{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,22]],"date-time":"2026-06-22T17:22:56Z","timestamp":1782148976019,"version":"3.54.5"},"reference-count":23,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2020,7,15]],"date-time":"2020-07-15T00:00:00Z","timestamp":1594771200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[2020,10,21]]},"abstract":"<jats:p>In recent years, with the rapid development of satellite technology, remote sensing inversion has been used as an important part of environmental monitoring. Remote sensing inversion has been prepared for large-scale water environment monitoring in the watershed that is difficult for the traditional water environment monitoring methods. This paper will discuss some shortcomings of traditional remote sensing inversion methods, and proposes a remote sensing inversion method based on convolutional neural network, which realizes large-scale remote sensing smart and automatic inversion monitoring of the water environment. The results show that the method is practical and effective, and can achieve high recognition accuracy for water blooms.<\/jats:p>","DOI":"10.3233\/jifs-189017","type":"journal-article","created":{"date-parts":[[2020,7,16]],"date-time":"2020-07-16T10:40:04Z","timestamp":1594896004000},"page":"5319-5327","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":17,"title":["Water remote sensing eutrophication inversion algorithm based on multilayer convolutional neural network"],"prefix":"10.1177","volume":"39","author":[{"given":"Feng","family":"Lei","sequence":"first","affiliation":[{"name":"College of Environment and Ecology, Chongqing University, Chongqing"},{"name":"Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Online Monitoring Center of Ecological and Environmental of the Three Gorges Project, Chongqing"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"You","family":"Yu","sequence":"additional","affiliation":[{"name":"College of Environment and Ecology, Chongqing University, Chongqing"},{"name":"Big Data Application Center of Ecological and Environment of Chongqing, Chongqing"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daijun","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Environment and Ecology, Chongqing University, Chongqing"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Feng","sequence":"additional","affiliation":[{"name":"College of Materials Science and Engineering, Chongqing University, Chongqing, Chongqing"},{"name":"Environmental Sciences Research Institute, Chongqing Collaborative Innovation Center of Big Data Application in Eco-Environmental Remote Sensing, Chongqing"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinsong","family":"Guo","sequence":"additional","affiliation":[{"name":"College of Environment and Ecology, Chongqing University, Chongqing"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yong","family":"Zhang","sequence":"additional","affiliation":[{"name":"Environmental Sciences Research Institute, Chongqing Collaborative Innovation Center of Big Data Application in Eco-Environmental Remote Sensing, Chongqing"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fang","family":"Fang","sequence":"additional","affiliation":[{"name":"College of Environment and Ecology, Chongqing University, Chongqing"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2020,7,15]]},"reference":[{"key":"e_1_3_1_2_2","article-title":"A Wireless Water Quality Monitoring System Based on LabVIEW and Web","author":"Sun Z.G","year":"2011","unstructured":"SunZ.G, LiC.G, ZhangZ.F, A Wireless Water Quality Monitoring System Based on LabVIEW and Web, International Conference on Applied Informatics and Communication, 2011.","journal-title":"International Conference on Applied Informatics and Communication"},{"key":"e_1_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.watres.2017.07.016"},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.envint.2016.03.023"},{"key":"e_1_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2016.06.239"},{"key":"e_1_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.54216\/JISIoT.010101"},{"key":"e_1_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.2166\/wst.2013.661"},{"key":"e_1_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1117\/12.210877"},{"key":"e_1_3_1_9_2","doi-asserted-by":"publisher","DOI":"10.54216\/JCIM.010102"},{"issue":"1","key":"e_1_3_1_10_2","first-page":"25","article-title":"Construction of smooth daily remote sensing time series data: a higher spatiotemporal resolution