Response of storm surge and M2 tide to typhoon speeds along coastal Zhejiang Province

Chen, Wei; Liu, Wenlong; Liang, Hongyu; Jiang, Mingtao; Dai, Zili

doi:10.1016/j.oceaneng.2023.113646

Cited by 29 publications

(12 citation statements)

References 28 publications

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“…On the other hand, using surveillance cameras allows for an increase in the density of data in coastal areas without monitoring stations. Remote sensing data combined with machine learning models have usually been applied to obtain physical features of the coastal areas, like water depth [82,83], storm surge [10,11,84], and hydrological parameters [85]. To date, few studies have focused on the assessment of meteo-marine parameters through deep learning and video monitoring [86][87][88].…”

Section: Resultsmentioning

confidence: 99%

Remote Measurement of Tide and Surge Using a Deep Learning System with Surveillance Camera Images

Sabato,

Scardino,

Kushabaha

et al. 2024

Water

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The latest progress in deep learning approaches has garnered significant attention across a variety of research fields. These techniques have revolutionized the way marine parameters are measured, enabling automated and remote data collection. This work centers on employing a deep learning model for the automated evaluation of tide and surge, aiming to deliver accurate results through the analysis of surveillance camera images. A mode of deep learning based on the Inception v3 structure was applied to predict tide and storm surges from surveillance cameras located in two different coastal areas of Italy. This approach is particularly advantageous in situations where traditional tide sensors are inaccessible or distant from the measurement point, especially during extreme events that require accurate surge measurements. The conducted experiments illustrate that the algorithm efficiently measures tide and surge remotely, achieving an accuracy surpassing 90% and maintaining a loss value below 1, evaluated through Categorical Cross-Entropy Loss functions. The findings highlight its potential to bridge the gap in data collection in challenging coastal environments, providing valuable insights for coastal management and hazard assessments. This research contributes to the emerging field of remote sensing and machine learning applications in environmental monitoring, paving the way for enhanced understanding and decision-making in coastal regions.

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Section: Resultsmentioning

confidence: 99%

Remote Measurement of Tide and Surge Using a Deep Learning System with Surveillance Camera Images

Sabato,

Scardino,

Kushabaha

et al. 2024

Water

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“…The coastal mountain forest ecosystems in southeastern Zhejiang Province suffer from frequent typhoon disturbances [25,26]. It is estimated that a total of 208 tropical cyclones made landfall in the southeastern coastal cities of China from 1984 to 2019, of which 88 were intense tropical storms [27].…”

Section: Introductionmentioning

confidence: 99%

The Short-Term Responses of Forest Soil Invertebrate Communities to Typhoon Disturbances

Xuan,

Pan,

Qin

et al. 2024

Forests

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Knowledge regarding the response of soil invertebrate communities to typhoon disturbance is limited, although it is known that soil invertebrates are sensitive to forest disturbances and that tropical cyclones (typhoons/hurricanes) are the most destructive natural disasters affecting the structure and function of forest ecosystems. To fill this knowledge gap, soil invertebrates in both litter and topsoil layers were investigated in four representative subtropical coastal forests of eastern China one week before the first typhoon (Hinnamnor) (T1), one day after the first typhoon (Hinnamnor) (T2), one day after the second typhoon (Muifa) (T3), and one week after the second typhoon (Muifa) (T4) in September 2022. Typhoon disturbances decreased the density and taxa abundance of soil invertebrate communities in litter layer, but the first typhoon disturbance increased these values in the topsoil layer. One week after the second typhoon disturbance, soil invertebrate communities in the litter layer showed a gradual recovery trend. Meanwhile, the soil invertebrate communities in the litter layer were more sensitive to typhoon disturbances than those in the topsoil layer. Furthermore, the responses of the soil invertebrate communities to the typhoon disturbances varied greatly with the forest types. The invertebrate densities in the litter layer decreased by 62.1%, 63.53%, 47.01%, and 46.92% in Chinese fir, second broad-leaved, mixed, and bamboo forests, respectively. Particularly, these two non-catastrophic typhoons significantly altered the functional group composition of detrital food webs in the short term, and the proportion of phytophages in detrital food webs in the litter layer increased after the typhoon disturbances. In conclusion, the effects of typhoon disturbances on soil invertebrate communities vary greatly with forest type and soil layer, and soil invertebrate communities can gradually recover after typhoon disturbances. The legacy effects of typhoon disturbances on the functional group composition of detrital food webs may influence carbon and nutrient cycling in forest ecosystems.

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“…As a result of the rapid changes in the global climate in recent years, many countries have experienced frequent disasters caused by extreme weather, resulting in significant loss of human and material resources (Li, 2022). Among them, typhoons are one of the most frequent and destructive meteorological disasters in the world, this cyclonic system, known for its powerful winds, torrential rains, and sea waves, poses a great threat and loss to many countries and is one of the global problems that mankind has to face for its survival and development nowadays (Xie et al, 2021;Chen et al, 2023). China is one of the countries in the world that are seriously affected by typhoons (Jiwei, 2023), and the northern part of the South China Sea, the Taiwan Strait, Taiwan Province, and its eastern coast, the western part of the East China Sea, and the Yellow Sea are all high-frequency zones through which typhoons pass, posing a serious threat to China's social and economic development (Sui and Tang, 2015).…”

Section: Introductionmentioning

confidence: 99%

Dynamic typhoon visualization based on the integration of vector and scalar fields

Feng,

Qin,

et al. 2024

Front. Mar. Sci.

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Typhoons and other marine meteorological disasters often bring significant losses to human beings, and their data are characterized by multiple sources and scales, making traditional visualization methods unable to accurately express the characteristics and movement trends of the disasters. To address the above problems, this study proposes a typhoon dynamic visualization method based on the integration of vector and scalar fields. To address the above problems, this study proposes a typhoon dynamic visualization method based on the integration of vector and scalar fields. The method uses the ray casting method to visualize the volume rendering of typhoon scalar data, proposes a hybrid interpolation method to improve the visualization efficiency, and introduces the Sobel operator to achieve the edge enhancement of the volume rendering effect. Meanwhile, a particle system approach is used for dynamic visualization of typhoon vector data, where the tedious particle motion calculation is divided into two parts: parallel tracking and dynamic rendering to improve the visualization efficiency, and the Lagrangian field representation of the particle system is achieved. The experimental results show that the typhoon visualization method proposed in this study has better comprehensive visual effects, with a rendering frame rate greater than 44, and is able to stably and smoothly express the continuous spatio-temporal dynamic visualization features of typhoon.This study is conducive to the understanding of the evolution law of marine meteorological disasters and the adoption of disaster prevention and mitigation measures, and is of great significance for the expression of marine meteorological data such as typhoons and the analysis of their spatial and temporal changes.

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Response of storm surge and M2 tide to typhoon speeds along coastal Zhejiang Province

Cited by 29 publications

References 28 publications

Remote Measurement of Tide and Surge Using a Deep Learning System with Surveillance Camera Images

Remote Measurement of Tide and Surge Using a Deep Learning System with Surveillance Camera Images

The Short-Term Responses of Forest Soil Invertebrate Communities to Typhoon Disturbances

Dynamic typhoon visualization based on the integration of vector and scalar fields

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