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Zastosuj identyfikator do podlinkowania lub zacytowania tej pozycji: http://hdl.handle.net/20.500.12128/22946
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dc.contributor.authorForoumandi, Ehsan-
dc.contributor.authorNourani, Vahid-
dc.contributor.authorDąbrowska, Dominika-
dc.contributor.authorKantoush, Sameh Ahmed-
dc.date.accessioned2022-03-25T12:24:09Z-
dc.date.available2022-03-25T12:24:09Z-
dc.date.issued2022-
dc.identifier.citation"Land", Vol. 11, iss. 1, 2022, art. nr 115, s. 1-28pl_PL
dc.identifier.issn2073-445X-
dc.identifier.issn2073-445X-
dc.identifier.urihttp://hdl.handle.net/20.500.12128/22946-
dc.description.abstractInvestigation of vegetation cover is crucial to the study of terrestrial ecological environments as it has a close relationship with hydroclimatological variables and plays a dominant role in preserving the characteristics of a region. In Iran, the current study selected the watersheds of two rivers, Nazloo-Chay and Aji-Chay, to systematically investigate the implications and causes of vegetation cover variations under changing environments. These two rivers are among the essential inflows to Lake Urmia, the second largest saline lake on Earth, and are located on the west and east sides of the lake, respectively. There has been a debate between the people living in the rivers’ watersheds about who is responsible for the decline in the level of Lake Urmia—does responsibility fall with those on the east side or with those on the west side? In this study, the normalized difference vegetation index (NDVI) was used as a remotely sensed index to study spatial–temporal pattern changes in vegetation. Moreover, the temperature, precipitation, and streamflow time series were gathered using ground measurements to explore the causes and implications of changing vegetation cover. Discrete wavelet transform was applied to separate the different components of the time series. The Mann–Kendall (MK) test was applied to the time series on monthly, seasonal, and annual time scales. The connections and relationship between the NDVI time series and temperature, pre-cipitation, and streamflow time series and any underlying causes were investigated using wavelet transform coherence (WTC). Land use maps were generated for different years using a support vector machine (SVM) in the final stage. The results indicated that the most dominant monthly, seasonal, and annual hydrological periodicities across the watersheds are 8 months, 6 months, and 2 years, respectively. The increasing vegetation cover during stable hydro-environmental periods revealed unusual conditions in the Aji-Chay watershed and reflected agricultural expansion. The WTC graphs indicated sudden changes in mutual periodicities and time-lags with different patterns between variables, which indicates the increasing anthropogenic activities in both watersheds. However, this was more dominant in the Aji-Chay watershed. The land use maps and investigation of the averaged NDVI maps also denoted that the areas of cultivated land have increased by 30% in the Aji-Chay watershed, and crop types have been changed to the crops with a higher demand for water in both watersheds.pl_PL
dc.language.isoenpl_PL
dc.rightsUznanie autorstwa 3.0 Polska*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/pl/*
dc.subjectvegetation coverpl_PL
dc.subjectremote sensingpl_PL
dc.subjectwavelet transformpl_PL
dc.subjectsupport vector machine (SVM)pl_PL
dc.subjectland use mappl_PL
dc.subjectLake Urmiapl_PL
dc.subjectAji-Chaypl_PL
dc.subjectNazloo-Chaypl_PL
dc.titleLinking Spatial-Temporal Changes of Vegetation Cover with Hydroclimatological Variables in Terrestrial Environments with a Focus on the Lake Urmia Basinpl_PL
dc.typeinfo:eu-repo/semantics/articlepl_PL
dc.identifier.doi10.3390/land11010115-
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Uznanie Autorstwa 3.0 Polska Creative Commons Creative Commons