He Peng, Bi Rutian, Xu Lishuai, Yang Fan, Wang Jingshu, Cao Chenbin
College of Resources and Environment, Shanxi Agricultural University, Jinzhong 030801, China.
Instituste of Desert Meteorology, China Meteorological Administration, Urumqi 830002, China.
Sensors (Basel). 2022 Aug 29;22(17):6494. doi: 10.3390/s22176494.
Obtaining surface albedo data with high spatial and temporal resolution is essential for measuring the factors, effects, and change mechanisms of regional land-atmosphere interactions in deserts. In order to obtain surface albedo data with higher accuracy and better applicability in deserts, we used MODIS and OLI as data sources, and calculated the daily surface albedo data, with a spatial resolution of 30 m, of Guaizi Lake at the northern edge of the Badain Jaran Desert in 2016, using the Spatial and Temporal Non-Local Filter-based Fusion Model (STNLFFM) and topographical correction model (C model). We then compared the results of STNLFFM and C + STNLFFM for fusion accuracy, and for spatial and temporal distribution differences in surface albedo over different underlying surfaces. The results indicated that, compared with STNLFFM surface albedo and MODIS surface albedo, the relative error of C + STNLFFM surface albedo decreased by 2.34% and 3.57%, respectively. C + STNLFFM can improve poor applicability of MODIS in winter, and better responds to the changes in the measured value over a short time range. After the correction of the C model, the spatial difference in surface albedo over different underlying surfaces was enhanced, and the spatial differences in surface albedo between shifting dunes and semi-shifting dunes, fixed dunes and saline-alkali land, and the Gobi and saline-alkali land were significant. C + STNLFFM maintained the spatial and temporal distribution characteristics of STNLFFM surface albedo, but the increase in regional aerosol concentration and thickness caused by frequent dust storms weakened the spatial difference in surface albedo over different underlying surfaces in March, which led to the overcorrection of the C model.
获取具有高空间和时间分辨率的地表反照率数据对于测量沙漠地区陆地 - 大气相互作用的因素、影响和变化机制至关重要。为了在沙漠地区获得更高精度和更好适用性的地表反照率数据，我们以MODIS和OLI为数据源，运用基于时空非局部滤波的融合模型（STNLFFM）和地形校正模型（C模型），计算了2016年巴丹吉林沙漠北缘拐子湖空间分辨率为30米的每日地表反照率数据。然后，我们比较了STNLFFM和C + STNLFFM在融合精度以及不同下垫面地表反照率的时空分布差异方面的结果。结果表明，与STNLFFM地表反照率和MODIS地表反照率相比，C + STNLFFM地表反照率的相对误差分别降低了2.34%和3.57%。C + STNLFFM可以改善MODIS在冬季适用性较差的问题，并且在短时间范围内能更好地响应测量值的变化。经过C模型校正后，不同下垫面地表反照率的空间差异增强，移动沙丘与半移动沙丘、固定沙丘与盐碱地、戈壁与盐碱地之间的地表反照率空间差异显著。C + STNLFFM保持了STNLFFM地表反照率的时空分布特征，但频繁沙尘暴导致的区域气溶胶浓度和厚度增加削弱了3月不同下垫面地表反照率的空间差异，从而导致C模型校正过度。
