Wetland dynamics in northern Australia’s tropical savanna (1987–2024): a multi-index Google Earth Engine approach for long-term monitoring

Wetlands are essential for biodiversity conservation and ecosystem services, yet they remain under-monitored in many parts of the world, including wet-dry tropical savannas. In Northern Australia, increasing development pressures and climate change raise concerns about the long-term conservation of...

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Main Authors: Kaline de Mello, Edimilson Rodrigues dos Santos Junior, Erica A. Garcia, Anna E. Richards, Peter Scott Waugh, Jessica Huxley, Simon Linke
Format: Article
Language:English
Published: Elsevier 2025-09-01
Series:Ecological Indicators
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Online Access:http://www.sciencedirect.com/science/article/pii/S1470160X25009793
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Summary:Wetlands are essential for biodiversity conservation and ecosystem services, yet they remain under-monitored in many parts of the world, including wet-dry tropical savannas. In Northern Australia, increasing development pressures and climate change raise concerns about the long-term conservation of the extensive and relatively intact wetlands. This study developed a wetland mapping framework tailored to the Australian tropical savanna, mapping change to wetlands in the Adelaide River Catchment from 1987 to 2024. A multi-index Landsat-based classification approach was implemented in Google Earth Engine, combining spectral indices, topography, and soil properties. To address the strong seasonality of tropical wetlands, the classification included separate wet/dry season processing. Post-classification refinement using hierarchical rules and auxiliary datasets helped resolve confusion among spectrally similar classes. Wetlands were categorized into twelve classes based on hydrological regime and vegetation structure. Validation showed high accuracy (93 % ± 1 %), with class-level accuracy above 80 % for most wetland types, including water bodies, mangroves, salt flats, swamps, marshes, and floodplains. Wetlands occupied a substantial portion of the catchment, covering approximately 40.5 % of the area in 1987 and 37.4 % in 2024, with marshes and floodplain woodlands dominating due to the flat terrain. Despite land use changes, 80 % of wetlands retained their class between 1987 and 2024. However, floodplain woodlands declined by 16,044 ha, often transitioning to other wetlands, non-wetland, or agricultural land, which increased by 29,000 ha. Internal transitions were common among estuarine and floodplain wetlands, reflecting natural dynamics. Dry periods reduced open water areas, while human-made wetlands increased. This is the first long-term assessment of wetland distribution in the region and provides essential spatial data for water management and conservation. The framework offers a transferable method for monitoring wetlands in other tropical savannas under environmental and development pressures.
ISSN:1470-160X