Spatial-temporal analysis of drought characteristics of Yunnan Province based on MODIS_TVDI/GNSS_PWV data
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摘要: 为了缓解现有干旱监测技术存在的监测易受环境影响、时效性不强等问题。本研究使用MODIS_TVDI和GNSS_PWV数据,利用相关性分析、回归分析等方法研究云南省2016—2020年春季干旱特征时空变化。研究结果表明: TVDI反演结果能较好地反映区域干旱时空特征变化,在空间上,旱情呈滇西北向滇东南增强的趋势; 在时间上,季内旱情呈先递增后减缓趋势,尤其3—4月份旱情变化特征最为明显。此外,基于Pearson相关分析方法发现PWV和TVDI存在较强的相关性,在季尺度上,相关系数基本均大于0.5; 在月尺度上,PWV变化趋势与TVDI变化趋势基本一致,但TVDI变化有一定的时间延迟; 在日尺度上,尤其是降雨时期,PWV变化和TVDI变化幅度契合度更高,表现出了一定的干旱特征信号,因此PWV为旱灾监测提供了一种新的技术手段。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.
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