☆ 4.7 Review

Coastline extraction using remote sensing: a review

GISCIENCE & REMOTE SENSING (2023)

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Spatio-temporal distribution of harmful algal blooms and their correlations with marine hydrological elements in offshore areas, China

Chao Chen et al.

OCEAN & COASTAL MANAGEMENT (2023)

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REMOTE SENSING OF ENVIRONMENT (2023)

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3D Model Construction and Ecological Environment Investigation on a Regional Scale Using UAV Remote Sensing

Chao Chen et al.

Summary: In this study, unmanned aerial vehicle (UAV) remote sensing technology was used to acquire oblique images and multispectral data in a campus area. Through the use of professional software, a 3D campus model, digital orthophoto map, and multispectral remote sensing map were created, and the geometric accuracy of the selected features were evaluated. The campus ecological environment was assessed based on vegetation and water body perspectives. The findings of this study have significant implications for the scientific management and sustainable development of regional natural resources.

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Arabian Journal of Geosciences (2022)

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Climate change driven shoreline change at Hasaki Beach Japan: A novel application of the Probabilistic Coastline Recession (PCR) model

Ali Dastgheib et al.

Summary: Low-lying coastal areas around the world are facing increasing threats from climate change, including slow coastal recession. This study applies the Probabilistic Coastline Recession (PCR) model to Hasaki Beach in Japan, and finds that the Bruun rule provides larger coastal recession projections compared to the PCR model. These findings highlight the urgent need for coastal zone management and adaptation measures.

COASTAL ENGINEERING (2022)

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Bibliometric Analysis of Data Sources and Tools for Shoreline Change Analysis and Detection

Johnson Ankrah et al.

Summary: This study is a bibliometric analysis of global scientific production on shoreline change analysis and detection. The results show that the USA has the highest scientific production in this field. Geospatial tools and machine learning are becoming increasingly important in shoreline change analysis. The study identifies some research gaps that have not yet been addressed.

SUSTAINABILITY (2022)

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Generating annual high resolution land cover products for 28 metropolises in China based on a deep super-resolution mapping network using Landsat imagery

Da He et al.

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GISCIENCE & REMOTE SENSING (2022)

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Can time-series Sentinel images be used to properly identify wetland plant communities?

Kaidong Feng et al.

Summary: In this study, a random forest classifier was proposed to classify wetland plant communities in the Momoge Ramsar wetland site (MRWS) in China by combining multi-source remote sensing features. The results showed that phenological and time-series features based on Sentinel-2 images were the most valuable discriminators for wetland plant community classification. Furthermore, the SAR_sum extracted from Sentinel-1 images also played an important role in classification. The classification map had high overall accuracy and Kappa coefficient, providing scientific decision-making support for the protection and management of migratory birds and plants in the MRWS.

GISCIENCE & REMOTE SENSING (2022)

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A deep learning model using geostationary satellite data for forest fire detection with reduced detection latency

Yoojin Kang et al.

Summary: This study proposed a deep learning-based forest fire detection algorithm that effectively reduced detection latency and false alarms. By combining input features, the research demonstrated that temporal and spatial information contributed to improving the accuracy of machine learning techniques for fire detection.

GISCIENCE & REMOTE SENSING (2022)

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Gang Yang et al.

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ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2022)

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Detection and characterization of coastal tidal wetland change in the northeastern US using Landsat time series

Xiucheng Yang et al.

Summary: Coastal tidal wetlands are highly altered ecosystems that are exposed to significant risk due to land-use change and sea-level rise. Understanding the changes in these wetlands is important for coastal communities and natural resource management. However, mapping these changes on a large scale is challenging due to the dynamic nature of coastal tidal wetlands.

REMOTE SENSING OF ENVIRONMENT (2022)

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Article Environmental Sciences

Coastline detection in satellite imagery: A deep learning approach on new benchmark data

Catherine Seale et al.

Summary: This study presents an automated coastline extraction methodology from Sentinel-2 images using a new labelled image dataset called SWED. The researchers trained and tested four convolutional neural network models and found that the model trained using their novel Sobel-edge loss function had greater sensitivity to fine-scale, narrow coastline features and demonstrated near top quantitative performance. The SWED dataset and Sobel-edge loss function are made openly available for use in remote sensing and machine learning applications.

REMOTE SENSING OF ENVIRONMENT (2022)

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Fifty years of Landsat science and impacts

Michael A. Wulder et al.

