基于多尺度遥感数据估算地表通量的方法及其验证分析

地表水热通量(显热通量、潜热通量)的遥感估算在全球气候变化、水资源、生态环境等研究领域具有重要的应用价值.MODIS数据的空间分辨率较低(热红外波段星下点为1 km),而地球表面的几何物理属性又具有高度非均匀性,因而在实际应用中面临较严重的尺度问题.探讨了多源卫星数据(中高分辨率Landsat TM与中低分辨率MODIS)相结合佑算像元通量的2种方法,分别利用高分辫率的地表分类及植被指数信息在混合像元内部进行亚像元处理,以提高非均匀地表混合像元的通量估算精度.研究数据来自于2008年黑河流域综合实验获取的遥感数据和辅助数据,验证数据来自于实验期间获取的不同下垫面的地表通量数据,包括涡度相关(EC)数据,以及大孔径闪烁仪(LAS)数据.计算结果表明,2种方法皆可在下垫面不均匀或者地表类型较复杂的情况下得到比较明显的纠正效果,纠正后的通量与观测更加接近.相比之下,利用植被指数分解温度的方法适用性更广,纠正效果更好.在地面验证中,对比分析了EC和LAS数据在TM尺度和MO-DIS尺度通量验证的适用性.LAS数据测量尺度与MODIS卫星像元尺度相匹配,可以直接验证MODIS通量计算结果,EC数据虽然可以直接验证TM计算的通量,但与MODIS数据对比,还需要进行尺度转换,即先用EC验证TM通量,然后将TM通量降尺度,与MODIS进行对比.最后对利用LAS验证通量的不确定性进行了分析,发现图像中LAS测点的几何定位误差以及LAS测量路径中像元的选取都对验证结果有一定影响.

Method and Validation for Surface Fluxes Estimation based on Multi-scale Remotely Sensed Data

Estimation of regional surface heat fluxes (sensible heat flux and latent heat flux) using remote sensing data is of important application value in the field of global climate change, water resource and ecological environment etc. The Moderate Resolution Imaging Spectroradiometer (MODIS) data has lower spatial resolution; however the geometric and physical properties of the Earth's surface also have a high degree of heterogeneity, which in practice are facing serious scaling problems. This paper discusses two methods of estimating the pixel fluxes using multi-source satellite data (the high-resolution Landsat TM data and low-resolution MODIS data), combining the land cover information or remotely sensed vegetation index provided by Landsat data with MODIS data to correct the spatial-scale errors. The remote sensing data and ancillary data used in this paper to evaluate the methods was obtained in comprehensive experiment held at Hei′he Watershed in 2008, validation data was surface flux data from the different surfaces during the experiment, including Eddy-Correlation (EC) data and Large Aperture Scintillometer (LAS) data. The results showed that, the combination method that use high resolution land class or vegetation index data can provide better estimation of surface heat fluxes, especially at the boundary of different land cover and heterogeneous land surfaces. By contrast, the method of using remotely sensed vegetation index provided by Landsat data to decompose temperature is more applicable and has a better validation result. The application of both Eddy-Correlation (EC) data and Large Aperture Scintillometer (LAS) data were analyzed by contrasting in the scaling process of fluxes validation by TM and MODIS. According to the pixel resolution of MODIS, LAS measurement can provided useful data at the scale of several kilometers, and can be used to validate MODIS fluxes directly. On the other hand, EC data need to be compared to the TM fluxes first, and then the downscaled TM fluxes can be used to validate MODIS fluxes. Finally, the uncertainties in the validation of fluxes using LAS data are mainly from the following aspect, ① the error from the positioning of the LAS site in the image; ② uncertainty in the contributing pixels of LAS observation in the image.