The Planimetric Update project focused on improving geospatial data quality assurance for the NYC Office of Technology and Innovation (OTI) by applying acceptance sampling methods to validate large-scale mapping updates. The approach ensured 100% topology integrity and high confidence in feature identification and drafting accuracy, achieving 95% confidence intervals for both feature validation and omission detection. The system establishes a foundation for next-generation quality control using AI-driven convolutional neural networks (CNN) and multi-modal data integration.
