Article
Environmental Sciences
Jian Zou, Hang Xie, Chengzhi Zheng, Songhui Lu
Summary: The study on benthic Prorocentrum concavum in Xincun Bay revealed seasonal variations in abundance and spatial heterogeneity, with seagrass beds potentially serving as a reservoir for harmful algal blooms and the dense cage-culture area providing organic nutrients for growth and reproduction.
FRONTIERS IN MARINE SCIENCE
(2022)
Article
Oceanography
Jessica S. Turner, Carl T. Friedrichs, Marjorie A. M. Friedrichs
Summary: While ecosystem health is improving in many estuaries worldwide following nutrient reductions, inconsistent trends in water clarity often remain. The study in Chesapeake Bay found that some measurements of downstream estuarine water clarity appear to be uncorrelated with watershed management actions, indicating the need for multiple metrics to address the issue. Satellite remote sensing provides an additional tool to assess long-term change in water clarity.
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS
(2021)
Review
Oceanography
A. Lheureux, V David, Y. Del Amo, D. Soudant, I Auby, F. Ganthy, H. Blanchet, M-A Cordier, L. Costes, S. Ferreira, L. Mornet, A. Nowaczyk, M. Parra, F. D'Amico, L. Gouriou, C. Meteigner, H. Oger-Jeanneret, L. Rigouin, M. Rumebe, M-P Tournaire, F. Trut, G. Trut, N. Savoye
Summary: Large amounts of nutrients have been released to coastal ecosystems, and this study focuses on the bi-decadal changes in nutrient concentrations and ratios in the Arcachon bay. The study finds that the concentration of nitrogen and silicic acid increased, while the concentration of orthophosphate decreased, leading to changes in nutrient ratios. The decline of seagrass meadow is identified as the main driver of these changes, through direct and indirect processes. Additionally, the study highlights the importance of abiotic drivers such as local climate, continental inputs, and bay hydrodynamics in influencing nutrient concentrations.
PROGRESS IN OCEANOGRAPHY
(2022)
Article
Engineering, Marine
Liadira Kusuma Widya, Chang-Hwan Kim, Jong-Dae Do, Sung-Jae Park, Bong-Chan Kim, Chang-Wook Lee
Summary: The study utilized support vector machine (SVM) technologies with corrected satellite imagery data to accurately identify the distribution of seagrasses.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2023)
Article
Environmental Sciences
Bozhong Zhu, Yan Bai, Zhao Zhang, Xianqiang He, Zhihong Wang, Shugang Zhang, Qian Dai
Summary: This study explores the use of satellite-based water quality monitoring and variation analysis to understand the impact of anthropogenic activities on semi-enclosed bays. The research highlights the need for continuous monitoring and long-term ecological protection and restoration to effectively address issues such as eutrophication and water quality deterioration. The findings can provide a reference for ecological environment monitoring and remote sensing data application in similar bays and support sustainable development.
Article
Oceanography
Jianbu Wang, Zhaoyang Lin, Yuanqing Ma, Guangbo Ren, Zijun Xu, Xiukai Song, Yi Ma, Andong Wang, Yajie Zhao
Summary: In this study, remote sensing monitoring of the invasive Spartina alterniflora in Jiaozhou Bay was conducted using a deep convolutional neural network method. The distribution characteristics and invasion mechanism of S. alterniflora were analyzed. The study found that S. alterniflora mainly distributed in specific locations in Jiaozhou Bay, gradually spreading over time.
ACTA OCEANOLOGICA SINICA
(2022)
Article
Remote Sensing
Shengguang Chu, Peng Li, Min Xia, Haifeng Lin, Ming Qian, Yonghong Zhang
Summary: In this paper, a Dual Branch Feature Guided Aggregation Network composed of convolutional neural network (CNN) and Transformer is proposed for Remote Sensing Change Detection (RS-CD), which is of great importance. By constructing a dual-branch backbone network to extract the spatial and semantic information of the image respectively, and guiding each other for feature mining through the Feature Guidance Aggregation Module, the occurrence of false detection and missed detection of change areas is avoided. The experimental results show significant improvements in the mean intersection over union (MIoU) index compared to existing methods on four public datasets.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2023)
Article
Environmental Sciences
Chen Cai, Yi Wang, Kim-Hui Yap
Summary: This paper proposes an Interactive Change-Aware Transformer Network (ICT-Net) for generating sentences describing the difference in content in remote sensing bitemporal images. The ICT-Net method improves change description generation by extracting and aggregating critical changes of interest and achieves state-of-the-art performance in the experiments.
