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Spatiotemporal dynamics of ecosystem service values under land use and land cover change in selected districts Hadiya zone, Central Ethiopian Region

2026Open accessJimma University

Abstract

Land use and land cover (LULC) change is the main factor for ecosystem service degradation. This study aimed to evaluate spatiotemporal dynamics of ecosystem service values in response to LULC change in selected districts of Hadiya zone. Landsat TM (1993), ETM+ (2003 and 2013), and OLI/TIRS (2023) imagery were processed and classified using ArcGIS and ERDAS Imagine software to analyze LULC change over three decades. Supervised classification techniques with maximum likelihood algorithms were applied to ensure accuracy, and temporal comparisons were conducted to detect spatial and environmental dynamics across the study area. The results showed that between 1993 and 2023, cultivated land increased by 484,295.6 ha, whereas water bodies experienced a sharp decline of 74,146.2 ha, reflecting the impacts of agricultural expansion and water resource depletion on ecosystem services. Forest land was declined over the study period. Its Ecosystem Service Values (ESV) fell by more than half during the first decade, dropping from $114.28 million in 1993 to $46.32 million in 2003. This shrinking trend persisted over the subsequent twenty years, ultimately bottoming out at just $22.57 million by 2023. In addition, Water Body and forest land exhibited the most dramatic percentage decline with a reduction of 92.30% and 80.25% from 1993 to 2023 respectively. The decline in ESV reflects degradation of ecosystem integrity especially forests and water bodies driven primarily by anthropogenic pressures. The results recommend prioritizing forest and water-body conservation within sustainable natural resource management to enhance ESV. Future research should assess woody species conservation options and the constraints posed by traditional land management systems.

Research topics

  • Land Use and Ecosystem Services
  • Conservation, Biodiversity, and Resource Management
  • Remote Sensing in Agriculture

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DOI: 10.1007/s43621-026-04161-1

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