Green Algae Detection in the Middle . Downstream of Nakdong River Using High-Resolution Satellite Data

被引:4
作者
Byeon, Yugyeong [1 ]
Seo, Minji [2 ]
Jin, Donghyun [1 ]
Jung, Daeseong [1 ]
Woo, Jongho [1 ]
Jeon, Uujin [1 ]
Han, Kyung-soo [1 ]
机构
[1] Pukyong Natl Univ, Div Earth Environm Sci, Spatial Informat Engn, Busan, South Korea
[2] Korea Polar Res Inst, Ctr Remote Sensing & GIS, Incheon, South Korea
关键词
Climate change; Green Algae; Sentinel-2; NDVI; SEI; FGAI;
D O I
10.7780/kjrs.2021.37.3.10
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Recently, because of changes in temperature and rising water temperatures due to increased pollution sources, many algae have been produced in the water system. Therefore, there has been a lot of research using satellite images for the generation and monitoring of green algae. However, in prior studies, it is difficult to consider the optical properties of the local water system by using only a single index, and by using medium and low-resolution satellite images to conduct large-scale algae detection, there is a problem of accuracy in narrow, broad rivers. Therefore, in this work, we utilize high-resolution images of Sentinel-2 satellites to perform green algae detection on a single index (NDVI, SEI, FGAI) and development index (NDVI & SEI, FGAI & SEI) that mixes single indices. In this study, POD, FAR, and PC values were utilized to evaluate the accuracy of green algae detection algorithms, and the FGAI & SEI index showed the highest accuracy with 98.29% overall accuracy PC.
引用
收藏
页码:493 / 502
页数:10
相关论文
共 18 条
[1]   Validation of Copernicus Sentinel-2 Cloud Masks Obtained from MAJA, Sen2Cor, and FMask Processors Using Reference Cloud Masks Generated with a Supervised Active Learning Procedure [J].
Baetens, Louis ;
Desjardins, Camille ;
Hagolle, Olivier .
REMOTE SENSING, 2019, 11 (04)
[2]   Shoreline change assessment for various types of coasts using multi-temporal Landsat imagery of the east coast of South Korea [J].
Choung, Yun-Jae ;
Jo, Myung-Hee .
REMOTE SENSING LETTERS, 2016, 7 (01) :91-100
[3]   Satellite monitoring of massive green macroalgae bloom (GMB): imaging ability comparison of multi-source data and drifting velocity estimation [J].
Cui, Ting-Wei ;
Zhang, Jie ;
Sun, Li-E ;
Jia, Yong-Jun ;
Zhao, Wenjing ;
Wang, Zong-Ling ;
Meng, Jun-Min .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2012, 33 (17) :5513-5527
[4]   A novel ocean color index to detect floating algae in the global oceans [J].
Hu, Chuanmin .
REMOTE SENSING OF ENVIRONMENT, 2009, 113 (10) :2118-2129
[5]  
Huete A., 1999, ALGORITHM THEORETICA, V3, P295
[6]  
Il Park, Jung, 2017, [Journal of Korean Institute of Intelligent Systems, 한국지능시스템학회 논문지], V27, P164
[7]  
Kim D. H., 2018, P 2018 KOREAN SOC SU, P231
[8]   Application of Multi-satellite Sensors to Estimate the Green-tide Area [J].
Kim, Keunyong ;
Shin, Jisun ;
Ryu, Joo-Hyung .
KOREAN JOURNAL OF REMOTE SENSING, 2018, 34 (02) :339-349
[9]  
최철만, 2007, [Korean Journal of Environmental Agriculture, 한국환경농학회지], V30, P159
[10]   Monitoring cyanobacterial blooms by satellite remote sensing [J].
Kutser, T ;
Metsamaa, L ;
Strömbeck, N ;
Vahtmäe, E .
ESTUARINE COASTAL AND SHELF SCIENCE, 2006, 67 (1-2) :303-312