农业机械学报2025，Vol.56Issue(8)：86-94,9.DOI:10.6041/j.issn.1000-1298.2025.08.008
基于随机森林算法的干旱半干旱区植被物候驱动机制与时滞累积效应研究
Phenological Driving Mechanism and Time-delay Cumulative Effect of Vegetation in Arid and Semi-arid Regions Based on Random Forest
摘要
Abstract
Vegetation phenology is a key ecological indicator to characterize the response of vegetation to climate change,and its dynamic changes have important effects on ecosystem stability in arid regions.To further reveal the response mechanism of vegetation onset period(SOS)to multiple climatic factors in arid and semi-arid areas,a comprehensive evaluation system combining random forest(RF)model,SHAP interpretation algorithm and time delay accumulation analysis was constructed based on NDVI data,multi-source climate data and SOS data from 2001 to 2020.The results showed that the pre-season length of diurnal temperature range(DTR),daily mean temperature(Tmean),cloud cover(CLD)and monthly total precipitation(Pre)were concentrated in 3～4 months(55.6％region),1～3 months(60.3％region),4～6 months(58.1％region)and 4～6 months(62.9％region),respectively.Pre was the most critical driver of SOS,while CLD,DTR andTmeanprovided complementary regulation in specific situations.The response characteristics of different types of climate factors were significantly different,among which the thermal factors such as Tmean and DTR mainly had a lag of 1～3 months and no cumulative effect.The response mechanism of water factors such as Pre,surface soil moisture(SM)and standardized precipitation evapotranspiration index(SPEI)was mainly the current month and short-term accumulation.CLD was mainly reflected in the regulation effect of two months lag and one month accumulation.The results revealed the response of vegetation phenology to multiple climatic factors in arid and semi-arid areas,which provided theoretical basis and method support for the construction of climate-vegetation interaction models at regional scale,the optimization of agricultural production layout,and the prediction of vegetation dynamics under climate change.关键词
毛乌素沙地/植被物候/气候变化/随机森林/SHAP分析/时滞累积效应Key words
Mu Us sandy land/vegetation phenology/climate change/random forest/SHAP analysis/time-delay cumulative effect分类
农业科技引用本文复制引用
李瑞平,王莹,郑和祥,秦子元,侯洪飞..基于随机森林算法的干旱半干旱区植被物候驱动机制与时滞累积效应研究[J].农业机械学报,2025,56(8):86-94,9.基金项目
内蒙古自治区"揭榜挂帅"项目(2024JBGS0020)、国家自然科学基金项目(52269004)和内蒙古农业大学旱区水工程生态环境全国重点实验室项目(SQ2024SKL08048) （2024JBGS0020）
