The monitoring of slope stability like rock slopes and embankments usually takes lots of manpower and costly equipment for just one location. With the application of satellite sensing technologies, monitoring multiple wide locations simultaneously is now possible. However, as Synthetic Aperture Rader (SAR) images taken by the SAR-enabled satellite are generally complex and data-overwhelming, making use of the massive amount of data and properly extracting useful data are complicated and time consuming. To address the current issue of extracting valuable information from satellite sensing data, the authors performed satellite sensing analysis on a slope failure location and then applied a trend filtering method which has not been introduced to the SAR sensing industry before: ℓ1 trend filtering technique. As ℓ1 trend filtering technique was not introduced prior, critical parameters such as lambda (λ) must be calibrated before the algorithm can be applied. Hence, this paper discussed the satellite sensing principles, ℓ1 trend filtering principles, the hyperparameters tuning as well as the trend filtering result. As a result, the application of ℓ1 trend filtering effectively filters out important slope behavior and as well as dates where the slope changes its behavior.