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Long-term trend and correlation between vegetation greenness and climate variables in Asia based on satellite data

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dc.contributor.authorLamchin, Munkhnasan-
dc.contributor.authorLee, Woo-Kyun-
dc.contributor.authorJeon, Seong Woo-
dc.contributor.authorWang, SonamWangyel-
dc.contributor.authorLim, Chul Hee-
dc.contributor.authorSong, Cholho-
dc.contributor.authorSung, Minjun-
dc.date.accessioned2021-09-02T13:45:30Z-
dc.date.available2021-09-02T13:45:30Z-
dc.date.created2021-06-16-
dc.date.issued2018-03-15-
dc.identifier.issn0048-9697-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/76717-
dc.description.abstractSatellite data has been used to ascertain trends and correlations between climate change and vegetation greenness in Asia. Our study utilized 33-year (1982-2014) AVHRR-GIMMS (Advanced Very High Resolution Radiometer - Global Inventory Modelling and Mapping Studies) NDVI3g and CRU TS (Climatic Research Unit Time Series) climate variable (temperature, rainfall, and potential evapotranspiration) time series. First, we estimated the overall trends for vegetation greenness, climate variables and analyzed trends during summer (April to October), winter (November to March), and the entire year. Second, we carried out correlation and regression analyses to detect correlations between vegetation greenness and climate variables. Our study revealed an increasing trend (0.05 to 0.28) in temperature in northeastern India (bordering Bhutan), Southeast Bhutan, Yunnan Province of China, Northern Myanmar, Central Cambodia, northern Laos, southern Vietnam, eastern Iran, southern Afghanistan, and southern Pakistan. However, a decreasing trend in temperature (0.00 to -0.04) was noted for specific areas in southern Asia including Central Myanmar and northwestern Thailand and the Guangxi, Southern Gansu, and Shandong provinces of China. The results also indicated an increasing trend for evapotranspiration and air temperature accompanied by a decreasing trend for vegetation greenness and rainfall. The temperature was found to be the main driver of the changing vegetation greenness in Kazakhstan, northern Mongolia, Northeast and Central China, North Korea, South Korea, and northern Japan, showing an indirect relationship (R= 0.84-0.96). (c) 2017 Elsevier B.V. All rights reserved.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherELSEVIER SCIENCE BV-
dc.subjectTEMPERATURE TRENDS-
dc.subjectAIR-TEMPERATURE-
dc.subjectPRECIPITATION-
dc.subjectNDVI-
dc.subjectRESPONSES-
dc.subjectGROWTH-
dc.subjectCHINA-
dc.subjectCONSEQUENCES-
dc.subjectVARIABILITY-
dc.subjectGROUNDWATER-
dc.titleLong-term trend and correlation between vegetation greenness and climate variables in Asia based on satellite data-
dc.typeArticle-
dc.contributor.affiliatedAuthorLee, Woo-Kyun-
dc.contributor.affiliatedAuthorJeon, Seong Woo-
dc.identifier.doi10.1016/j.scitotenv.2017.09.145-
dc.identifier.scopusid2-s2.0-85033666926-
dc.identifier.wosid000424130500114-
dc.identifier.bibliographicCitationSCIENCE OF THE TOTAL ENVIRONMENT, v.618, pp.1089 - 1095-
dc.relation.isPartOfSCIENCE OF THE TOTAL ENVIRONMENT-
dc.citation.titleSCIENCE OF THE TOTAL ENVIRONMENT-
dc.citation.volume618-
dc.citation.startPage1089-
dc.citation.endPage1095-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaEnvironmental Sciences & Ecology-
dc.relation.journalWebOfScienceCategoryEnvironmental Sciences-
dc.subject.keywordPlusTEMPERATURE TRENDS-
dc.subject.keywordPlusAIR-TEMPERATURE-
dc.subject.keywordPlusPRECIPITATION-
dc.subject.keywordPlusNDVI-
dc.subject.keywordPlusRESPONSES-
dc.subject.keywordPlusGROWTH-
dc.subject.keywordPlusCHINA-
dc.subject.keywordPlusCONSEQUENCES-
dc.subject.keywordPlusVARIABILITY-
dc.subject.keywordPlusGROUNDWATER-
dc.subject.keywordAuthorVegetation greenness-
dc.subject.keywordAuthorPrecipitation-
dc.subject.keywordAuthorEvaporation-
dc.subject.keywordAuthorTemperature-
dc.subject.keywordAuthorCorrelation-
dc.subject.keywordAuthorTrend-
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