An Optimal Two Bands Ratio Model to Monitor Chlorophyll-a in Urban Lake Using Landsat 8 Data

An Optimal Two Bands Ratio Model to Monitor Chlorophyll-a in Urban Lake Using Landsat 8 Data

Chlorophyll-a (Chl-a) estimation in inland waters is an essential environmental issue. This study aimed to identify a band ratio model for Chl-a simulation using Landsat 8 OLI data and in situ Chl-a measuring in Lake Donghu. The band B1and B2, respectively at the wavelength of 443 nm and 483 nm, in...

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Main Authors: Chen Qi, Huang Mutao, Bai Kaiyuan, Li Xiaojuan
Format: Article
Language:English
Published: EDP Sciences 2020-01-01
Series:E3S Web of Conferences
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/03/e3sconf_arfee2020_02003.pdf
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spelling doaj-1ca2a2e629ac4efa839df841fcee98cc2021-04-02T14:52:42ZengEDP SciencesE3S Web of Conferences2267-12422020-01-011430200310.1051/e3sconf/202014302003e3sconf_arfee2020_02003An Optimal Two Bands Ratio Model to Monitor Chlorophyll-a in Urban Lake Using Landsat 8 DataChen Qi0Huang Mutao1Bai Kaiyuan2Li Xiaojuan3College of Hydropower and Information Engineering, Huazhong University of Science and TechnologyCollege of Hydropower and Information Engineering, Huazhong University of Science and TechnologyCollege of Hydropower and Information Engineering, Huazhong University of Science and TechnologyCollege of Hydropower and Information Engineering, Huazhong University of Science and TechnologyChlorophyll-a (Chl-a) estimation in inland waters is an essential environmental issue. This study aimed to identify a band ratio model for Chl-a simulation using Landsat 8 OLI data and in situ Chl-a measuring in Lake Donghu. The band B1and B2, respectively at the wavelength of 443 nm and 483 nm, in the band ratio model [B1/B2] performed best in Chl-a estimation with the R2 of 0.6215. K-means cluster analysis based on water quality indexes (Chl-a, pH, DO, TN, TP, COD, Turbidity) was conducted to further improve the accuracy of inversion model. The MAPE of the optimal [B1/B2] algorithm has decreased by 4.81% and 39.87% respectively for 17 December 2017 (R2=0.7669, N=42) and 26 March 2018 (R2=0.9156, N=45).https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/03/e3sconf_arfee2020_02003.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Chen Qi
Huang Mutao
Bai Kaiyuan
Li Xiaojuan
spellingShingle Chen Qi
Huang Mutao
Bai Kaiyuan
Li Xiaojuan
An Optimal Two Bands Ratio Model to Monitor Chlorophyll-a in Urban Lake Using Landsat 8 Data
E3S Web of Conferences
author_facet Chen Qi
Huang Mutao
Bai Kaiyuan
Li Xiaojuan
author_sort Chen Qi
title An Optimal Two Bands Ratio Model to Monitor Chlorophyll-a in Urban Lake Using Landsat 8 Data
title_short An Optimal Two Bands Ratio Model to Monitor Chlorophyll-a in Urban Lake Using Landsat 8 Data
title_full An Optimal Two Bands Ratio Model to Monitor Chlorophyll-a in Urban Lake Using Landsat 8 Data
title_fullStr An Optimal Two Bands Ratio Model to Monitor Chlorophyll-a in Urban Lake Using Landsat 8 Data
title_full_unstemmed An Optimal Two Bands Ratio Model to Monitor Chlorophyll-a in Urban Lake Using Landsat 8 Data
title_sort optimal two bands ratio model to monitor chlorophyll-a in urban lake using landsat 8 data
publisher EDP Sciences
series E3S Web of Conferences
issn 2267-1242
publishDate 2020-01-01
description Chlorophyll-a (Chl-a) estimation in inland waters is an essential environmental issue. This study aimed to identify a band ratio model for Chl-a simulation using Landsat 8 OLI data and in situ Chl-a measuring in Lake Donghu. The band B1and B2, respectively at the wavelength of 443 nm and 483 nm, in the band ratio model [B1/B2] performed best in Chl-a estimation with the R2 of 0.6215. K-means cluster analysis based on water quality indexes (Chl-a, pH, DO, TN, TP, COD, Turbidity) was conducted to further improve the accuracy of inversion model. The MAPE of the optimal [B1/B2] algorithm has decreased by 4.81% and 39.87% respectively for 17 December 2017 (R2=0.7669, N=42) and 26 March 2018 (R2=0.9156, N=45).
url https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/03/e3sconf_arfee2020_02003.pdf
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