Assessing the impact of illumination on UAV pushbroom hyperspectral imagery collected under various cloud cover conditions

被引:59
作者
Arroyo-Mora, J. Pablo [1 ]
Kalacska, Margaret [2 ]
Loke, Trond [3 ]
Schlapfer, Daniel [4 ]
Coops, Nicholas C. [5 ]
Lucanus, Oliver [2 ]
Leblanc, George [1 ]
机构
[1] Natl Res Council Canada, Flight Res Lab, 1920 Res Rd, Ottawa, ON, Canada
[2] McGill Univ, Dept Geog, Appl Remote Sensing Lab ARSL, Montreal, PQ, Canada
[3] Norsk Elektro Opt AS, Prost Stabels Vei 22, N-2019 Skedsmokorset, Norway
[4] ReSe Applicat LLC, Langeggweg 3, CH-9500 Wil, Switzerland
[5] Univ British Columbia, Fac Forestry, Integrated Remote Sensing Studio IRSS, 2424 Main Mall, Vancouver, BC, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Drones; Hyperspectral; Atmospheric compensation; Signal to noise ratio; Spectral vegetation indices; Garry oak; UNMANNED AERIAL VEHICLE; IMAGING SPECTROMETRY DATA; TO-NOISE RATIO; HIGH-RESOLUTION; ATMOSPHERIC CORRECTION; CAROTENOID CONTENT; SATELLITE DATA; VEGETATION; SPECTROSCOPY; REQUIREMENTS;
D O I
10.1016/j.rse.2021.112396
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The recent development of small form-factor (<6 kg), full range (400-2500 nm) pushbroom hyperspectral imaging systems (HSI) for unmanned aerial vehicles (UAV) poses a new range of opportunities for passive remote sensing applications. The flexible deployment of these UAV-HSI systems have the potential to expand the data acquisition window to acceptable (though non-ideal) atmospheric conditions. This is an important consideration for time-sensitive applications (e.g. phenology) in areas with persistent cloud cover. Since the majority of UAV studies have focused on applications with ideal illumination conditions (e.g. minimal or non-cloud cover), little is known to what extent UAV-HSI data are affected by changes in illumination conditions due to variable cloud cover. In this study, we acquired UAV pushbroom HSI (400-2500 nm) over three consecutive days with various illumination conditions (i.e. cloud cover), which were complemented with downwelling irradiance data to characterize illumination conditions and in-situ and laboratory reference panel measurements across a range of reflectivity (i.e. 2%, 10%, 18% and 50%) used to evaluate reflectance products. Using these data we address four fundamental aspects for UAV-HSI acquired under various conditions ranging from high (624.6 - 16.63 W.m(2)) to low (2.5 - 0.9 W.m(2)) direct irradiance: atmospheric compensation, signal-to-noise ratio (SNR), spectral vegetation indices and endmembers extraction. For instance, two atmospheric compensation methods were applied, a radiative transfer model suitable for high direct irradiance, and an Empirical Line Model (ELM) for diffuse irradiance conditions. SNR results for two distinctive vegetation classes (i.e. tree canopy vs herbaceous vegetation) reveal wavelength dependent attenuation by cloud cover, with higher SNR under high direct irradiance for canopy vegetation. Spectral vegetation index (SVIs) results revealed high variability and index dependent effects. For example, NDVI had significant differences (p < 0.05) across illumination conditions, while NDWI appeared insensitive at the canopy level. Finally, often neglected diffuse illumination conditions may be beneficial for revealing spectral features in vegetation that are obscured by the predominantly non-Lambertian reflectance encountered under high direct illumination. To our knowledge, our study is the first to use a full range pushbroom UAV sensor (400-2500 nm) for assessing illumination effects on the aforementioned variables. Our findings pave the way for understanding the advantages and limitations of ultra-high spatial resolution full range high fidelity UAV-HSI for ecological and other applications.
引用
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页数:20
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