Tracking site-scale tidal flat dynamics using time-series satellite data and Google Earth Engine over the past 40 years

Arif, Maham; Xing, Qianguo; Li, Jie

doi:10.26881/oahs-2025.1.28

Abstract

Tidal flats (TFs), the global hotspots of biodiversity and providers of coastal protection, are changing due to land reclamation, industrialization, and climate change. However, conventional mapping methods are often inadequate for site-scale monitoring due to their coarse resolution and computational demands. This research has tried to generate accurate spatial-temporal maps of TFs by using a pixel-based composite method and satellite data for Karachi Port Trust (KPT), Pakistan, and Yangma Island, Yantai, China. High- and low-tide images were generated using the maximum value composite algorithm (MVCA_max) and the minimum quantile composite algorithm (MQCA_min). The results show that (i) over 40 years, KPT has an area decrease of 270 ha (16.1% reduction), divided into three phases: minimal reduction (1986–1991), reduction (1991–2003), and expansion (2003–2024), (ii) Yangma Island experienced a more drastic reduction of 682 ha, with reduction rate of 70.16%, and (iii) annual 10-m resolution TF maps from 2017 to 2024 revealed a slight increase in KPT area, while Yangma Island exhibited a decreasing trend. This study provides a baseline for monitoring TF dynamics, offers guidelines for preserving coastal biodiversity, and supports sustainable coastal management to mitigate anthropogenic impacts on these vital ecosystems.

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Tracking site-scale tidal flat dynamics using time-series satellite data and Google Earth Engine over the past 40 years

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