Impacts of urbanization and land transitions on seagrass beds in tropical lagoon in central Vietnam

Tu, Nguyen H. C.; Uyen, Nguyen T.; Doc, Luong Quang; Tuan, Le Cong; Thu, Mai A.; Tín, Hoàng Công

doi:10.1016/j.rsma.2021.101860

Cited by 1 publication

(1 citation statement)

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“…As reviewed by Hossain et al (2015) and Veettil et al, (2020), seagrass mapping approaches should consider habitat conditions including water depth (exposed intertidal, submerged intertidal, shallow subtidal or deep subtidal) and water clarity (clear or turbid). For submerged seagrasses in subtidal area (e.g., water depth > 2 m), water depth corrections are usually required to reduce the effects of water attenuation and retrieve bottom reflectance, based on which seagrasses are identified (Kuhwald et al, 2021;Tu et al, 2021). For intertidal seagrasses which are exposed during low tide, surface reflectance-based vegetation indices, such as Normalized Differential Vegetation Index (NDVI) have been adopted to delineate seagrass extents (Valle et al, 2015;Zoffoli et al, 2020;Zoffoli et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Developing seagrass index for long term monitoring of Zostera japonica seagrass bed: a case study in Yellow River Delta, China

Zhou¹,

Ke²,

Wang³

et al. 2022

Preprint

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Seagrass beds offer unique and vital ecological services as an important blue carbon ecosystem in coastal wetlands. Zostera japonica is an intertidal seagrass species native to eastern Asia and is one of the most widely distributed seagrass species in China. However, little is known on the long-term variations of Z. japonica extents. Automatic mapping method for Z. japonica seagrass beds is in urgent need to fill this knowledge gap. In this study, we proposed a new SeaGrass Index (SGI) for automatic and rapid mapping of Z. japonica based on time-series Landsat satellite imagery, aiming to alleviate the influence of tidal inundation and enhance the separability from other coastal cover types. The SGI considers both spectral and phenological characteristics of Z. japonica, as well as the spatial location of Z. japonica. We took the Yellow River Delta (YRD), China as our study area, where Z. japonica was first discovered and reported in 2015. Based on SGI, Z. japonica extents during 1985-2018 were extracted using multi-Otsu thresholding algorithm. Accuracy assessments based on field investigations and high-resolution imagery showed that SGI has successfully separated seagrass beds from other cover types, especially intertidal salt marshes, with overall accuracies >95%, producer’s accuracies >90% and user’s accuracies >94%. Our study provides the first long-term maps of seagrass beds in YRD. The area of Z. japonica showed large variations during 1985-2018, ranging from 149 ha in 2005-2006 to 1302.9 ha in 2011-2012. The spatial distribution of Z. japonica varied with the morphological change of the estuary caused by river channel shifts. Since 2011, Z. japonica seagrass beds have undergone area degradation due to the invasion of S. alterniflora. The area was only 332.3 ha in 2017-2018. Coastal erosion and extreme climate events such as drought and typhoon might also explain degradation of seagrass beds in YRD. We expect that the SGI will advance automatic and rapid mapping methods for intertidal seagrass beds, and the Z. japonica maps will provide a baseline data for restoration and management of seagrasses at regional scale.

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