Abstract
Topographic data at selected areas within the Alabama River flood plain near Montgomery, Alabama, were collected using a truck-mounted mobile terrestrial light detection and ranging system. These data were collected for inclusion in a flood inundation model developed by the National Weather Service in Birmingham, Alabama. Data are presented as ArcGIS point shapefiles with the extension .shp.
Introduction
A truck-mounted mobile terrestrial light detection and ranging (T-LiDAR) system was used by the U.S. Geological Survey (USGS) to collect topographic data at selected sites within the Alabama River flood plain near Montgomery, Alabama. T-LiDAR technology typically provides higher point density than traditional survey methods and, when mounted on a vehicle, is particularly useful for rapid data collection at a range of spatial scales. Two surveys were conducted in March and April 2013. The data were collected for use in a flood inundation model developed by the National Weather Service (NWS) in Birmingham, Alabama. The NWS also used elevation data from both airborne LiDAR and traditional ground surveys in their modeling efforts. The inundation models provide a useful tool for hazard mitigation along the Alabama River. Specific details of the mobile T-LiDAR collection methods and data format are included in this report.
Data Collection and Processing Methods
T-LiDAR technology uses laser pulses that are sent from the instrument and reflected off objects within its field of view. The instrument calculates the distance of each returned laser pulse on the basis of the velocity of the pulse, while also logging the vertical and horizontal angle of each pulse (Kimbrow and Lee, 2013). Topographic data were collected in March and April 2013 using an Optech ILRIS HD-ER-MC instrument (Optech, 2013) in conjunction with an Applanix position and orientation system (POSMV) (Applanix, 2013). The Optech ILRIS HD-ER-MC has a laser repetition rate of 10 kilohertz and a laser wavelength of 1,535 nanometers, which falls within the near-infrared portion of the electromagnetic spectrum. The T-LiDAR instrument was mounted on top of the truck, facing toward the rear of the truck, and scanned the road surface and adjacent shoulder at speeds of less than 10 kilometers (km) per hour. The truck was driven along approximately 32 km of road within the Alabama River flood plain. The POSMV system collected attitude and trajectory information during the survey, and these data were later post-processed using global positioning system (GPS) data from a nearby continuously operating reference station (CORS) with Applanix POSPac MMS software. The POSPac MMS software uses differential correction algorithms to compute a smoothed best estimate of trajectory (SBET) file. The SBET file is then applied to the raw T-LiDAR data using Optech Parser software to produce a geo-referenced point-cloud dataset. Forty-three additional topographic data points were collected for survey control using a real-time kinematic global positioning system (RTK-GPS) unit. The RTK-GPS survey followed the quality standards of a USGS Level III survey (Rydlund and Densmore, 2012). The control points were evenly distributed throughout the survey site and were also visible within the point-cloud dataset (that is, cross sections of road, points along curbs, and reflective paint on the pavement). The RTK-GPS control points were compared to data points within the T-LiDAR point-cloud, and the residual error was computed. A block translation of the dataset was then conducted to reduce the observed error. The data were then down-sampled to a 7.5 meter (m) grid using ArcGIS (Environmental Systems Research Institute, 2013) software.
Electronic Data Format
This report provides topographic data in ArcGIS point shapefile format with the extension .shp. The horizontal XY coordinates have been positioned in the North American Datum of 1983, Universal Transverse Mercator, Zone 16 North coordinate system. The vertical Z values are referenced to the North American Vertical Datum of 1988 vertical reference system. Two data files are provided in this report and are separated based on observed vertical error values. The file Alabama_River_LiDAR_A.shp exhibits geo-referenced vertical error of +/– 0.035 m, whereas Alabama_River_LiDAR_B.shp exhibits vertical error of +/– 0.50 m due to GPS outage from collecting the data under a highly forested canopy environment. Metadata are also included for each of the files in ASCII text and .xml format. Data and metadata are available in the Downloads directory.
References Cited
Applanix, 2013, Applanix marine products—POSMV, accessed October 2013 at http://www.applanix.com/products/marine/pos-mv.html.
Environmental Systems Research Institute, 2013, ArcGIS—Mapping and analysis for understanding our World, accessed September 2013 at http://www.esri.com/software/arcgis.
Kimbrow, D.R., and Lee, K.G., 2013, Erosion monitoring along the Coosa River below Logan Martin Dam near Vincent, Alabama, using terrestrial light detection and ranging (T-LiDAR) technology: U.S. Geological Survey Scientific Investigations Report 2013–5128, 7 p., https://pubs.usgs.gov/sir/2013/5128/.
Optech, 2013, Optech ILRIS-3d Intelligent Laser Ranging and Imaging System, accessed October 2013 at http://www.optech.ca/i3dprodline-ilris3d.htm.
Rydlund, P.H., Jr., and Densmore, B.K., 2012, Methods of practice and guidelines for using survey-grade global navigation satellite systems (GNSS) to establish vertical datum in the United States Geological Survey: U.S. Geological Survey Techniques and Methods, book 11, chap. D1, 102 p. with appendixes.