ISSN (Print):
2210-2981
ISSN (Online):
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Current Chinese Science

Volume 4 , Issues 6, 2024

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Limited Time Complementary Open Access Offer Papers submitted before December 31st, 2024, will be published as Open Access free of charge

About The Section


Journal
Remote Sensing

Publishes original research articles, letters, reviews/mini- reviews and guest edited thematic issues on various topics related to remote sensing. 

The Remote Sensing section of the journal Current Chinese Science publishes original research articles, letters, reviews/mini- reviews and guest edited thematic issues on various topics related to remote sensing. 

This section is not limited to a specific aspect of the field but is instead devoted to a wide range of sub fields in the area. Articles of a multidisciplinary nature are particularly welcome. Submissions in the following remote sensing areas are of special interest to the readers of this journal:

• Atmospheric science and meteorology
• Dedicated satellite missions
• Economic surveys and cost-benefit analyses
• Empirical analysis techniques
• Environmental remote sensing and applications
• Geometric reconstruction
• Hyperspectral remote sensing of water and minerals
• Image processing
• Image processing and pattern recognition
• Imaging and related sensors
• Land cover and land use change
• Lidar and laser scanning
• Marine remote sensing and coastal studies
• Mechanistic modeling and inversion
• Microwave remote sensing
• Multi-spectral and hyperspectral remote sensing
• New sensor systems
• Optical and microwave remote sensing of earth observation
• Remote sensing applications
• Remotely sensed data collection and use
• Sensor networks and sensing systems
• Support to land management
• Time series/change analysis
• Others

Section Editor-in-Chief(s) remsens_tang-bohui-as_001 Tang Bo-Hui Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences China

Dr Bo-Hui Tang received his PhD degree in Quantitative Remote Sensing in 2007 from the Institute of Geographic Sciences and Natural Resources Research (IGSNRR), Chinese Academy of Sciences, Beijing, China. Currently, he is a Researcher at IGSNRR. His research interests include quantitative estimation of land surface variables from satellite data, hyperspectral thermal infrared data analysis, parameterization of land surface processes at large scale with parameters directly/indirectly accessible from space measurements, and radiative transfer modelling. He has published more than 130 peer-reviewed scientific publications. He was honoured by the Chinese government in 2019 with “the Second Prize of the State Natural Science Award.”.

tangbh@igsnrr.ac.cn Scopus RsearcherId
remsens_yuanzhi-zhang-as_001 Zhang Yuanzhi Nanjing University of Information Science and Technology Nanjing China

Dr. Yuanzhi Zhang is currently working as a Professor at the Nanjing University of Information Science and Technology, China. He received his Doctor of Science from the Helsinki University of Technology, Espoo, Finland in 2005. His research interests include marine remote sensing and coastal studies, hyperspectral remote sensing of water and minerals, environmental remote sensing and applications, optical and microwave remote sensing of earth observation. Moreover, due to his contribution in his relevant field, he received several awards and has published some articles in well-reputed journals.

yuanzhizhang@cuhk.edu.hk Scopus RsearcherId
Editorial Board Members ccs_ebm_Hu-rong_001 Hu Ronghai College of Resources and Environment University of Chinese Academy of Science Beijing China

Ronghai Hu obtained his PHD in Remote Sensing from the University of Strasbourg in 2018. He is currently a Lecturer in the College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China. His research interests include indirect measurement, airborne and satellite retrieval of Leaf Area Index (LAI), Light Detection and Ranging (LiDAR), vegetation remote sensing and ecological application, and scale effect on remote sensing. Dr. Hu has achieved several awards including Best Poster Award, International Workshop on Terrestrial Water Cycle Observation and Modeling from Space: Innovation and Reliability of Data Products in 2013.

