基于地表温度-植被指数特征空间的区域土壤干湿状况

Assessment of regional soil moisture status based on characteristics of surface temperature/vegetation index space

土壤干湿状况是监测土地状况的重要指标之一,在水文、气候和生态等多个领域有广泛应用。地表温度-植被指数特征空间(Ts/VI)综合了传感器从可见光到近红外波段的信息,能较好地反映区域土壤干湿状况。以华北平原作为研究区,选择了研究区的云量较少的16幅MODIS产品,包括每日500m地表反射率产品(MOD09GA),每日1km地表温度产品(MOD11A1),建立温度-植被指数特征空间。首先利用线性方程拟合了特征空间的上下边界,改进了计算特征空间的干湿边的方法,并分析了干湿边参数随时间变化的趋势,比较了归一化植被指数(NDVI)和增强型植被指数(EVI)构建的地表温度-植被指数特征空间形状的差异。基于研究区107个土壤湿度站点的数据,讨论分别由Ts/NDVI和Ts/EVI特征空间计算得到的温度植被干旱指数(temperature vegetation dryness index,简称TVDI,分别为TVDIN与TVDIE)和土壤湿度的相关性,以此验证TVDI反映区域土壤干湿状况的能力。利用Ts/EVI空间计算得到的TVDI分析了研究区4个时期土壤湿度的5空间分布规律。同时在气象站点尺度上,讨论了TVDI与降水变化的相关性。研究结果表明,TVDI能够反映土壤表层的干湿状况;Ts/EVI空间计算得到的TVDI与土壤湿度的相关性比Ts/NDVI空间计算得到的TVDI与土壤湿度的相关性要高。降水随时间变化的规律和TVDI也有明显的相关性,即:每次连续降水以后TVDI值下降,表明土壤湿度升高;经过一段无降水的时间之后,TVDI值上升,土壤湿度降低。研究区不同时期的TVDIE图表明,TVDIE能够有效的反映土壤湿度的时空差异,是一种有效的实时监测土壤干湿状况的手段。

Soil moisture has been considered as one of the most important indicators of soil conditions, and the measurement of soil moisture has been widely used to monitor the status of soil in the fields of hydrology, meteorology and ecology. Surface temperature/vegetation index space （Ts/VI） synthesizes the information from both visible and near-infrared bands of the processed remote sensing image products. Therefore, it can be used to assess the status of soil moisture. In this paper, the North China Plain was chosen as the study area. Sixteen MODIS/Terra images with relatively less cloud shadow contamination, including the surface reflectance daily L2G 500m and 1 km product （MOD09 GA） and the land surface temperature daily 1 km product （ MOD11 A1 ） , were used to establish the Ts/VI space,. In the establishment of the Ts/VI space, Linear regression functions were used to approximately fit the lower and upper boundaries of the the Ts/VI space so that the dry and wet edges of the space can be determined. Furthermore, the trend of changes in the parameters of the two edges was analyzed in the time series. Two surface temperature/vegetation index spaces were established based on the Ts/NDV1 and the Ts/EVI, and the difference between the characteristics of the shapes in these two spaces were investigated. Based on the data obtained from the 107 soil moisture stations in the study area, the correlation between the Temperature Vegetation Dryness Index （TVDI） which was calculated from the Ts/NDVI and the Ts/EVI spaces and the soil moisture was developed and analyzed. The development of the correlation provides a way to use the TVDI to infer soil moisture status. In this paper, the TVDI calculated from Ts/EVI in the study area was used to assess the spatial distribution of soil moisture in the four different crop growth stages. Moreover, the relationship between the TVDI and rainfall was also investigated in those regions with rainfall data from the meteorological stations. The results show that TVDI can be successfully used to infer the near surface soil moisture status. The TVDI calculated from T lEVI has a better correlation with soil moisture comparing to the TVDI calculated from Ts/NDVI. It is also found that there is a similar trend in the change of the TVDI and rainfall in the time series. Continuous rainfall for a certain time is followed by a decline in the TVDI which indicates the increase of soil moisture, and vice versa. The analysis of the TVDI and soil moisture changes of the study area in the different crop growth stages shows that the TVDI space calculated from Ts/EVI can effectively reflect the spatial difference of soil moisture. Therefore, it provides a useful method to monitor and assess the status of regional soil moisture.