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UAV-hyperspectral imaging of spectrally complex environments

2020; Taylor & Francis; Volume: 41; Issue: 11 Linguagem: Inglês

10.1080/01431161.2020.1714771

1366-5901

Bikram Pratap Banerjee, Simit Raval, Patrick J. Cullen,

Remote-Sensing Image Classification

Unmanned aerial vehicle (UAV) based hyperspectral imaging is a relatively new remote sensing technology. Near-earth spectroscopy from UAV-hyperspectral systems addresses the limitations of resolution, signal-to-noise ratio, and cloud cover from traditional satellite or airborne platforms. The technology is increasingly being used to obtain fast and accurate information. Recently developed methods for data acquisition and pre-processing have mostly focused on agriculture and forestry applications. This paper addresses the challenges in the methods of sensor calibration, data acquisition, radiometric correction for illumination variation, mosaicking and geometric correction for UAV-hyperspectral imaging of highly heterogeneous environments, such as swamps. A pre-processing workflow was developed to address the specific issues of monitoring the heterogenous distribution of the swamp vegetation and assess its condition. The workflow was used to produce reflectance products and vegetation indices. The developed framework would be useful in remote environments where satellite or airborne hyperspectral observations are limited due to the presence of spectrally complex environment.