Article
Marine & Freshwater Biology
Luis Lizcano-Sandoval, Christopher Anastasiou, Enrique Montes, Gary Raulerson, Edward Sherwood, Frank E. Muller-Karger
Summary: This study used multiple satellite imagery products to estimate seagrass areal cover in West-Central Florida over almost 30 years. The results showed an overall increase in seagrass cover in the region, especially after improvements in water quality. This study provides important tools for resource managers to assess seagrass cover.
ESTUARINE COASTAL AND SHELF SCIENCE
(2022)
Article
Ecology
Ken Joseph E. Clemente, Mads S. Thomsen, Richard C. Zimmerman
Summary: This study used high-resolution remote sensing and seascape metrics to analyze the spatiotemporal dynamics of intertidal and shallow subtidal seagrass meadows in 20 estuaries in New Zealand. The results showed that the distribution and extent of seagrass meadows varied over time and space, with no clear patterns observed over the 5-year period. However, some estuaries experienced seagrass expansion during periods of higher sea surface temperature.
REMOTE SENSING IN ECOLOGY AND CONSERVATION
(2023)
Article
Geochemistry & Geophysics
Daniel F. S. Santos, Joao P. Papa
Summary: This paper introduces a lightweight temporal attention network, TITAN, to address false positive and false negative alarms in change detection and reduce processing overhead. Experimental results show that the proposed approach outperforms other techniques in various evaluation metrics.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2023)
Article
Environmental Sciences
Stephen Carpenter, Val Byfield, Stacey L. Felgate, David M. Price, Valdemar Andrade, Eliceo Cobb, James Strong, Anna Lichtschlag, Hannah Brittain, Christopher Barry, Alice Fitch, Arlene Young, Richard Sanders, Claire Evans
Summary: This study presents a three-step approach for mapping percentage seagrass cover in Turneffe Atoll, Belize, combining in situ, aerial, and satellite data analysis.
Article
Environmental Sciences
Jonathan R. Rodemann, W. Ryan James, Rolando O. Santos, Bradley T. Furman, Zachary W. Fratto, Valentina Bautista, Jan Lara Hernandez, Natasha M. Viadero, Joshua O. Linenfelser, Lulu A. Lacy, Margaret O. Hall, Christopher R. Kelble, Christopher Kavanagh, Jennifer S. Rehage
Summary: Different disturbances can impact seagrass ecosystems at varying scales with varying consequences. Combining satellite imagery with field data helps monitor disturbances and investigating disturbances at various scales is important to understand seagrass resilience in the context of future extreme events.
FRONTIERS IN MARINE SCIENCE
(2021)
Article
Environmental Sciences
Hongyang Yin, Chong Ma, Liguo Weng, Min Xia, Haifeng Lin
Summary: This study proposes a bitemporal remote sensing image change detection network called SAFNet, which is based on a Siamese-attention feedback architecture and achieves satisfying results using deep learning and fully convolutional neural networks. The network addresses the issue of incomplete change detection results by introducing a global semantic module (GSM), a temporal interaction module (TIM), and two auxiliary modules (CFEM and FRM).
Article
Environmental Sciences
Md Ataullah Raza Khan, Shaktiman Singh, Pratima Pandey, Anshuman Bhardwaj, Sheikh Nawaz Ali, Vasudha Chaturvedi, Prashant Kumar Champati Ray
Summary: This study quantified the distribution of permafrost in the Western Himalaya using multisource satellite datasets, revealing a large portion of barren land and majority of the area with a mean annual air temperature below 1 degree Celsius. The research also showed high interannual variability in permafrost distribution and a significant decrease in permafrost cover from 2002 to 2020.
