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遥感技术与应用  2022, Vol. 37 Issue (5): 1029-1042    DOI: 10.11873/j.issn.1004-0323.2022.5.1029
综述     
空间观测技术在油棕研究中的应用
赵强1(),俞乐2(),徐伊迪2,李唯嘉3,郑珏鹏2,付昊桓2,卢麾2,张永光1,宫鹏4
1.南京大学 地理与海洋科学学院,江苏 南京 210023
2.清华大学 地球系统科学系,北京 100084
3.香港中文大学 CUHK-商汤联合实验室,香港
4.香港大学 地理系/地球科学系,香港
Application of Space Observation Technology in Oil Palm Research
Qiang Zhao1(),Le Yu2(),Yidi Xu2,Weijia Li3,Juepeng Zheng2,Haohuan Fu2,Hui Lu2,Yongguang Zhang1,Peng Gong4
1.School of Geography and Ocean Science,Nanjing University,Nanjing 210023,China
2.Department of Earth System Science,Tsinghua University,Beijing 100084,China
3.CUHK-SenseTime Joint Lab,The Chinese University of Hong Kong,Hong Kong,China
4.Department of Geography and Earth Sciences,The University of Hong Kong,Hong Kong,China
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摘要:

油棕是一种重要的热带经济作物,在热带地区种植面积迅速扩张,已经成为全球最大的植物油来源。油棕扩张在带来经济效益的同时,也在不断侵占全球现有的森林、耕地和泥炭地,造成严重的生态环境问题。空间观测技术(RS、GIS、GNSS,3S技术)是空间信息收集、分析和管理的有效工具,在优化土地利用类型空间布局和可持续发展规划中发挥着重要作用。通过文献综述和文献计量学的方法,分析3S技术在油棕研究中的应用进展,并探讨影响油棕制图精度的关键因素。研究发现:该领域的论文主要以土地覆被变化研究为知识基础,来自马来西亚、美国、中国、印度尼西亚和英国的科研机构和研究人员是最主要参与者;目前3S技术在油棕研究中的应用包括油棕制图、油棕变化监测、油棕树计数、树龄估算、地上生物量与碳储量估算、适宜性评估、产量估算、病虫害监测、种植园管理等;制图精度与论文发表时间并没有明显相关性,与遥感数据源、分类方法具有相关性;目前油棕研究中的3S技术以RS为主导,RS应用于油棕研究的各个关键方向,GIS技术主要应用于油棕变化制图、适宜性评估、种植园管理、病虫害监测等,GNSS主要作为辅助工具,应用于病虫害监测和种植园管理等。

关键词: 油棕3S技术文献计量学分析可持续发展    
Abstract:

Oil palm is a major economic crop and the area of land converted to oil palm cultivation in the tropics has expanded rapidly. Oil palm has become the world's largest source of vegetable oil and it provides tremendous regional economic benefits. However, the expansion of oil palm cultivation has led to the loss of forests, arable land, and peatland, which has caused severe ecological and environmental problems. Application of 3S (RS, GIS, GNSS) technology is useful for the collection, analysis, and management of spatial information, and is essential for both optimizations of the spatial distribution of land use and sustainable development. This paper analyzes the progress of 3S technology application in oil palm research on the basis of a literature review and scientometric analysis. The factors affecting the precision of oil palm mapping are also discussed. We established that papers describing 3S technology application in oil palm research are based primarily on the study of land cover change, and that scientific institutions and researchers in Malaysia, the United States, China, Indonesia, and the United Kingdom are the major contributors. Currently, the application of 3S technology in oil palm research includes oil palm mapping, oil palm land change monitoring, oil palm tree counting, tree age estimation, aboveground biomass and carbon storage estimation, suitability analysis, yield estimation, pest and disease monitoring, and plantation management. The accuracy of mapping is not correlated significantly with the year of publication of specific literature but is correlated with RS data sources and classification methods. The use of 3S technology in oil palm research is currently dominated by RS, which has been used in diverse fields of oil palm research. GIS technology is used mainly for oil palm land change mapping, suitability analysis, plantation management, and pest and disease monitoring, while GNSS is used largely as an additional tool in pest and disease monitoring and plantation management.

Key words: Oil palm    3S technology    Scientometric analysis    Sustainable development
收稿日期: 2021-07-30 出版日期: 2022-12-13
ZTFLH:  TP79  
基金资助: 国家重点研发计划(2019YFA0606601);国家自然科学基金项目(41661144022)
通讯作者: 俞乐     E-mail: qiang.zhao@smail.nju.edu.cn;leyu@tsinghua.edu.cn
作者简介: 赵强(1997-),男,江苏宜春人,硕士研究生,主要从事土地覆盖/土地利用变化遥感和农业遥感研究。E?mail:qiang.zhao@smail.nju.edu.cn
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引用本文:

赵强,俞乐,徐伊迪,李唯嘉,郑珏鹏,付昊桓,卢麾,张永光,宫鹏. 空间观测技术在油棕研究中的应用[J]. 遥感技术与应用, 2022, 37(5): 1029-1042.

Qiang Zhao,Le Yu,Yidi Xu,Weijia Li,Juepeng Zheng,Haohuan Fu,Hui Lu,Yongguang Zhang,Peng Gong. Application of Space Observation Technology in Oil Palm Research. Remote Sensing Technology and Application, 2022, 37(5): 1029-1042.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2022.5.1029        http://www.rsta.ac.cn/CN/Y2022/V37/I5/1029

图1  不同时间段油棕研究的空间分布情况
图2  逐年油棕研究论文发表数量和引用次数统计
图3  关键词共现网络
图4  发文机构合作和地区合作图谱
图5  制图精度与论文出版时间的关系
图6  不同遥感数据源的使用频率
图7  不同遥感数据集的分类精度
图8  不同分类方法的使用频率与分类精度(MLC(Maximum Likelihood Classifier):最大似然分类器, OO(Object Based):基于对象的图像分析, RF(Random Forest):随机森林,SVM(Support Vector Machine):支持向量机)
图9  分类系统类别数量与精度的关系
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