Estimation of chlorophyll-a concentration with semi-analytical algorithms using airborne hyperspectral imagery in Nakdong river of South Korea
In this study, semi-analytical algorithms such as two-band and three-band models were used to estimate the chlorophyll- a (Chl- a ) concentration in the turbid river using an airborne hyperspectral imagery. In order to select the optimal wavelength band to be used in the empirical equation, surface...
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Published in | Spatial information research (Online) Vol. 27; no. 1; pp. 97 - 107 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
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Springer Singapore
01.02.2019
대한공간정보학회 |
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Abstract | In this study, semi-analytical algorithms such as two-band and three-band models were used to estimate the chlorophyll-
a
(Chl-
a
) concentration in the turbid river using an airborne hyperspectral imagery. In order to select the optimal wavelength band to be used in the empirical equation, surface water was collected at the same time of acquisition of the aerial hyperspectral imagery. The spectral characteristic of the Chl-
a
, PC, CDOM, NAP, and phytoplankton were analyzed from by collected samples. The concentrations of PC and CDOM which affect the spectral characteristics to Chl-
a
were low and there was no change over time. So the range of wavelengths was able to broaden than the existing cases. As the result of widening the wavelength band, the two-band and three-band models were found to be higher R
2
than the results obtained by using the existing formula. Because the three-band model is more statistical significance than the two-band model, it is more appropriate to estimate the chlorophyll-
a
concentration in the turbid river. However, the Chl-
a
concentration of this study was relatively low at 45 mg/m
3
, and the effect of PC and CDOM also was small. To estimate the correct Chl-
a
concentration, data such as airborne hyperspectral imagery and water sample need to be accumulated in different years and the correlation between optical properties and concentration should be thoroughly analyzed. |
---|---|
AbstractList | In this study, semi-analytical algorithms such as two-band and three-band models were used to estimate the chlorophyll-
a
(Chl-
a
) concentration in the turbid river using an airborne hyperspectral imagery. In order to select the optimal wavelength band to be used in the empirical equation, surface water was collected at the same time of acquisition of the aerial hyperspectral imagery. The spectral characteristic of the Chl-
a
, PC, CDOM, NAP, and phytoplankton were analyzed from by collected samples. The concentrations of PC and CDOM which affect the spectral characteristics to Chl-
a
were low and there was no change over time. So the range of wavelengths was able to broaden than the existing cases. As the result of widening the wavelength band, the two-band and three-band models were found to be higher R
2
than the results obtained by using the existing formula. Because the three-band model is more statistical significance than the two-band model, it is more appropriate to estimate the chlorophyll-
a
concentration in the turbid river. However, the Chl-
a
concentration of this study was relatively low at 45 mg/m
3
, and the effect of PC and CDOM also was small. To estimate the correct Chl-
a
concentration, data such as airborne hyperspectral imagery and water sample need to be accumulated in different years and the correlation between optical properties and concentration should be thoroughly analyzed. In this study, semi-analytical algorithms such as two-band and three-band models were used to estimate the chlorophyll-a (Chl-a) concentration in the turbid river using an airborne hyperspectral imagery. In order to select the optimal wavelength band to be used in the empirical equation, surface water was collected at the same time of acquisition of the aerial hyperspectral imagery. The spectral characteristic of the Chl-a, PC, CDOM, NAP, and phytoplankton