Scholarlink

To minimize the emission of greenhouse gases (GHGs) and save fragile forest ecosystems, it is recommended to decrease deforestation and forest degradation. This research focuses on utilizing Landsat imagery to determine Land Use Land Cover (LULC) change detection and its impact on surface water extent and carbon sequestration in the southern region of Punjab, Pakistan. In order to gather the necessary remote sensing (RS) data for the study, Landsat imagery from the years 2000, 2007, 2014, and 2021 was used. A ground-truth LULC change classification was performed using a supervised classification technique, namely maximum likelihood classification (MLC) algorithm using Geographic Information System (GIS) software (ArcMap v.10.7.1). In 2000, 2007, 2014, and 2021, overall accuracy (OA) and Kappa coefficient (K) for water, cropland, forest, settlements, and barren land classifications recorded as 88% and 85%, 86% and 82.76%, 90% and 84.7%, 90.63% and 88.24%, 88.89% and 84.38%, respectively. Upon analysis, it was revealed that 1.02% increase in water areas, 2.63% expansion in agricultural land, significant decrease of 31.03% in forest cover, a notable rise of 14.52% in settlement areas, and a substantial increase of 12.87% in barren land. In addition, a total of − 58,467,308.08 metric tons of emissions were recorded as a result of forest degradation from 2000 to 2021. The research provides crucial information that may be used by decision-makers and environmental managers to promote afforestation and preserve the country’s current forests, to mitigate climate change.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Impact of Land Use Land Cover Change on Surface Water Extent and Carbon Sequestration in Southern Punjab Using Geospatial Techniques

  • 章节

  • 发表日期：

    2025年

查看全文
  • Ali Raza,
  • Neyha Rubab Syed,
  • Muhammad Zubair,
  • Siham Acharki,
  • Dinesh Kumar Vishwakarma,
  • Sajjad Hussain,
  • Sudhir Kumar Singh,
  • Romana Fahmeed,
  • Ram L. Ray,
  • Fahad M. Alqahtani

摘要

To minimize the emission of greenhouse gases (GHGs) and save fragile forest ecosystems, it is recommended to decrease deforestation and forest degradation. This research focuses on utilizing Landsat imagery to determine Land Use Land Cover (LULC) change detection and its impact on surface water extent and carbon sequestration in the southern region of Punjab, Pakistan. In order to gather the necessary remote sensing (RS) data for the study, Landsat imagery from the years 2000, 2007, 2014, and 2021 was used. A ground-truth LULC change classification was performed using a supervised classification technique, namely maximum likelihood classification (MLC) algorithm using Geographic Information System (GIS) software (ArcMap v.10.7.1). In 2000, 2007, 2014, and 2021, overall accuracy (OA) and Kappa coefficient (K) for water, cropland, forest, settlements, and barren land classifications recorded as 88% and 85%, 86% and 82.76%, 90% and 84.7%, 90.63% and 88.24%, 88.89% and 84.38%, respectively. Upon analysis, it was revealed that 1.02% increase in water areas, 2.63% expansion in agricultural land, significant decrease of 31.03% in forest cover, a notable rise of 14.52% in settlement areas, and a substantial increase of 12.87% in barren land. In addition, a total of − 58,467,308.08 metric tons of emissions were recorded as a result of forest degradation from 2000 to 2021. The research provides crucial information that may be used by decision-makers and environmental managers to promote afforestation and preserve the country’s current forests, to mitigate climate change.