一种顾及物侯信息的植被冠层蒸腾反演方法

本发明公开了一种顾及物侯信息的植被冠层蒸腾反演算法，属于水循环关键参数定量反演的技术领域，本发明利用卫星遥感植被指数数据获取植被冠层季节性叶面积变化和物候节律信息，提供了一种"光合-导度"模型中气孔导度斜率参数的动态参数化方法；通过遥感叶面积指数(LAI)指代植被冠层叶片的生长活性，表明年周期内LAI与气孔导度斜率参数具有很好的线性关系。利用LAI时序变化将植被生长季划分为生长期和衰落期，对不同物候期分别建立LAI与气孔导度斜率参数关系，可清晰识别气孔导度斜率参数对LAI变化的非对称响应，体现物候对叶片功能具有重要影响，表明非线性模型对气孔导度斜率参数的估算精度更高，可有效降低冠层气孔导度以及蒸腾的季节性误差。 The invention discloses a vegetation canopy transpiration inversion algorithm considering phenological information, belongs to the technical field of water circulation key parameter quantitative inversion. According to the invention, seasonal leaf area change and phenological rhythm information of a vegetation canopy by utilizing satellite remote sensing vegetation index data. The invention provides a dynamic parameterization method for a stomatal conductance slope parameter in a photosynthetic conductance model. The remote sensing leaf area index (LAI) refers to the growth activity of the vegetation canopy leaf, which indicates that the LAI and the stomatal conductance slope parameter have a good linear