Summary: Since 1972, the Landsat program has provided 50 years of digital, multispectral, medium spatial resolution observations, playing a crucial role in scientific and technical advancements. The program's early years brought technological breakthroughs and established a template for global Earth observation missions. The knowledge gained from Landsat has been recognized for its economic and scientific value, leading to continuous improvement and increased usage through the introduction of free and open access to data.

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Improvement of Mangrove Soil Carbon Stocks Estimation in North Vietnam Using Sentinel-2 Data and Machine Learning Approach

Tien Dat Pham et al.

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GISCIENCE & REMOTE SENSING (2021)

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Exploring the Relationship between River Discharge and Coastal Erosion: An Integrated Approach Applied to the Pisa Coastal Plain (Italy)

Monica Bini et al.

Summary: Coastal erosion and human-induced pressure have had a severe impact on the Mediterranean region, particularly the Pisa coastal plain. Historical maps, airborne surveys, and GIS analysis were used to study shoreline changes over the past 142 years, revealing a correlation between river discharge and erosion. Remote sensing with Sentinel-2 images provided insights into sediment transport by the Arno River.

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Summary: Mapping subtidal banks in mud-dominated coastal systems is important for understanding their impact on shoreline dynamics, ecosystems, economic activities, and local communities. Spectral unmixing using an unsupervised decision tree can help separate coastal features and detect diffuse boundaries of mudbanks accurately in remote sensing images. The spatially explicit and spectrally coherent image endmembers derived from this approach facilitate the characterization of mud fractions and improve the representation of cross-shore gradients in coastal regions like Suriname.

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Southeast Asia island coastline changes and driving forces from 1990 to 2015

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Changes of the spatial and temporal characteristics of land-use landscape patterns using multi-temporal Landsat satellite data: A case study of Zhoushan Island, China

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Monitoring the Coastal Changes of the Po River Delta (Northern Italy) since 1911 Using Archival Cartography, Multi-Temporal Aerial Photogrammetry and LiDAR Data: Implications for Coastline Changes in 2100 AD

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IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE (2021)

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Changes in coastline and coastal reclamation in the three most developed areas of China, 1980?2018

Xuege Wang et al.

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Potential of Video Cameras in Assessing Event and Seasonal Coastline Behaviour: Grand Popo, Benin (Gulf of Guinea)

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Shoreline changes interpreted from multi-temporal aerial photographs and high resolution satellite images: Wotje Atoll, Marshall Islands

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REMOTE SENSING OF ENVIRONMENT (2013)

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Extraction of Coastline in Aquaculture Coast from Multispectral Remote Sensing Images: Object-Based Region Growing Integrating Edge Detection

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IEEE JOURNAL OF OCEANIC ENGINEERING (2012)

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InSAR Study of Shoreline Change along the Damietta Promontory, Egypt

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Remote Sensing of Coastal and Ocean Currents: An Overview

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A Geomatics Approach to Multitemporal Shoreline Analysis in Western Mediterranean: The Case of Platamona-Maritza Beach (Northwest Sardinia, Italy)

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A Geospatial Appraisal of Ecological and Geomorphic Change on Diego Garcia Atoll, Chagos Islands (British Indian Ocean Territory)

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Coastal environmental monitoring using remotely sensed data and GIS techniques in the Modern Yellow River delta, China

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2011)

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Environmental monitoring of spatial-temporal changes using remote sensing and GIS techniques in the Abandoned Yellow River Delta coast, China

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INTERNATIONAL JOURNAL OF ENVIRONMENT AND POLLUTION (2011)

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Spatio-temporal shoreline changes along the southern Black Sea coastal zone

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Quantitative analysis of shoreline changes at the Mediterranean Coast in Turkey

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Two coastline detection methods in Synthetic Aperture Radar imagery based on Level Set Algorithm

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Coastline interpretation from multispectral remote sensing images using an association rule algorithm

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Coastline change detection with satellite remote sensing for environmental management of the Pearl River Estuary, China

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Multi-source remote sensing data fusion: status and trends

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Separation Between Water and Land in SAR Images Using Region-Based Level Sets

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Shoreline definition and detection: A review

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Historical shoreline changes along the US Gulf of Mexico: A summary of recent shoreline comparisons and analyses

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Automated extraction of coastline from satellite imagery by integrating Canny edge detection and locally adaptive thresholding methods

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