Paper No. JAWRA-12-0013-P of the Journal of the American Water Resources Association (JAWRA). Discussions are open until six months from print publication.
Hydrography Change Detection: The Usefulness of Surface Channels Derived From LiDAR DEMs for Updating Mapped Hydrography1
Article first published online: 28 JAN 2013
© 2013 American Water Resources Association. This article is a U.S. Government work and is in the public domain in the USA.
JAWRA Journal of the American Water Resources Association
Volume 49, Issue 2, pages 371–389, April 2013
How to Cite
Poppenga, S. K., Gesch, D. B. and Worstell, B. B. (2013), Hydrography Change Detection: The Usefulness of Surface Channels Derived From LiDAR DEMs for Updating Mapped Hydrography. JAWRA Journal of the American Water Resources Association, 49: 371–389. doi: 10.1111/jawr.12027
- Issue published online: 1 APR 2013
- Article first published online: 28 JAN 2013
- Received January 17, 2012; accepted October 31, 2012.
- LiDAR DEMs;
- LiDAR surface channels;
- National Hydrography Dataset;
- hydrography change detection;
- surface water;
- remote sensing;
- geospatial analysis.
Abstract: The 1:24,000-scale high-resolution National Hydrography Dataset (NHD) mapped hydrography flow lines require regular updating because land surface conditions that affect surface channel drainage change over time. Historically, NHD flow lines were created by digitizing surface water information from aerial photography and paper maps. Using these same methods to update nationwide NHD flow lines is costly and inefficient; furthermore, these methods result in hydrography that lacks the horizontal and vertical accuracy needed for fully integrated datasets useful for mapping and scientific investigations. Effective methods for improving mapped hydrography employ change detection analysis of surface channels derived from light detection and ranging (LiDAR) digital elevation models (DEMs) and NHD flow lines. In this article, we describe the usefulness of surface channels derived from LiDAR DEMs for hydrography change detection to derive spatially accurate and time-relevant mapped hydrography. The methods employ analyses of horizontal and vertical differences between LiDAR-derived surface channels and NHD flow lines to define candidate locations of hydrography change. These methods alleviate the need to analyze and update the nationwide NHD for time relevant hydrography, and provide an avenue for updating the dataset where change has occurred.