Extraction and spatiotemporal evolution analysis of tidal flats in the Bohai Rim during 1984–2019 based on remote sensing

Xu, Haijue; Jia, Ao; Song, Xiaolong; Bai, Yuchuan

doi:10.1007/s11442-023-2075-0

Cited by 8 publications

(3 citation statements)

References 56 publications

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“…In this work, the random forest (RF) model can be used to assess the main factors controlling the aggregation of the spatial distribution of karst depressions. The final results are produced by automatically generating multiple decision trees and predicting the votes through the combination of these decision trees, which can be used to perform some analyses, such as discriminant, clustering and regression, while assessing the importance of independent variables (Wang et al, 2019;Xu et al, 2023). The RF model has the following characteristics: (1) no variable selection is needed; (2) no multivariate covariance problem needs to be considered; (3) overfitting of results is avoided; (4) the importance of independent variables can be evaluated; and (5) the learning process is fast.…”

Section: Methodology For Main Controlling Factorsmentioning

confidence: 99%

Spatial patterns and controlling factors of the evolution process of karst depressions in Guizhou province, China

Zhang,

Zuo,

et al. 2023

J. Geogr. Sci.

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Karst depressions are common negative topographic landforms formed by the intense dissolution of soluble rocks and are widely developed in Guizhou province. In this work, an inventory of karst depressions in Guizhou was established, and a total of approximately 256,400 karst depressions were extracted and found to be spatially clustered based on multidistance spatial cluster analysis with Ripley's K function. The kernel density (KD) can transform the position data of the depressions into a smooth trend surface, and five different depression concentration areas were established based on the KD values. The results indicated that the karst depressions are clustered and developed in the south and west of Guizhou, while some areas in the southeast, east and north have poorly developed or no clustering. Additionally, the random forest (RF) model was used to rank the importance of factors affecting the distribution of karst depressions, and the results showed that the influence of lithology on the spatial distribution of karst depressions is absolutely dominant, followed by that of fault tectonics and hydrological conditions. The research results will contribute to the resource investigation of karst depressions and provide theoretical support for resource evaluation and sustainable utilization.

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Section: Methodology For Main Controlling Factorsmentioning

confidence: 99%

Spatial patterns and controlling factors of the evolution process of karst depressions in Guizhou province, China

Zhang,

Zuo,

et al. 2023

J. Geogr. Sci.

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“…Although the tidal flat area has generally decreased in the aforementioned regions, there have been periods of increase in tidal flat wetland areas throughout the time series. In the case of H2, the diversion of the Yellow River northward in 1996 resulted in the loss of its primary sediment supply to the southern region of the estuary [63]. Consequently, the tidal flats in the region have experienced a gradual erosion process.…”

Section: Drivers Of Tidal Flat Dynamics In Ybs 421 Tidal Flat Changes...mentioning

confidence: 99%

Tracking the 2D/3D Morphological Changes of Tidal Flats Using Time Series Remote Sensing Data in Northern China

Gan,

Guo,

Chen

et al. 2024

Remote Sensing

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Tidal flats in northern China are essential parts of the East Asian-Australasian Flyway, the densest pathway for migratory waterbirds, and are of great ecological and economic importance. They are threatened by human activities and climate change, raising the urgency surrounding tracking the spatiotemporal dynamics of tidal flats. However, there is no cost-effective way to map morphological changes on a large spatial scale due to the inaccessibility of the mudflats. In this study, we proposed a pixel-based multi-indices tidal flat mapping algorithm that precisely characterizes 2D/3D morphological changes in tidal flats in northern China using time-series remote sensing data. An overall accuracy of 0.95 in delineating tidal flats to a 2D extent was achieved, with 11,716 verification points. Our results demonstrate that the reduction in sediment discharge from rivers along the coastlines of the Yellow and Bohai Seas has resulted in an overall decline in the area of tidal flats, from 4856.40 km2 to 4778.32 km2. Specifically, 3D analysis showed that significant losses were observed in the mid-to-high-tidal flat zones, while low-elevation tidal flats experienced an increase in area due to the transformations in mid-to-high-tidal flats. Our results indicate that the sediment inputs from rivers and the succession of native vegetation are the primary drivers leading to 2D/3D morphological changes of tidal flats following the cessation of extensive land reclamation in northern China.

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“…Reclamation activities can directly modify land cover types, leading to rapid and immediate changes in the extent of tidal flats within a short timeframe (Xu et al, 2023). These changes occur through the direct alteration of the land-sea boundary.…”

Section: Reclamation Activitiesmentioning

confidence: 99%

Evolution of tidal flats in the Yellow River Qingshuigou sub-delta: spatiotemporal analysis and mechanistic changes (1996-2021)

Cao,

Wang,

Zhan

et al. 2023

Front. Mar. Sci.

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The Yellow River Delta has undergone significant changes, developing a temperate chalk-sand silty coast with expansive and level tidal flats. However, the area is currently facing the threat of erosion due to coastal area construction, decreased river sediment discharge into the sea, and intensified marine hydrodynamic forces. Remote sensing technology has important applications in spatial and temporal monitoring of tidal flats. This study employs tidal data to establish the threshold range for the extraction of tidal flats in the Yellow River Qingshuigou sub-delta, using the water frequency method based on the image element proposed by previous authors. The study successfully identifies and analyzes the range of tidal flats, and further delves into their evolutionary process and underlying mechanisms. The study concludes that the area of tidal flats has shown a decreasing trend and was divided into a “rapid decline phase” and an “overall stabilization phase” with 2006 as the boundary. The spatial and temporal evolution of tidal flats is primarily influenced by three main factors: river sediment discharges, marine hydrodynamic forces, and anthropogenic reclamation activities. Specifically, the river sediment discharges and marine hydrodynamic forces impact the extent of tidal flats by modifying the boundary conditions, primarily at the sea boundary. Reclamation activities have a direct and rapid effect on the extent of tidal flats, primarily at the land boundary. In this study, we determined the contribution of three factors to the spatial and temporal evolution of tidal flats in different periods. During the two phases of the tidal flats’ spatial and temporal evolution in the Yellow River Qingshuigou sub-delta, the driving mechanisms were identified as “reclamation - marine hydrodynamic forces - river sediment discharges” and “marine hydrodynamic forces - river sediment discharges - reclamation”.

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Extraction and spatiotemporal evolution analysis of tidal flats in the Bohai Rim during 1984–2019 based on remote sensing

Cited by 8 publications

References 56 publications

Spatial patterns and controlling factors of the evolution process of karst depressions in Guizhou province, China

Spatial patterns and controlling factors of the evolution process of karst depressions in Guizhou province, China

Tracking the 2D/3D Morphological Changes of Tidal Flats Using Time Series Remote Sensing Data in Northern China

Evolution of tidal flats in the Yellow River Qingshuigou sub-delta: spatiotemporal analysis and mechanistic changes (1996-2021)

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