{"title":"中国绿化特征差异及其对全球绿化的贡献","authors":"X. Zhang, D. H. Yan, T. L. Qin, C. H. Li, H. Wang","doi":"10.3808/jei.202300502","DOIUrl":null,"url":null,"abstract":"With the rapid emergence of the global greening phenomenon under remote sensing monitoring, the prevailing trend of phenomenon analysis and traceability research is self-evident. However, identifying characteristics is basic research of the greening phenomenon, which sometimes subverts research results. The choice of method may directly affect the difference in the greening-browning range, which is easily overlooked. At the same time, influenced by the regional vegetation state’s basic value, the greening contribution’s spatialization still needs to be further verified. Based on the enhanced vegetation index results at the global kilometer-grid scale, this research chose to use the maximum value composite and the simple average method to explore the differences in China’s characteristic identification process initially. While paying attention to results and phenomena, scholars’ attention to basic research needs further improvement. The results show that the widely used two groups of basic methods have shown noticeable differences in greening and browning, and are affected by human activities, climate, geographical environment, etc. And this directional error and the phenomenon of hasty generalization are the most easily ignored in much basic research. The vegetation information considering the inherent stock and changing flux has quantified the greening contribution between regions. China, Brazil, and India dominate global greening, and Canada significantly contributes to browning. Some regions must promote the greening trend of changing flux while maintaining the inherent stock advantage.","PeriodicalId":54840,"journal":{"name":"Journal of Environmental Informatics","volume":null,"pages":null},"PeriodicalIF":6.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Differences in China Greening Characteristics and its Contribution to Global Greening\",\"authors\":\"X. Zhang, D. H. Yan, T. L. Qin, C. H. Li, H. Wang\",\"doi\":\"10.3808/jei.202300502\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the rapid emergence of the global greening phenomenon under remote sensing monitoring, the prevailing trend of phenomenon analysis and traceability research is self-evident. However, identifying characteristics is basic research of the greening phenomenon, which sometimes subverts research results. The choice of method may directly affect the difference in the greening-browning range, which is easily overlooked. At the same time, influenced by the regional vegetation state’s basic value, the greening contribution’s spatialization still needs to be further verified. Based on the enhanced vegetation index results at the global kilometer-grid scale, this research chose to use the maximum value composite and the simple average method to explore the differences in China’s characteristic identification process initially. While paying attention to results and phenomena, scholars’ attention to basic research needs further improvement. The results show that the widely used two groups of basic methods have shown noticeable differences in greening and browning, and are affected by human activities, climate, geographical environment, etc. And this directional error and the phenomenon of hasty generalization are the most easily ignored in much basic research. The vegetation information considering the inherent stock and changing flux has quantified the greening contribution between regions. China, Brazil, and India dominate global greening, and Canada significantly contributes to browning. Some regions must promote the greening trend of changing flux while maintaining the inherent stock advantage.\",\"PeriodicalId\":54840,\"journal\":{\"name\":\"Journal of Environmental Informatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":6.0000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Environmental Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3808/jei.202300502\",\"RegionNum\":1,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Environmental Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3808/jei.202300502","RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Differences in China Greening Characteristics and its Contribution to Global Greening
With the rapid emergence of the global greening phenomenon under remote sensing monitoring, the prevailing trend of phenomenon analysis and traceability research is self-evident. However, identifying characteristics is basic research of the greening phenomenon, which sometimes subverts research results. The choice of method may directly affect the difference in the greening-browning range, which is easily overlooked. At the same time, influenced by the regional vegetation state’s basic value, the greening contribution’s spatialization still needs to be further verified. Based on the enhanced vegetation index results at the global kilometer-grid scale, this research chose to use the maximum value composite and the simple average method to explore the differences in China’s characteristic identification process initially. While paying attention to results and phenomena, scholars’ attention to basic research needs further improvement. The results show that the widely used two groups of basic methods have shown noticeable differences in greening and browning, and are affected by human activities, climate, geographical environment, etc. And this directional error and the phenomenon of hasty generalization are the most easily ignored in much basic research. The vegetation information considering the inherent stock and changing flux has quantified the greening contribution between regions. China, Brazil, and India dominate global greening, and Canada significantly contributes to browning. Some regions must promote the greening trend of changing flux while maintaining the inherent stock advantage.
期刊介绍:
Journal of Environmental Informatics (JEI) is an international, peer-reviewed, and interdisciplinary publication designed to foster research innovation and discovery on basic science and information technology for addressing various environmental problems. The journal aims to motivate and enhance the integration of science and technology to help develop sustainable solutions that are consensus-oriented, risk-informed, scientifically-based and cost-effective. JEI serves researchers, educators and practitioners who are interested in theoretical and/or applied aspects of environmental science, regardless of disciplinary boundaries. The topics addressed by the journal include:
- Planning of energy, environmental and ecological management systems
- Simulation, optimization and Environmental decision support
- Environmental geomatics - GIS, RS and other spatial information technologies
- Informatics for environmental chemistry and biochemistry
- Environmental applications of functional materials
- Environmental phenomena at atomic, molecular and macromolecular scales
- Modeling of chemical, biological and environmental processes
- Modeling of biotechnological systems for enhanced pollution mitigation
- Computer graphics and visualization for environmental decision support
- Artificial intelligence and expert systems for environmental applications
- Environmental statistics and risk analysis
- Climate modeling, downscaling, impact assessment, and adaptation planning
- Other areas of environmental systems science and information technology.