Land surface temperature is an important indicator for characterizing the habitat conditions and ecological disturbances of ion-adsorbed rare earth mining areas. Because the ions in an ion-adsorbed type rare earth mining area are scattered and the area of a single mining site is small, it is important to obtain practical surface temperature data for monitoring the ecological environment of the area. In this study, Landsat-8 and Gaofen-1(GF-1) satellite images were used as data sources. In view of the characteristics of rare earth mining areas, and the thermal infrared data were used to retrieve the land surface temperature (LST), a land surface temperature downscaling model TDFSU based on remote sensing data fusion and mixed pixel decomposition is proposed. ultimately verifying the quantitative and qualitative accuracy of the downscaled results. The results show that the model can effectively improve the spatial resolution of surface temperature and reflect the spatial differences of surface temperature. This model has high feasibility and applicability in ionic rare earth mining areas.

地表温度是表征离子吸附稀土矿区栖息地条件和生态干扰的重要指标。由于离子吸附型稀土矿区中的离子分散且单个矿区的面积较小，因此获取实用的表面温度数据以监测该地区的生态环境非常重要。在这项研究中，Landsat-8和Gaofen-1（GF-1）卫星图像被用作数据源。针对稀土矿区的特点，利用红外热数据检索地表温度（LST），提出了基于遥感数据融合和混合像素分解的地表温度降尺度模型TDFSU。最终验证缩减结果的定量和定性准确性。结果表明，该模型可以有效提高地表温度的空间分辨率，反映地表温度的空间差异。该模型在离子稀土矿区具有较高的可行性和适用性。