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Evaluating Ecological Stability and Vegetation Dynamics in Bavaria’s Protected Areas Using Google Earth Engine-Derived Remote Sensing and Environmental Modeling

Author

Listed:
  • Heba Bedair

    (Quantitative Landscape Ecology Group, Department of Natural and Environmental Sciences, University of Kaiserslautern-Landau (RPTU), 76829 Landau der Pfalz, Germany
    Botany and Microbiology Department, Faculty of Science, Tanta University, Tanta 31527, Egypt)

  • Youssef M. Youssef

    (Geological and Geophysical Engineering Department, Faculty of Petroleum and Mining Engineering, Suez University, Suez 43518, Egypt)

  • Wafa Saleh Alkhuraiji

    (Department of Geography and Environmental Sustainability, College of Humanities and Social Sciences, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia)

  • Mohamed A. Atalla

    (Department of Natural Studies, General Organization for Physical Planning (GOPP), Ministries District, New Administrative Capital, Cairo 85863, Egypt
    Department of GIS and Environment, Enshaat Al-Sayer General Trading and Contracting Company, Floors 14 & 19, Panasonic Tower, Safat, P.O. Box 126, Kuwait City 13002, Kuwait)

Abstract

Understanding land-use and land-cover (LULC) dynamics within protected areas (PAs) is fundamental for assessing conservation effectiveness and ecosystem resilience under increasing anthropogenic and climatic pressures. This study examines the spatio-temporal evolution of LULC across Bavaria’s protected areas between 2000 and 2023 by integrating categorical land-cover data, satellite-derived vegetation indices, and environmental drivers. Annual LULC changes were first quantified using MODIS MCD12Q1 land-cover classifications to evaluate class persistence, transitions, and area trajectories and were subsequently interpreted alongside 16-day MODIS NDVI and SAVI composites to assess associated vegetation greening and browning trends. Ecological stability was characterized by using class-level persistence indicators, coefficients of variation (CVs), and linear trend slopes. The results reveal a marked greening signal after 2010, coinciding with pronounced land-cover transitions, including a decline in evergreen needleleaf forests (−480.6 km 2 ; −32.2%) and substantial expansion of deciduous broadleaf forests (+390.8 km 2 ; +106.1%) and grasslands (+275.8 km 2 ; +28.4%), while wetlands experienced a severe contraction (−203.4 km 2 ; −73.7%), indicating heightened hydrological sensitivity within protected ecosystems. Correlation analysis further indicates that anthropogenic pressure, quantified using the human footprint index, remains a dominant driver of change in croplands and urban areas, even within legally protected boundaries. Overall, this study demonstrates that vegetation trends, land-cover transitions, climatic exposure, and human pressure jointly shape ecological stability in protected areas, highlighting the value of an integrated indicator-based framework.

Suggested Citation

  • Heba Bedair & Youssef M. Youssef & Wafa Saleh Alkhuraiji & Mohamed A. Atalla, 2026. "Evaluating Ecological Stability and Vegetation Dynamics in Bavaria’s Protected Areas Using Google Earth Engine-Derived Remote Sensing and Environmental Modeling," Sustainability, MDPI, vol. 18(6), pages 1-27, March.
  • Handle: RePEc:gam:jsusta:v:18:y:2026:i:6:p:2886-:d:1895208
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