Evaluation of LULC Use Classification for the Municipality of Deva, Hunedoara County, Romania Using Sentinel 2A Multispectral Satellite Imagery—A Comparative Study of GIS Software Analysis and Accuracy Assessment
Source abstract
Abstract
The degree of urbanization and the uncontrolled expansion of the built environment play a defining role in shaping contemporary society, contributing significantly to abrupt temperature fluctuations and a declining quality of life. This study aims to analyze land use and land cover (LULC) patterns in the municipality of Deva, located in the central part of Hunedoara County, Romania (45°52′ N, 22°54′ E). The analysis covers the period from March 2022 to March 2023 and is based on open-source datasets. Supervised classification of LULC was performed using two GIS software platforms: ArcGIS Pro and QGIS. Sentinel-2A satellite imagery, with spatial resolutions of 10 m, 20 m, and 60 m, was processed using two different classification algorithms—the Minimum Distance classifier (via the Semi-Automatic Classification Plugin in QGIS) and the k-Nearest Neighbor (k-NN) algorithm in ArcGIS Pro. The comparative accuracy assessment indicated that the k-NN classifier in ArcGIS Pro performed better, achieving an overall accuracy of 89.7% and a Kappa coefficient of 0.86, while the Minimum Distance classifier in QGIS obtained an overall accuracy of 81.2% and a Kappa coefficient of 0.78. The outputs of both classification workflows were compared, and an accuracy assessment was conducted during the post-processing stage. The best results were obtained using the k-NN algorithm. The classification maps generated in this study can serve as a valuable foundation for local authorities to monitor environmental changes and support urban planning initiatives in Deva.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Land Use and Ecosystem Services · Urban Heat Island Mitigation · Remote-Sensing Image Classification
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Doctoral School, Technical University of Civil Engineering Bucharest, 020396 Bucharest, Romania
Faculty of Geodesy, Technical University of Civil Engineering Bucharest, 020396 Bucharest, Romania
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