http://rdf.ncbi.nlm.nih.gov/pubchem/reference/6060896

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contentType Journal Article
issn 1424-8220
issueIdentifier 19
pageRange 4247-
publicationName Sensors (Basel, Switzerland)
startingPage 4247
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bibliographicCitation Luo S, Song C, Liu K, Ke L, Ma R. An Effective Low-Cost Remote Sensing Approach to Reconstruct the Long-Term and Dense Time Series of Area and Storage Variations for Large Lakes. Sensors (Basel). 2019 Sep 30;19(19). PMID: 31574940; PMCID: PMC6806627.
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date 2019-09-30^^<http://www.w3.org/2001/XMLSchema#date>
identifier https://pubmed.ncbi.nlm.nih.gov/PMC6806627
https://doi.org/10.3390/s19194247
https://pubmed.ncbi.nlm.nih.gov/31574940
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http://rdf.ncbi.nlm.nih.gov/pubchem/journal/31883
language English
source https://www.crossref.org/
https://pubmed.ncbi.nlm.nih.gov/
title An Effective Low-Cost Remote Sensing Approach to Reconstruct the Long-Term and Dense Time Series of Area and Storage Variations for Large Lakes

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