Nowadays, technology and remote sensing data have developed significantly. These developments started with conventional data to become dynamic data. Technology and remote sensing data can be used for various applications such as mapping of inland water. Inland water resources that include lakes, rivers, and swamps are one of the national priorities, especially in lake mapping. One of the problems with floodplain lakes is that it is difficult to determine the fixed boundaries of the lake surface area. This study aims to obtain a forensic geological boundary mapping of a lake using the least-square adjustment approach in a floodplain lake with multi-data remote sensing. The floodplain lake in this study was Mahakam Cascade Lake in East Kalimantan Province. The fixed boundary of the surface area of the lake was determined using the least-square adjustment approach. One method in the adjustment was the harmonic modeling algorithm. This mapping used multi-data remote sensing in the form of Synthetic Aperture Radar (SAR) and optical imagery. The imagery used was Sentinel-1 which was acquired from 2014 to 2018 and Landsat from 2014 to 2018. This algorithm showed that the fixed boundaries of Mahakam Cascade Lake can be determined with certain tolerances. These fixed boundaries ignored lake tide parameters because the maximum tide value in the lake was only +5 cm. This value was ignored because the vertical accuracy of the topographic data in the big data engine was about 2 m. The fixed delineation of lake edges can be used to determine the lake volume and surface area. The surface area of the lake obtained from the Sentinel-1 imageries was ~ 399,017 km2. Based on Landsat imageries, the surface area of the lake was ~ 399,495 km2. The difference was due to the mixing of sediments and thin turbidity at the edge of the lake. This condition caused differences in reflectance values when acquisitioning the two types of imageries. Basically, this method could be applied for determining the edge of a lake.