A systematic scheme to maintain multiple characteristics for effective polygon rasterization

Polygon characteristics, including area, shape, and topology, may be lost during rasterization, leading to inaccurate analyses. Maintaining multiple characteristics remains a challenging multi-objective optimization problem. This study introduces improved strategies for flexibly maintaining multiple characteristics (ISMMC). Errors related to area (A), shape (S), and topology (T) are addressed using six prioritized sequences: AST, ATS, TAS, TSA, STA, and SAT, where the order of the letters denotes the sequence of error correction. The importance (I) of land-use types (LUT) is also considered when developing a strategy based on the TSA (ITSA) that maintains characteristics for important LUTs. The ISMMC achieved a total improved accuracy (IA) of ≥0.05 for 98.67% of 150 tested cases. The STA, SAT, TAS, and TSA yielded the highest area, shape, topological, and total accuracies. The STA achieved a summed AI increase ≥20.36% compared to the existing version. The runtime was ≥85.46 times the scanline runtime, and the threshold cell size (≤50 m) balanced the IA and runtime. The ITSA improved accuracy by 83.33% and 6.67% of solutions when preferentially maintaining one or two important LUTs, outperforming the existing STA. Overall, these developments improve accuracy with flexibility in rasterization results and subsequent raster applications.