were analyzed from by collected samples. The concentrations of PC and CDOM which affect the spectral characteristics to Chl-a were low and there was no change over time. So the range of wavelengths was able to broaden than the existing cases. As the result of widening the wavelength band, the two-band and three-band models were found to be higher R2 than the results obtained by using the existing formula. Because the three-band model is more statistical significance than the two-band model, it is more appropriate to estimate the chlorophyll-a concentration in the turbid river. However, the Chl-a concentration of this study was relatively low at 45 mg/m3, and the effect of PC and CDOM also was small. To estimate the correct Chl-a concentration, data such as airborne hyperspectral imagery and water sample need to be accumulated in different years and the correlation between optical properties and concentration should be thoroughly analyzed. KCI Citation Count: 2 |
Author | Lee, Keum-Young Kang, Seong-Joo Jeon, Eui-Ik |
Author_xml | – sequence: 1 givenname: Eui-Ik surname: Jeon fullname: Jeon, Eui-Ik organization: R&D Institute, Asia Aero Survey – sequence: 2 givenname: Seong-Joo surname: Kang fullname: Kang, Seong-Joo email: ksjdol@gmail.com organization: R&D Institute, Asia Aero Survey – sequence: 3 givenname: Keum-Young surname: Lee fullname: Lee, Keum-Young organization: R&D Institute, Asia Aero Survey |
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CitedBy_id | crossref_primary_10_1021_acs_est_1c03211 crossref_primary_10_1016_j_jag_2022_103053 crossref_primary_10_2139_ssrn_3998983 crossref_primary_10_3390_rs12152463 |
Cites_doi | 10.1016/j.watres.2011.11.068 10.7780/kjrs.2014.30.1.6 10.1046/j.1529-8817.1998.340383.x 10.1080/01431169208904125 10.1016/j.ecoinf.2014.07.004 10.1078/0176-1617-00887 10.1100/tsw.2001.16 10.1007/s41324-016-0075-1 10.1016/j.isprsjprs.2013.11.016 10.1016/j.rse.2007.01.016 10.4236/gep.2014.22004 10.1016/j.rse.2012.11.023 10.2307/1312927 10.1007/s41324-016-0069-z 10.3390/rs9060542 10.4491/KSEE.2016.38.2.71 10.1117/12.346731 |
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Keywords | Chlorophyll Hyperspectral imagery Remote sensing Airborne Semi-analytical algorithms |
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References | Maity, Mondal, Das, Mondal, Bandyopadhyay (CR5) 2017; 25 Dall’Olmo, Gitelson, Rundquist (CR24) 2003; 30 Fan (CR14) 2014; 2 Pyo, Pachepsky, Baek, Kwon, Kim, Lee, Park (CR20) 2017; 9 Moses, Gitelson, Perk, Gurlin, Rundquist, Leavitt, Brakhage (CR12) 2012; 46 CR19 Awad (CR15) 2014; 24 CR18 Gitelson, Gritz, Merzlyak (CR25) 2003; 160 CR11 Gitelson, Schalles, Hladik (CR10) 2007; 109 Govender, Chetty, Bulcock (CR7) 2007; 33 Kim, Shin, Suh (CR16) 2014; 30 Gitelson (CR21) 1992; 13 CR4 Kim, Lee, Ma, Kook (CR6) 2005; 21 Zhou, Roberts, Ma, Zhang, Tang (CR27) 2014; 88 Richardson (CR3) 1996; 46 CR26 Park, Jang, Kim, Baik, Lee (CR9) 2014; 17 CR22 Schalles, Gitelson, Yacobi, Kroenke (CR2) 1998; 34 Patra, Dubey, Trivedi, Sahu, Rout (CR8) 2017; 25 Olmanson, Brezonik, Bauer (CR13) 2013; 130 Gitelson, Keydan, Shishkin (CR23) 1985; 6 Paerl, Fulton, Moisander, Dyble (CR1) 2001; 1 Gwak, Kim (CR17) 2016; 38 204_CR18 204_CR11 BR Gwak (204_CR17) 2016; 38 TW Kim (204_CR16) 2014; 30 PP Patra (204_CR8) 2017; 25 C Fan (204_CR14) 2014; 2 LL Richardson (204_CR3) 1996; 46 G Dall’Olmo (204_CR24) 2003; 30 J Pyo (204_CR20) 2017; 9 M Awad (204_CR15) 2014; 24 M Govender (204_CR7) 2007; 33 204_CR26 SH Kim (204_CR6) 2005; 21 S Maity (204_CR5) 2017; 25 L Zhou (204_CR27) 2014; 88 204_CR22 WJ Moses (204_CR12) 2012; 46 YJ Park (204_CR9) 2014; 17 LG Olmanson (204_CR13) 2013; 130 HW Paerl (204_CR1) 2001; 1 A Gitelson (204_CR21) 1992; 13 AA Gitelson (204_CR25) 2003; 160 204_CR4 JF Schalles (204_CR2) 1998; 34 AA Gitelson (204_CR10) 2007; 109 204_CR19 A Gitelson (204_CR23) 1985; 6 |
