【摘要】 近年来随着全球极端天气的加剧,中国南方地区干旱灾害频繁发生,研究适合特定区域的旱情监测方法意义重大。TVDI是目前广泛使用的农业旱情遥感监测指标之一,在中国北方地区的农业旱情监测中得到了较好的应用,但其对于中国南方高植被覆盖区的旱情监测效果不理想。基于此该文提出了增强温度植被指数(ETVDI,enhanced temperature vegetation dryness index),该方法克服了TVDI在高植被覆盖区植被指数饱和的缺陷,并采用多项式拟合干湿边方程构建特征空间。利用该方法对珠江流域片2015年5月干旱状况进行监测,并结合标准化降水指数对其结果进行了验证。结果表明:1)ETVDI监测的旱情空间分布与标准化降水指数的旱情空间分布基本一致,能够较好地体现出不同旱情等级的空间分布状况;2)ETVDI模型中采用的多项式拟合干湿边方程的方法,将原来湿边拟合趋势线可靠性由0.16提高到0.97,提高了模型参数计算的精确度。同时,多项式拟合的方法是在保障拟合精度的前提下获得模型参数,相对于传统的线性拟合方式,受数据自身的影响较小,能够保证旱情监测结果的精确性。该研究提出的ETVDI模型,为中国南方地区的旱情监测提供了一种新的方法手段。更多还原

【Abstract】 In recent years,the extreme weathers occurred frequently with the constant changes in the global climate. In China,drought generally occurred in the northern region,but recently droughts have also happened frequently in the southern region. So it is very important to study the suitable drought monitoring method for the southern China. Temperature Vegetation Dryness Index( TVDI) as one of drought monitoring index has been widely used,and got a better application in northern China,but it is not ideal for monitoring the effects of the drought in southern China where is the high vegetation coverage area. In this research,we proposed a new drought monitoring index: enhanced temperature vegetation dryness index( ETVDI),which overcomes the defect of vegetation index saturation in temperature vegetation dryness index( TVDI) in high vegetation cover area.Meanwhile,we constructed an irregular polygon feature space by using polynomial equation manner fitting dry edge and wet edge of the model. Then,we used ETVDI model to monitor droughts in the Pearl River basin in May 2015,and the results were verified combined with the standardized precipitation index. The results show that: 1) the spatial distribution of droughts monitored by ETVDI is consistent with the distribution of the standardized precipitation index,it can better reflect the different levels of the spatial distribution of droughts. 2) The dry edge and wet edge based on the polynomial equation are more accuracy than that based on the linear equation for reversion of the drought. The polynomial equation method increased the original wet edge fitting trend line from 0. 16 to 0. 97,and improved the accuracy of the model parameter calculation. Meanwhile,comparing to traditional linear equation fitting,using polynomial equation to fit wet edge and dry edge is more accuracy,and impacted less by the data itself. Lastly,ETVDI model proposed for drought monitoring in southern China provides a new methodological approaches.更多还原