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Article detail · 2024

Predicting climate-based changes of landscape structure for Turkiye via global climate change scenarios: a case study in Bartin river basin with time series analysis for 2050

Natural Hazards

YÖKSİS OpenAlex ISSN 0921-030X DOI 10.1007/s11069-024-06706-x Citations 8 Open access · hybrid SJR Q1 JCR Q1

10.1007/s11069-024-06706-x

YÖKSİS YÖKSİS article record

OpenAlex OpenAlex enrichment (abstract, citations, topics)

Abstract

OpenAlex record

English (OpenAlex)

Abstract This study was designed to reveal the possible effects of climate change on the landscape structure of the Bartın Stream Basin. Remote sensing (RS) and Geographic Information Systems (GIS) tools and statistical methods were employed throughout the study. Landsat satellite images, which are 30 m × 30 m resolution images produced by Landsat 4–5, Landsat 7, and Landsat 8-Oli satellites, were used. In addition, 42 variables were produced, including 19 bioclimatic variables, plant index data from satellite images, and environmental variables. The effect of the produced variables on land use-land cover (LULC) was investigated. Then, the expected situation in 2050 according to the RCP climate change scenarios was estimated using the R Studio software with time series analysis. The data for 2050 were modeled and mapped using the Maximum Entropy method. As a result, it was revealed that LULC changes within the basin would be in the form of artificialization and increased fragmentation, that bare lands and residential areas would increase, and that agricultural areas and forest areas would decrease by approximately 50%. Planning should be made in order to reduce the breakdown of landscape resistance by predicting the adverse events to be experienced due to climate change in the future. It was concluded that agriculture, which was determined as the development strategy of the region in the current Environmental Plan (EP) of the basin, would not be possible due to the approximately 50% loss in agricultural areas. This study revealed that the effects of climate change, which is the biggest threat of the age, could be revealed with statistical models. Graphical Abstract

OpenAlex enrichment

Topics

  • Species Distribution and Climate Change
  • Remote Sensing in Agriculture
  • Plant Water Relations and Carbon Dynamics

Type: article Species Distribution and Climate Change

Index information

WoS (JCR) and Scopus (SJR) quartiles by ISSN and publication year. · 2024

Scopus (SJR) / WoS (JCR)

Natural Hazards

Scopus (SJR) Q1 0,942 Year 2024
WoS (JCR) Q1 JIF 3,7 Year 2024

Universities

  • ISPARTA UYGULAMALI BİLİMLER ÜNİVERSİTESİ

Authors

  1. MERVE KALAYCI KADAK
  2. SEVGİ ÖZTÜRK
  3. AHMET MERT ISPARTA UYGULAMALI BİLİMLER ÜNİVERSİTESİ