Evaluating mangrove conservation and sustainability through spatiotemporal (1990–2020) mangrove cover change analysis in Pakistan

Abstract

This study provides the first comprehensive mangrove cover change assessment from 1990 to 2020, at five-year intervals, across all five mangrove areas in Pakistan, i.e. Indus Delta, Sandspit, Sonmiani, Kalmat Khor, and Jiwani. Using the Google Earth Engine (GEE) geospatial cloud computing platform, Random Forest (RF) classifier was applied on Landsat 30 m spatial resolution satellite images to classify three major land cover classes: ‘mangrove’, ‘water’ and ‘other’. High temporal and spectral resolutions of Landsat images, with a low saturation level of spectral bands with the integration of indices, are the main factors that ensured >90% overall accuracy of land cover maps. Over the last three decades (1990–2020), the annual rate of change calculation, cross-tabulated method, and fragmentation analysis were carried out to identify the changes in mangrove cover. Overall, the findings of this paper revealed that, at the national scale, an estimated 477.22 km2 was covered with mangrove in 1990, which increased to 1463.59 km2 in 2020, a 3.74% annual rate of change. Mangrove fragmentation mapping results have also showed enhancement in mangrove tree canopy density. Due to planting and effective conservation practices, the current study shows positive changes in mangrove cover across all five study sites. The findings of this study will prove useful for design and implementation of mangrove ecosystem management plans, initiatives for adaptation to extreme weather events, carbon budgeting, and others.