Hydrography Change Detection: Three-Dimensional Analysis of Lidar Data for Updating Mapped Hydrography
By Sandra K. Poppenga, Dean B. Gesch, and Bruce B. Worstell
Location where hydrography change was detected in the lidar-derived digital elevation model (DEM). Lidar DEM data courtesy of The National Elevation Dataset, U.S. Geological Survey, Earth Resources Observation and Science (EROS) Center.
Aerial photograph from 1958 acquired of a location where hydrography change was detected. Aerial imagery courtesy of the U.S. Geological Survey, Earth Resources Observation and Science (EROS) Center.
Aerial photograph from 2008 of a location where hydrography change was detected. Aerial imagery courtesy of the U.S. Geological Survey, Earth Resources Observation and Science (EROS) Center.
Whether by human or natural causes, as land changes occur over time, the spatial information that represents mapped hydrography needs to be updated to reflect the current state of surface waters. Accomplishing this monumental task by re-digitizing National Hydrography Dataset (NHD) flow lines would be exceedingly expensive. Although digitized hydrography may appear to be integrated with ancillary datasets, the digitized data are not vertically integrated with precision to the corresponding elevation data. Therefore, to improve efficiency and reduce costs associated with NHD updates, hydrography change detection methods were developed to identify locations of land changes that alter the location of surface waters. These methods employ detailed light detection and ranging (lidar) elevation data to define surface channels that are compared with NHD flow lines.
Although frequently referenced by increased horizontal resolution, the inherent value of lidar elevation data is the vertical component, or the three-dimensionality, of the topographic ground surface. Three-dimensional (3D) data are useful for defining the gravitational direction of surface waters. Subsequently, lidar surface channels were generated in both low relief and rugged terrain, and were compared with available 1:24,000-scale NHD hydrography flow lines to detect horizontal discrepancies exceeding National Map Accuracy Standard (NMAS) guidelines, which state that mapped features need to be within 12.2 meters of their true location at a 90 percent confidence level.
Horizontal discrepancies exceeding the NMAS guidelines were quantified and ranked according to their horizontal displacements and length ratios. Absolute vertical elevation differences were quantified and ranked for each of these locations by using a newly developed elevation profile tool. A composite ranking of horizontal displacements, length ratios, and absolute vertical elevation differences defined locations that were considered candidates for hydrography change. These change metrics were developed for the purpose of directing attention to those locations that are most in need of being updated in the NHD.
By using both the horizontal and vertical components of lidar 3D data, it is possible to detect discrepancies in surface water channels that are valuable for updating NHD flow lines. More importantly, the benefit of this 3D analysis is that only locations suspected of hydrography change need to be reviewed for spatial accuracy and currency rather than attempting to update an entire mapped hydrography dataset.
Additional information regarding this research is available online at http://dx.doi.org/10.1111/jawr.12027.