Publication:
Creating Bioclimatic Maps Using Spatial Interpolation Techniques in Northern Turkey

dc.authorscopusid35589838100
dc.authorscopusid55976027400
dc.authorscopusid56586294100
dc.contributor.authorGüler, M.
dc.contributor.authorCemek, B.
dc.contributor.authorArslan, H.
dc.date.accessioned2020-06-21T13:51:14Z
dc.date.available2020-06-21T13:51:14Z
dc.date.issued2015
dc.departmentOndokuz Mayıs Üniversitesien_US
dc.department-temp[Güler] Mustafa, Middle Black Sea Development Agency, Samsun, Turkey; [Cemek] Bilal, Department of Agricultural Engineering, Ondokuz Mayis Üniversitesi, Samsun, Turkey; [Arslan] Hakan, Department of Agricultural Engineering, Ondokuz Mayis Üniversitesi, Samsun, Turkeyen_US
dc.description.abstractThis study used Geographical Information System (GIS) and spatial interpolation techniques to calculate the spatial distribution of various bioclimatic indices for Northern Turkey. The results varied among the indices. Ordinary Kriging (OK) was the most appropriate method for producing bioclimatic maps of summer drought stress (SDS), winter cold stress (WCS), Rivas-Martínez om-brothermic (O<inf>i</inf>) and continentality (C<inf>i</inf>) in the study area. On the other hand, Simple Kriging (SK) was the best fitted interpolation method for De Martonne Aridity Index (I<inf>dm</inf>)-Thin Plate Spline (TPS) had the highest root mean square error (RMSE), whereas the lowest RMSE values were derived from Inverse Distance Weighting (IDW) and Spline with P=2. In general, the lowest RMSE values were obtained with N=8 and N=12. Spatial maps produced by the most appropriate methods showed different climatic conditions. Whereas SDS values were similar along the coast and then increased in line with movement towards the interior, WCS values were lower along the coastline, and then increased with movement inland.In terms of I<inf>dm</inf>, the study area was classified into 5 different regions, from semi-dry to very humid. Whereas the results for SDS, WCS and I<inf>dm</inf> were in harmony with one another, O<inf>i</inf>, showed the entire region to be hyperhumid, which is incompatible with the results of the other indexes as well as with the observable conditions in the region. C<inf>i</inf> indicated the region to be predominantly defined as oceanic. © by PSP.en_US
dc.identifier.endpage3544en_US
dc.identifier.issn1018-4619
dc.identifier.issue11en_US
dc.identifier.scopus2-s2.0-84958164617
dc.identifier.startpage3537en_US
dc.identifier.volume24en_US
dc.identifier.wosWOS:000367698400001
dc.language.isoenen_US
dc.publisherParlar Scientific Publications parlar@masell.comen_US
dc.relation.ispartofFresenius Environmental Bulletinen_US
dc.relation.journalFresenius Environmental Bulletinen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBioclimatic Indexen_US
dc.subjectGISen_US
dc.subjectInterpolationen_US
dc.subjectTurkeyen_US
dc.titleCreating Bioclimatic Maps Using Spatial Interpolation Techniques in Northern Turkeyen_US
dc.typeArticleen_US
dspace.entity.typePublication

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