Radiometric calibration of a dual-wavelength terrestrial laser scanner using neural networks

Schofield, LA; Danson, FM; Entwistle, NS; Gaulton, R; Hancock, S

Abstract

The Salford Advanced Laser Canopy Analyser (SALCA) is a unique dual-wavelength full-waveform terrestrial laser scanner (TLS) designed to measure forest canopies. This paper has two principle objectives, first to present the detailed analysis of the radiometric properties of the SALCA instrument, and second, to propose a novel method to calibrate the recorded intensity to apparent reflectance using a neural network approach. The results demonstrate the complexity of the radiometric response to range, reflectance, and laser temperature and show that neural networks can accurately estimate apparent reflectance for both wavelengths (root mean square error (RMSE) of 0.072 and 0.069 for the 1063 nm and 1545 nm wavelengths respectively). The trained network can then be used to calibrate full hemispherical scans in a forest environment, providing new opportunities for quantitative data analysis.

Citation

Schofield, L., Danson, F., Entwistle, N., Gaulton, R., & Hancock, S. (2016). Radiometric calibration of a dual-wavelength terrestrial laser scanner using neural networks. Remote Sensing Letters, 7(4), 299-308. https://doi.org/10.1080/2150704X.2015.1134843

• Journal Article Type: Article
• Acceptance Date: Dec 12, 2015
• Online Publication Date: Jan 14, 2016
• Publication Date: Jan 14, 2016
• Deposit Date: Dec 21, 2015
• Publicly Available Date: Apr 5, 2016
• Journal: Remote Sensing Letters
• Print ISSN: 2150-704X
• Electronic ISSN: 2150-7058
• Publisher: Taylor and Francis
• Volume: 7
• Issue: 4
• Pages: 299-308
• DOI: https://doi.org/10.1080/2150704X.2015.1134843
• Publisher URL: http://dx.doi.org/10.1080/2150704X.2015.1134843
• Related Public URLs: http://www.tandfonline.com/toc/trsl20/current#.Vngo6q0nzcs
• Additional Information: Projects : PhD entitled 'Quantifying structural change in UK woodland canopies with a dual-wavelength full-waveform terrestrial laser scanner' funded via a studentship from NERC