Time Series Analysis of Bindi Dheraja Riverine Forest of Sukkar, Sindh, Pakistan using Remote Sensing

Abstract

Estimating and detecting changes in forest coverage and land-use land-cover (LULC) change due to human and natural sources is critical for long-term management. In the assessment, planning, and monitoring of forest resources, geographic information systems (GIS) and remote sensing (RS) play a critical role. This study used multi - temporal Landsat satellite images to assess changes in forests and other LULC along the Indus River’s Bindi Dheraja Sukkar in southern Pakistan. Forest and other LULC were classified using multitemporal Landsat data obtained during the years 2008, 2012, 2014, and 2017. In addition, from the classed maps of 2008 and 2017, forest cover and other LULC change detection maps were created. Ground sample locations and high-resolution Google Earth images were used to verify the final maps. According to the findings, forest area reduced by 17.18 percent with a yearly decline rate of 1.72 percent from 2008 to 2017, whereas agriculture land rose by 26.4 percent with a yearly growth rate of 2.6 percent. With a yearly drop rate of 0.48 percent, the area of water bodies and barren land declined by 4.85 percent and 4.81 percent, respectively. These findings will help with long-term planning and monitoring of the region’s forest resources, and they may be used by local, regional, and national forest authorities in the context of riverine forest management.