DOI: 10.6071/m33d4n
title: Merced Vernal Pools and Grassland Reserve sUAS-LiDAR High Resolution 0.25-meter DEM

description: The Merced Vernal Pools and Grassland Reserve is 6,500 acres of protected
 habitat adjacent to the University of California Merced containing rare
 and endangered species and a unique seasonal wetland habitat. These data
 were gathered to be used for hydrological modelling on the Reserve for
 potential restoration projects and to be made public for other researchers
 who may find very high resolution topographical information useful for
 their work. This dataset contains a Digital Elevation Model created from 8
 field survey days of Aerial LiDAR Scanning (ALS) with a small Unmanned
 Aerial System (sUAS).
description: <em>Work Completed by Researchers at University of
 California, Merced under the direction of Dean/Director/Professor Joshua
 H. Viers | Vicelab and CITRIS Aviation</em>
 <strong>Spatial Reference:</strong> WGS 1984 UTM Zone
 10N / WGS84 Geoid <strong>Units:</strong>
 Meters <strong>Equipment:</strong> DJI M600
 Pro with Phoenix Aerial Systems AL3-32 LiDAR
 <strong>Software:</strong> Phoenix LiDAR Systems
 SpatialSuite 4.0.3, LasTools, ArcGIS Pro 2.4, Litchi, ArduPilot Mission
 Planner <strong>Field
 Crew/Processing:</strong> Michael Kalua (sUAS Pilot/Mission
 Planning/Sensor Operator/Data Processing), Andreas Anderson (sUAS
 Pilot/Mission Planning/Sensor Operator), Daniel Gomez (Sensor Operator),
 Hayden Namgostar (Sensor Operator) <strong>Field
 Methods:</strong> An RTK reference station was set up before each
 field day over a previously-surveyed benchmark near the entrance of the
 Reserve, which would continuously send RTK corrections to the LiDAR system
 over an internet connection service. Before flight the LiDAR system was
 allowed at least 15 minutes to reach thermal equilibrium and for the
 onboard Intertial Measurement Unit (IMU) to get a fix on the sensor's
 position and attitude. At the beginning of each set of flights the Pilot
 in Command (PIC) would perform a manual takeoff and IMU calibration
 maneuvers (straight-and-level flight and figure-eights) as per Phoenix
 LiDAR System's recommended procedures. Once the manuevers were
 completed and the Sensor Operator determined IMU attitude and position
 uncertainties were below threshold (0.003- typical values ranged an order
 of magnitude lower) the PIC would begin the automated waypoint mission via
 Litchi. During flight, the Sensor Operator would ensure the scanner was
 operational, that the IMU uncertainties were below margin, and address any
 potential error messages. In the event of errors, the PIC would bring the
 sUAS back and the section would be re-surveyed after the issues were
 addressed. <strong>Processing
 Methods:</strong> The raw flightlines were fused using Phoenix
 SpatialExplorer 4.0.3 to include only the straight-and-level flightlines
 over the region of interest. The output were individual flightline .las
 point clouds conforming to LAS 1.4 format. These flightlines were then
 passed through a noise filter using LasNoise to remove any
 "birds" or unwanted noise. Using LasTools these noise-removed
 flightlines were then tiled, classified into ground/non-ground points, and
 rasterized into 0.25-meter Digital Surface Models (DSM) containing all
 points and Bare-Earth Digital Elevation Models (DEM) containing only
 ground-classified points. These tiled raster outputs were then mosiaced
 together in ArcGIS Pro.     Please reach out to Michael
 Kalua (mkalua@ucmerced.edu) for any questions about this dataset.  
  
description: This dataset contains a 0.25-meter spatial resolution Digital
 Elevation Model (DEM) produced by a small Unmanned Aerial System (sUAS)
 with Airborne Laser Scanning (ALS) capabilities collected over 8 days from
 November 2019 to March 2020 by CITRIS Aviation and Vicelab at Univerity of
 California, Merced. These data were collected by a Phoenix LiDAR Systems
 AL3-32 LiDAR attached to a DJI M600 Pro flown at approximately 60 meters
 AGL with 60 meter flightline spacing. Points were geolocated in realtime
 with RTK GPS accuracy with corrections being consistently uploaded to the
 LiDAR system during aquisition. To view the raster,
 please load the 'MVPGR_ALS_DEM.tif' file into your preferred
 GIS.    There are two known holes (Avocet Pond
 & a small area in the NW corner) where no LiDAR returns were
 obtained due to water. There are also some areas; particularly
 outside/near borders, where there are visible artifacts from the drone
 slowing for turns. Please contact Michael Kalua at mkalua@ucmerced.edu
 with any questions or if you find issues; we would love to know!