Results 41 to 50 of about 13,268,437 (192)

Coastal Aquaculture Extraction Using GF-3 Fully Polarimetric SAR Imagery: A Framework Integrating UNet++ with Marker-Controlled Watershed Segmentation

Remote Sensing, 2023
Coastal aquaculture monitoring is vital for sustainable offshore aquaculture management. However, the dense distribution and various sizes of aquacultures make it challenging to accurately extract the boundaries of aquaculture ponds.
Juanjuan Yu, Xiufeng He, Peng Yang, M. Motagh, Jia Xu, Jiacheng Xiong   +5 more
semanticscholar   +1 more source

Analysis of Wave Breaking on Gaofen-3 and TerraSAR-X SAR Image and Its Effect on Wave Retrieval

Remote Sensing, 2023
The main purpose of our work is to investigate the performance of wave breaking and its effect on wave retrieval in data acquired from the Chinese Gaofen-3 (GF-3) synthetic aperture radar (SAR) at C-band and the German TerraSAR-X (TS-X) at X-band.
Ruozhu Zhong, W. Shao, Chi Zhao, Xingwei Jiang, J. Zuo   +4 more
semanticscholar   +1 more source

A Three-Hierarchy Evaluation of Polarimetric Performance of GF-3, Compared with ALOS-2/PALSAR-2 and RADARSAT-2

Sensors, 2019
GaoFen-3 (GF-3) is the first Chinese civilian multi-polarization synthetic aperture radar (SAR) satellite, launched on 10 August of 2016, and put into operation at the end of January 2017.
Zezhong Wang, Jian Jiao, Qiming Zeng, Junyi Liu   +3 more
doaj   +1 more source

Robust boundary extraction of great lakes by blocking Active Contour Model using Chinese GF-3 SAR data: a case study of Danjiangkou reservoir, China

The Journal of Engineering, 2019
Chinese Gaofen-3 (GF-3) satellite is a spaceborne multi-polarisation synthetic aperture radar (SAR) mission in C-band and it can be applied in the multiple fields. GF-3 can achieve accurate water boundary extraction based on its high-resolution SAR image
Shilin Niu, Ning Li, Zhengwei Guo, Robert Wang, Yuexiu Guo, Lin Wu, Jianhui Zhao   +6 more
doaj   +1 more source

GF-3 Polarimetric Data Quality Assessment Based on Automatic Extraction of Distributed Targets

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
With the needs of continuous data quality assessment for massive Gaofen-3 (GF-3) polarimetric data, an automatic and efficient quality evaluation method is urgently needed.
Songtao Shangguan, Xiaolan Qiu, Kun Fu, Bin Lei, Wen Hong   +4 more
doaj   +1 more source

Preliminary analysis of wave retrieval from Chinese Gaofen-3 SAR imagery in the Arctic Ocean

, 2022
Synthetic aperture radar (SAR) is a powerful tool for sea surface monitoring. The 2017–2020 mission of the Chinese Gaofen-3 (GF-3) over the Arctic Ocean provided a unique opportunity to investigate the feasibility of wave retrieval in the Arctic Ocean ...
Xing-Wei Jiang, Wei Shen, Jun-Cheng Zuo, Wei-Zeng Shao, Chi Zhao, Wei-Li Wang   +5 more
core   +1 more source

Deep Learning Based Sea Ice Classification with Gaofen-3 Fully Polarimetric SAR Data

Remote Sensing, 2021
In this paper, the performance of C-band synthetic aperture radar (SAR) Gaofen-3 (GF-3) quad-polarization Stripmap (QPS) data is assessed for classifying late spring and summer sea ice types.
Tianyu Zhang, Ying Yang, M. Shokr, C. Mi, Xiaoming Li, Xiao Cheng, Fengming Hui   +6 more
semanticscholar   +1 more source

Investigation of Polarimetric Decomposition for Arctic Summer Sea Ice Classification Using Gaofen-3 Fully Polarimetric SAR Data

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
The aim of this article was to investigate the potential of polarimetric decomposition of Chinese Gaofen-3 (GF-3) C-band fully polarimetric synthetic aperture radar (PolSAR) data for Arctic sea ice classification during summer season.
Lian He, Xiyi He, Fengming Hui, Yufang Ye, Tianyu Zhang, Xiao Cheng   +5 more
semanticscholar   +1 more source

Improving Forest Aboveground Biomass Estimation Accuracy via Optical and SAR Data Fusion Using Deep Learning Algorithms

Remote Sensing
Forest above-ground biomass (AGB) estimation is crucial for evaluating carbon dynamics. Although optical and synthetic aperture radar (SAR) data provide complementary spectral and structural information, limitations in existing fusion approaches restrict
Guoqing Wang, Lixian Zhao, Ci Song, Wangfei Zhang, Wenquan Dong, Yongjie Ji   +5 more
doaj   +1 more source

Integration of GF2 Optical, GF3 SAR, and UAV Data for Estimating Aboveground Biomass of China’s Largest Artificially Planted Mangroves

Remote Sensing, 2020
Accurate methods to estimate the aboveground biomass (AGB) of mangroves are required to monitor the subtle changes over time and assess their carbon sequestration. The AGB of forests is a function of canopy-related information (canopy density, vegetation
Yuanhui Zhu, Kai Liu, Soe W. Myint, Zhenyu Du, Yubin Li, Jingjing Cao, Lin Liu, Zhifeng Wu   +7 more
doaj   +1 more source