Evaluation of multi-sensor satellite data for monitoring different drought impacts

被引:24
|
作者
Park, Seo-Yeon [1 ]
Sur, Chanyang [2 ]
Kim, Jong-Suk [3 ]
Lee, Joo-Heon [1 ]
机构
[1] Joongbu Univ, Dept Civil Engn, Goyang Si 10279, Gyeonggi Do, South Korea
[2] Joongbu Univ, Drought Res Ctr, Goyang Si 10279, Gyeonggi Do, South Korea
[3] Wuhan Univ, State Key Lab Water Resources & Hydropower Engn S, Wuhan 430072, Hubei, Peoples R China
基金
新加坡国家研究基金会;
关键词
Drought; Drought impact assessment; Remote sensing; SPI; VHI; ESI; INDEXES;
D O I
10.1007/s00477-018-1537-x
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Drought is a natural disaster that significantly affects human life; therefore, precise monitoring and prediction is necessary to minimize drought damage. Conventional drought monitoring is based predominantly on ground observation stations; however, satellite imagery can be used to overcome the disadvantages of existing monitoring methods and has the advantage of monitoring wide areas. In this research, we assess the applicability of drought monitoring based on satellite imagery, focusing on historic droughts in 2001 and 2014, which caused major agricultural and hydrological issues in South Korea. To assess the applicability and accuracy of the drought index, drought impact areas in the study years were investigated, and spatiotemporal comparative analyses between the calculated drought index and previously affected areas were conducted. For drought monitoring based on satellite imagery, we used hydro-meteorological factors such as precipitation, land surface temperature, vegetation, and evapotranspiration, and applied remote sensing data from various sensors. We verified the effectiveness of using precipitation data for meteorological drought monitoring, vegetation and land surface temperature data for agricultural drought monitoring, and evapotranspiration data for hydrological drought monitoring. Moreover, we confirmed that the Standard Precipitation Index (SPI) can be indirectly applied to agricultural or hydrological drought monitoring by determining the temporal correlation between SPI, calculated for various time scales, and satellite-based drought indices.
引用
收藏
页码:2551 / 2563
页数:13
相关论文
共 50 条
  • [21] A new station-enabled multi-sensor integrated index for drought monitoring
    Jiao, Wenzhe
    Wang, Lixin
    Novick, Kimberly A.
    Chang, Qing
    JOURNAL OF HYDROLOGY, 2019, 574 : 169 - 180
  • [22] Processing system for tropical cyclone multi-sensor satellite data sets
    Helveston, MJ
    Hawkins, JD
    May, DA
    Poe, G
    Sandlin, G
    12TH INTERNATIONAL CONFERENCE ON INTERACTIVE INFORMATION AND PROCESSING SYSTEMS (IIPS) FOR METEOROLOGY, OCEANOGRAPHY, AND HYDROLOGY: JOINT SESSION WITH FIFTH SYMPOSIUM ON EDUCATION, 1996, : 476 - 478
  • [23] Multi-sensor data fusion framework for CNC machining monitoring
    Duro, Joao A.
    Padget, Julian A.
    Bowen, Chris R.
    Kim, H. Alicia
    Nassehi, Aydin
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2016, 66-67 : 505 - 520
  • [24] Automatic Flood Duration Estimation Based on Multi-Sensor Satellite Data
    Raettich, Michaela
    Martinis, Sandro
    Wieland, Marc
    REMOTE SENSING, 2020, 12 (04)
  • [25] Satellite multi-sensor data analysis of urban surface temperatures and landcover
    Dousset, B
    Gourmelon, F
    ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2003, 58 (1-2) : 43 - 54
  • [26] A comparative data-fusion analysis of multi-sensor satellite images
    Abdikan, Saygin
    Sanli, Fusun Balik
    Sunar, Filiz
    Ehlers, Manfred
    INTERNATIONAL JOURNAL OF DIGITAL EARTH, 2014, 7 (08) : 671 - 687
  • [27] Assessing tundra-taiga boundary with multi-sensor satellite data
    Ranson, KJ
    Sun, G
    Kharuk, VI
    Kovacs, K
    REMOTE SENSING OF ENVIRONMENT, 2004, 93 (03) : 283 - 295
  • [28] Application of Multi-Sensor Satellite Data to Observe Water Storage Variations
    Singh, Alka
    Seitz, Florian
    Schwatke, Christian
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2013, 6 (03) : 1502 - 1508
  • [29] CONVOLUTIONAL AUTOENCODER MODEL FOR HYPERSPECTRAL MULTI-SENSOR SATELLITE DATA COMPRESSION
    Kuester, J.
    Gross, W.
    Schreiner, S.
    Middelmann, W.
    Heizmann, M.
    IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2023, : 5383 - 5386
  • [30] Evaluation of Utilization of Satellite Remote Sensing Data for Drought Monitoring
    Won, Jeongeun
    Son, Youn-Suk
    Lee, Sangho
    Kong, Limseok
    Kim, Sangdan
    KOREAN JOURNAL OF REMOTE SENSING, 2021, 37 (06) : 1803 - 1818