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地理研究 >

2016 , Vol. 35 >Issue 3: 493 - 503

DOI: https://doi.org/10.11821/dlyj201603008

研究论文

黄土高原地区NDVI与气候因子空间尺度依存性及非平稳性研究

  • 王宇航 , 1, 2 ,
  • 赵鸣飞 1, 2 ,
  • 康慕谊 , 1, 2 ,
  • 左婉怡 2
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  • 1. 北京师范大学地表过程与资源生态国家重点实验室,北京 100875
  • 2. 北京师范大学资源学院,北京 100875
康慕谊(1952- ),男,陕西西安人,博士,教授,主要从事植被地理学及生态学研究.E-mail:

作者简介:王宇航(1990- ),女,辽宁抚顺人,博士研究生,主要从事地理空间分析研究.E-mail:

收稿日期: 2015-09-13

  要求修回日期: 2015-12-22

  网络出版日期: 2016-03-20

基金资助

国家自然科学基金项目(41271059)

国家科技基础性工作专项项目 (2011FY110300)

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Spatial scale-dependent and non-stationarity relationships between NDVI and climatic factors in the Loess Plateau

  • WANG Yuhang , 1, 2 ,
  • ZHAO Mingfei 1, 2 ,
  • KANG Muyi , 1, 2 ,
  • ZUO Wanyi 2
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  • 1. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
  • 2. College of Resources Science and Technology, Beijing Normal University, Beijing 100875, China

Received date: 2015-09-13

  Request revised date: 2015-12-22

  Online published: 2016-03-20

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《地理研究》编辑部
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摘要

基于MODIS传感器的植被指数产品(MOD13Q1)及50年气候数据,通过地理加权回归与普通最小二乘回归模型对比,对中国黄土高原地区NDVI与气候因子间的空间尺度依存性及非平稳性进行研究,以期准确建立二者间关系.结果表明:① 研究区域内,NDVI与气候因子间存在很强的空间尺度依存关系,相同空间尺度下,年均降水较年均温对NDVI影响的波动性更大;② 与普通最小二乘回归模型相比,地理加权回归模型能够更准确地展现二者间关系;③气候因子对该地区NDVI的影响差异明显,降水存在直接正向影响,而温度的影响则较复杂;④ NDVI与气候因子间沿东北--西南的分布格局体现出区域内不同植被--气候区差异特征.二者间的异质情况还反映出除气候外,人类活动,地形等其他因素对NDVI的影响.

关键词： 归一化植被指数; 气候因子; 地理加权回归; 黄土高原

本文引用格式

王宇航 , 赵鸣飞 , 康慕谊 , 左婉怡 . 黄土高原地区NDVI与气候因子空间尺度依存性及非平稳性研究[J]. 地理研究, 2016 , 35(3) : 493 -503 . DOI: 10.11821/dlyj201603008

Abstract

Understanding the relationship between vegetation and climate is the premise and foundation to reveal the distribution pattern of vegetation in large areas. Normalized Differentiation Vegetation Index (NDVI) has been regarded as an effective indicator for vegetation growth and distribution, especially for the large scope. To establish the accurate relationship between NDVI and climatic factors, this paper, based on the vegetation index product (MOD13Q1) relating to the Loess Plateau Area, northern China, and the climatic data observed in resent 50 years from the same area, has conducted a comparison between the two models named Geographically Weighted Regression, GWR, and Ordinary Least Squares, OLS, respectively. We analyzed the non-stationarity and scale-dependent characteristics between the two models with validation tool of corrected Akaike's Information Criterion, AICc, and calculated Moran's Index. The results showed: (1) the NDVI and the climatic factors had a strong scale-dependent relationship in the study area, and when the bandwidth approached to about 330 km in scale, they came up to a stable status. The annual mean precipitation, AMP, presented a larger fluctuation than the annual mean temperature, AMT, at the same scale of bandwidth. (2) Compared with OLS, the results of GWR showed a more accurate spatial distribution of vegetation, through validation by its model performance (AICc, R2, R2 adjusted) and Moran's Index of residuals (P<0.01). (3) The predicated result of GWR reflected the heterogeneity to some extent between the NDVI and the climatic factors. Precipitation had direct and positive influence on NDVI, whereas that of temperature was complicated. (4) The northeastern to southwestern distribution pattern between the NDVI and the climatic factors indicated a remarkable difference of climate-vegetation distribution pattern within the Loess Plateau. The heterogeneity between them also showed that some other factors such as human activities and/or orographic rains exerted influence on NDVI.

