Assessment of nutrient distributions in Lake Champlain using satellite remote sensing
The introduction of nutrients to lakes causing eutrophic conditions is a major problem around the world. Proper monitoring and modeling are important to effectively manage eutrophication in lake waters. The goal is to develop remote sensing models for nutrients, total phosphorus and total nitrogen,...
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Veröffentlicht in: | Journal of environmental sciences (China) 2014-09, Vol.26 (9), p.1831-1836 |
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creator | Isenstein, Elizabeth M. Park, Mi-Hyun |
description | The introduction of nutrients to lakes causing eutrophic conditions is a major problem around the world. Proper monitoring and modeling are important to effectively manage eutrophication in lake waters. The goal is to develop remote sensing models for nutrients, total phosphorus and total nitrogen, in Lake Champlain. The remote sensing models were created using multivariate linear regression with the unique band combinations of Landsat Enhanced Thematic Mapper Plus (ETM+) imagery based on the empirical relationship with the field observations. The resulting models successfully showed nutrient distributions in the most eutrophic part of Lake Champlain, Missisquoi Bay, with reasonable adjusted coefficient of determination values (R2 = 0.81 and 0.75 for total phosphorus and total nitrogen, respectively). The results show the feasibility and the utility of satellite imagery to detect spatial distributions of lake water quality constituents, which can be used to better understand nutrient distributions in Lake Champlain. This approach can be applicable to other lakes experiencing eutrophication assisting decision making when implementing Best Management Practices and other mitigation techniques to lakes. |
doi_str_mv | 10.1016/j.jes.2014.06.019 |
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Proper monitoring and modeling are important to effectively manage eutrophication in lake waters. The goal is to develop remote sensing models for nutrients, total phosphorus and total nitrogen, in Lake Champlain. The remote sensing models were created using multivariate linear regression with the unique band combinations of Landsat Enhanced Thematic Mapper Plus (ETM+) imagery based on the empirical relationship with the field observations. The resulting models successfully showed nutrient distributions in the most eutrophic part of Lake Champlain, Missisquoi Bay, with reasonable adjusted coefficient of determination values (R2 = 0.81 and 0.75 for total phosphorus and total nitrogen, respectively). The results show the feasibility and the utility of satellite imagery to detect spatial distributions of lake water quality constituents, which can be used to better understand nutrient distributions in Lake Champlain. This approach can be applicable to other lakes experiencing eutrophication assisting decision making when implementing Best Management Practices and other mitigation techniques to lakes.</description><identifier>ISSN: 1001-0742</identifier><identifier>EISSN: 1878-7320</identifier><identifier>DOI: 10.1016/j.jes.2014.06.019</identifier><identifier>PMID: 25193831</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>Assessments ; Eutrophic lakes ; Eutrophication ; Lakes ; Lakes - analysis ; Monitoring ; New York ; Nitrogen - analysis ; Nutrients ; Phosphorus ; Phosphorus - analysis ; Remote sensing ; Remote Sensing Technology ; Satellite imagery ; Vermont ; Water quality ; 卫星遥感技术 ; 多元线性回归 ; 最佳管理 ; 水体富营养化 ; 湖泊富营养化 ; 营养分布 ; 评估 ; 遥感模型</subject><ispartof>Journal of environmental sciences (China), 2014-09, Vol.26 (9), p.1831-1836</ispartof><rights>2014</rights><rights>Copyright © 2014. Published by Elsevier B.V.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c516t-9fa5f64844823e7f17419895b9b53f8dbcce4ad6f61f1de7a09c21cc830c9bd33</citedby><cites>FETCH-LOGICAL-c516t-9fa5f64844823e7f17419895b9b53f8dbcce4ad6f61f1de7a09c21cc830c9bd33</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttp://image.cqvip.com/vip1000/qk/85265X/85265X.jpg</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.jes.2014.06.019$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25193831$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Isenstein, Elizabeth M.