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Accurate quantification of the distribution and characteristics of frozen soil is critical for evaluating the impacts of climate change on the ecological and hydrological systems in high-latitude and-altitude regions, such as the Tibetan Plateau (TP). However, field observations have been limited by the harsh climate and complex terrain on the plateau, which greatly restricts our ability to predict the existence of and variations in frozen soils, especially at the regional scale. Here, we present a study relying solely on satellite data to drive process-based simulation of soil freeze-thaw processes. Modifications are made to an existing process-based model (Geomorphology-Based Eco-Hydrological Model, GBEHM) such that the model is fully adaptable to remote sensing inputs. The developed model fed with a combination of MODIS, TRMM and AIRX3STD satellite products is applied in the upper Yellow River Basin (coverage of similar to 2.54 x 10(5) km(2)) in the northeast TP and validated against field observations of freezing and thawing front depths (D-ft) and soil temperature (T-soil) at 54 China Meteorological Administration (CMA) stations, as well as frozen-ground types at 22 boreholes. Results indicate that the developed model performs reasonably well in simulating D-ft (R-2 = 0.69; mean bias = -0.03 m) and T-soil (station averaged R-2 and mean bias range between 0.90-0.96 and -0.51 similar to -0.14 degrees C at eight observational depths, respectively), and outperforms the original GBEHM forced with ground-measured meteorological variables. The frozen-ground types are also (in general) accurately identified by the satellite-based approach, except for a few permafrost boreholes located near the permafrost boundary regions. Additionally, we also demonstrate the importance of considering dynamic soil water content in frozen soil simulation: We find that a static-soil-moisture assumption (as used in previous studies) would lead to biased soil temperature estimates by > 0.5 degrees C. Our study demonstrates the value of using satellite data in frozen-soil simulation over complex landscapes, potentially leading to a greater understanding of soil freeze-thaw processes at the regional scale.