Articles | Volume 13, issue 5
https://doi.org/10.5194/essd-13-1829-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-13-1829-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A new satellite-derived dataset for marine aquaculture areas in China's coastal region
Yongyong Fu
College of Environmental and Resource Sciences, Zhejiang University,
Hangzhou, 310058, China
Jinsong Deng
CORRESPONDING AUTHOR
College of Environmental and Resource Sciences, Zhejiang University,
Hangzhou, 310058, China
Hongquan Wang
College of Environmental and Resource Sciences, Zhejiang University,
Hangzhou, 310058, China
Alexis Comber
School of Geography, University of Leeds, Leeds LS1 9JT, UK
Wu Yang
College of Environmental and Resource Sciences, Zhejiang University,
Hangzhou, 310058, China
Wenqiang Wu
College of Environmental and Resource Sciences, Zhejiang University,
Hangzhou, 310058, China
Shixue You
College of Environmental and Resource Sciences, Zhejiang University,
Hangzhou, 310058, China
Yi Lin
Department of Geography, University of Hong Kong, Hong Kong SAR
999077, China
Ke Wang
College of Environmental and Resource Sciences, Zhejiang University,
Hangzhou, 310058, China
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- Remote sensing and computer vision for marine aquaculture S. Quaade et al. 10.1126/sciadv.adn4944
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- Spatiotemporal Expansion of Algal Blooms in Coastal China Seas K. Zeng et al. 10.1021/acs.est.4c01877
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- Dynamics of coastal land-based aquaculture pond in China and Southeast Asia from 1990 to 2020 Y. Jiang et al. 10.1016/j.jag.2024.103654
- Intelligent Detection of Marine Offshore Aquaculture with High-Resolution Optical Remote Sensing Images D. Dong et al. 10.3390/jmse12061012
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36 citations as recorded by crossref.
- Deep-Learning-Based Marine Aquaculture Zone Extractions From Dual-Polarimetric SAR Imagery W. Chen & X. Li 10.1109/JSTARS.2024.3384511
- OMAD-6: Advancing Offshore Mariculture Monitoring with a Comprehensive Six-Type Dataset and Performance Benchmark Z. Mo et al. 10.3390/rs16234522
- Mapping the spatial distribution of global mariculture production G. Clawson et al. 10.1016/j.aquaculture.2022.738066
- TCNet: A Transformer–CNN Hybrid Network for Marine Aquaculture Mapping from VHSR Images Y. Fu et al. 10.3390/rs15184406
- Marine floating raft aquaculture extraction of hyperspectral remote sensing images based decision tree algorithm T. Hou et al. 10.1016/j.jag.2022.102846
- Estimating four-decadal variations of seagrass distribution using satellite data and deep learning methods in a marine lagoon L. Wang et al. 10.1016/j.scitotenv.2024.170936
- Long Time-Series Mapping and Change Detection of Coastal Zone Land Use Based on Google Earth Engine and Multi-Source Data Fusion D. Chen et al. 10.3390/rs14010001
- Mapping China’s offshore mariculture based on dense time-series optical and radar data X. Liu et al. 10.1080/17538947.2022.2108923
- A Deep Learning Method for Offshore Raft Aquaculture Extraction Based on Medium-Resolution Remote Sensing Images J. Liu et al. 10.1109/JSTARS.2023.3291499
- RaftNet: A New Deep Neural Network for Coastal Raft Aquaculture Extraction from Landsat 8 OLI Data H. Su et al. 10.3390/rs14184587
- Harbor Aquaculture Area Extraction Aided with an Integration-Enhanced Gradient Descent Algorithm Y. Zhong et al. 10.3390/rs13224554
- Segment Anything Model (SAM) Assisted Remote Sensing Supervision for Mariculture—Using Liaoning Province, China as an Example Y. Ren et al. 10.3390/rs15245781
- Mapping the fine spatial distribution of global offshore surface seawater mariculture using remote sensing big data Y. Liu et al. 10.1080/17538947.2024.2402418
- Red tide detection based on high spatial resolution broad band optical satellite data R. Liu et al. 10.1016/j.isprsjprs.2021.12.009
