Bibliometric Analysis of Global NDVI Research Trends from 1985 to 2021

被引:40
|
作者
Xu, Yang [1 ,2 ]
Yang, Yaping [2 ,3 ,4 ]
Chen, Xiaona [2 ,3 ,4 ]
Liu, Yangxiaoyue [2 ,3 ,4 ]
机构
[1] Henan Univ, Coll Geog & Environm Sci, Kaifeng 475004, Peoples R China
[2] Natl Sci & Technol Infrastruct China, Natl Earth Syst Sci Data Ctr, Beijing 100101, Peoples R China
[3] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
[4] Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Peoples R China
关键词
bibliometrix; NDVI; remote sensing; network analysis; visualization; Web of Science; DIFFERENCE VEGETATION INDEX; TIME-SERIES DATA; INDUCED LAND DEGRADATION; GOOGLE EARTH ENGINE; WATER INDEX; LEAF-AREA; SPOT-VEGETATION; ABSORBED PAR; NOAA-AVHRR; GREEN LAI;
D O I
10.3390/rs14163967
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
As one of the earliest remote sensing indices, the Normalized Difference Vegetation Index (NDVI) has been employed extensively for vegetation research. However, despite an abundance of NDVI review articles, these studies are predominantly limited to either one subject area or one area, with systematic NDVI reviews being relatively rare. Bibliometrics is a useful method of analyzing scientific literature that has been widely used in many disciplines; however, it has not yet been applied to comprehensively analyze NDVI research. Therefore, we used bibliometrics and scientific mapping methods to analyze citation data retrieved from the Web of Science during 1985-2021 with NDVI as the topic. According to the analysis results, the amount of NDVI research increased exponentially during the study period, and the related research fields became increasingly varied. Moreover, a greater number of satellite and aerial remote sensing platforms resulted in more diverse NDVI data sources. In future, machine learning methods and cloud computing platforms led by Google Earth Engine will substantially improve the accuracy and production efficiency of NDVI data products for more effective global research.
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页数:20
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