Cartographic sounding selection, the process of identifying navigationally relevant soundings for chart-display, is a time-consuming generalization process in the chart production workflow. Advances in bathymetric data collection and processing techniques are resulting in higher resolution data, which compounds the bottleneck of sounding selection. Thus, a comprehensive algorithm for generating a chart-ready set of soundings that adheres to cartographic constraints could vastly decrease the time from data collection to chart dissemination. Towards this goal, this work presents enhancements to our label-based hydrographic sounding selection (Dyer et al., 2022) and methods for identifying soundings for chart display. Enhancements to the hydrographic sounding selection algorithm include a method for cartographically generalizing Category Zone of Confidence (CATZOC) polygons (MQUALs), utilizing said generalized polygons for a constrained triangulation during validation, and an adjustment procedure to eliminate functionality (safety) constraint violations. This results in a hydrographic selection with zero functionality violations, albeit at the expense of legibility, where the introduced overlapping labels are handled later when deriving the chart-ready selection. The hydrographic sounding selection results serve as input to our cartographic sounding selection process that begins with defining the types of soundings found on nautical charts: least depth, critical, deep, supportive, and fill soundings. We present a method to extract these soundings based on analyzing the surface model of the hydrographic selection, the associated survey CATZOC value, and existing chart features.