用回归树模型分析陕北黄土丘陵沟壑区气候因子对NDVI变异的影响  

Application of regression tree in analyzing the effects of climate factors on NDVI in loess hilly area of Shaanxi Province

作　　者：刘洋[1,2] 吕一河[2] 郑海峰[2,3] 陈利顶[2] 

机构地区：[1]中国科学院城市环境研究所,福建厦门361003 [2]中国科学院生态环境研究中心,北京100085 [3]中国科学院东北地理与农业生态研究所,长春130012

出　　处：《应用生态学报》2010年第5期1153-1158,共6页Chinese Journal of Applied Ecology

基　　金：中国科学院知识创新工程重要方向项目(KZCX2-YW-421);国家自然科学基金项目(40925003)资助

摘　　要：基于延安市1998年4月到2008年7月SPOT VEGETATION的旬合成NDVI数据,以及同时期延安市的气象资料,用回归树法分析了影响该地区NDVI年内及年际变异的主要气象因子.结果显示:各气象因子对NDVI变异性的影响随季节及滞后时间的不同而不同;气温和降水是影响NDVI年内变异的主要气象因子;导致NDVI年际变异的气象因子为平均最高气温.回归树在判断影响NDVI的主要气象因子方面具有较强的优势,但它无法建立气象因子与NDVI之间的定量表达关系,从而限制了对其更加广泛的应用.Based on the 10-day SPOT VEGETATION NDVI data and the daily meteorological data from 1998 to 2007 in Yan＇an City,the main meteorological variables affecting the annual and inter-annual variations of NDVI were determined by using regression tree. It was found that the effects of test meteorological variables on the variability of NDVI differed with seasons and time lags. Temperature and precipitation were the most important meteorological variables affecting the annual variation of NDVI,and the average highest temperature was the most important meteorological variable affecting the inter-annual variation of NDVI. Regression tree was very powerful in determining the key meteorological variables affecting NDVI variation,but could not build quantitative relations between NDVI and meteorological variables,which limited its further and wider application.

关 键 词：黄土丘陵沟壑区 气候 NDVI 回归树 

分 类 号：Q948[生物学—植物学]