07-17, 17:00–17:30 (Europe/Sarajevo), PA01 (Quarticle)
Urban Change Detection in Tirana, Albania (2000-2025) Using Remote Sensing and Open Geospatial Data
Tirana, the capital of Albania, has experienced rapid and often unregulated urbanization since the early 2000s, resulting in profound changes in land use, environmental conditions, and urban structure. This study examines the spatial and temporal dynamics of urban change in Tirana over the last 25 years by leveraging multi-temporal satellite imagery and open geospatial data to map and assess land cover transitions. The analysis utilizes freely available Landsat and Sentinel-2 satellite images acquired at multiple intervals, aiming for regular coverage throughout the period. Open data from the Urban Atlas is used to complement the classification and support a more detailed evaluation of land cover change. Change detection techniques are applied using key spectral indices—such as the Normalized Difference Vegetation Index (NDVI) to monitor vegetation loss and the Normalized Difference Built-up Index (NDBI) to identify the expansion of built-up areas. Urban change is assessed and modeled using the MOLUSCE plugin in QGIS, which enables both quantification and prediction of land use transformations based on historical trends and infrastructure development. The results indicate widespread urban expansion, considerable loss of vegetation, and increasing land consumption for built-up areas. These findings provide important insights for urban planning and sustainable development in Tirana, while also demonstrating the value of open geospatial data and free software tools for monitoring urban change in rapidly transforming cities.
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Select at least one general theme that best defines your proposal – I make my conference contribution available under the CC BY 4.0 license. The conference contribution comprises the abstract, the text contribution for the conference proceedings, the presentation materials as well as the video recording and live transmission of the presentation – yes
Skilled in advanced spatial data analysis, management, and visualization using GIS platforms. Proficient in Python for geospatial workflows and solving complex real-world problems.
Research interest focuses on the application of GIS in urban planning and spatial modeling, with an emphasis on integrating innovative technologies and open-source development practices.