Key words： NDVI; climatic factor; geographically weighted regression; Loess Plateau

1 引言

气候制约着植被的地理分布,植被是区域气候特征的反映和指示,两者之间存在密不可分的联系.揭示植被与气候之间的关系是植物地理学及植被生态学的一个关键问题[1].归一化植被指数(Normalized Difference Vegetation Index, NDVI)由于与植被盖度,生物量和生产力等密切相关,近年来被广泛用作大范围地表植被的指示因子[2-4].
基于传统数量方法,以往研究发现,NDVI与气温,降水等因子间关系最为密切[5-7].但由于地理数据的空间自相关性和非平稳性[8],将一般相关分析和回归分析,如普通最小二乘(Ordinary Least Squares, OLS)模型,直接应用于具有空间结构特征的地理学研究中,往往不能充分刻画变量间真实关系,在环境空间异质性较大的地区问题更加凸显[9-11].地理加权回归(Geographically Weighted Regression, GWR)模型能将数据的空间信息纳入分析过程,通过计算回归模型的局部参数来解决地理数据中存在的空间自相关性及空间非平稳性问题,从而提高模型的拟合优度及模拟效果[12].在青藏高原[13]及北方农牧交错带[14]的研究表明,通过GWR与OLS模型拟合结果的对比,能够得出NDVI与气候因子间的空间尺度依存性及非平稳性的特征,并更准确拟合二者间关系.
黄土高原位于中国地势的第二阶梯,地理环境复杂,生态脆弱,是开展生态建设的典型区域[15].由于该地区的植被历史上曾受到过严重破坏,因此在当今的生态建设过程中,植被状况备受关注.准确分析并建立该地区NDVI与气候因子的关系,对了解植被现状,开展植被保护,生态恢复及生态建设均具有重要意义.国内外学者已在该方面做了许多研究[16-18],但大部分未考虑变量空间属性的影响.随着研究的深入,尺度问题引起了研究者关注.罗隆诚等通过主观划分不同的研究范围展开研究[19,20],但本质上并未消除空间尺度效应的影响.究竟在黄土高原地区NDVI与气候因子间受空间尺度影响有何特征,二者间的非平稳性有何表现,以及本质上存在何种空间格局,需进一步深入探讨.
拟将地理加权回归模型与普通最小二乘回归模型进行对比,探讨黄土高原地区NDVI与气候因子间的空间尺度依存性及非平稳性特征,并进而厘定出NDVI与气候因子二者之间的相互关联关系,以期为黄土高原的植被保护,生态恢复及生态建设等提供必要的科学依据.

2 研究方法与数据来源

2.1 研究区概况

黄土高原位于103°E~114°E,34°N~40°N,包括太行山以西,日月山以东,秦岭以北,阴山以南,面积约63万 km2的广阔地区,属一个相对独立的地貌单元(图1).整个高原区平均海拔800~1200 m,其内部分基岩裸露的山地海拔可达1300~1700 m,不乏一些海拔逾2000 m的山峰.除少数石质山地外,黄土层堆积平均厚达50~80 m.区域气候以温带季风性向大陆性过渡为主,年均温6~14°C,年均降水300~800 mm,气温和降水皆从东南向西北逐渐递减,对应的气候带亦依次分为湿润半湿润暖温带,半湿润半干旱温带,半干旱干旱温带.受气候差异的影响,黄土高原的植被自东南向西北也表现出由落叶阔叶林向温带草原过渡的特征,并随海拔的变化呈现出垂直带性分异.
Fig. 1 Location of the study area. Map of digital elevation (a), vegetation cover (b) and annual mean temperature (°C) and isohyets of annual precipitation (mm) in the study area

图1 研究区地理位置:a. 研究区域海拔起伏;b. 研究区植被覆盖;c. 研究区年均温及年降水分异

2.2 数据来源

2.2.1 NDVI数据 NDVI数据来自美国国家航天局(NASA)EOS/Terra卫星MODIS传感器的植被指数产品MOD13Q1(http://ladsweb.nascom.nasa.gov/),空间分辨率250 m,时间分辨率16d.选择的时间范围为2000年,共19个时间段,76景影像.采用MRT(Modis Reprojection Tool)软件对同一时间的4景影像进行镶嵌,投影变换及重采样等处理,然后以最大合成法(Maximum Value Composite, MVC)得到的数据最大值作为基础数据.在ArcGIS中依据研究区域范围,对此NDVI数据进行裁剪,将栅格数据转换为矢量点数据,随机选取5000个矢量点,提取出该点处所对应的栅格数据值.
2.2.2 气象数据 气象数据来自WorldClim数据库1.4版(http://www.worldclim.org).该数据空间分辨率为1 km2,时间为1950-2000年[21].提取出研究区内各样点的年均温,年降水量等19个气候--生物学变量.根据19个气候指标与NDVI的皮尔逊相关分析结果,选择对气候表征最强的年均降水(AMP)与年均温(AMT)两因子参与分析.

