Hydrographic Generalization Tailored to Dry Mountainous Regions

Abstract

A wide variety of climate and terrain conditions exist in the United States and optimal cartographic generalization techniques for one area of the country may not be suitable for another, particularly when working with surface hydrographic data. This paper presents generalization and data modeling to produce reduced scale versions of hydrographic data for a multi-resolution national data set, The National Map, of the United States Geological Survey (USGS). The approach distinguishes regional differences in geographic factors to demonstrate that knowledge about varying terrain and climate conditions can support the design of tailored generalization operations that preserve distinct hydrographic patterns. Hydrographic generalization procedures are being tailored for different terrain (mountainous, hilly, and flat) and climate (humid and dry) conditions within the United States. We demonstrate using a sequence of automated generalization operations tailored for a dry mountainous subbasin watershed of the United States National Hydrography Dataset (NHD). NHD data for the subbasin, compiled from 1:24,000-scale source material, were generalized to create hydrographic data that are appropriate for cartographic mapping at scales between about 1:50,000 and 1:200,000. Generalization results are metrically compared to a 1:100,000-scale NHD benchmark through the Coefficient of Line Correspondence (CLC) and the Coefficient of Area Correspondence (CAC). Confidence intervals for the CLC and CAC are generated through a non-parametric bootstrapping approach. These metrics and associated confidence intervals can help establish the geographic extents that are suitable for each set of tailored generalization procedures.