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Application progress of Google Earth Engine in land use and land cover remote sensing information extraction |
MOU Xiaoli1,2(), LI He1(), HUANG Chong1, LIU Qingsheng1, LIU Gaohuan1 |
1. State Key Laboratory of Resource and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China 2. School of Earth Science and Resources, China University of Geosciences (Beijing), Beijing 100083, China |
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Abstract Google Earth Engine is a cloud-based, global-scale geospatial analysis platform that makes full use of Google Earth’s rich data resources and cloud computing power to store and process petabyte-level data, being an effective and convenient tool for remote sensing research. Based on the introduction of Google Earth Engine system architecture, the authors firstly sorted out the research fields of Google Earth Engine. 291 related articles on CNKI and Web of Science published from 2011 to 2019 were analyzed, and some results were concluded such as publication time, research field, research area, the first author’s institution and journal of the article. Then the authors analyzed Google Earth Engine’s application and research trends of land use and land cover. The authors found that Google Earth Engine is widely used in the field of land cover remote sensing information extraction and has advantages in global or large-scale study. Based on the advantages of Google Earth Engine in remote sensing information extraction, the authors divided the study fields into agricultural remote sensing mapping, vegetation extent mapping and dynamic monitoring, building extraction, hydrological information extraction and land cover classification mapping. The research and application progress of Google Earth Engine was elaborated from two aspects: large-area mapping and multi-temporal dynamic monitoring. Finally, the authors discussed the Google Earth Engine’s problems and the development potential in land use and land cover. This paper is intended to serve as a basis for further understanding the advantages, application status, trends and potential of Google Earth Engine as well as for further understanding and using Google Earth Engine in the future.
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Keywords
cloud computing
Google Earth Engine
remote sensing
land cover
information extraction
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Corresponding Authors:
LI He
E-mail: 2804747677@qq.com;lih@lreis.ac.cn
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Issue Date: 21 July 2021
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