Remote cyanobacteria detection by multispectral drone imagery

被引:0
|
作者
Bartelt, Garrett [1 ]
You, Jiaqi [2 ]
Hondzo, Miki [1 ]
机构
[1] Univ Minnesota, Dept Civil Environm & Geoengn, St Anthony Falls Lab, 2 Third Ave SE, Minneapolis, MN 55414 USA
[2] Guangdong Univ Technol, Inst Environm & Ecol Engn, Guangzhou, Peoples R China
关键词
Unmanned aerial system; drone; multispectral imagery; chlorophyll; PIGMENTS;
D O I
10.1080/10402381.2024.2341250
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Bartelt G, You J, Hondzo M. 2024. Remote cyanobacteria detection by multispectral drone imagery. Lake Reserv Manage. XX:XXX-XX.Cyanobacteria play a crucial role in the ecological services of aquatic environments. Remote detection of cyanobacteria in water using satellite-based sensor images has been proven effective in monitoring eutrophication and harmful algal blooms. Satellite-based sensors are good at tracking large blooms in oceans and lakes, but not in small bodies of water. This study seeks to use remote-sensing techniques on images obtained from a multispectral camera mounted on an unmanned aerial system (UAS). We investigated a small freshwater lake, Brownie Lake, in Minneapolis, Minnesota, using the UAS. We compared the collected imagery to the measurements of chlorophyll and phycocyanin concentrations. Cyanobacterial chlorophyll a (Chl-a) concentrations and multispectral UAS data showed good agreement (r2 = 0.54) in this study. Chl-a concentration strongly correlated with the presence of the near-infrared band at 840 nm and the red band at 668 nm. The most correlated spectral band combinations were the normalized difference vegetative index (NDVI) and 2 band algorithm (2BDA). Our research demonstrates the usefulness of UAS technologies in water quality monitoring.
引用
收藏
页码:236 / 247
页数:12
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