Temporal and spatial dynamics of spring drought in Qinghai-Tibet region based on VCI index
JI Min1(), ZHANG Chao1, ZHAO Jianwei1, YAN Juan2, LIANG Liang2
1. College of Geomatics,Shandong University of Science and Technology, Qingdao 266590, China 2. School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, China
The spatial-temporal characteristics of spring drought are very important for decision-making and many agricultural applications. In this study, the spatial-temporal analysis of vegetation drought in Qinghai-Tibet region from 1995 to 2010 was carried out by using the vegetation state index of NOAA. According to the characteristics of VCI as a drought index, a variety of methods were used, which included frequency analysis, trend analysis and man Kendall experiment. The results show that the Qinghai-Tibet Region is less affected by monsoon, the frequency of drought in Hengduan Mountain and Qilian Mountain is relatively low, and most of the droughts are light and medium drought. According to the analysis, the trend of drought in this area is not unidirectional and can be divided into two stages. Before 2000, the VCI index was relatively high, and the volatility was relatively large; after 2000, the VCI index was relatively low, and relatively stable.
季民, 张超, 赵建伟, 严娟, 梁亮. 基于VCI指数的青藏地区春旱时空动态变化分析[J]. 国土资源遥感, 2021, 33(1): 152-157.
JI Min, ZHANG Chao, ZHAO Jianwei, YAN Juan, LIANG Liang. Temporal and spatial dynamics of spring drought in Qinghai-Tibet region based on VCI index. Remote Sensing for Land & Resources, 2021, 33(1): 152-157.
Tang Y, Sun R. Drought characteristics in Henan Province with meteorological and remote sensing data[J]. Journal of Natural Resources, 2013,28(4):646-655.
doi: 10.11849/zrzyxb.2013.04.011
Yang B, Ma S, Wang B W, et al. Agricultural drought monitoring model based on MODIS data in Hunan Province[J]. Journal of Natural Resources, 2012,27(10):1788-1796.
[4]
Yilmaz M T, Hunt E R, Jackson T J. Remote sensing of vegetation water content from equivalent water thickness using satellite imagery[J]. Remote Sensing of Environment, 2008,112(5):2514-2522.
doi: 10.1016/j.rse.2007.11.014
[5]
Kogan F N. Droughts of the late 1980s in the United States as derived from NOAA polar-orbiting satellite data[J]. Bulletin of the American Meteorological Society, 1995,76(5):655-668.
doi: 10.1175/1520-0477(1995)076<0655:DOTLIT>2.0.CO;2
[6]
Sahoo A K, Sheffield J, Pan M, et al. Evaluation of the tropical rainfall measuring mission multi-satellite precipitation analysis (TMPA) for assessment of large-scale meteorological drought[J]. Remote Sensing of Environment, 2015,159:181-193.
doi: 10.1016/j.rse.2014.11.032
[7]
Di L P, Rundquist D C, Han L H. Modeling relationships between NDVI and precipitation during vegetative growth cycles[J]. International Journal of Remote Sensing, 1994,15(10):2121-2136.
doi: 10.1080/01431169408954231
[8]
Kogan F, Sullivan J. Development of global drought- watch system using NOAA/AVHRR data[J]. Advances in Space Research, 1993,13(5):219-222.
[9]
Gitelson A A, Kogan F N, Zakarin E, et al. Using AVHRR data for quantitative estimationof vegetation conditions:Calibration and validation[J]. Advance in Space Research, 1998,22:673-676.
[10]
Burgan R E, Hartford R A. Monitoring vegetation greenness with satellite data[R]. United States Department of Agriculture,Forest Service,Intermountain Research Station, 1993.
[11]
Kogan F N. Operational space technology for global vegetation assessment[J]. Bulletin of the American Meteorological Society, 2001,82(9):1949-1964.
Lyu X R, Yin X T, Gong E D, et al. Temporal and spatial analysis of agricultural drought in Yunnan Province based on vegetation condition index[J]. Journal of Geoinformation Science, 2016,18(12):1634-1644.
Li X Y, Yang L A, Nie H M, et al. Assessment of temporal and spatial dynamics of agricultural drought in Shaanxi Province based on vegetation condition index[J]. Chinese Journal of Ecology, 2018,37(4):1172-1180.