References_xml | – volume: 46 start-page: 993 issue: 4 year: 2012 end-page: 1004 ident: CR12 article-title: Estimation of chlorophyll- concentration in turbid productive waters using airborne hyperspectral data publication-title: Water Research doi: 10.1016/j.watres.2011.11.068 – ident: CR22 – ident: CR18 – volume: 30 start-page: 61 issue: 1 year: 2014 end-page: 73 ident: CR16 article-title: Airborne hyperspectral imagery availability to estimate inland water quality parameter publication-title: Korean Journal of Remote Sensing doi: 10.7780/kjrs.2014.30.1.6 – ident: CR4 – volume: 34 start-page: 383 issue: 2 year: 1998 end-page: 390 ident: CR2 article-title: Estimation of chlorophyll a from time series measurements of high spectral resolution reflectance in an eutrophic lake publication-title: Journal of Phycology doi: 10.1046/j.1529-8817.1998.340383.x – volume: 13 start-page: 3367 issue: 17 year: 1992 end-page: 3373 ident: CR21 article-title: The peak near 700 nm on radiance spectra of algae and water: Relationships of its magnitude and position with chlorophyll concentration publication-title: International Journal of Remote Sensing doi: 10.1080/01431169208904125 – volume: 24 start-page: 60 year: 2014 end-page: 68 ident: CR15 article-title: Sea water chlorophyll- estimation using hyperspectral images and supervised artificial neural network publication-title: Ecological Informatics doi: 10.1016/j.ecoinf.2014.07.004 – volume: 160 start-page: 271 issue: 3 year: 2003 end-page: 282 ident: CR25 article-title: Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves publication-title: Journal of Plant Physiology doi: 10.1078/0176-1617-00887 – volume: 1 start-page: 76 year: 2001 end-page: 113 ident: CR1 article-title: Harmful freshwater algal blooms, with an emphasis on cyanobacteria publication-title: The Scientific World Journal doi: 10.1100/tsw.2001.16 – volume: 25 start-page: 57 issue: 1 year: 2017 end-page: 66 ident: CR5 article-title: Pollution tolerance performance index for plant species using geospatial technology: Evidence from Kolaghat Thermal Plant area, West Bengal, India publication-title: Spatial Information Research doi: 10.1007/s41324-016-0075-1 – volume: 88 start-page: 41 year: 2014 end-page: 47 ident: CR27 article-title: Estimation of higher chlorophyll concentrations using field spectral measurement and HJ-1A hyperspectral satellite data in Dianshan Lake, China publication-title: ISPRS Journal of Photogrammetry and Remote Sensing doi: 10.1016/j.isprsjprs.2013.11.016 – volume: 21 start-page: 341 issue: 4 year: 2005 end-page: 369 ident: CR6 article-title: Current status of hyperspectral remote sensing: Principle, data processing techniques, and applications publication-title: Korean Journal of Remote Sensing – volume: 6 start-page: 28 year: 1985 end-page: 36 ident: CR23 article-title: Inland waters quality assessment from satellite data in visible range of the spectrum publication-title: Soviet Remote Sensing – volume: 109 start-page: 464 issue: 4 year: 2007 end-page: 472 ident: CR10 article-title: Remote chlorophyll- retrieval in turbid, productive estuaries: Chesapeake Bay case study publication-title: Remote Sensing of Environment doi: 10.1016/j.rse.2007.01.016 – ident: CR19 – volume: 17 start-page: 113 issue: 3 year: 2014 end-page: 125 ident: CR9 article-title: A research on the applicability of water quality analysis using the hyperspectral sensor publication-title: Journal of the Korean Society for Environmental Analysis – volume: 2 start-page: 19 issue: 2 year: 2014 end-page: 27 ident: CR14 article-title: Spectral analysis of water reflectance for hyperspectral remote sensing of water quality in estuarine water publication-title: Journal of Geoscience and Environment Protection doi: 10.4236/gep.2014.22004 – volume: 130 start-page: 254 year: 2013 end-page: 265 ident: CR13 article-title: Airborne hyperspectral remote sensing to assess spatial distribution of water quality characteristics in large rivers: The Mississippi River and its tributaries in Minnesota publication-title: Remote Sensing of Environment doi: 10.1016/j.rse.2012.11.023 – ident: CR11 – volume: 33 start-page: 145 issue: 2 year: 2007 end-page: 151 ident: CR7 article-title: A review of hyperspectral remote sensing and its application in vegetation and water resource studies publication-title: Water Sa – volume: 46 start-page: 