- The Assessment of More Suitable Image Spatial Resolutions for Offshore Aquaculture Areas Automatic Monitoring Based on Coupled NDWI and Mask R-CNN Y. Wang et al. 10.3390/rs14133079
- Marine Infrastructure Detection with Satellite Data—A Review R. Spanier & C. Kuenzer 10.3390/rs16101675
- Heavy metals in riverine/estuarine sediments from an aquaculture wetland in metropolitan areas, China: Characterization, bioavailability and probabilistic ecological risk H. Li et al. 10.1016/j.envpol.2023.121370
- Mapping of Greek Marine Finfish Farms and Their Potential Impact on the Marine Environment G. Katselis et al. 10.3390/jmse10020286
- Changes in the spatial distribution of mariculture in China over the past 20 years Y. Liu et al. 10.1007/s11442-023-2181-z
- Remote sensing and computer vision for marine aquaculture S. Quaade et al. 10.1126/sciadv.adn4944
- Detection and Statistics of Offshore Aquaculture Rafts in Coastal Waters C. Zhou et al. 10.3390/jmse10060781
- Spatial Distribution and Differentiation Analysis of Coastal Aquaculture in China Based on Remote Sensing Monitoring D. Meng et al. 10.3390/rs16091585
- Spatiotemporal Expansion of Algal Blooms in Coastal China Seas K. Zeng et al. 10.1021/acs.est.4c01877
- The influence of shellfish farming on sedimentary organic carbon mineralization: A case study in a coastal scallop farming area of Yantai, China M. Zhao & S. Zhang 10.1016/j.marpolbul.2022.113941
- Policy-driven opposite changes of coastal aquaculture ponds between China and Vietnam: Evidence from Sentinel-1 images Z. Sun et al. 10.1016/j.aquaculture.2023.739474
- Preparation and application of multi-source solid wastes as clean aggregates: A comprehensive review J. Wang & H. Dong 10.1016/j.conbuildmat.2024.135414
- Ecosystem Services of Ecosystem Approach to Mariculture: Providing an Unprecedented Opportunity for the Reform of China’s Sustainable Aquaculture X. Zhou et al. 10.3389/fmars.2022.909231
- Dynamics of coastal land-based aquaculture pond in China and Southeast Asia from 1990 to 2020 Y. Jiang et al. 10.1016/j.jag.2024.103654
- Intelligent Detection of Marine Offshore Aquaculture with High-Resolution Optical Remote Sensing Images D. Dong et al. 10.3390/jmse12061012
- Mapping of land-based aquaculture regions in Southeast Asia and its Spatiotemporal change from 1990 to 2020 using time-series remote sensing data J. Zhang et al. 10.1016/j.jag.2023.103518
- Seagrass classification using unsupervised curriculum learning (UCL) N. Abid et al. 10.1016/j.ecoinf.2024.102804
- Marine aquaculture mapping using GF-1 WFV satellite images and full resolution cascade convolutional neural network Y. Fu et al. 10.1080/17538947.2022.2133184
- Long-term human expansion and the environmental impacts on the coastal zone of China Y. Wang et al. 10.3389/fmars.2022.1033466
- An Attention-Fused Deep Learning Model for Accurately Monitoring Cage and Raft Aquaculture at Large-Scale Using Sentinel-2 Data Y. Xu & L. Lu 10.1109/JSTARS.2024.3390762
- Remote Data for Mapping and Monitoring Coastal Phenomena and Parameters: A Systematic Review R. Cavalli 10.3390/rs16030446
- Ecological Security Pattern Construction in Loess Plateau Areas—A Case Study of Shanxi Province, China Y. Fu et al. 10.3390/land13050709
Latest update: 13 Dec 2024
Short summary
Marine aquaculture areas in a region up to 30 km from the coast in China were mapped for the first time. It was found to cover a total area of ~1100 km2, of which more than 85 % is marine plant culture areas, with 87 % found in four coastal provinces. The results confirm the applicability and effectiveness of deep learning when applied to GF-1 data at the national scale, identifying the detailed spatial distributions and supporting the sustainable management of coastal resources in China.
Marine aquaculture areas in a region up to 30 km from the coast in China were mapped for the...
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