Lidar Survey of Deltaic Wetlands, LA 2023

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Overview

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This lidar dataset was collected as part of an NCALM Seed grant for Donald Davidson at the University of New Orleans. This dataset was collected to help understand the vegetation-sediment-flow interplay in deltaic wetlands. Data was collected southeast of New Orleans, LA, over Quarantine Bay.

Publications associated with this dataset can be found at NCALM's Data Tracking Center.

Platform: Airborne Lidar
Survey Area: 59.83 km2
Point Density: 10.92 pts/m2
Survey Date: 09/20/2023
Full Metadata
Data Citation     Copied
Use License: CC BY 4.0
Funder: NSF     Collector: NCALM

Other Available Data Products: RasterPoint Cloud Bulk Download
1a. Select area of data to download or process  
  Usage Heat Map
 

1. Coordinates & Classification

Horizontal Coordinates: NAD83 (2011) / UTM Zone 16N Meters [EPSG: 6345]
Vertical Coordinates: NAVD88 (GEOID 12B) [EPSG: 5703]
Units: meter
Data Selection Coordinates (Select an area on map)
  Manually enter selection coordinates (in the horizontal coordinate system listed above)  

  Choose Return Classification:       All Points         Standard Classifications         Advanced Classifications
  Exclude Noise

2. Point Cloud Data Download

     Point cloud data in LAZ format
    Point cloud data in LAS format
     Point cloud data in ASCII format

3A. Custom DEM Generation (TIN)  

    Calculate TIN
Gridding Parameters
  Grid Resolution (Default = 1 meter)
  Max. triangle size (Default 50 units)
  Grid Format

4A. 3D Point Cloud Visualization  

  Generate 3D point cloud browser visualization

5A. Raster Visualization  

Visualization type:
    Hillshade
    Color-relief
    Color hillshade
    Slope
    Aspect
    Roughness

3B. Custom DEM Generation (Local Gridding)  

Gridding Method
     Calculate Zmin grid
     Calculate Zmax grid
     Calculate Zmean grid
     Calculate Zidw grid
     Calculate standard deviation
     Calculate point count

4B. Contour Lines  

Job Description & Notification

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Data Citation     |     Use License: CC BY 4.0