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ORIGINAL RESEARCH article

Front. Environ. Sci.
Sec. Environmental Informatics and Remote Sensing
Volume 12 - 2024 | doi: 10.3389/fenvs.2024.1416450

Time Series Monitoring and Analysis of Pakistan's Mangrove using Sentinel-2 Data

Provisionally accepted
Syed Ahmed Raza Syed Ahmed Raza 1,2,3Li Zhang Li Zhang 1,2Jian Zuo Jian Zuo 1,2,3*Bowei Chen Bowei Chen 1,2*
  • 1 Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China, Beijing, China
  • 2 International Research Center of Big Data for Sustainable Development Goals (CBAS), Beijing, Beijing Municipality, China
  • 3 University of Chinese Academy of Sciences, Beijing, Beijing, China

The final, formatted version of the article will be published soon.

    Sustainable Development Goal-14 (SDG-14) directly demands the protection, conservation, restoration and sustainable management of the global mangrove ecosystem. Assessment of the development Pakistan has made towards the sustainable management of mangrove ecosystems necessitates the remote sensing-based evaluation of national-level mangrove cover. Using Google Earth Engine (GEE) for geoprocessing 12000+ 10-m high-spatial resolution Sentinel-2 time series images (2016-23) and applying Random Forest (RF) classifier, current research provides the latest spatial distribution of mangroves along Pakistan’s coastline and 8-year long temporal changes in it. Additionally, this research provides the first spatiotemporal health assessment of Pakistan’s national mangroves as well. Rational analysis of the results indicated splitting the entire timeline based on two seasons (Jan-Jun and Jul-Dec). Results revealed an overall 1210 km2 (2023) national-level mangroves; a 3.42 km2 average annual increase from 2016 (1186 km2). Mangrove gain/loss assessment based on Land Use Land Cover (LULC) transition matrix illustrated 223 km2 gain whereas 199 km2 loss; a 24 km2 net gain. 20.28% and 7.91% declines were found in maximum- and mean-NDVI (2016-23), depicting the deteriorating mangrove health conditions. Likewise, significant Sen’s slope analysis (p<0.05) indicated that 88.8% of all the mangrove-NDVI pixels exhibited an overall decrease whereas 11.2% pixels showing an overall increase (2016-23). It was concluded that despite showing a growth in the extent, the Pakistan’s mangroves have shown a decline in health, primarily due to deforestation for urban operations and sea-level rise, still making them vulnerable and potentially leading to disrupted ecosystem including carbon release in atmosphere. This study will assist in the formulation of mangroves conservation and management strategies whereas future research can explore the potentials of Land Surface Temperature (LST) and evapotranspiration in combination to NDVI for an in-depth analysis of health status of mangroves.

    Keywords: Mangrove Extent Mapping, Mangrove Health Mapping, Sustainable Development Goal-14 (SDG-14), SDG Target 14.2, Google Earth Engine (GEE)

    Received: 15 Apr 2024; Accepted: 12 Jul 2024.

    Copyright: © 2024 Raza, Zhang, Zuo and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Jian Zuo, Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China, Beijing, China
    Bowei Chen, Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China, Beijing, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.