Abstract: Hills cutting and land reclaiming (HCLR) serves as the most direct way for cities that are constrained by terrain to overcome land scarcity and facilitate urban spatial expansion. Obtaining the range of HCLR quickly and accurately using remote sensing technology is significant for assessing the regional ecosystem and new city development planning scientifically. Based on the Google Earth Engine (GEE) cloud computing platform for remote sensing, as well as multi-temporal data from Sentinel-1 SAR and Sentinel-2 multispectral imager (MSI), this study determined the spatiotemporal distribution of the 2017-2022 HCLR range in the study area using multi-temporal change monitoring and a random forest algorithm. Using a combination of Sentinel-1 ascending and descending images and based on noise filtering and multi-temporal image synthesis, this study calculated the difference in the backscattering intensity before and after HCLR. Then, the excavation range was determined using a threshold determined using the percentile threshold method combined with sample data. The results demonstrate that this method exhibited high operability, with an overall classification accuracy and Kappa coefficient of 85% and 0.83, respectively. By monitoring multi-temporal changes in the VH polarization band of Sentinel-1 and using a combination of Sentinel-1 ascending and descending images, this study acquired the spatial distribution of excavation areas within the study area from 2017 to 2022. Before 2019, the excavation areas were primarily concentrated in Jiuzhou Development Zone, Country Garden, and Poly Lingxiu Mountain. After 2020, new excavation areas, such as Liujiagou and Shuiyuan Station, emerged, with the scope and intensity of excavation gradually increasing. By combining the spectral, texture, and topographic features of SAR and optical data and based on feature optimization combined with a random forest algorithm, this study determined the spatial distribution of yearly HCLR from 2017 to 2022. Before 2018, the HCLR scale was small, with an area of 2.655 km². After 2019, the scale increased each year, especially in 2021, when the area reached 12.607 km², accounting for 34.56% of the total land reclamation area during the monitoring period. In 2022, the reclamation area obtained through further excavation on previously reclaimed land was estimated at only 2.686 km² due to the increasing slope and excavation volume. The method developed in this study for monitoring excavation areas and extracting land reclaiming ranges enables effective monitoring and extraction of the HCLR range.