultural Meteorology
[2] Nanjing University of Information Science and Technology,College of Applied Meteorology
来源
Natural Hazards | 2014年 / 71卷
关键词
Drought relief; Typhoon Saomai; Normalized difference vegetation index (NDVI); Precipitation; Vegetation supply water index (VSWI);
D O I
暂无
中图分类号
学科分类号
摘要
Typhoons are one of the major natural hazards occurring frequently in Shanghai. The comprehensive assessment of drought relief by typhoon has become a major concern of scientists and government agencies in Shanghai, China. In this article, with the support of remote sensing data and the available data from local meteorological stations, the regional drought relief was investigated and the change of drought intensity was quantified by the typhoon “Saomai” between 5 and 8 August 2005. The precipitation anomaly calculated on the basis of recorded rainfall was adopted to analyze drought condition changes before and after the typhoon. Then, vegetation supply water index (VSWI) and normalized difference vegetation index (NDVI) were used to monitor the drought relief due to the consecutive shortage of summer rainfall. Impact of typhoon on drought was compared by VSWI before and after typhoon Saomei. The results showed that the typhoon alleviated the drought of the vegetation by more than 70 %, based on the spatial and temporal distribution of precipitation, the ground temperature, relative humidity, high temperature, NDVI from Shanghai area. The result shows that MODIS remote sensing data are a useful quantitative monitoring tool in drought relief by local typhoons. More strategies are necessary to be adopted for prevention and mitigation of meteorological disaster in Shanghai in recent years.
引用
收藏
页码:1215 / 1225
页数:10
相关论文
共 50 条
  • [1] The assessment of drought relief by typhoon Saomai based on MODIS remote sensing data in Shanghai, China
    Jing, Yuanshu
    Li, Jian
    Weng, Yongyuan
    Wang, Jing
    [J]. NATURAL HAZARDS, 2014, 71 (02) : 1215 - 1225
  • [2] Estimation and Assessment of Drought in North China based on Evapotranspiration Drought Index and Remote Sensing Data
    Zhang, Jiahua
    Yao, Fengmei
    Shao, Xiaolu
    [J]. PROCEEDINGS OF THE AASRI INTERNATIONAL CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (IEA 2015), 2015, 2 : 456 - 459
  • [3] Remote-sensing assessment of forest damage by Typhoon Saomai and its related factors at landscape scale
    Zhang, Xiuying
    Wang, Ying
    Jiang, Hong
    Wang, Xiaoming
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2013, 34 (21) : 7874 - 7886
  • [4] Drought Monitoring and Analyzing by Remote Sensing Based on MODIS Data in Heilongjiang Province of 2009
    Wu, Dongping
    Jiang, Lixia
    Ma, Jianwei
    Sun, Yayong
    [J]. GEO-INFORMATICS IN RESOURCE MANAGEMENT AND SUSTAINABLE ECOSYSTEM, 2016, 569 : 277 - 285
  • [5] Assessment of Urban Heat Islands in Brazil based on MODIS remote sensing data
    Monteiro, Felipe Ferreira
    Goncalves, Weber Andrade
    Barbosa Andrade, Lara de Melo
    Mendoza Villavicencio, Lourdes Milagros
    dos Santos Silva, Cassia Monalisa
    [J]. URBAN CLIMATE, 2021, 35
  • [6] Probability assessment of vegetation vulnerability to drought based on remote sensing data
    Alamdarloo, Esmail Heydari
    Manesh, Maliheh Behrang
    Khosravi, Hassan
    [J]. ENVIRONMENTAL MONITORING AND ASSESSMENT, 2018, 190 (12)
  • [7] Probability assessment of vegetation vulnerability to drought based on remote sensing data
    Esmail Heydari Alamdarloo
    Maliheh Behrang Manesh
    Hassan Khosravi
    [J]. Environmental Monitoring and Assessment, 2018, 190
  • [8] Agricultural Drought Monitoring by MODIS Potential Evapotranspiration Remote Sensing Data Application
    Szewczak, Kamil
    Los, Helena
    Pudelko, Rafal
    Doroszewski, Andrzej
    Gluba, Lukasz
    Lukowski, Mateusz
    Rafalska-Przysucha, Anna
    Slominski, Jan
    Usowicz, Boguslaw
    [J]. REMOTE SENSING, 2020, 12 (20) : 1 - 18
  • [9] Remote-Sensing Drought Monitoring in Sichuan Province from 2001 to 2020 Based on MODIS Data
    Chen, Yuxin
    Yang, Jiajia
    Xu, Yuanyuan
    Zhang, Weilai
    Wang, Yongxiang
    Wei, Jiaxuan
    Cheng, Wuxue
    [J]. ATMOSPHERE, 2022, 13 (12)
  • [10] Application of MODIS time series data for drought assessment in the East China
    Liu, Chaoshun
    Shi, Runhe
    Gao, Wei
    Gao, Zhiqiang
    [J]. REMOTE SENSING AND MODELING OF ECOSYSTEMS FOR SUSTAINABILITY VII, 2010, 7809