Modeling hemispherical reflectance for natural surfaces based on terrestrial laser scanning backscattered intensity...

Area of Science:

• Geomatics Engineering
• Remote Sensing
• Environmental Science

Background:

• Terrestrial Laser Scanning (TLS) records intensity data alongside 3D coordinates, offering insights into surface reflectance.
• Raw TLS intensity is distorted by confounding variables like distance and incidence angle, limiting direct reflectance retrieval.
• Accurate target reflectance is crucial for TLS data processing, especially in multi-temporal and multi-sensor analyses.

Purpose of the Study:

• To develop and validate a novel method for modeling hemispherical reflectance of natural surfaces using TLS intensity data.
• To eliminate the distorting effects of incidence angle and distance on raw TLS intensity measurements.
• To enhance the utility of TLS data for applications requiring accurate surface reflectance information.

Main Methods:

• Proposed a new method to model hemispherical reflectance by correcting TLS intensity data for incidence angle and distance effects.
• Employed the Oren-Nayar reflectance model to account for surface roughness and correct incidence angle effects.
• Utilized reference targets to eliminate distance-related distortions without needing to estimate specific distance-intensity functions.

Main Results:

• The proposed method accurately retrieves reflectance values from TLS intensity data.
• The deviation from spectrometer-measured reflectance was approximately 4.29%.
• The root mean square error (RMSE) for the retrieved reflectance values was approximately 0.0562.

Conclusions:

• The developed method effectively models natural surface reflectance from TLS data, overcoming limitations of raw intensity.
• The approach demonstrates high accuracy and reliability for reflectance retrieval in geomatics and environmental studies.
• This technique significantly improves the potential for utilizing TLS intensity data in various scientific and practical applications.