Study on Spatial and Temporal Characteristics of Surface Albedo at the Northern Edge of the Badain Jaran Desert Based on C + STNLFFM Model.

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.

[Using geographical detection to analyze responses of vegetation growth to climate change in the Loess Pla-teau, China]. / 基于地理探测的黄土高原植被生长对气候的响应.

In order to explore the responses of different vegetation types to climatic change in the Chinese Loess Plateau (CLP), we analzyed the changes of different vegetation types and their relationships with meteorological factors using trend analysis, Hurst index, and geographical detector model based on normalized difference vegetation index (NDVI). The results showed that NDVI of different vegetation types from 2002 to 2019 was dominated by a growing trend and codirectional moderate persistence. The NDVI of crops in the built-up and adjacent areas decreased significantly. Except for grassland or meadow that was affected by mixed pixels, the spatial variation of NDVI was significant in the growing season (from April to October). The mean NDVI of different vegetation types followed an oder: coniferous forest > broadleaved forest > scrub > meadow > grassland > crop > steppe > desert. The interactions between meteorological factors were synergistic and non-linear enhancement in the CLP. Moreover, the interaction was more prominent under steppe and desert where habitat was fragile. The synergistic effect of precipitation and temperature had a great influence on all vegetation types. Water vapor, relative humidity, sunshine duration, atmospheric pressure, and wind speed had different explanatory powers on NDVI through indirectly affec-ting hydrothermal conditions.