Sub-continental-scale mapping of tidal wetland composition for East Asia: A novel algorithm integrating satellite tide-level and phenological features

Zhang, Zhen; Xu, Nan; Li, Yangfan; Li, Yang

doi:10.1016/j.rse.2021.112799

Cited by 72 publications

(66 citation statements)

References 64 publications

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“…After the cloud masking, we calculated the NDWI [51] of every pixel in the image collection. The NDWI has been widely used to distinguish open surface water from other features across different sensors, such as Landsat [8,27], and Sentinel-2 [10]. Although the NDWI may not be very sensitive to water with vegetation within one scene, the deciduous nature of the vegetation in the study area combined with the following mentioned compositing method could permit an effective mitigation.…”

Section: Maximum and Minimum Water Area Extractionmentioning

confidence: 99%

“…Additionally, tidal flats also play a vital role in navigation, tourism, food production, and economy [6,8,9]. However, as one of the most vulnerable ecosystems in the world [10], tidal flats are facing accumulating threats. For example, the growing frequency and severity of coastal flooding caused by the sea level rise leads to the erosion of tidal flats [11,12], resulting in sea water intrusion [13].…”

Section: Introductionmentioning

confidence: 99%

“…Remoting-sensing methods based on satellite images could monitor land cover and its changes in near real time and over extensive ranges. Using satellite imagery, land cover mapping concerned with tidal flats has been achieved at local [7,[20][21][22][23], national [2][3][4]8,[24][25][26], continental [10,27], and global scales [1]. At the same time, various tidal flat mapping methodologies have been proposed.…”

Section: Introductionmentioning

confidence: 99%

“…The image composition method composites all the eligible pixels in an image stack into one image. This method exploits the valuable data in time series images to the greatest extent, so pixels not covered by cloud within one scene could still be utilized [10]. Leveraging the full time series Landsat observations, Sagar et al [25] composited the median Normalized Difference Water Index (NDWI) value at different tide stages to extract the Australian intertidal ranges.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, the tidal flat range could be produced. Furthermore, Zhang et al [10] combined random forest algorithm and image compositing method, which achieved sub-continentalscale tidal flat mapping in East Asia. These studies show that image compositing methods have high practicability in tidal flat mapping, inspiring further attempts in this field.…”

Section: Introductionmentioning

confidence: 99%

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Mapping Tidal Flats of the Bohai and Yellow Seas Using Time Series Sentinel-2 Images and Google Earth Engine

Chang

et al. 2022

Remote Sensing

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Tidal flats are one of the most productive ecosystems on Earth, providing essential ecological and economical services. Because of the increasing anthropogenic interruption and sea level rise, tidal flats are under great threat. However, updated and large-scale accurate tidal flat maps around the Bohai and Yellow Seas are still relatively rare, hindering the assessment and management of tidal flats. Based on time-series Sentinel-2 imagery and Google Earth Engine (GEE), we proposed a new method for tidal flat mapping with the Normalized Difference Water Index (NDWI) extremum composite around the Bohai and Yellow Seas. Tidal flats were derived from the differences of maximum and minimum water extent composites. Overall, 3477 images acquired from 1 Oct 2020 to 31 Oct 2021 produced a tidal flat map around the Bohai and Yellow Seas with an overall accuracy of 94.55% and total area of 546,360.2 ha. The resultant tidal flat map at 10 m resolution, currently one of the most updated products around the Bohai and Yellow Seas, could facilitate the process of sustainable policy making related to tidal flats and will help reveal the processes and mechanisms of its responses to natural and human disturbance.

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Section: Maximum and Minimum Water Area Extractionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Mapping Tidal Flats of the Bohai and Yellow Seas Using Time Series Sentinel-2 Images and Google Earth Engine

Chang

et al. 2022

Remote Sensing

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Detailed detection and extraction of estuarine tidal channels with multispectral and full‐polarised SAR remote sensing

Li,

et al. 2024

Earth Surf Processes Landf

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Estuarine tidal channels are active geomorphic units in tidal flats. However, accurate information on the spatiotemporal changes in tidal channel systems remains scarce. The width of the tidal channels may vary from several kilometres to tens of centimetres. Monitoring tidal channel evolution is complicated because of periodic tidal scouring, anthropogenic activities and sea level rise. In this study, we propose a synergetic classification method to detect and extract morphological information of estuarine tidal channels with a spatial resolution of up to 3 m by fusing PlanetScope multispectral data with C‐band GaoFen‐3 fully polarised Synthetic Aperture Radar (SAR) data and machine learning algorithms. Considering the Yellow River Estuary as an example, the spectral features, vegetation and water index, polarisation and texture features derived from the multispectral and SAR images were selected as input data for classifiers according to feature importance ranking. Comparison to the maximum likelihood, and support vector machine classifiers, the synergetic classification with random forest showed the best performance, with an overall accuracy of 99.6%. Based on these results, the total number of tidal channels in the Yellow River Estuary reached 872, with a total length of 348.8 km. The spatiotemporal changes in the central axis over the last 4 years (2019–2022) suggest that the evolution of tidal channels was mainly controlled by ocean dynamics and anthropogenic activities. This method provides a cost‐effective alternative to accurately map tidal channel systems in global estuarine and coastal zones and helps to quantitatively describe their morphological evolution, stability and drivers.

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Monitoring China’s Mangrove Forest Change from 1990 to 2020: A New Algorithm Based on Spatio-temporal Detection Frequency Threshold

Wen,

Yao,

Wang

et al. 2023

Environmental Science and Engineering

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Sub-continental-scale mapping of tidal wetland composition for East Asia: A novel algorithm integrating satellite tide-level and phenological features

Cited by 72 publications

References 64 publications

Mapping Tidal Flats of the Bohai and Yellow Seas Using Time Series Sentinel-2 Images and Google Earth Engine

Mapping Tidal Flats of the Bohai and Yellow Seas Using Time Series Sentinel-2 Images and Google Earth Engine

Detailed detection and extraction of estuarine tidal channels with multispectral and full‐polarised SAR remote sensing

Monitoring China’s Mangrove Forest Change from 1990 to 2020: A New Algorithm Based on Spatio-temporal Detection Frequency Threshold

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