492 issue: 7 year: 1996 end-page: 501 ident: CR3 article-title: Remote sensing of algal bloom dynamics publication-title: BioScience doi: 10.2307/1312927 – volume: 25 start-page: 75 issue: 1 year: 2017 end-page: 87 ident: CR8 article-title: Estimation of chlorophyll- concentration and trophic states in Nalban Lake of East Kolkata Wetland, India from Landsat 8 OLI data publication-title: Spatial Information Research doi: 10.1007/s41324-016-0069-z – volume: 30 start-page: 1938 issue: 18 year: 2003 ident: CR24 article-title: Towards a unified approach for remote estimation of chlorophyll- in both terrestrial vegetation and turbid productive waters publication-title: Geophysical Research Letters – ident: CR26 – volume: 9 start-page: 542 year: 2017 ident: CR20 article-title: Optimizing semi-analytical algorithms for estimating chlorophyll- and phycocyanin concentrations in Inland Waters in Korea publication-title: Remote Sensing doi: 10.3390/rs9060542 – volume: 38 start-page: 71 issue: 2 year: 2016 end-page: 78 ident: CR17 article-title: Characterization of water quality in Changnyeong-Haman weir section using statistical analyses publication-title: Journal of Korean Society of Environmental Engineers doi: 10.4491/KSEE.2016.38.2.71 – ident: 204_CR19 – volume: 46 start-page: 993 issue: 4 year: 2012 ident: 204_CR12 publication-title: Water Research doi: 10.1016/j.watres.2011.11.068 – volume: 109 start-page: 464 issue: 4 year: 2007 ident: 204_CR10 publication-title: Remote Sensing of Environment doi: 10.1016/j.rse.2007.01.016 – volume: 21 start-page: 341 issue: 4 year: 2005 ident: 204_CR6 publication-title: Korean Journal of Remote Sensing – volume: 9 start-page: 542 year: 2017 ident: 204_CR20 publication-title: Remote Sensing doi: 10.3390/rs9060542 – volume: 1 start-page: 76 year: 2001 ident: 204_CR1 publication-title: The Scientific World Journal doi: 10.1100/tsw.2001.16 – volume: 160 start-page: 271 issue: 3 year: 2003 ident: 204_CR25 publication-title: Journal of Plant Physiology doi: 10.1078/0176-1617-00887 – volume: 30 start-page: 1938 issue: 18 year: 2003 ident: 204_CR24 publication-title: Geophysical Research Letters – volume: 25 start-page: 75 issue: 1 year: 2017 ident: 204_CR8 publication-title: Spatial Information Research doi: 10.1007/s41324-016-0069-z – ident: 204_CR11 – volume: 24 start-page: 60 year: 2014 ident: 204_CR15 publication-title: Ecological Informatics doi: 10.1016/j.ecoinf.2014.07.004 – volume: 88 start-page: 41 year: 2014 ident: 204_CR27 publication-title: ISPRS Journal of Photogrammetry and Remote Sensing doi: 10.1016/j.isprsjprs.2013.11.016 – volume: 46 start-page: 492 issue: 7 year: 1996 ident: 204_CR3 publication-title: BioScience doi: 10.2307/1312927 – volume: 2 start-page: 19 issue: 2 year: 2014 ident: 204_CR14 publication-title: Journal of Geoscience and Environment Protection doi: 10.4236/gep.2014.22004 – ident: 204_CR18 – ident: 204_CR22 – ident: 204_CR26 – volume: 33 start-page: 145 issue: 2 year: 2007 ident: 204_CR7 publication-title: Water Sa – volume: 6 start-page: 28 year: 1985 ident: 204_CR23 publication-title: Soviet Remote Sensing – ident: 204_CR4 doi: 10.1117/12.346731 – volume: 30 start-page: 61 issue: 1 year: 2014 ident: 204_CR16 publication-title: Korean Journal of Remote Sensing doi: 10.7780/kjrs.2014.30.1.6 – volume: 13 start-page: 3367 issue: 17 year: 1992 ident: 204_CR21 publication-title: International Journal of Remote Sensing doi: 10.1080/01431169208904125 – volume: 25 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Snippet | In this study, semi-analytical algorithms such as two-band and three-band models were used to estimate the chlorophyll-
a
(Chl-
a
) concentration in the turbid... In this study, semi-analytical algorithms such as two-band and three-band models were used to estimate the chlorophyll-a (Chl-a) concentration in the turbid... |
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Title | Estimation of chlorophyll-a concentration with semi-analytical algorithms using airborne hyperspectral imagery in Nakdong river of South Korea |
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