SN Applied Sciences · 2023 · 10 citations · 69 references
Natural ResourcesGeographyGeoinformaticsClimatologyLandscape Change DetectionRemote SensingChange DetectionLand Cover Change DetectionLand Cover MappingLand UseLand Use Change DetectionRemote Sensing Change DetectionChange Detection From Remote SensingLand Change DetectionLand Surface Temperature MappingLand Use Change AnalysisSpatial Temperature VariationStudy Area DelineationSupervised ClassificationSurface Temperature
Abstract The current study determined the changes in Land Use/Land Change (LU/LC) and variation in land surface temperature (LST) in the Green Belt (Nasirabad district) area of Balochistan, Pakistan. To achieve this, we used GIS software (ArcMap 10.7.1) to analyze remote sensing data acquired from Landsat imagery taken in 1993, 2003, 2013, and 2023. A supervised classification technique using the maximum likelihood algorithm (MLC) was applied to generate a ground-truth LU/LC classification. Based on our findings, almost 415.28 km 2 (− 12.89%) of formerly undeveloped land has been transformed into urban neighborhoods and green spaces during the last three decades. Between 1993 and 2023, the study area gained 288.29 km 2 (8.94%) of vegetation and 136.10 km 2 (4.22%) of settled land. Minimum, maximum, and average LST changes were recorded as 7.50, − 5.06, and 1.22 °C for the whole thirty years. Overall, the analysis data showed that an increase in human settlements in the area investigated led to a rise in mean LST (1.22 °C). Finally, GIS and RS may be used together to track land usage over time, a crucial piece of data for eco-friendly planning. While the LU/LC and LST provide valuable insights into the rational and optimal use of land resources, the implications of policy remain constrained.
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M. Tauhid Ur Rahman, Faheemah Tabassum, Md Rasheduzzaman et al. · Environmental Monitoring and Assessment · 2017 · 252 citations
Hamere Yohannes, Teshome Soromessa, Mekuria Argaw et al. · Journal of Environmental Management · 2020 · 228 citations