</creatorcontrib><creatorcontrib>Park, Mi-Hyun</creatorcontrib><title>Assessment of nutrient distributions in Lake Champlain using satellite remote sensing</title><title>Journal of environmental sciences (China)</title><addtitle>Journal of Environmental Sciences</addtitle><description>The introduction of nutrients to lakes causing eutrophic conditions is a major problem around the world. Proper monitoring and modeling are important to effectively manage eutrophication in lake waters. The goal is to develop remote sensing models for nutrients, total phosphorus and total nitrogen, in Lake Champlain. The remote sensing models were created using multivariate linear regression with the unique band combinations of Landsat Enhanced Thematic Mapper Plus (ETM+) imagery based on the empirical relationship with the field observations. The resulting models successfully showed nutrient distributions in the most eutrophic part of Lake Champlain, Missisquoi Bay, with reasonable adjusted coefficient of determination values (R2 = 0.81 and 0.75 for total phosphorus and total nitrogen, respectively). The results show the feasibility and the utility of satellite imagery to detect spatial distributions of lake water quality constituents, which can be used to better understand nutrient distributions in Lake Champlain. This approach can be applicable to other lakes experiencing eutrophication assisting decision making when implementing Best Management Practices and other mitigation techniques to lakes.</description><subject>Assessments</subject><subject>Eutrophic lakes</subject><subject>Eutrophication</subject><subject>Lakes</subject><subject>Lakes - analysis</subject><subject>Monitoring</subject><subject>New York</subject><subject>Nitrogen - analysis</subject><subject>Nutrients</subject><subject>Phosphorus</subject><subject>Phosphorus - analysis</subject><subject>Remote sensing</subject><subject>Remote Sensing Technology</subject><subject>Satellite imagery</subject><subject>Vermont</subject><subject>Water quality</subject><subject>卫星遥感技术</subject><subject>多元线性回归</subject><subject>最佳管理</subject><subject>水体富营养化</subject><subject>湖泊富营养化</subject><subject>营养分布</subject><subject>评估</subject><subject>遥感模型</subject><issn>1001-0742</issn><issn>1878-7320</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkU9v1DAQxS0Eon8_ABcUceKSdMaxnVicqhUUpJV6oWfLcSatl02yzSRIfHsc7dIjcJpn-c3zk39CvEMoENDc7IodcSEBVQGmALSvxDnWVZ1XpYTXSQNgDpWSZ-KCeQcASoN-K86kRlvWJZ6Lh1tmYu5pmLOxy4ZlnuKq28hJNcscx4GzOGRb_4OyzZPvD3ufjgvH4TFjP9N-H2fKJurHNJiG9eJKvOn8nun6NC_Fw5fP3zdf8-393bfN7TYPGs2c287rzqhaqVqWVHVYKbS11Y1tdNnVbRMCKd-azmCHLVUebJAYQl1CsE1blpfi4zH3MI3PC_Hs-sghVfIDjQs7NAagAonwH1aVjKAB_23VJgVqlGsBPFrDNDJP1LnDFHs__XIIbmXkdi4xcisjB8YlRmnn_Sl-aXpqXzb-QEmGT0cDpa_7GWlyHBKUQG2cKMyuHeNf4z-cKj2Nw-NzovHygjFSWWllXf4GZbKtIA</recordid><startdate>20140901</startdate><enddate>20140901</enddate><creator>Isenstein, Elizabeth M.</creator><creator>Park, Mi-Hyun</creator><general>Elsevier B.V</general><scope>2RA</scope><scope>92L</scope><scope>CQIGP</scope><scope>W92</scope><scope>~WA</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7QH</scope><scope>7ST</scope><scope>7TG</scope><scope>7TV</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H97</scope><scope>KL.</scope><scope>L.G</scope><scope>SOI</scope><scope>7SU</scope><scope>8FD</scope><scope>FR3</scope><scope>H8D</scope><scope>KR7</scope><scope>L7M</scope></search><sort><creationdate>20140901</creationdate><title>Assessment of nutrient distributions in Lake Champlain using satellite remote sensing</title><author>Isenstein, Elizabeth M. ; 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Proper monitoring and modeling are important to effectively manage eutrophication in lake waters. The goal is to develop remote sensing models for nutrients, total phosphorus and total nitrogen, in Lake Champlain. The remote sensing models were created using multivariate linear regression with the unique band combinations of Landsat Enhanced Thematic Mapper Plus (ETM+) imagery based on the empirical relationship with the field observations. The resulting models successfully showed nutrient distributions in the most eutrophic part of Lake Champlain, Missisquoi Bay, with reasonable adjusted coefficient of determination values (R2 = 0.81 and 0.75 for total phosphorus and total nitrogen, respectively). The results show the feasibility and the utility of satellite imagery to detect spatial distributions of lake water quality constituents, which can be used to better understand nutrient distributions in Lake Champlain. 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subjects | Assessments Eutrophic lakes Eutrophication Lakes Lakes - analysis Monitoring New York Nitrogen - analysis Nutrients Phosphorus Phosphorus - analysis Remote sensing Remote Sensing Technology Satellite imagery Vermont Water quality 卫星遥感技术 多元线性回归 最佳管理 水体富营养化 湖泊富营养化 营养分布 评估 遥感模型 |
title | Assessment of nutrient distributions in Lake Champlain using satellite remote sensing |
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