Investigation of changes in land use/land cover using principal component analysis and supervised classification from operational land imager satellite data: a case study of under developed regions, Pakistan

• DOI: 10.1007/s43621-024-00263-w
• Publication Date: 2024-04-22T13:01:31Z
• Authors: Ali Raza; Neyha Rubab Syed; Romana Fahmeed; Siham Acharki; Taghreed Hamdi Al...; Sajjad Hussain; Muhammad Zubair; Syeda Mishal Zahra; Abu Reza Md. Towf...; Hussein Almohamad; Hazem Ghassan Abdo
• Keywords: Land Cover

Abstract Monitoring and understanding Land Use/Land Cover (LU/LC) is critical for sustainable development, as it can impact various environmental, social, economic systems. For example, deforestation land degradation lead to soil erosion, loss of biodiversity, greenhouse gas emissions, affecting the quality soil, air, water resources. The present research examined changes in within underdeveloped regions Balochistan Sindh provinces, which are situated Pakistan. In order monitor temporal variations LU/LC, we employed Geographic Information System (GIS) technique, conduct an analysis satellite imagery obtained from Landsat 8 Operational Imager (OLI) during time period spanning 2013 2023. obtain accurate LU/LC classification, used principal component (PCA) a supervised classification approach using maximum likelihood algorithm (MLC). According results our study, there was decrease extent bodies (− 593.24 km 2 ) vegetation 68.50 by − 3.43% 0.40% respectively. contrast, area occupied settlements investigated region had 2.23% rise, reaching total 385.66 square kilometers. Similarly, barren also expanded 1.60%, encompassing 276.04 kilometers, course last decade. overall accuracy (94.25% 95.75%) K value (91.75% 93.50%) were achieved year 2023 enhancement agricultural output Pakistan utmost importance improve income farmers, mitigate food scarcity, stimulate growth, facilitate expansion exports. To enhance productivity, recommended that government undertake targeted initiatives aimed at enhancing infrastructure optimizing use foster ecological framework. Integrating framework provides foundation informed decision-making effective resource management. By identifying areas urban expansion, intensification, or alterations natural stakeholders design conservation strategies, mitigating potential environmental promoting biodiversity conservation. conclusion, integration GIS Remote Sensing (RS) may effectively monitoring patterns over time. This combined offers valuable insights recommendations judicious optimal management resources, well informing policy decisions.