Zobrazeno 1 - 10 of 28 pro vyhledávání: '"Yuqiao Long"'
1
Akademický článek
Mapping the Spatiotemporal Dynamics of Cropland Abandonment and Recultivation across the Yangtze River Basin
Autor: Yuqiao Long, Jing Sun, Joost Wellens, Gilles Colinet, Wenbin Wu, Jeroen Meersmans
Publikováno v: Remote Sensing, Vol 16, Iss 6, p 1052 (2024)
Whether China can achieve the United Nations’ Sustainable Development Goals (SDGs) largely depends on the ability of main food-producing areas to cope with multiple land use change challenges. Despite the fact that the Yangtze River basin is one of
Externí odkaz: https://doaj.org/article/ed38e8c7cbc74b238a928917fef514c5
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2
Akademický článek
An In-Depth Assessment of the Drivers Changing China’s Crop Production Using an LMDI Decomposition Approach
Autor: Yuqiao Long, Wenbin Wu, Joost Wellens, Gilles Colinet, Jeroen Meersmans
Publikováno v: Remote Sensing, Vol 14, Iss 24, p 6399 (2022)
Over the last decades, growing crop production across China has had far-reaching consequences for both the environment and human welfare. One of the emerging questions is “how to meet the growing food demand in China?” In essence, the consensus i
Externí odkaz: https://doaj.org/article/a995f60ac97c493b89763976a1f60176
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3
Cropland abandonment across the Yangtze River Basin does provide only limited benefits for C sequestration
Autor: Yuqiao Long, Jing Sun, Joost Wellens, Gilles Colinet, Wenbin Wu, Jeroen Meersmans
Recent estimates from satellite imageries indicated that extensive cropland abandonment took place across China due to rural outmigration, agricultural policy and environment changes[1-3]. Cropland abandonment provides an opportunity for C sequestrat
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::a081c200ab2d6315d1a06896045cbec8
https://doi.org/10.5194/egusphere-egu23-13923
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5
Groundwater contaminant source identification via Bayesian model selection and uncertainty quantification
Autor: Yuanyuan Sun, Jichun Wu, Tongtong Cao, Dong Wang, Xiankui Zeng, Yuqiao Long, Jin Lin, Xiaobin Zhu
Publikováno v: Hydrogeology Journal. 27:2907-2918
Many deterministic and stochastic approaches have been applied for groundwater contaminant source identification (GCSI) in recent decades. Usually, these implementations are based on a single groundwater model or fixed model structure and ignore the
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::03e6845f7939cc12b2299867ca22da8e
https://doi.org/10.1007/s10040-019-02055-3
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6
Integrating MT-DREAMzs and nested sampling algorithms to estimate marginal likelihood and comparison with several other methods
Autor: Jin Lin, Dong Wang, Yuqiao Long, Xiankui Zeng, Tongtong Cao, Xiaobin Zhu, Yuanyuan Sun, Jichun Wu
Publikováno v: Journal of Hydrology. 563:750-765
Marginal likelihood (or Bayesian evidence) estimation is the basis for model evaluation and model selection, which is the key research content of the uncertainty quantification of groundwater model structure. Recently, the nested sampling estimator (
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ce3b6b34870e82562e74439f5b649291
https://doi.org/10.1016/j.jhydrol.2018.06.055
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8
Choosing the LID for Urban Storm Management in the South of Taiyuan Basin by Comparing the Storm Water Reduction Efficiency
Autor: Yintang Wang, Yuqiao Long, Tingting Cui
Publikováno v: Water
Volume 11
Issue 12
Low impact development (LID) is a storm management philosophy. This paper aims at choosing the LID for urban storm management by comparing the efficiency in the south urban district in the Taiyuan Basin. Firstly, we set up a 1D&ndash
2D model to
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::66fd34559008e112e241bf53524d4d2b
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9
Extending the Pairwise Separability Index for Multicrop Identification Using Time-Series MODIS Images
Autor: Qiong Hu, Yuqiao Long, Peng Yang, Miao Lu, Huajun Tang, Qian Song, Wenbin Wu, Qiangyi Yu
Publikováno v: IEEE Transactions on Geoscience and Remote Sensing. 54:6349-6361
The pairwise separability index (SI) has been demonstrated as an effective indicator for capturing crucial phenological differences between two plant species. However, its application to crop types, which have more obvious phenological characteristic
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d2c164cbd77f3518cc95dd56e2097868
https://doi.org/10.1109/tgrs.2016.2581210
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