The study addresses the problem of optimizing the placement of terrestrial laser scanners to ensure complete coverage of real estate objects within the boundaries of a study area, accounting for obstacles such as buildings and structures. A mathematical model based on integer linear programming methods was developed to minimize the number of required scanner setups without compromising the quality of acquired data. Experiments conducted on various sites with differing building densities confirmed the effectiveness of the proposed approach. A nonlinear relationship was identified between the percentage of coverage by buildings and structures, the total area of the site, and the minimum number of scanner setups required for full coverage of both the territory and the objects designated for scanning. The results demonstrate that the application of the proposed model reduces time and labor costs during 3D object identification and can be integrated into planning and management systems for geodetic and cadastral operations.