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Surface water/ice dynamic monitoring is crucial for 1 many purposes, such as water resource management, agriculture, 2 climate change, drought, and flood forecasting. New advances in 3 remote sensing satellite data have made it possible to monitor 4 the surface water/ice dynamics both spatially and temporally. 5 However, there are many challenges when using these data, 6 such as the availability of valid imagery, cloud contamination 7 issues for Landsat-8, and sensitivity of Sentinel-1 C-band to wind 8 speed, topography, and others. A combined methodology using 9 Landsat-8 and Sentinel-1 Synthetic Aperture Radar (SAR) data 10 was proposed to create monthly change maps at 30m spatial 11 resolution for the Lesser Slave Lake in Alberta, Canada, for 12 the period 2017-2020. The potentials of multi-spectral indices 13 for Landsat-8, such as the Normalized Difference Vegetation 14 Index (NDVI), Normalized Difference Water Index (NDWI), 15 and Modified NDWI (MNDWI) as well as the Sentinel-1 SAR 16 backscattering coefficients (VV-VH) and Normalized Difference 17 Polarized Index (NDPI) for separating water/ice from the land 18 were investigated. The results obtained from satellite data with 19 historical discharge and water level measurements for the lake 20 were compared. Furthermore, the results show that the MNDWI 21 and VH are the most effective indices for creating the change 22 maps. The overall accuracies achieved for MNDWI and VH are 23 92.10% and 68.86% for cold months and 99.88% and 98.49% 24 for warm months, respectively.25