Comparison of Lake Optical Water Types Derived from Sentinel-2 and Sentinel-3

被引:18
作者
Soomets, Tuuli [1 ]
Uudeberg, Kristi [2 ]
Jakovels, Dainis [1 ]
Zagars, Matiss [1 ]
Reinart, Anu [2 ]
Brauns, Agris [1 ]
Kutser, Tiit [3 ]
机构
[1] Inst Environm Solut, LV-4101 Priekulu Parish, Latvia
[2] Univ Tartu, Tartu Observ, Observatooriumi 1, EE-61602 Toravere, Estonia
[3] Univ Tartu, Estonian Marine Inst, Miealuse 14, EE-12618 Tallinn, Estonia
基金
欧盟地平线“2020”;
关键词
optical water type; lakes; optically complex waters; remote sensing; Sentinel-2; Sentinel-3; CLASSIFICATION; VARIABILITY; INLAND;
D O I
10.3390/rs11232883
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Inland waters play a critical role in our drinking water supply. Additionally, they are important providers of food and recreation possibilities. Inland waters are known to be optically complex and more diverse than marine or ocean waters. The optical properties of natural waters are influenced by three different and independent sources: phytoplankton, suspended matter, and colored dissolved organic matter. Thus, the remote sensing of these waters is more challenging. Different types of waters need different approaches to obtain correct water quality products; therefore, the first step in remote sensing of lakes should be the classification of the water types. The classification of optical water types (OWTs) is based on the differences in the reflectance spectra of the lake water. This classification groups lake and coastal waters into five optical classes: Clear, Moderate, Turbid, Very Turbid, and Brown. We studied the OWTs in three different Latvian lakes: Burtnieks, Lubans, and Razna, and in a large Estonian lake, Lake Vortsjarv. The primary goal of this study was a comparison of two different Copernicus optical instrument data for optical classification in lakes: Ocean and Land Color Instrument (OLCI) on Sentinel-3 and Multispectral Instrument (MSI) on Sentinel-2. We found that both satellite OWT classifications in lakes were comparable (R-2 = 0.74). We were also able to study the spatial and temporal changes in the OWTs of the study lakes during 2017. The comparison between two satellites was carried out to understand if the classification of the OWTs with both satellites is compatible. Our results could give us not only a better overview of the changes in the lake water by studying the temporal and spatial variability of the OWTs, but also possibly better retrieval of Level 2 satellite products when using OWT guided approach.
引用
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页数:16
相关论文
共 34 条
[11]   Remote estimation of chlorophyll a in optically complex waters based on optical classification [J].
Le, Chengfeng ;
Li, Yunmei ;
Zha, Yong ;
Sun, Deyong ;
Huang, Changchun ;
Zhang, Hong .
REMOTE SENSING OF ENVIRONMENT, 2011, 115 (02) :725-737
[12]  
Maemets A., 1977, EESTI NSV JARVED JA
[13]   How optically diverse is the coastal ocean? [J].
Melin, F. ;
Vantrepotte, V. .
REMOTE SENSING OF ENVIRONMENT, 2015, 160 :235-251
[14]   Regional Models for High-Resolution Retrieval of Chlorophyll a and TSM Concentrations in the Gorky Reservoir by Sentinel-2 Imagery [J].
Molkov, Alexander A. ;
Fedorov, Sergei V. ;
Pelevin, Vadim V. ;
Korchemkina, Elena N. .
REMOTE SENSING, 2019, 11 (10)
[15]   An optical water type framework for selecting and blending retrievals from bio-optical algorithms in lakes and coastal waters [J].
Moore, Timothy S. ;
Dowell, Mark D. ;
Bradt, Shane ;
Ruiz Verdu, Antonio .
REMOTE SENSING OF ENVIRONMENT, 2014, 143 :97-111
[16]   A class-based approach to characterizing and mapping the uncertainty of the MODIS ocean chlorophyll product [J].
Moore, Timothy S. ;
Campbell, Janet W. ;
Dowell, Mark D. .
REMOTE SENSING OF ENVIRONMENT, 2009, 113 (11) :2424-2430
[17]   ANALYSIS OF VARIATIONS IN OCEAN COLOR [J].
MOREL, A ;
PRIEUR, L .
LIMNOLOGY AND OCEANOGRAPHY, 1977, 22 (04) :709-722
[18]  
Noges Peeter, 2012, Estonian Journal of Ecology, V61, P227, DOI 10.3176/eco.2012.4.01
[19]   Water level as the mediator between climate change and phytoplankton composition in a large shallow temperate lake [J].
Noges, T ;
Noges, P ;
Laugaste, R .
HYDROBIOLOGIA, 2003, 506 (1-3) :257-263
[20]  
Ogashawara I, 2017, BIO-OPTICAL MODELING AND REMOTE SENSING OF INLAND WATERS, P1, DOI 10.1016/B978-0-12-804644-9.00001-X