Vertical Differencing [ Video Tutorial ]

UAV Lidar Survey of Volcan Mountain Wilderness Preserve, CA 2024
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Overview

SDSU logo This dataset was collected to provide high-density, contemporary ground-truth data on 3D vegetation structure in the fire-prone montane ecosystems of Southern California. It served as a benchmark for developing and validating deep learning models designed to enhance sparse, historical airborne light detection and ranging (lidar) data by fusing it with multi-temporal optical National Agriculture Imaging Program (NAIP) and L-band synthetic aperture radar (UAVSAR) imagery for applications in ecological modeling and land management.
Reference Dataset
Total points: pts
Survey Area: km2
Point Density: pts/m2
Compare Dataset  
Total points: pts
Survey Area: km2
Point Density: pts/m2
Select area of data to process  
 

1. Vertical Differencing Datasets and Coordinate System  


  Reference dataset:
  Compare dataset:  
Dataset:
Survey Date:
Horizontal Coordinates:
Vertical Coordinates:
Units:
Data Selection Coordinates (Select an area on map)
  Manually enter selection coordinates (in the horizontal coordinate system listed above)  

2. DEM Generation (TIN)  

  Grid Resolution (Default = 1.0 meter)
  Max. triangle size (Default 50 units)

3. Error handling (optional)  

  User-defined Minimum Level of Detection  

4. Visualization  

  Generate additional hillshade images from DEMs for reference and compare datasets.

Altitude of the light:  (in range: [0-90] degrees)
Azimuth of the light:  (in range: [0-360] degrees)

Job Description & Notification

These options allow users to describe and keep track of their jobs. Information entered below is saved along with other job parameters in your personal myOpenTopo dashboard (available only to registered OpenTopography users).

Email address
for notification upon completion of processing
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Data Citation     |     Use License: CC BY 4.0