Title: Application of ground-based LIDAR for gully investigation in agricultural landscapes Authors
Submitted to: American Society for Photogrammetry and Remote Sensing Proceedings
Publication Type: Proceedings
Publication Acceptance Date: April 5, 2011
Publication Date: May 1, 2011
Citation: Momm, H.G., Bingner, R.L., Wells, R.R., Dabney, S.M., Frees, L.D. 2011. Application of ground-based LIDAR for gully investigation in agricultural landscapes. American Society for Photogrammetry and Remote Sensing Proceedings. May 1-45, 2011, Milwaukee, WI. 331-340. Interpretive Summary: Sediment is a major pollutant from agricultural landscapes that originates from many sources. A significant source of sediment is produced from eroding gullies, which is also difficult to assess and differentiate from other sources. Accurate and detailed topographic information from gully surveys can provide critical information when understanding and assessing the impact of gully erosion control practices. Existing technologies to measure topography can range from land-based surveys to airborne LIght Detection and Ranging (LIDAR) systems. These systems are capable of collecting topographic information with a wide range of ground point sampling densities, but may not be detailed enough to capture gully information. New technologies, such as ground-based LIDAR systems are capable of increasing the point sampling density of field surveys, thus, increasing topographic information needed for gully studies, but also increasing the complexity of data analysis. In this study, the effect of point sampling density was investigated at individual gully scales. Overall guiding principles were developed for multi-temporal gully surveys based on various levels of ground-based LIDAR sampling points and relief variation. For each level considered, an analysis of the full dataset was compared to reduced datasets. Results indicated a point sampling density threshold that produces little or no additional topographic information when exceeded. A reduced dataset was created using the density thresholds and compared to the original dataset with no major discrepancy. Although variations in relief can lead to different sampling requirements, the outcome of this study serves as guidance for future field surveys of gully evolution and erosion. Improved characterization of gullies provides action agencies with information critical to developing effective conservation management practices.
Technical Abstract: Detailed scientific investigation of gullies in agricultural fields requires accurate topographic information with adequate temporal and spatial resolution. New technologies, such as ground-based LIDAR systems, are capable of generating datasets with high temporal and spatial resolutions. The spatial resolution is dependent on the ground point sampling density, which is a result of operator controlled factors such as the area of data collection (scan angle), average point density of scans, and degree of overlap between scans. The selection of the appropriate point density sampling is especially important in research sites where the same location needs to be surveyed multiple times over lengthy periods of time as conditions change due to precipitation and runoff events, field management changes, and/or implementation of different conservation practices. This study investigated the relationship between point sampling density and topographic information through the use of variograms. A Monte Carlo-type experiment was performed by interactively and randomly reducing points to created reduced point sets and comparing theoretical variograms of reduced datasets to theoretical variogram of the original dataset. Results indicated point sampling density thresholds for low to high relief variation datasets that produced little or no additional topographic information when exceeded. Although variations in local relief can lead to different point sampling density requirements, the outcome of this study serves as guidance for future field surveys of gully evolution and erosion.