Pub Date : 2023-01-11DOI: 10.34133/remotesensing.0022
Suming Jin, J. Dewitz, P. Danielson, B. Granneman, Catherine Costello, Kelcy Smith, Zhe Zhu
{"title":"National Land Cover Database 2019: A new strategy for creating clean leaf-on and leaf-off Landsat composite images","authors":"Suming Jin, J. Dewitz, P. Danielson, B. Granneman, Catherine Costello, Kelcy Smith, Zhe Zhu","doi":"10.34133/remotesensing.0022","DOIUrl":"https://doi.org/10.34133/remotesensing.0022","url":null,"abstract":"","PeriodicalId":38304,"journal":{"name":"Yaogan Xuebao/Journal of Remote Sensing","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47922990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-05DOI: 10.34133/remotesensing.0005
Zhongbing Chang, L. Fan, J. Wigneron, Ying‐ping Wang, P. Ciais, J. Chave, R. Fensholt, Jing-Ming Chen, Wenping Yuan, W. Ju, Xin Li, Fei Jiang, Mousong Wu, Xiuzhi Chen, Yuanwei Qin, F. Frappart, Xiaojun Li, Mengjia Wang, Xiangzhuo Liu, Xuli Tang, Sanaa Hobeichi, Mengxiao Yu, Mingguo Ma, Jianguang Wen, Q. Xiao, W. Shi, Dexin Liu, Junhua Yan
{"title":"Estimating aboveground carbon dynamic of China using optical and microwave remote sensing datasets from 2013 to 2019","authors":"Zhongbing Chang, L. Fan, J. Wigneron, Ying‐ping Wang, P. Ciais, J. Chave, R. Fensholt, Jing-Ming Chen, Wenping Yuan, W. Ju, Xin Li, Fei Jiang, Mousong Wu, Xiuzhi Chen, Yuanwei Qin, F. Frappart, Xiaojun Li, Mengjia Wang, Xiangzhuo Liu, Xuli Tang, Sanaa Hobeichi, Mengxiao Yu, Mingguo Ma, Jianguang Wen, Q. Xiao, W. Shi, Dexin Liu, Junhua Yan","doi":"10.34133/remotesensing.0005","DOIUrl":"https://doi.org/10.34133/remotesensing.0005","url":null,"abstract":"","PeriodicalId":38304,"journal":{"name":"Yaogan Xuebao/Journal of Remote Sensing","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44529243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xin XIAO, Hao CHEN, Bingli XU, Chaoyang FANG, Hui LIN
{"title":"A Preliminary Study of semantic Virtual Geographic Environment in the Context of Wetland Monitoring","authors":"Xin XIAO, Hao CHEN, Bingli XU, Chaoyang FANG, Hui LIN","doi":"10.11834/jrs.20233111","DOIUrl":"https://doi.org/10.11834/jrs.20233111","url":null,"abstract":"","PeriodicalId":38304,"journal":{"name":"Yaogan Xuebao/Journal of Remote Sensing","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135358427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.34133/remotesensing.0003
Carmen Morales, A. S. Díaz, Daniel Dionisio, Laura Guarnieri, G. Marchi, D. Maniatis, D. Mollicone
Earth Map ( https://earthmap.org/ ) is an innovative and free application developed by the Food and Agriculture Organization of the United Nations that was designed in the framework of the Food and Agriculture Organization of the United Nations–Google partnership and facilitates the visualization, processing, and analysis of land and climate data. Earth Map makes petabytes of multitemporal, multiscale, multiparametric, and quasi-real-time satellite imagery and geospatial datasets available to any user thanks to the power of Google Earth Engine ( https://earthengine.google.com/ ) and a point-and-click graphical user interface. These are further complemented with more planetary-scale analytical capabilities so that global and local changes and trends on Earth’s surface can be easily detected, quantified, and visualized. It does not require users to master coding techniques, thereby avoiding bottlenecks in terms of technical capacities of nonexpert users. It ultimately paves the way for countries, research institutes, farmers, and members of the general public to access critical knowledge to develop science-based policy interventions, leverage investments, and sustain livelihoods. We provide a full overview of Earth Map’s software architecture, design, features, and datasets. To illustrate the possible applications of the tool, different examples are presented including a few case studies that show how quick historical analysis of environmental and climate parameters can be performed and research questions answered. The examples demonstrate that Earth Map is a comprehensive and user-friendly tool for land monitoring and climate assessment and that it has the potential to be used to assess land use, land use change, climate change impacts, and natural disasters.
