Historical city plans and rasters of Warsaw are contained within local coordinate systems (Warsaw-25/75), which makes it difficult to address and integrate them quickly into contemporary data processing pipelines. This paper systematises the problem by defining rigorous rocedures for section encoding and decoding: 1) transforming planar coordinates (X, Y) → a sheet code compliant with the N/S–O/W grammar (row, column), and 2) mapping a sheet code → the section envelope [Xmin, Ymin, Xmax, Ymax]. The proposed approach has constant time complexity O(1), employs unambiguous boundary rules, and is parameterisable (sheet dimensions, the position of the Warsaw origin), which simplifies adaptation to heterogeneous cartographic series. We demonstrate how these mechanisms plug into practical workflows: they allow one to identify the target sheet immediately from a given point, reconstruct its bounding box before loading data, and verify consistency between a code stored in metadata and a code computed from coordinates. These procedures interoperate with transformations to PUWG 2000 (PL-2000), enabling the seamless linkage of Warsaw materials with current reference databases. In AI/ML scenarios, the section code acts as a stable spatial identifier that facilitates sample selection and dataset organisation. We additionally provide numerical recommendations (ε and floor) that stabilise the classification of edge cases and remove ambiguities. The algorithms were implemented in Bentley MicroStation with Visual Basic for Applications, ensuring portability to other VBA-capable environments such as Microsoft Office. The solution requires no series lookup tables, operates directly on a metric grid, and is robust to coordinate precision variations, thereby supporting ETL automation and quality control across public administration and industry.