LiDAR and 3D from EO - Remote Sensing Center

Research Projects - LiDAR

LiDAR & EO Derived 3D

LiDAR (Light Detection and Ranging) technology is rapidly advancing and has proven to be valuable in the fields of terrain mapping, bathymetry, and more.


Simulated LiDAR waveforms

Simulated LiDAR waveforms


(Poster presented at SPIE 2011, authors: Angela M. Kim and Richard C. Olsen)

LiDAR works as an optical analog to RADAR with advantages related to the smaller wavelengths of the laser pulse.


Nested Applications
RSC - Research Projects - Image 8

Lidar image Elkhorn Slough

Lidar image Elkhorn Slough

RSC - Research Projects - Image 9
Lidar image Elkhorn Slough
RSC - Research Projects - Image 10

LiDAR ranges in wavelength from ultra-violet (0.3-0.45 um) to visible (0.45-0.70 um) to the infrared (1-15 um), which is at least 1000 times smaller than RADAR. The RADARSAT satellite, for example, has a wavelength of 5.6 cm.


The raw form of data is a set of x, y, z coordinate points. With recent advances, these points can be seen as distinguishable returns. An instrument that would once give only a bare earth model can now differentiate between the ground and bottoms and tops of tree canopies.

The raw data can be processed to remove unwanted areas or features. Outputs such as topographic maps with contour lines can also be derived from LiDAR.


Programs to manipulate LiDAR data include ENVI, ERDAS Imagine, ArcInfo,Quick Terrain Modeler, and ESRI ArcView (with 3D analyst ext.).


One useful derivation of LiDAR data is the DEM (digital elevation model).

DEMS are displayed in a raster format with a matrix. The DEM has a specified cell size that corresponds to the earth’s surfaces. The cell contains the average elevation of the points within it.

LiDAR can detect much smaller particles than RADAR in the atmosphere (which cannot detect things smaller than cloud particles) and thus can be used for aerosol detection.

Related Thesis Work

Related Thesis Work

Spectral LiDAR Analysis and Terrain Classification in a Semi-Urban Environment
Charles A McIver, Space Systems Operations, March 2017n
Thesis Advisor: R. C. Olsenn
Co-Advisor: M.A. Stefanou

Terrain classification using multi-wavelength LiDAR data 
Judson J. C. Thomas, Space Systems Operation
September 2015
Thesis Advisor: R. C. Olsen
Second Reader: Jeremy P. Metcalf