{"title":"Earth Map: A Novel Tool for Fast Performance of Advanced Land Monitoring and Climate Assessment","authors":"Carmen Morales, A. S. Díaz, Daniel Dionisio, Laura Guarnieri, G. Marchi, D. Maniatis, D. Mollicone","doi":"10.34133/remotesensing.0003","DOIUrl":"https://doi.org/10.34133/remotesensing.0003","url":null,"abstract":"\u0000 Earth Map (\u0000 https://earthmap.org/\u0000 ) is an innovative and free application developed by the Food and Agriculture Organization of the United Nations that was designed in the framework of the Food and Agriculture Organization of the United Nations–Google partnership and facilitates the visualization, processing, and analysis of land and climate data. Earth Map makes petabytes of multitemporal, multiscale, multiparametric, and quasi-real-time satellite imagery and geospatial datasets available to any user thanks to the power of Google Earth Engine (\u0000 https://earthengine.google.com/\u0000 ) and a point-and-click graphical user interface. These are further complemented with more planetary-scale analytical capabilities so that global and local changes and trends on Earth’s surface can be easily detected, quantified, and visualized. It does not require users to master coding techniques, thereby avoiding bottlenecks in terms of technical capacities of nonexpert users. It ultimately paves the way for countries, research institutes, farmers, and members of the general public to access critical knowledge to develop science-based policy interventions, leverage investments, and sustain livelihoods. We provide a full overview of Earth Map’s software architecture, design, features, and datasets. To illustrate the possible applications of the tool, different examples are presented including a few case studies that show how quick historical analysis of environmental and climate parameters can be performed and research questions answered. The examples demonstrate that Earth Map is a comprehensive and user-friendly tool for land monitoring and climate assessment and that it has the potential to be used to assess land use, land use change, climate change impacts, and natural disasters.\u0000","PeriodicalId":38304,"journal":{"name":"Yaogan Xuebao/Journal of Remote Sensing","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45085550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Accurately retrieving vegetation phenology at high spatial and temporal resolutions based on GEE and multi-source remote sensing data fusion","authors":"Jie Song, Zhao Zhang, Jichong Han","doi":"10.11834/jrs.20232646","DOIUrl":"https://doi.org/10.11834/jrs.20232646","url":null,"abstract":"","PeriodicalId":38304,"journal":{"name":"Yaogan Xuebao/Journal of Remote Sensing","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135101424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yifu Li, Bin Sun, Zhihai Gao, Bengyu Wang, Ziyu Yan, Wensen Su, Ting Gao, Wei Yue
{"title":"Farmland Shelterbelt Information Extraction Based on Multispectral Image of ZY-1-02E Satellite","authors":"Yifu Li, Bin Sun, Zhihai Gao, Bengyu Wang, Ziyu Yan, Wensen Su, Ting Gao, Wei Yue","doi":"10.11834/jrs.20232526","DOIUrl":"https://doi.org/10.11834/jrs.20232526","url":null,"abstract":"","PeriodicalId":38304,"journal":{"name":"Yaogan Xuebao/Journal of Remote Sensing","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135550134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Discussion on flood control application technology of digital twin Basin based on virtual geographic environment","authors":"Yi LI, Shi-feng HUANG, Wen-bin ZANG, Zhi-guo GAO","doi":"10.11834/jrs.20233022","DOIUrl":"https://doi.org/10.11834/jrs.20233022","url":null,"abstract":"","PeriodicalId":38304,"journal":{"name":"Yaogan Xuebao/Journal of Remote Sensing","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135758449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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