Geospatial analysis of creeks evolution in the Indus Delta, Pakistan using multi sensor satellite data. (5th January 2018)

• Record Type: Journal Article
• Authors: Ijaz, Muhammad Wajid; Mahar, Rasool Bux; Siyal, Altaf Ali; Anjum, Muhammad Naveed
• Is Part Of: Estuarine, coastal and shelf science. Volume 200(2018)
• Page Start: 324
• Page End: 334
• Publication Date: 2018-01-05
• Subjects: Satellite imagery -- Coastal morphology -- Sindh coast -- Mangrove; Estuarine oceanography -- Periodicals; Coasts -- Periodicals; Estuarine biology -- Periodicals; Seashore biology -- Periodicals; Coasts; Estuarine biology; Estuarine oceanography; Seashore biology; Periodicals; 551.461805
• DOI: 10.1016/j.ecss.2017.11.025
• Languages: English
• ISSNs: 0272-7714

Abstract

Abstract: Sea level rise (SLR) in response to looming climate change is being considered as a major impediment to coastal areas. Acute wave activities and tidal propagations of semi-diurnal to mixed type are impairing the morphology of the Indus Delta in Pakistan. In this study a synthetic approach has been adopted using multi sensor satellite and ground data in order to integrate the individual effect of topography, oceanic activities and vegetative canopy for deduction of a synergic impact over the morphology of the Indus Delta creeks system from 1972 to 2017. Geomorphologic anomalies in the planform of fourteen major creeks were explored. Spatiotemporal variations suggested that a substantial amount of the delta alluvium had been engulfed by the Arabian Sea. On average, the creeks located on the right side of the Indus River were relatively less wide (3.9 km) than those of on the left side (5.2 km). Zonal statistics calculated with topographic position index (TPI) enabled to understand the tide induced inundation extents. The mangrove canopy on the right side was found greater, which is why tidal basins on that side experienced less erosive activities. Thus, it could be maintained that the coastal sedimentary processes may be monitored effectively with the remotely sensed data and temporal pattern of changes can be quantified for future planning and mitigation of adverse effects. Graphical abstract: