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• 地理科学与资源研究... [41]

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• OAI收割 [41]

内容类型

• 期刊论文 [41]

发表日期

• 2024 [2]
• 2023 [5]
• 2022 [10]
• 2021 [4]
• 2020 [6]
• 2019 [3]
• 更多

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• Multidisci... [1]

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浏览/检索结果: 共41条，第1-10条 帮助 限定条件 专题：地理科学与资源研究所    第一署名单位    第一作者单位    通讯作者单位     条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择提交时间升序提交时间降序发表日期升序发表日期降序题名升序题名降序作者升序作者降序 A four-band index for both liquid and solid water and its applications in the Aral Sea Basin 期刊论文  OAI收割 SCIENCE CHINA-EARTH SCIENCES, 2024, 卷号: N/A 作者:  Yue, Bing;  Chen, Xi;  Li, Saibo;  Du, Zhengping;  Wilson, John   |  收藏  |  浏览/下载：17/0  |  提交时间：2024/04/08 Aral Sea Basin  Syr river basin  Amu river basin  Water indices  Water-coverage area  Water deficit  Climate change   The Greenhouse Gas Budget of Terrestrial Ecosystems in East Asia Since 2000 期刊论文  OAI收割 GLOBAL BIOGEOCHEMICAL CYCLES, 2024, 卷号: 38, 期号: 2, 页码: 21 作者:  Wang, Xuhui;  Gao, Yuanyi;  Jeong, Sujong;  Ito, Akihiko;  Bastos, Ana   |  收藏  |  浏览/下载：5/0  |  提交时间：2024/04/01 East Asia  greenhouse gas  terrestrial ecosystems  budget  RECCAP-2   Ecosystem responses dominate the trends of annual gross primary productivity over terrestrial ecosystems of China during 2000-2020 期刊论文  OAI收割 AGRICULTURAL AND FOREST METEOROLOGY, 2023, 卷号: 343, 页码: 109758 作者:  Zhu, Xian-Jin;  Yu, Gui-Rui;  Chen, Zhi;  Zhang, Wei-Kang;  Han, Lang   |  收藏  |  浏览/下载：13/0  |  提交时间：2023/12/04 Carbon cycles  Eddy covariance  Terrestrial ecosystems  Machine learning  Ecosystem responses   Competition for nitrogen between plants and microorganisms in grasslands: effect of nitrogen application rate and plant acquisition strategy 期刊论文  OAI收割 BIOLOGY AND FERTILITY OF SOILS, 2023, 页码: 10 作者:  Zhang, Li;  Liu, Jie;  Xi, Jiazhen;  Pang, Rui;  Gunina, Anna   |  收藏  |  浏览/下载：7/0  |  提交时间：2024/01/02 Nitrogen cycling  Plant functional composition  Plant-microbial N competition  Rhizosphere interactions  Root traits   Co-firing plants with retrofitted carbon capture and storage for power-sector emissions mitigation 期刊论文  OAI收割 NATURE CLIMATE CHANGE, 2023, 页码: 14 作者:  Fan, Jing-Li;  Fu, Jingying;  Zhang, Xian;  Li, Kai;  Zhou, Wenlong   |  收藏  |  浏览/下载：8/0  |  提交时间：2023/10/09 Mapping Chinese annual gross primary productivity with eddy covariance measurements and machine learning 期刊论文  OAI收割 SCIENCE OF THE TOTAL ENVIRONMENT, 2023, 卷号: 857, 页码: 18 作者:  Zhu, Xian-Jin;  Yu, Gui-Rui;  Chen, Zhi;  Zhang, Wei-Kang;  Han, Lang   |  收藏  |  浏览/下载：41/0  |  提交时间：2022/12/09 Carbon cycle  Climate change  Eddy covariance  Terrestrial ecosystem  Machine learning  Scale extension   Mapping Chinese annual gross primary productivity with eddy covariance measurements and machine learning 期刊论文  OAI收割 SCIENCE OF THE TOTAL ENVIRONMENT, 2023, 卷号: 857, 页码: 18 作者:  Zhu, Xian-Jin;  Yu, Gui-Rui;  Chen, Zhi;  Zhang, Wei-Kang;  Han, Lang   |  收藏  |  浏览/下载：28/0  |  提交时间：2022/12/09 Carbon cycle  Climate change  Eddy covariance  Terrestrial ecosystem  Machine learning  Scale extension   CCHZ-DISO: A Timely New Assessment System for Data Quality or Model Performance From Da Dao Zhi Jian 期刊论文  OAI收割 GEOPHYSICAL RESEARCH LETTERS, 2022, 卷号: 49, 期号: 23, 页码: 9 作者:  Hu, Zengyun;  Chen, Deliang;  Chen, Xi;  Zhou, Qiming;  Peng, Yuzhou   |  收藏  |  浏览/下载：16/0  |  提交时间：2023/03/20 CCHZ-DISO assessment system  model performance  data quality  statistical metric   Spatiotemporal Pattern of Ecosystem Respiration in China Estimated by Integration of Machine Learning With Ecological Understanding 期刊论文  OAI收割 GLOBAL BIOGEOCHEMICAL CYCLES, 2022, 卷号: 36, 期号: 11, 页码: 15 作者:  Han, Lang;  Yu, Gui-Rui;  Chen, Zhi;  Zhu, Xian-Jin;  Zhang, Wei-Kang   |  收藏  |  浏览/下载：45/0  |  提交时间：2022/12/23 ecosystem respiration  eddy covariance  terrestrial ecosystem  machine learning  substrate  scale extension   Spatiotemporal Pattern of Ecosystem Respiration in China Estimated by Integration of Machine Learning With Ecological Understanding 期刊论文  OAI收割 GLOBAL BIOGEOCHEMICAL CYCLES, 2022, 卷号: 36, 期号: 11, 页码: 15 作者:  Han, Lang;  Yu, Gui-Rui;  Chen, Zhi;  Zhu, Xian-Jin;  Zhang, Wei-Kang   |  收藏  |  浏览/下载：34/0  |  提交时间：2022/12/23 ecosystem respiration  eddy covariance  terrestrial ecosystem  machine learning  substrate  scale extension