perspective","volume":"2","author":"Pan Z","year":"2017","unstructured":"PanZ, HuY, CaoB, Construction of smooth daily remote sensing time series data: a higher spatiotemporal resolution perspective, Standards 2(1) (2017), 25.","journal-title":"Standards"},{"key":"e_1_3_1_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0025-326X(99)00014-4"},{"key":"e_1_3_1_12_2","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1099-128X(199609)10:5\/6<697::AID-CEM453>3.0.CO;2-5"},{"key":"e_1_3_1_13_2","article-title":"Learning Deep CNN Denoiser Prior for Image Restoration","author":"Kai Z.","year":"2017","unstructured":"KaiZ., ZuoW., GuS., et al., Learning Deep CNN Denoiser Prior for Image Restoration, Pattern Recognition, 2017.","journal-title":"Pattern Recognition"},{"key":"e_1_3_1_14_2","doi-asserted-by":"publisher","DOI":"10.54216\/IJNS.010204"},{"issue":"5","key":"e_1_3_1_15_2","first-page":"813","article-title":"Small Object Detection in Optical Remote Sensing, mages via Modified Faster R-CNN","volume":"8","author":"Yun R.","year":"2018","unstructured":"YunR., ZhuC., XiaoS., Small Object Detection in Optical Remote Sensing, mages via Modified Faster R-CNN, Applied Sciences 2017 8(5) (2018)813.","journal-title":"Applied Sciences 2017"},{"key":"e_1_3_1_16_2","doi-asserted-by":"crossref","unstructured":"ShenT. ZhouT. LongG. et al. DiSAN: Directional Self-Attention Network for RNN\/CNN-Free Language Understanding 2017.","DOI":"10.1609\/aaai.v32i1.11941"},{"issue":"5","key":"e_1_3_1_17_2","first-page":"2811","article-title":"When Deep Learning Meets Metric Learning: Remote Sensing Image Scene Classification via Learning Discriminative CNNs","volume":"56","author":"Gong C.","year":"2018","unstructured":"GongC., YangC., YaoX., et al., When Deep Learning Meets Metric Learning: Remote Sensing Image Scene Classification via Learning Discriminative CNNs, Remote Sensing 56(5) (2018)2811\u20132821.","journal-title":"Remote Sensing"},{"key":"e_1_3_1_18_2","article-title":"Deep feature extraction and combination for remote sensing image classification based on pre-trained CNN models","author":"Chaib S.","year":"2017","unstructured":"ChaibS., YaoH., GuY., et al., Deep feature extraction and combination for remote sensing image classification based on pre-trained CNN models, Ninth International Conference on Digital Image Processing (ICDIP 2017).","journal-title":"Ninth International Conference on Digital Image Processing"},{"key":"e_1_3_1_19_2","first-page":"7361","article-title":"Sitcom-star-based clothing retrieval for video advertising: a deep learning framework","volume":"31","author":"Zhang H.","year":"2019","unstructured":"ZhangH., JiY., HuangW., et al., Sitcom-star-based clothing retrieval for video advertising: a deep learning framework, Applic 31 (2019)7361\u20137380.","journal-title":"Applic"},{"key":"e_1_3_1_20_2","article-title":"A Novel Algorithm for Edge Detection of Remote Sensing Image Based on CNN and PSO","author":"Wang J.","year":"2009","unstructured":"WangJ., YangC., SunC., A Novel Algorithm for Edge Detection of Remote Sensing Image Based on CNN and PSO, Signal Processing 2009.","journal-title":"Signal Processing"},{"key":"e_1_3_1_21_2","doi-asserted-by":"publisher","DOI":"10.1080\/01431161.2016.1275056"},{"key":"e_1_3_1_22_2","unstructured":"WaheedT. Artificial intelligence analysis of hyperspectral remote sensing data for management of water weed and nitrogen stresses in corn fields 2005."},{"key":"e_1_3_1_23_2","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2015.2472456"},{"key":"e_1_3_1_24_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijleo.2018.11.113"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/JIFS-189017","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.3233\/JIFS-189017","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/JIFS-189017","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:40:54Z","timestamp":1777455654000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.3233\/JIFS-189017"}},"subtitle":[],"editor":[{"given":"Andino","family":"Maseleno","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]},{"given":"Xiaohui","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]},{"given":"Valentina E.","family":"Balas","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2020,7,15]]},"references-count":23,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2020,10,21]]}},"alternative-id":["10.3233\/JIFS-189017"],"URL":"https:\/\/doi.org\/10.3233\/jifs-189017","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,7,15]]}}}