Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing

NWIPB OpenIR

	Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing
	Xie, Mingjuan; Ma, Xiaofei; Wang, Yuangang; Li, Chaofan; Shi, Haiyang; Yuan, Xiuliang; Hellwich, Olaf; Chen, Chunbo; Zhang, Wenqiang; Zhang, Chen; Ling, Qing; Gao, Ruixiang; Zhang, Yu; Ochege, Friday Uchenna; Frankl, Amaury; De Maeyer, Philippe; Buchmann, Nina; Feigenwinter, Iris; Olesen, Jorgen E.; Juszczak, Radoslaw; Jacotot, Adrien; Korrensalo, Aino; Pitacco, Andrea; Varlagin, Andrej; Shekhar, Ankit; Lohila, Annalea; Carrara, Arnaud; Brut, Aurore; Kruijt, Bart; Loubet, Benjamin; Heinesch, Bernard; Chojnicki, Bogdan; Helfter, Carole; Vincke, Caroline; Shao, Changliang; Bernhofer, Christian; Bruemmer, Christian; Wille, Christian; Tuittila, Eeva-Stiina; Nemitz, Eiko; Meggio, Franco; Dong, Gang; Lanigan, Gary; Niedrist, Georg; Wohlfahrt, Georg; Zhou, Guoyi; Goded, Ignacio; Gruenwald, Thomas; Olejnik, Janusz; Jansen, Joachim; Neirynck, Johan; Tuovinen, Juha-Pekka; Zhang, Junhui; Klumpp, Katja; Pilegaard, Kim; Sigut, Ladislav; Klemedtsson, Leif; Tezza, Luca; Hoertnagl, Lukas; Urbaniak, Marek; Roland, Marilyn; Schmidt, Marius; Sutton, Mark A.; Hehn, Markus; Saunders, Matthew; Mauder, Matthias; Aurela, Mika; Korkiakoski, Mika; Du, Mingyuan; Vendrame, Nadia; Kowalska, Natalia; Leahy, Paul G.; Alekseychik, Pavel; Shi, Peili; Weslien, Per; Chen, Shiping; Fares, Silvano; Friborg, Thomas; Tallec, Tiphaine; Kato, Tomomichi; Sachs, Torsten; Maximov, Trofim; di Cella, Umberto Morra; Moderow, Uta; Li, Yingnian; He, Yongtao; Kosugi, Yoshiko; Luo, Geping
	2023
发表期刊	SCIENTIFIC DATA
卷号	10 期号:1
摘要	Simulating the carbon-water fluxes at more widely distributed meteorological stations based on the sparsely and unevenly distributed eddy covariance flux stations is needed to accurately understand the carbon-water cycle of terrestrial ecosystems. We established a new framework consisting of machine learning, determination coefficient (R2), Euclidean distance, and remote sensing (RS), to simulate the daily net ecosystem carbon dioxide exchange (NEE) and water flux (WF) of the Eurasian meteorological stations using a random forest model or/and RS. The daily NEE and WF datasets with RS-based information (NEE-RS and WF-RS) for 3774 and 4427 meteorological stations during 2002-2020 were produced, respectively. And the daily NEE and WF datasets without RS-based information (NEE-WRS and WF-WRS) for 4667 and 6763 meteorological stations during 1983-2018 were generated, respectively. For each meteorological station, the carbon-water fluxes meet accuracy requirements and have quasi-observational properties. These four carbon-water flux datasets have great potential to improve the assessments of the ecosystem carbon-water dynamics.
收录类别	SCIE
文献类型	期刊论文
条目标识符	http://210.75.249.4/handle/363003/61580
专题	中国科学院西北高原生物研究所
推荐引用方式 GB/T 7714	Xie, Mingjuan,Ma, Xiaofei,Wang, Yuangang,et al. Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing[J]. SCIENTIFIC DATA,2023,10(1).
APA	Xie, Mingjuan.,Ma, Xiaofei.,Wang, Yuangang.,Li, Chaofan.,Shi, Haiyang.,...&Luo, Geping.(2023).Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing.SCIENTIFIC DATA,10(1).
MLA	Xie, Mingjuan,et al."Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing".SCIENTIFIC DATA 10.1(2023).