Akademik Veri Yönetim Sistemi
Journal of Environmental Science and Engineering Technology, cilt.13, ss.80-92, 2025 (Hakemli Dergi)
This study aims to quantitatively assess the effects of
socioeconomic changes experienced during the COVID-19 pandemic on urban sprawl
dynamics. The research was conducted in the Döşemealtı District of Antalya
Province, located in the Mediterranean Region of Türkiye, which stands out with
its semi-rural urban characteristics and is part of one of the country’s most
important tourism destinations. Settlement dynamics, expansion patterns of
built-up areas, and their spatiotemporal changes in the study area were
analyzed for the pre- and post-pandemic periods using artificial
intelligence–supported land use/land cover (LULC) data. In this context, the
Built-up class filtered from the ArcGIS Living Atlas LULC dataset was compared
between 2017 (pre-pandemic) and 2023 (post-pandemic), and thematic maps of
built-up surfaces were produced for each reference year. These maps were
analyzed using geographic information system (GIS) technologies to evaluate the
magnitude, spatial direction, and temporal trends of changes in impervious
surfaces.The findings indicate that the spatial restructuring tendencies
triggered by the pandemic reached a remarkable scale in the Döşemealtı
District, with an increase in construction clusters within rural belts and a
rapid conversion of vacant lands into built-up areas. Impervious surfaces,
which covered 4146,94 km2 in 2017, increased to 4412,74 km2 in 2020, reached
5426,62 km2 in 2023. Accordingly, a short-term increase of 30,9% in impervious
surfaces was observed, largely attributable to the pandemic period. By
providing a rapid, low-cost, and objective analytical framework, this study
demonstrates strong potential for application in remote sensing–based urban
planning and spatial change monitoring during crisis periods. The results are
expected to serve as an important data source for regional and local
authorities in defining urban growth strategies, supporting sustainable
planning decisions, and evaluating spatial transformations in future disaster
or crisis scenarios