Climate Change Impacts and Mitigation Approach: Coastal Landscape, Transport, and Health Aspects

Islam, Md. Mozahidul; Shahin, Md.; Miraj, Md.; Ghosh, S. K.; Islam, Md. Nazrul; Islam, Israt

doi:10.1007/978-3-030-71950-0_2

Cited by 3 publications

(4 citation statements)

References 76 publications

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“…Erosion in many coastal areas has increased due to the complex effects of climate change. Rising sea levels and changes in weather patterns have intensified the frequency of extreme events occurring on our planet [1,3,[34][35][36].…”

Section: Study Areamentioning

confidence: 99%

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Coastal Monitoring Using Unmanned Aerial Vehicles (UAVs) for the Management of the Spanish Mediterranean Coast: The Case of Almenara-Sagunto

Chapapría

Peris

González-Escrivá

2022

IJERPH

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The concentration of the world’s population in coastal areas means an increase in pressure on the environment and coastal ecosystems. The impacts of climate change affect natural biophysical and ecological systems and human health. Research has been developed to create coastal monitoring with Unmanned Aerial Vehicles (UAVs) that allow data to be obtained and methodologies that integrate computer vision algorithms for 3D and image processing techniques for analysis, combined with maritime information. The Valencian oval is located on the Spanish Mediterranean coast and registers significant coastal erosion. It is a densely populated area, with high economic relevance and tourist activity. The main goals of the developed research in this coastal area include creating a methodology of data collection that identifies environmental indicators significant to community health and uses in the coastal areas, to test progression of interventions and to assess coastal erosion detection and monitoring. The final objective is to aid in decision-making and coastal management. Sediment characterization was obtained, and continuous maritime information was collected. The dynamic evolution of coastal areas was researched by using UAVs on the Spanish Mediterranean coast. This technique is suitable for measuring medium to small coastal changes. Flight planning was carried out using the grid mode and adapted to areas in order to obtain a homogeneous pixel size and precision. This monitoring program takes advantage of technological development with very low economic costs and is a good tool for making decisions that must be based on scientific information. With the monitoring work, an annual erosion between 12 and 6 m was detected. The monitoring program has evidenced the shoreline trend as a result of the impact of rigid structures, mainly ports and groins, in promoting down-drift erosion processes in the area.

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Section: Study Areamentioning

confidence: 99%

“…The impacts of climate change affect natural biophysical and ecological systems and human health [1][2][3][4]. Coastal erosion is affecting the environment and economic activities globally [5].…”

Section: Introductionmentioning

confidence: 99%

Coastal Monitoring Using Unmanned Aerial Vehicles (UAVs) for the Management of the Spanish Mediterranean Coast: The Case of Almenara-Sagunto

Chapapría

Peris

González-Escrivá

2022

IJERPH

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“…Bangladesh is one of the world's disaster-prone countries located downstream of the Ganges-Brahmaputra-Meghna (GBM) catchment area (Islam et al, 2021). Due to the flat and low-lying deltaic topographic position, people's lives and livelihoods are susceptible to various natural hazardous conditions (Mojid, 2020).…”

Section: Introductionmentioning

confidence: 99%

Livelihood Impact Due to Riverbank Erosion Among the Affected Households Along the River Jamuna of Bangladesh

Hossain,

Fahad

2023

J. Asiat. Soc. Bangladesh, Sci.

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The present study examines the impacts of riverbank erosion on locals' lives and livelihoods in a particular area of the Jamuna River floodplain of Bangladesh. Riverbank erosion causes thousands of people to be affected, resulting in damage and loss of crops, cattle, housing structures, and farmland. It also erodes public infrastructures and communication networks significantly. This study undertakes empirical methods (including the open-ended questionnaire with a total of 155 households) to demonstrate the study's findings. The lack of adequate measures is the major factor associated with riverbank erosion in the study area. Land property loss becomes one of the major threats among the surveyed families. Some mitigation measures, such as using Geo bags and concrete blocks to protect the banks and operation of dredging machines to divert the water flow, are observed in the study area to reduce erosion. However, these measures are not bringing any effective solution to the local people’s livelihoods due to the slow ongoing work processes. J. Asiat. Soc. Bangladesh, Sci. 49(2): 179-191, December 2023

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“…In some cases, the speed breakers are not even and are constructed at dissimilar heights [7]. This instance leads to pothole formation, which is mainly because of the continuous movement of vehicles, heavy rainfall, etc., and causes damage to human lives [8]. Moreover, it leads to financial losses for the government's transport agencies.…”

Section: Introductionmentioning

confidence: 99%

An Optimized Deep Learning Framework For Pothole Detection

Sridhar Patthi

2023

IJRITCC

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Pothole detection plays a crucial role in preventing road accidents and is effective in establishing road maintenance and safety. Although various pothole detection models are designed to accurately identify the pothole based on road images, they face issues in accuracy and hyperparameter tuning. The presented research work concentrates on developing a novel optimized deep learning model for the accurate prediction of potholes on the road infrastructure using the recurrent neural network (RNN) and grey wolf optimization (GWO). Initially, the road images are collected and pre-processed. The pre-processing includes the removal of noises, image resizing, etc., to improve the image quality. Further, texture-based feature extraction was employed to extract the most relevant features from the pre-processed image. Then, the RNN architecture was trained using the extracted features to learn the interconnections between the image features and pothole detection. In addition, the GWO fitness solution was integrated into the classification module to tune and optimize the RNN hyperparameters, which increases the detection performances such as accuracy, and reduces the loss function. Finally, the presented model was evaluated with the publically available road image detection database and the outcomes are determined. The performance assessment demonstrates that the designed model attained greater accuracy of 98.76%, and a loss function of 0.06. Furthermore, a comparative assessment was performed with existing methods to evaluate the effectiveness of the proposed model.

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Climate Change Impacts and Mitigation Approach: Coastal Landscape, Transport, and Health Aspects

Cited by 3 publications

References 76 publications

Coastal Monitoring Using Unmanned Aerial Vehicles (UAVs) for the Management of the Spanish Mediterranean Coast: The Case of Almenara-Sagunto

Coastal Monitoring Using Unmanned Aerial Vehicles (UAVs) for the Management of the Spanish Mediterranean Coast: The Case of Almenara-Sagunto

Livelihood Impact Due to Riverbank Erosion Among the Affected Households Along the River Jamuna of Bangladesh

An Optimized Deep Learning Framework For Pothole Detection

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