Long-term mapping of land use and cover changes using Landsat images on the Google Earth Engine Cloud Platform in bay area - A case study of Hangzhou Bay, China

被引：0
|
作者：
Liang, Jintao [1 ]
Chen, Chao [2 ]
Song, Yongze [3 ]
Sun, Weiwei [4 ]
Yang, Gang [4 ]
机构：
[1] Marine Science and Technology College, Zhejiang Ocean University, Zhoushan,316022, China
[2] School of Geography Science and Geomatics Engineering, Suzhou University of Science and Technology, Suzhou,215009, China
[3] School of Design and the Built Environment, Curtin University, Perth,6102, Australia
[4] Department of Geography and Spatial Information Techniques, Ningbo University, Zhejiang, Ningbo,315211, China
来源：
Sustainable Horizons | 2023年 / 7卷
关键词：
The authors would like to thank the editors and the anonymous reviewers for their outstanding comments and suggestions; which greatly helped to improve the technical quality and presentation of this manuscript. We also greatly appreciate the United States Geological Survey (www.usgs.gov); the National Aeronautics and Space Administration (www.nasa.gov); and the Chinese Academy of Science (www.ids.ceode.ac.cn) for the free availability of Landsat remote sensing images. This work was supported by the National Natural Science Foundation of China (Grant Nos. 42171311; 42122009; 41971296); the Key Scientific and Technological Projects in Ningbo City (2021Z107); and the Zhejiang Provincial Natural Science Foundation of China (LR19D010001); the Public Projects of Ningbo City (2021S089); and the Training Program of Excellent Master Thesis of Zhejiang Ocean University. We thank LetPub (www.letpub.com) for its linguistic assistance during the preparation of this manuscript.The authors would like to thank the editors and the anonymous reviewers for their outstanding comments and suggestions; which greatly helped to improve the technical quality and presentation of this manuscript. We also greatly appreciate the United States Geological Survey ( www.usgs.gov ); the National Aeronautics and Space Administration ( www.nasa.gov ); and the Chinese Academy of Science ( www.ids.ceode.ac.cn ) for the free availability of Landsat remote sensing images. This work was supported by the National Natural Science Foundation of China (Grant Nos. 42171311; 41971296; the Key Scientific and Technological Projects in Ningbo City ( 2021Z107 ); and the Zhejiang Provincial Natural Science Foundation of China ( LR19D010001 ); the Public Projects of Ningbo City ( 2021S089 ); and the Training Program of Excellent Master Thesis of Zhejiang Ocean University. We thank LetPub ( www.letpub.com ) for its linguistic assistance during the preparation of this manuscript;
D O I：
10.1016/j.horiz.2023.100061
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