Application of the Categorical Change Detection Technique in Investigating the Trends of Urbanization in Wales, Southwest Britain
This study, employing remote sensing and Geographic Information System (GIS) techniques, was carried out using the categorical change detection technique to analyze land use and land cover (LULC) dynamics in Wales, United Kingdom, from the year 1992 to 2019 with a view to understanding the trend of urbanization in the area. Using data from the Global Land Cover 1992 to 2019 image service accessible via ArcGIS Pro 3.0 Living Atlas, with a spatial resolution of 300 meters, the study revealed that grassland, being the predominant land cover in the area, decreased in coverage from 73.98% in 1992 to 72.16% in 2019, cropland decreased from 17.91% to 17.48%, all categories of forest increased from 5.30% to 5.93%, water bodies decreased from 1% to 0.7%, while bare areas remained constant at 0.2% in both years. Results also revealed a significant expansion of urban areas, growing from 1.81% to 3.48% of the land area. The mean percentage change across all counties is approximately 97.29%, indicating substantial urban expansion, while the median percentage change is 68.88%. Counties in South Wales experienced substantial urbanization influenced by coastal proximity, while Western and Northern regions showed significant percentage changes in urban areas but had smaller land area expansions. This research provides insights into the evolving landscape of Wales vital for understanding trends in land use, environmental changes, and urban expansion over this period and contributes valuable insights for sustainable urban planning, environmental preservation, and possible ecological impacts within the study area.
Authors
- C. C. Agoha (ORCID: https://orcid.org/0000-0002-9513-1358)
- Nwokeabia Charity Nkiru
- Eluwa Ndidiamaka Nchedo
- Egereonu Chinwendu
- Njoku Obiageli
- Offodile Paschal
- Chilakpu Caroline
- Ahaji Kelechi
Institutions
- Federal University of Technology Owerri (NG)
- Nnamdi Azikiwe University (NG)
- Federal Polytechnic Nekede (NG)
- Sheffield Hallam University (GB)
- Michael Okpara University of Agriculture (NG)
Publication Details
- Journal
- American Journal of Remote Sensing
- Published
- 2025-05-29
- DOI
- https://doi.org/10.11648/j.ajrs.20251301.13
- Primary Topic
- Land Use and Ecosystem Services
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Sheffield Hallam University