Evaluating Ecological Stability and Vegetation Dynamics in Bavaria’s Protected Areas Using Google Earth Engine-Derived Remote Sensing and Environmental Modeling
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 km2; −32.2%) and substantial expansion of deciduous broadleaf forests (+390.8 km2; +106.1%) and grasslands (+275.8 km2; +28.4%), while wetlands experienced a severe contraction (−203.4 km2; −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.
Authors
- Heba Bedair (ORCID: https://orcid.org/0000-0001-9824-2443)
- Youssef M. Youssef (ORCID: https://orcid.org/0000-0001-5939-732X)
- Wafa Saleh Alkhuraiji
- Mohamed A. Atalla
Institutions
- Princess Nourah bint Abdulrahman University (SA)
- Suez University (EG)
- Tanta University (EG)
- University of Koblenz and Landau (DE)
- Kuwait University (KW)
- Central Laboratory For Agricultural Expert Systems (EG)
Publication Details
- Journal
- Sustainability
- Published
- 2026-03-15
- DOI
- https://doi.org/10.3390/su18062886
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 0.00