{"title":"Using multi-source data and time series features to construct a global terrestrial CO2 coverage by deep learning","authors":"Wenjie Tian, Lili Zhang, Tao Yu, Yu Wu, Wenhao Zhang, Zeyu Wang, Hao Zhu","doi":"10.1109/tgrs.2024.3462589","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":13213,"journal":{"name":"IEEE Transactions on Geoscience and Remote Sensing","volume":null,"pages":null},"PeriodicalIF":7.5000,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Geoscience and Remote Sensing","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1109/tgrs.2024.3462589","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
期刊介绍:
IEEE Transactions on Geoscience and Remote Sensing (TGRS) is a monthly publication that focuses on the theory, concepts, and techniques of science and engineering as applied to sensing the land, oceans, atmosphere, and space; and the processing, interpretation, and dissemination of this information.