Towards Monitoring of Nutrient Pollution in Coastal Lake Using Remote Sensing and Regression Analysis

The last few decades have witnessed a tremendous increase in nutrient levels (phosphorus and nitrogen) in coastal water leading to excessive algal growth (Eutrophication). The presence of large amounts of algae turns the water’s color into green or red, in the case of algal blooms. Chlorophyll-a is...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Mortula, Maruf (author)
مؤلفون آخرون: Ali, Tarig (author), Bachir, Abdallah (author), Elaksher, Ahmed (author), Abouleish, Mohamed (author)
التنسيق: article
منشور في: 2020
الموضوعات:
الوصول للمادة أونلاين:http://hdl.handle.net/11073/21444
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author Mortula, Maruf
author2 Ali, Tarig
Bachir, Abdallah
Elaksher, Ahmed
Abouleish, Mohamed
author2_role author
author
author
author
author_facet Mortula, Maruf
Ali, Tarig
Bachir, Abdallah
Elaksher, Ahmed
Abouleish, Mohamed
author_role author
dc.creator.none.fl_str_mv Mortula, Maruf
Ali, Tarig
Bachir, Abdallah
Elaksher, Ahmed
Abouleish, Mohamed
dc.date.none.fl_str_mv 2020
2021-04-26T08:59:46Z
2021-04-26T08:59:46Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv Mortula, M.; Ali, T.; Bachir, A.; Elaksher, A.; Abouleish, M. Towards Monitoring of Nutrient Pollution in Coastal Lake Using Remote Sensing and Regression Analysis. Water 2020, 12, 1954. https://doi.org/10.3390/w12071954
2073-4441
http://hdl.handle.net/11073/21444
10.3390/w12071954
dc.language.none.fl_str_mv en_US
dc.publisher.none.fl_str_mv MDPI
dc.relation.none.fl_str_mv https://doi.org/10.3390/w12071954
dc.subject.none.fl_str_mv Chlorophyll-a
GIS
WorldView-2 imagery
Nutrients
Eutrophication
dc.title.none.fl_str_mv Towards Monitoring of Nutrient Pollution in Coastal Lake Using Remote Sensing and Regression Analysis
dc.type.none.fl_str_mv Peer-Reviewed
Published version
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
description The last few decades have witnessed a tremendous increase in nutrient levels (phosphorus and nitrogen) in coastal water leading to excessive algal growth (Eutrophication). The presence of large amounts of algae turns the water’s color into green or red, in the case of algal blooms. Chlorophyll-a is often used as an indicator of algal biomass. Due to increased human activities surrounding Dubai creek, there have been eutrophication concerns given the levels of nutrients in that creek. This study aims to map chlorophyll-a in Dubai Creek from WorldView-2 imagery and explore the relationship between chlorophyll-a and other eutrophication indicators. A geometrically and atmospherically-corrected WorldView-2 image and in-situ data have been utilized to map chlorophyll-a in the creek. A spectral model, developed from theWorldView-2 multispectral image to monitor Chlorophyll-a concentration, yielded 0.82 R² with interpolated in-situ chlorophyll-a data. To address the time lag between the in-situ data and the image, L and sat 7 Enhanced Thematic Mapper Plus (ETM+) images were used to demonstrate the accuracy of the WorldView-2 model. The images, acquired on 20 May and 23 July 2012, were processed to extract chlorophyll-a band ratios (Band 4/Band 3) following the standard approach. Based on the availability, the 20 May image acquisition date is the closest to the middle of Quarter 2 (Q2) of the in-situ data (15 May). The 23 July 2012 image acquisition date is the closest to theWorldView-2 image date (24 July). Another model developed to highlight the relationship between spectral chlorophyll-a levels, and total nitrogen and orthophosphate levels, yielded 0.97 R², which indicates high agreement. Furthermore, the generated models were found to be useful in mapping chlorophyll-a, total nitrogen, and orthophosphate, without the need for costly in-situ data acquisition efforts.
