https://doi.org/10.1140/epjp/s13360-025-06371-4
Regular Article
Trend analysis of climatic parameters using geographical information systems: a case study of Sivas Province (1982–2021)
1
Department of Environmental Engineering, Faculty of Engineering, Sivas Cumhuriyet University, 58140, Sivas, Turkey
2
Department of Surveying (Geomatics) Engineering, Faculty of Engineering, Sivas Cumhuriyet University, 58140, Sivas, Turkey
Received:
6
November
2024
Accepted:
27
April
2025
Published online:
20
May
2025
Climate change has become a significant concern globally, and understanding regional patterns and trends is crucial for effective mitigation and adaptation strategies. This article presents a comprehensive Mann–Kendall trend and Sen’s slope estimator test conducted to examine the long-term trends in surface temperature, 2-m above temperature, and precipitation in Sivas Province, Turkey. Utilizing a dataset spanning several decades, Mann–Kendall and Sen’s slope estimator tests were applied to assess the presence of statistically significant trends in the selected climatic parameters. Additionally, remote sensing (RS) and geographical information systems (GIS) were incorporated as supplementary and validation data sources to enhance the accuracy and reliability of our analysis. Furthermore, GIS techniques facilitated the integration of diverse geospatial data layers, including land cover, offering valuable insights into the complex interactions between climate variables and the environment. The combined analysis of MK trends, SS test, and RS/GIS data yielded a robust understanding of the changing climate dynamics in Sivas Province. Our findings not only contribute to the growing body of knowledge on regional climate change but also underscore the importance of utilizing advanced technologies like RS and GIS for accurate trend analysis and informed decision making. This study highlights the potential of these supplementary data sources in enhancing our understanding of climate trends and supports the development of climate change adaptation strategies.
© The Author(s) 2025
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