A high-resolution, ground-based 3D laser scanner was recently evaluated for terrestrial site characterization of variable-surface minefield sites and generation of surface and terrain models. The instrument used to conduct this research was a Leica HDS3000 3D laser scanner. Two study sites located in the mid-western United States were used for this analysis. A very dense vegetation site (Grass Site) and a bare soil site (Dirt Site) with intermittent rocks and sparse vegetation were selected for data collection to simulate both obscured and semi-obscured minefield sites. High-density scans (0.2 cm to 2.0 cm) were utilized for Cyra target acquisition and were commensurate with size and distance to target from scanner location. Medium-density scans (2.0 cm to 5.0 cm) were chosen for point cloud generation of each site with approximately 10 percent overlap between field scans. To provide equivalent, unobstructed viewing perspectives from all scan locations at each site, the scanner was positioned on a trailer-mounted, chain-driven lift and raised to a scan height of 7.62 m above the ground. Final registration to UTM projected coordinate system of the multiple scan locations for the Dirt Site and Grass Site produced mean absolute errors of 0.014 m and 0.017 m, respectively. The laser scanner adequately characterized surface roughness and vegetation height to produce contour and terrain models for the respective site locations. The detailed scans of the sites along with the inherent, natural vegetation characteristics present at each site provide real-time discrimination of site components under contrasting land surface conditions.
Using LiDAR data collected on the levees along the Rio Grande River in New Mexico and Texas, an algorithm has been developed to automatically extract longitudinal elevation profiles. This algorithm consists of a series of filters, interpretation of geophysical properties, and digitized levee centerlines. The series of filters, in order of operation, include an alignment buffer filter, bare-earth filter, sampling filter and a maximum value filter. The result of the filter configuration is a 3-D polyline that models the levee crest. This algorithm allows for efficient identification of portions of levee that are lower than original design specifications. A comparison between the LiDAR levee crown extraction filter and a least-cost-path technique are offered.
In a study conducted for the U.S. Army Corps of Engineers, Mississippi Valley Division (MVD), we used ArcGIS software to interpolate, analyze, and display spatially explicit data describing fish and physical habitat factors (bathymetry, current velocity, and substratum) associated with a dike notching project in Bondurant towhead secondary channel in the lower Mississippi River between River Miles 390 - 394. Data were collected throughout project areas using hydroacoustic equipment. We used ArcGIS to interpolate coverages of each physical habitat variable, which were then compared with fish distribution data to determine patterns of habitat association. After analyzing data from several locations, we concluded that bathymetry, water velocity, and substrate composition
were most variable in areas immediately behind dike notches. However, the habitat diversity associated with notches was limited throughout the remaining portion of each project location. Data collected from throughout the side channel were analyzed. Habitat diversity (i.e., bathymetry, current velocity, and substratum) was greatest in
areas of immediate proximity with the notched dike. However, the lack of pre-notching data precluded a direct quantification of how dike-notching activities changed habitat quality.
Remote sensing technologies are used to collect data that measure properties of materials that comprise the earth's surface, subsurface, and man-made features such as levees constructed of these materials. Scientists use, manipulate, and analyze these data to make inferences about levee materials as well as identify local areas where intensive field investigation resources might most efficiently be spent. In this current study, airborne LiDAR and electromagnetic (EM) conductivity data have been processed and integrated with other digital data to identify specific areas within a levee system where anomalies exist. Preliminary results support the idea that changes in material type and the presence of man-made, levee-perforating structures do cause recognizable effects on recorded EM conductivities. Planned site investigations at identified EM anomalous areas will focus the efforts of field crews to determine the causes and significance of anomalies. As the field season progresses and data from in situ testing of levee materials are analyzed, relationships between material types and the EM data will be represented in graphics. Results of the study will be used to calibrate a model with which levee systems can be assessed for compliance with certain design specifications as well as predicting performance during flood events.
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