Polygonal simplification and its use in DEM generalization for land surface segmentation

Abstract

As the amount of detailed altitude data grows, so does the importance of generalization. When a coarser analytical scale is required, the original finer-resolution digital elevation model (DEM) needs to be generalized or simplified to reduce data redundancy (Zhou & Chen, 2011). The issue of scale and resolution is very important

Evaluating Scaling Frameworks for Multiscale Geomorphometric Analysis

“…Along with the increased detail captured by fine-resolution sampling come noise and measurement error. Recent advances in feature-preserving DEM generalization have addressed this weakness by selectively avoiding the generalization of topographic features while generalizing other areas [59,60]. Feature-preserving generalization methods are a promising option for pre-processing elevation data prior to analysis as they differentiate the application of generalization for de-noising from a scaling operation.…”