Marine Science Faculty Publications
Sensing an Intense Phytoplankton Bloom in the Western Taiwan Strait from Radiometric Measurements on a UAV
Document Type
Article
Publication Date
2017
Keywords
Unmanned aerial vehicle, Remote sensing reflectance, Phytoplankton bloom
Digital Object Identifier (DOI)
https://doi.org/10.1016/j.rse.2017.05.036
Abstract
Rapid assessment of algal blooms in bays and estuaries has been difficult due to lack of timely shipboard measurements and lack of spatial resolution from current ocean color satellites. Airborne measurements may fill the gap, yet they are often hindered by the high cost and difficulty in deployment. Here we demonstrate the capacity of a low-cost, low-altitude unmanned aerial vehicle (UAV) in assessing an intense phytoplankton (Phaeocystis globosa) bloom (chlorophyll concentrations ranged from 7.3 to 45.6 mg/m3) in Weitou Bay in the western Taiwan Strait. The UAV was equipped with a hyperspectral sensor to measure the water color with a footprint of 5 m at every 30 m distance along the flight track. A novel approach was developed to obtain remote sensing reflectance (Rrs) from the UAV at-sensor radiometric measurements. Compared with concurrent and co-located field measured Rrs (14 stations in total), the UAV-derived Rrs showed reasonable agreement with root mean square difference ranging 0.0028–0.0043 sr− 1 (relative difference ~ 20–32%) of such turbid waters for the six MODIS bands (412–667 nm). The magnitude of the bloom was further evaluated from the UAV-derived Rrs. For the bloom waters, the estimated surface chlorophyll a concentration (Chl) ranged 6–98 mg/m3, which is 3–50 times of the Chl under normal conditions. This effort demonstrates for the first time a successful retrieval of both water color (i.e., Rrs) and Chl in a nearshore environment from UAV hyperspectral measurements, which advocates the use of UAVs for rapid assessment of water quality, especially for nearshore or difficult-to-reach waters, due to its flexibility, low cost, high spatial resolution, and sound accuracy.
Was this content written or created while at USF?
Yes
Citation / Publisher Attribution
Remote Sensing of Environment, v. 198, p. 85-94
Scholar Commons Citation
Shang, Shaoling; Lee, Zhongping; Lin, Gong; Hu, Chuanmin; Shi, Lianghai; Zhang, Yongnian; Li, Xueding; Wu, Jingyu; and Yan, Jing, "Sensing an Intense Phytoplankton Bloom in the Western Taiwan Strait from Radiometric Measurements on a UAV" (2017). Marine Science Faculty Publications. 1972.
https://digitalcommons.usf.edu/msc_facpub/1972
