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Remote Sensing for Natural Resources    2021, Vol. 33 Issue (3) : 202-210     DOI: 10.6046/zrzyyg.2020329
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Spatial-temporal analysis of drought characteristics of Yunnan Province based on MODIS_TVDI/GNSS_PWV data
YU Wei1(), KE Fuyang1(), CAO Yunchang2
1. School of Remote Sensing & Geomatics Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
2. Meteorological Observation Center, China Meteorological Administration, Beijing 100081, China
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Abstract  

Existing drought monitoring technologies are liable to be affected by the environment and suffer poor timeliness. Given this, this study utilized the MODIS_TVDI and GNSS_PWV data to investigate the spatial-temporal changes in the drought characteristics in spring from 2016 to 2020 in Yunnan province through correlation analysis and regression analysis. The research results are as follows. The TVDI inversion results can accurately reflect the spatial-temporal changes in the regional drought characteristics during 2016—2020. In space, the drought showed the trend of increasing from northwest to southeast in Yunnan. In terms of time, the drought increased first and then alleviated in spring, especially from March to April. In addition, there was a strong correlation between PWV and TVDI according to Pearson correlation analysis. The correlation coefficient was largely greater than 0.5 on a quarterly scale. On a monthly scale, the variation trend of PWV was roughly consistent with that of TVDI, except that the variation of TVDI showed a certain time delay. On a daily scale, the variation amplitude of PWV was highly consistent with that of TVDI, especially during rainfall, and both of them showed certain signals of drought characteristics. Therefore, PWV can serve as a new technical means for drought monitoring.
Keywords temperature vegetation drought index      precipitable water vapor      correlation analysis      Yunnan Province     
ZTFLH:  TP79  
Corresponding Authors: KE Fuyang     E-mail: 2232446236@qq.com;ke.fuyang@qq.com
Issue Date: 24 September 2021
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Wei YU
Fuyang KE
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Wei YU,Fuyang KE,Yunchang CAO. Spatial-temporal analysis of drought characteristics of Yunnan Province based on MODIS_TVDI/GNSS_PWV data[J]. Remote Sensing for Natural Resources, 2021, 33(3): 202-210.
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https://www.gtzyyg.com/EN/10.6046/zrzyyg.2020329     OR     https://www.gtzyyg.com/EN/Y2021/V33/I3/202
Fig.1  The study area and the distribution map of CORS stations and weather stations
Fig.2  The Ts-NDVI feature space
Fig.3  Fitting diagram of Ts-NDVI feature space(2016—2020)
日期 干边 R2 湿边 R2
2016年1月 y=0.69x+22.42 0.01 y=2.93x-2.59 0.17
2016年2月 y=-6.73x+29.48 0.58 y=7.34x-1.03 0.56
2016年3月 y=-14.94x+39.20 0.92 y=6.77x+2.32 0.49
2016年4月 y=-17.03x+43.78 0.90 y=11.22x+0.27 0.56
2016年5月 y=-12.76x+43.45 0.86 y=4.96x+6.53 0.09
2017年1月 y=-14.21x+43.78 0.11 y=2.12x-0.17 0.07
2017年2月 y=-8.40x+31.79 0.57 y=1.56x+3.82 0.05
2017年3月 y=-10.56x+36.34 0.89 y=6.50x+1.61 0.51
2017年4月 y=-11.29x+39.89 0.87 y=7.41x+2.98 0.50
2017年5月 y=-14.21x+43.81 0.83 y=9.76x+2.95 0.39
2018年1月 y=-1.42x+24.63 0.07 y=2.59x-1.71 0.14
2018年2月 y=-8.25x+32.20 0.72 y=2.5x+1.76 0.13
2018年3月 y=-19.6x+40.82 0.91 y=5.07x+3.36 0.35
2018年4月 y=-20.2x+45.22 0.93 y=3.97x+6.08 0.22
2018年5月 y=-15.61x+44.51 0.86 y=12.73x-1.81 0.21
2019年1月 y=-5.53x+26.78 0.39 y=2.53x-1.94 0.10
2019年2月 y=-8.59x+32.99 0.71 y=6.97x-2.49 0.41
2019年3月 y=-14.72x+39.55 0.89 y=6.91x+2.167 0.47
2019年4月 y=-17.29x+45.31 0.88 y=7.77x+5.54 0.49
2019年5月 y=-11.42x+43.64 0.84 y=7.89x+6.11 0.33
2020年1月 y=-2.94x+26.43 0.24 y=4.27x-3.59 0.35
2020年2月 y=-6.15x+30.65 0.65 y=4.28x-1.34 0.35
2020年3月 y=-13.8x+40.16 0.87 y=4.75x+3.57 0.36
2020年4月 y=-15.41x+43.68 0.87 y=6.05x+5.49 0.31
2020年5月 y=-13.14x+43.93 0.87 y=2.32x+7.29 0.05
Tab.1  The fitting equation and correlation coefficient of dry and wet edge in characteristic space (2016—2020)
时间 相关系数
2016年 0.73
2017年 0.70
2018年 0.73
2019年 0.50
2020年 0.30
Tab.2  Correlation coefficient between TVDI and PWV (2016—2020)
Fig.4  Change trend chart of PWV and TVDI (2016—2020)
Fig.5  Change trend chart of TVDI, rainfall and PWV of YNMJ Station
干旱等级 TVDI 干旱类型
1 0.0<TVDI≤0.2 湿润
2 0.2<TVDI≤0.4 正常
3 0.4<TVDI≤0.6 轻旱
4 0.6<TVDI≤0.8 中旱
5 0.8<TVDI≤1.0 重旱
Tab.3  Drought grade
Fig.6  Distribution map of spring drought from 2016 to 2020
Fig.7  The proportion of light drought, medium drought and severe drought in Yunnan Province
Fig.8  Trend of temperature and relative humidity
Fig.9  The correlation between TVDI and temperature,relative humidity, PWV and temperature,relative humidity
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