Identification of extent and drivers of urbanisation in Ireland: A remote sensing-based approach

Population growth in conjunction with rapid urbanization and industrialization has put immense pressure on global land use and land cover (LULC) patterns, and subsequently, adversely affect the water quantity and quality of associated water resources. The involved rate of change, spatio-temporal distribution of altered LULC classes, and the corresponding trend of LULC classes are quite challenging to monitor by using the conventional field survey-based approach. This study aims to analyse the changes in urbanization extent over Ireland during the past two decades, i.e., 2001-2021 using remotely sensed imageries. In addition, the extent of urbanization and its association with population growth is studied in detail over 43 spatially distributed study catchments of Ireland. One advantage of using remotely sensed LANDSAT observations include high-resolution spatial data available at a high temporal scale and also that the imagery is available for such long period covering the entire study period. The urbanization mapping is confined to two meteorological seasons, viz., summer and winter of every year analyzed. To aid more reliability in the outcomes of this study, the ACOLITE-based atmospheric correction algorithm has been adopted and the imageries were pre-processed before performing the image classification. The urbanisation trend over the period 2001-2021 revealed that the urban area expansion across the chosen catchments has happened at a rate of 0.13 to 1.14 km²/yr with the highest urban expansion rate is confined to the Dublin region of Ireland during the summer season. Furthermore, a correlation-based approach has been extended to study the drivers of increased urbanization in Ireland. The outcome of the correlation analysis revealed that population growth is the major driver behind increased urbanization and does affect the water resource quality adversely. The developed approach could be well replicated at any global catchment/regional-scale applications to generate essential database and analyse its impact on the water resources of the region of interest.