植被类型对温度植被干旱指数(TVDI)的影响研究——以黑河绿洲区为例

Evaluating Effects of Vegetation Types on Temperature Vegetation Drought Index(TVDI) in the Heihe Oasis Region

温度植被干旱指数(TVDI)是进行干旱研究的有效指标,是反演土壤湿度的重要方法。植被覆盖类型是影响TVDI大小的重要因素。利用修正的土壤调整植被指数MSAVI替换NDVI,以便最小化土壤背景影响和提高对密植被的光谱敏感性,并在此基础上,比较基于植被分类计算的TVDI与基于传统方法计算的TVDI的大小,来研究植被类型对TVDI提取结果的影响。对比分析表明,阔叶林、灌丛和密草地的平均值与传统方法计算的差别较大,变化分别是+7.2%、-5.5%和-6.6%,产生平均值偏移主要是由于植被类型的冠层结构和光学属性的差异带来的LST-MSAVI空间特征干湿边的变化引起的。因此,在应用TVDI指数进行大范围干旱化研究和土壤湿度反演时,不同植被类型不能一起作LST-MSAVI空间特征来计算TVDI指数,需要考虑植被类型等影响因素,达到提高土壤湿度反演精度的目的。

Temperature Vegetation Drought Index （TVDI） is a valid indicator of drought and also an important parameter for retrieval of soil moisture. Vegetation cover type is an important factor affects the retrieval of TVDI with remotely sensed data. To reduce the impact of soil back ground on the accurate retrieval of TDVI and enhance the sensitivity of densely populated vegetation, this paper utilizes modified soil-adjusted vegetation index （MSAVI） to replace NDVI. After the vegetation cover was classified,TVDI retrieved after classification was compared to that derived with traditional method that employ all the pixels of remotely sensed data of region to examine the effects induced by the introduction of vegetation classification. The results show that the average TVDI of broad-leaf forest, scrub and close grassland is evidently different from those obtained with traditional method, the differences between the retrieved TDVI with these two different procedures reach to about ＋7.2%,-6.6% and -5.5% respectively. This was mainly attributed to the difference of canopy structure and optical properties of vegetation types,which causes the shifting of ＂wet＂ and ＂dry＂ lines in the LST-MSAVI space characteristics. Therefore,for the large-scale drought evaluating research and soil moisture retrieval by means of TDVI,different vegetation types should be taken into account for modeling LST-MSAVI space to achieve the goal for improving soil moisture retrieval accuracies.