Interpretable machine learning algorithms to predict leaf senescence date of deciduous trees

Author:

Gao Chengxi,Wang HuanjiongORCID,Ge Quansheng

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

Elsevier BV

Subject

Atmospheric Science,Agronomy and Crop Science,Global and Planetary Change,Forestry

Reference63 articles.

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5. Detecting temporal changes in the temperature sensitivity of spring phenology with global warming: Application of machine learning in phenological model;Dai;Agricultural and Forest Meteorology,2019

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