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identifier_str_mv Mortula, M.; Ali, T.; Bachir, A.; Elaksher, A.; Abouleish, M. Towards Monitoring of Nutrient Pollution in Coastal Lake Using Remote Sensing and Regression Analysis. Water 2020, 12, 1954. https://doi.org/10.3390/w12071954
2073-4441
10.3390/w12071954
language_invalid_str_mv en_US
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oai_identifier_str oai:repository.aus.edu:11073/21444
publishDate 2020
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spelling Towards Monitoring of Nutrient Pollution in Coastal Lake Using Remote Sensing and Regression AnalysisMortula, MarufAli, TarigBachir, AbdallahElaksher, AhmedAbouleish, MohamedChlorophyll-aGISWorldView-2 imageryNutrientsEutrophicationThe last few decades have witnessed a tremendous increase in nutrient levels (phosphorus and nitrogen) in coastal water leading to excessive algal growth (Eutrophication). The presence of large amounts of algae turns the water’s color into green or red, in the case of algal blooms. Chlorophyll-a is often used as an indicator of algal biomass. Due to increased human activities surrounding Dubai creek, there have been eutrophication concerns given the levels of nutrients in that creek. This study aims to map chlorophyll-a in Dubai Creek from WorldView-2 imagery and explore the relationship between chlorophyll-a and other eutrophication indicators. A geometrically and atmospherically-corrected WorldView-2 image and in-situ data have been utilized to map chlorophyll-a in the creek. A spectral model, developed from theWorldView-2 multispectral image to monitor Chlorophyll-a concentration, yielded 0.82 R² with interpolated in-situ chlorophyll-a data. To address the time lag between the in-situ data and the image, L and sat 7 Enhanced Thematic Mapper Plus (ETM+) images were used to demonstrate the accuracy of the WorldView-2 model. The images, acquired on 20 May and 23 July 2012, were processed to extract chlorophyll-a band ratios (Band 4/Band 3) following the standard approach. Based on the availability, the 20 May image acquisition date is the closest to the middle of Quarter 2 (Q2) of the in-situ data (15 May). The 23 July 2012 image acquisition date is the closest to theWorldView-2 image date (24 July). Another model developed to highlight the relationship between spectral chlorophyll-a levels, and total nitrogen and orthophosphate levels, yielded 0.97 R², which indicates high agreement. Furthermore, the generated models were found to be useful in mapping chlorophyll-a, total nitrogen, and orthophosphate, without the need for costly in-situ data acquisition efforts.American University of SharjahMDPI2021-04-26T08:59:46Z2021-04-26T08:59:46Z2020Peer-ReviewedPublished versioninfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfMortula, M.; Ali, T.; Bachir, A.; Elaksher, A.; Abouleish, M. Towards Monitoring of Nutrient Pollution in Coastal Lake Using Remote Sensing and Regression Analysis. Water 2020, 12, 1954. https://doi.org/10.3390/w120719542073-4441http://hdl.handle.net/11073/2144410.3390/w12071954en_UShttps://doi.org/10.3390/w12071954oai:repository.aus.edu:11073/214442024-08-22T12:06:57Z
spellingShingle Towards Monitoring of Nutrient Pollution in Coastal Lake Using Remote Sensing and Regression Analysis
Mortula, Maruf
Chlorophyll-a
GIS
WorldView-2 imagery
Nutrients
Eutrophication
status_str publishedVersion
title Towards Monitoring of Nutrient Pollution in Coastal Lake Using Remote Sensing and Regression Analysis
title_full Towards Monitoring of Nutrient Pollution in Coastal Lake Using Remote Sensing and Regression Analysis
title_fullStr Towards Monitoring of Nutrient Pollution in Coastal Lake Using Remote Sensing and Regression Analysis
title_full_unstemmed Towards Monitoring of Nutrient Pollution in Coastal Lake Using Remote Sensing and Regression Analysis
title_short Towards Monitoring of Nutrient Pollution in Coastal Lake Using Remote Sensing and Regression Analysis
title_sort Towards Monitoring of Nutrient Pollution in Coastal Lake Using Remote Sensing and Regression Analysis
topic Chlorophyll-a
GIS
WorldView-2 imagery
Nutrients
Eutrophication
url http://hdl.handle.net/11073/21444