Li Wenge,Chen Nan,Sun Zhenzhen.Study on simulation and spatial differentiation of vegetation GPP in the Loess Plateau from the perspective of terrain and geomorphology[J].Research of Soil and Water Conservation,2025,32(02):331-339.[doi:10.13869/j.cnki.rswc.2025.02.021]
地形地貌视角下黄土高原植被GPP模拟及空间分异研究
- Title:
- Study on simulation and spatial differentiation of vegetation GPP in the Loess Plateau from the perspective of terrain and geomorphology
- 文章编号:
- 1005-3409(2025)02-0331-09
- Keywords:
- Loess Plateau; gross primary production; machine learning; digital elevation model; spectrum
- 分类号:
- TP181; Q948
- 文献标志码:
- A
- 摘要:
- [目的]揭示在地势起伏影响下植被GPP时空格局特征,进而深入分析地形地貌与植被GPP之间的相互作用机制,为植被碳通量模拟以及空间分异性研究提供新的视角。[方法]采用机器学习模型,基于宏观地形因子构建植被GPP模拟模型。通过谱模型提取6个典型地貌样区的植被GPP空间谱,并运用定性和定量分析方法研究了其空间异质性。[结果]XGBoost模型的模拟精度较好,且引入宏观地形因子特征组模型的决定系数(R2)相较于经典特征组提升11.26%,与微观地形因子特征组相比提高了0.94%,同时均方根误差(RMSE)分别降低了21.27%和2.27%。2003—2023年,黄土高原植被GPP整体上升了19.12%,呈现出东南高西北低的空间分布特征。区域内6种典型样区的GPP在不同地形条件下表现出明显的地形分异性,且普遍随着地形崎岖度的增加,呈现先降后升的波动变化趋势。[结论]地形因子在植被GPP的模拟中起到了关键作用,且宏观地形因子比微观地形因子更能揭示地形起伏对GPP的影响。
- Abstract:
- [Objective]The study aims to reveal the spatiotemporal patterns of gross primary productivity(GPP)of vegetation under the influence of terrain undulation, to further delve into the interaction mechanisms between topography and vegetation GPP, and to provide new perspectives for the simulation of vegetation carbon flux and the study of its heterogeneity. [Methods]Machine learning models were employed to construct a vegetation GPP simulation model based on macro-scale terrain factors. Spectral models were utilized to extract the spatial spectra of GPP in six typical geomorphic sample areas, and qualitative and quantitative analysis methods were applied to investigate their spatial heterogeneity. [Results]The XGBoost model in this study showed the XGBoost model in this study showed the improved accuracy in vegetation GPP simulation. The R2 of the model with macroscopic topographic features increased by 11.26% over the conventional feature set and by 0.94% over the micro-topographic feature set. Correspondingly, the RMSE was reduced by 21.27% and 2.27%, respectively. From 2003 to 2023, Loess Plateau vegetation GPP rose by 19.12%, with higher values in the southeast and lower values in the northwest. GPP varied notably across six typical regions, generally peaking after an initial decline with increasing terrain ruggedness. [Conclusion]Topographic factors play a crucial role in simulating vegetation GPP, with macroscopic topographic factors more effectively revealing the impact of terrain undulation on GPP than microscopic ones.
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备注/Memo
收稿日期:2024-05-27 修回日期:2024-06-17 接受日期:2024-06-27
资助项目:国家自然科学基金(41771423); 福建省自然科学基金(2023J01421)
第一作者:李文戈(1999—),男,湖南冷水江人,在读硕士研究生,研究方向为地理信息系统。E-mail:outlooks@qq.com
通信作者:陈楠(1975—),男,福建厦门人,博士,研究员,主要从事数字地形分析研究。E-mail:chennan@fzu.edu.cn