Developing the vegetation drought response index for South Korea (VegDRI-SKorea) to assess the vegetation condition during drought events

被引:26
作者
Nam, Won-Ho [1 ,2 ,3 ,4 ]
Tadesse, Tsegaye [1 ,2 ]
Wardlow, Brian D. [2 ,5 ]
Hayes, Michael J. [2 ]
Svoboda, Mark D. [1 ,2 ]
Hong, Eun-Mi [6 ]
Pachepsky, Yakov A. [6 ]
Jang, Min-Won [7 ]
机构
[1] Univ Nebraska, Natl Drought Mitigat Ctr, Lincoln, NE USA
[2] Univ Nebraska, Sch Nat Resources, Lincoln, NE USA
[3] Hankyong Natl Univ, Dept Bioresources & Rural Syst Engn, Anseong, South Korea
[4] Hankyong Natl Univ, Inst Agr Environm Sci, Anseong, South Korea
[5] Univ Nebraska, Ctr Adv Land Management Informat Technol, Lincoln, NE USA
[6] USDA ARS, Beltsville Agr Res Ctr, Environm Microbial & Food Safety Lab, Beltsville, MD 20705 USA
[7] Gyeongsang Natl Univ, Inst Agr & Life Sci, Dept Agr Engn, Jinju, South Korea
基金
美国国家航空航天局;
关键词
REMOTE-SENSING DATA; SEVERITY INDEX; CLIMATE-CHANGE; GREAT-PLAINS; SATELLITE; EVAPOTRANSPIRATION; MANAGEMENT; STRESS; NDVI; VARIABILITY;
D O I
10.1080/01431161.2017.1407047
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
South Korea has experienced severe droughts and water scarcity problems that have influenced agriculture, food prices, and crop production in recent years. Traditionally, climate-based drought indices using point-based meteorological observations have been used to help quantify drought impacts on the vegetation in South Korea. However, these approaches have a limited spatial precision when mapping detailed vegetation stress caused by drought. For these reasons, the development of a drought index that provides detailed spatial-resolution information on drought-affected vegetation conditions is essential to improve the country's drought monitoring capabilities, which are needed to help develop more effective adaptation and mitigation strategies. The objective of this study was to develop a satellite-based hybrid drought index called the vegetation drought response index for South Korea (VegDRI-SKorea) that could improve the spatial resolution of agricultural drought monitoring on a national scale. The VegDRI-SKorea was developed for South Korea, modifying the original VegDRI methodology (developed for the USA) by tailoring it to the available local data resources. The VegDRI-SKorea utilizes a classification and regression tree (CART) modelling approach that collectively analyses remote-sensing data (e.g. normalized difference vegetation index (NDVI)), climate-based drought indices (e.g. self-calibrated Palmer drought severity index (PDSI) and standardized precipitation index (SPI)), and biophysical variables (e.g. elevation and land cover) that influence the drought-related vegetation stress. This study evaluates the performance of the recently developed VegDRI-SKorea for severe and extreme drought events that occurred in South Korea in 2001, 2008, and 2012. The results demonstrated that the hybrid drought index improved the more spatially detailed drought patterns compared to the station-based drought indices and resulted in a better understanding of drought impacts on the vegetation conditions. The VegDRI-SKorea model is expected to contribute to the monitoring of drought conditions nationally. In addition, it will provide the necessary information on the spatial variations of those conditions to evaluate local and regional drought risk assessment across South Korea and assist local decision-makers in drought risk management.
引用
收藏
页码:1548 / 1574
页数:27
相关论文
共 39 条
  • [1] Building the vegetation drought response index for Canada (VegDRI-Canada) to monitor agricultural drought: first results
    Tadesse, Tsegaye
    Champagne, Catherine
    Wardlow, Brian D.
    Hadwen, Trevor A.
    Brown, Jesslyn F.
    Demisse, Getachew B.
    Bayissa, Yared A.
    Davidson, Andrew M.
    GISCIENCE & REMOTE SENSING, 2017, 54 (02) : 230 - 257
  • [2] Ecological Drought Condition Index to Monitor Vegetation Response to Meteorological Drought in Korean Peninsula
    Won, Jeongeun
    Kim, Sangdan
    REMOTE SENSING, 2023, 15 (02)
  • [3] Evaluating the utility of the Vegetation Condition Index (VCI) for monitoring meteorological drought in Texas
    Quiring, Steven M.
    Ganesh, Srinivasan
    AGRICULTURAL AND FOREST METEOROLOGY, 2010, 150 (03) : 330 - 339
  • [4] Drought index revisited to assess its response to vegetation in different agro-climatic zones
    Faiz, Muhammad Abrar
    Zhang, Yongqiang
    Tian, Xiaoqiang
    Tian, Jing
    Zhang, Xuanze
    Ma, Ning
    Aryal, Santosh
    JOURNAL OF HYDROLOGY, 2022, 614
  • [5] Monitoring vegetation drought in the nine major river basins of China based on a new developed Vegetation Drought Condition Index
    Lili Zhao
    Lusheng Li
    Yanbin Li
    Huayu Zhong
    Fang Zhang
    Junzhen Zhu
    Yibo Ding
    Journal of Arid Land, 2023, 15 : 1421 - 1438
  • [6] Monitoring vegetation drought in the nine major river basins of China based on a new developed Vegetation Drought Condition Index
    Zhao, Lili
    Li, Lusheng
    Li, Yanbin
    Zhong, Huayu
    Zhang, Fang
    Zhu, Junzhen
    Ding, Yibo
    JOURNAL OF ARID LAND, 2023, 15 (12) : 1421 - 1438
  • [7] Using leaf area index (LAI) to assess vegetation response to drought in Yunnan province of China
    Kim, Kwangchol
    Wang, Ming-cheng
    Ranjitkar, Sailesh
    Liu, Su-hong
    Xu, Jian-chu
    Zomer, Robert J.
    JOURNAL OF MOUNTAIN SCIENCE, 2017, 14 (09) : 1863 - 1872
  • [8] Assessment of Vegetation Response to Drought in Nebraska Using Terra-MODIS Land Surface Temperature and Normalized Difference Vegetation Index
    Swain, Sharmistha
    Wardlow, Brian D.
    Narumalani, Sunil
    Tadesse, Tsegaye
    Callahan, Karin
    GISCIENCE & REMOTE SENSING, 2011, 48 (03) : 432 - 455
  • [9] Drought Forecasting with Vegetation Temperature Condition Index Using ARIMA Models in the Guanzhong Plain
    Tian, Miao
    Wang, Pengxin
    Khan, Jahangir
    REMOTE SENSING, 2016, 8 (09)
  • [10] Remote Sensing Drought Monitoring Under Dense Vegetation Cover Condition Based on Perpendicular Drought Index
    Li, Zhe
    Tan, Debao
    Cui, Yuanlai
    Zhang, Sui
    2009 17TH INTERNATIONAL CONFERENCE ON GEOINFORMATICS, VOLS 1 AND 2, 2009, : 212 - +