huronghai@ucas.ac.cn
remsens_ren-h-as_001 Ren H. Peking University Beijing China

Dr. Huazhong REN is currently an Assistant Professor with the Institute of Remote and Geographic Information System, School of Earth and Space Sciences, Peking University, China. His research interests include land surface temperature/emissivity retrieval from thermal infrared remote-sensing images, such as Chinese Gaofen-5, Landsats, MODIS and Sentinel-3. Moreover, Dr. REN also conducts the modelling of directional thermal radiation over land surface and makes angular correction on land surface temperature.

renhuazhong@pku.edu.cn
remsens_zhong-r-as_001 Zhong R. Capital Normal University Beijing China

Dr. Ruofei Zhong received the Ph.D. degree from the Chinese Academy of Science’s Institute of Remote Sensing Applications, Beijing, China, in 2005. He is currently a Professor at Key Lab of 3-Dimensional Information Acquisition and Application, Ministry of Education, College of Resource Environment and Tourism, Capital Normal University, Beijing, China. His research interests include remote sensing satellite design and data preprocessing, multi-sensor LiDAR integration and post-processing, deep learning and computer vision.

zrfsss@163.com
remsens_cheng-j-as_001 Cheng J. Beijing Normal University Beijing China

Dr. Jie Cheng, received the Ph.D. degree in cartography and remote sensing from the Institute of Remote Sensing Applications of Chinese Academy of Sciences, Beijing, China, in 2008. He was a Postdoctoral Fellow with the State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing, China, from 2008 to 2010, an Assistant Research Scientist with the University of Maryland, College Park, from 2009 to 2010, and a Visiting Scientist with the Hydrology and Remote Sensing Laboratory, United States Department of Agriculture-Agricultural Research Service, Beltsville, MD, USA, from 2017 to 2018. He is currently an Associate Professor with the State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University. His main research interests include estimation of land surface variables from satellite observations, radiative transfer modeling, and studies on surface energy balance. He published over 60 SCI indexed peer-reviewed papers, 7 book chapters, and 2 special issues of Remote Sensing.

brucechan2003@126.com
remsens_jiang-gm-as_001 Jiang G-M. Fudan University Shanghai China

Dr. Jiang received the B.S. degree in photogrammetric engineering and remote sensing from Wuhan Technical University of Surveying and Mapping, Wuhan, China, in 1997, the M.S. degree in cartography and geographical information system from the Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing, China, in 2003, and the Ph.D. degree in remote sensing from Université Louis Pasteur, Strasbourg, France, in 2007. Dr. Jiang is currently an Associate Professor at the Key Laboratory for Information Science of Electromagnetic Waves (Ministry of Education), Fudan University, Shanghai, China. His research interest mainly focuses on intercalibration of satellite instruments and quantitative remote sensing.

jianggm@fudan.edu.cn
remsens_huang-j-as_001 Huang J. China Agricultural University Beijing China

Prof. Jianxi Huang currently works at the Department of Geographical Information Engineering, China Agricultural University. His research interests include agricultural monitoring with remote sensing, data assimilation; deep learning; crop yield prediction; crop modeling.

08038@cau.edu.cn

Section: Remote Sensing


Research Article

Multi-temporal Cloud Pixels Reconstruction Method for Optical Remote Sensing Satellite Images

Volume: 2, Issue: 6
Pp: 479-488
Author: Huiqian Liu, Ruofei Zhong*, Haiyin Wang, Shiyong Wu, Qingyang Li and Cankun Yang
DOI: 10.2174/2210298102666220616114622
Published on: 25 August, 2022

Research Article

High-Performance Fault Classification Based on Feature Importance Ranking-XgBoost Approach with Feature Selection of Redundant Sensor Data

Volume: 2, Issue: 3
Pp: 243-251
Author: Jilun Tian, Yuchen Jiang, Jiusi Zhang, Zhenhua Wang, Juan J. Rodríguez-Andina and Hao Luo*
DOI: 10.2174/2210298102666220318100051
Published on: 26 April, 2022

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