Multi-source remote sensing and machine learning reveal spatiotemporal variations and drivers of NPP in the Tianshan Mountains,ChinaOA
Multi-source remote sensing and machine learning reveal spatiotemporal variations and drivers of NPP in the Tianshan Mountains,China
LI Jiani;XU Denghui;XU Zhonglin;WANG Yao;YANG Jianjun
College of Ecology and Environment,Xinjiang University,Urumqi 830017,China||Key Laboratory of Oasis Ecology,Xinjiang University,Urumqi 830017,China||Xinjiang Jinghe Observation and Research Station of Temperate Desert Ecosystem,Ministry of Education,Urumqi 830017,China||Technology Innovation Center for Ecological Monitoring and Restoration of Desert-Oasis,Urumqi 830001,ChinaCollege of Ecology and Environment,Xinjiang University,Urumqi 830017,China||Key Laboratory of Oasis Ecology,Xinjiang University,Urumqi 830017,China||Xinjiang Jinghe Observation and Research Station of Temperate Desert Ecosystem,Ministry of Education,Urumqi 830017,China||Technology Innovation Center for Ecological Monitoring and Restoration of Desert-Oasis,Urumqi 830001,ChinaCollege of Ecology and Environment,Xinjiang University,Urumqi 830017,China||Key Laboratory of Oasis Ecology,Xinjiang University,Urumqi 830017,China||Xinjiang Jinghe Observation and Research Station of Temperate Desert Ecosystem,Ministry of Education,Urumqi 830017,China||Technology Innovation Center for Ecological Monitoring and Restoration of Desert-Oasis,Urumqi 830001,ChinaCollege of Ecology and Environment,Xinjiang University,Urumqi 830017,China||Institute of Desert Meteorology,China Meteorological Administration,Urumqi 830002,ChinaCollege of Ecology and Environment,Xinjiang University,Urumqi 830017,China||Key Laboratory of Oasis Ecology,Xinjiang University,Urumqi 830017,China||Xinjiang Jinghe Observation and Research Station of Temperate Desert Ecosystem,Ministry of Education,Urumqi 830017,China||Technology Innovation Center for Ecological Monitoring and Restoration of Desert-Oasis,Urumqi 830001,China
net primary productivity(NPP)Carnegie–Ames–Stanford Approach(CASA)Hurst exponentland use changeExtreme Gradient Boosting(XGBoost)SHapley Additive exPlanations(SHAP)hydrothermal thresholds
net primary productivity(NPP)Carnegie–Ames–Stanford Approach(CASA)Hurst exponentland use changeExtreme Gradient Boosting(XGBoost)SHapley Additive exPlanations(SHAP)hydrothermal thresholds
《干旱区科学》 2026 (1)
56-83,28
This research was supported by the Natural Science Foundation of Xinjiang Uygur Autonomous Region(2023E01006,2024TSYCCX0004).
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