2.3 模型方法

2.3.1 地理加权回归模型 地理加权回归模型是普通线性回归模型的扩展.该模型将数据地理位置嵌入到回归参数之中,使回归参数变成观测点地理位置的函数,表达式为[22]:
yi = β 0 μi , vi + ∑ k = 1 p β k μi , vi xik + εi , i = 1,2 , … n (1)
式中:yi为因变量;xik是n×k维自变量矩阵元素;(μᵢ, vᵢ)是第i个样本点的空间位置;b0 (μᵢ, vᵢ)代表变量k在回归点i的回归系数;βk (μᵢ, vᵢ) 是第i个采样点上的第k个回归参数,是地理位置的函数;εi为误差项,满足条件:εi ~ N(0, σ2),Cov(εi, εj) =0 (i≠j).
Fotheringham等根据地理学第一定律,认为距离i点位置较近的观测值对i点的参数估计的影响要大于距离i点位置较远的观测值,因而利用距离加权最小二乘法来估计参数,得到i点的地理加权回归参数估计 β ^ ( μ i , v i ) [22]:
β ^ μi , vi = X T W μi , vi X - 1 X T W μi , vi Y (2)
式中: β ^ 为 β 的估计值;X是自变量观测值构成的矩阵;Y为由因变量观测值构成的列向量;W为空间权值矩阵.常用到的空间权值矩阵计算方法包括高斯距离权值(Gaussian Distance),指数距离权值(Exponential Distance)和三次方距离权值(Tricube Distance)等.因高斯函数法中权重是样点距离的连续单调递减函数,可以克服一般空间函数不连续的缺点,故采用高斯距离权值方法确定权重函数.其表达式如下:
Wij = exp ( - d ij 2 b 2 ) (3)
式中:dij为点 (μᵢ, vi) 到点 (μj, vj) 的欧氏距离;b为带宽(bandwidth),是用来控制权重与距离之间衰减速率的参数.带宽越大,权重随距离增加衰减得越慢;反之,权重随距离增加得越快.
2.3.2 空间平稳性判定及带宽的选择 空间平稳是指与地理空间关联的自变量与因变量之间不存在空间差异,即βk(μᵢ, vᵢ) 不随自变量xk位置而变化,反之则为空间不平稳.Brunsdon等引入平稳性指数(Stationarity Index, SI)表来估计GWR的平稳性[23,24],公式如下:
SI = β GWR _ IQR 2 × GLM _ se (4)
式中:SI为空间平稳指数;βGWR_IQR为xn系数标准误的四分位差;GLM_se为全局回归模型系数的标准误.当SI<1时,认为因变量y与自变量x间达到空间平稳.
通过调整带宽以获取模型达到空间平稳带宽范围,再依据交叉验证(cross-validation, CV)及AICc原则获得最优带宽参数,从而降低空间不确定性对变量的影响.
2.3.3 模型拟合结果的评估 选用AICc对GWR与OLS模型拟合结果进行比较,AICc为AIC对于有限样本量的修正.对模型拟合结果残差进行loess拟合分析其空间随机性.通过计算基于GWR与OLS模型的不同气候因子拟合结果的残差莫兰指数(Moran's Index),来比较模型对空间相关性的处理程度.莫兰指数作为空间自相关的指示因子,取值在-1~1之间,绝对值越大表示空间自相关性越强,取值为0表示理想的空间随机状态.

3 结果分析

3.1 NDVI与气候因子关系的尺度依存性

年均温与年降水两变量在不同空间尺度下对应的平稳性指数,随着带宽增加,空间平稳性指数逐渐下降,不同带宽对应的平稳性指数差异反映出尺度对变量间关系的影响(图2).自变量间平稳指数的差异体现了NDVI的空间分布在不同空间尺度主导气候因子的差异性.在整个黄土高原范围内,NDVI与年降水,年均温在150 km后的空间尺度下平稳性指数小于1,此后趋于不变.在建立NDVI与气候因子的关系时,基于平稳性指数结果,并依据CV及AICc原则,得出在整个黄土高原区范围内选择带宽330 km较为适宜.
Fig. 2 Stationarity indexes at multi-scales for two explanatory variables

图2 两气候自变量在不同尺度下的平稳性指数

3.2 GWR与OLS对比

3.2.1 GWR与OLS拟合结果比较 研究区NDVI空间分布格局,总体来看,高值区集中于研究区的东部,东南部及西南部;低值区域位于研究区的西部及西北部(图3a).以气候因子为自变量,NDVI为因变量,并分别基于GWR与OLS模型拟合的NDVI空间分布情况中,GWR预测值与NDVI真实值的空间分布较为接近(图3b),OLS预测值则呈现较为规则的条带状分布,体现出NDVI的真实空间分异格局不明显(图3c).
Fig. 3 The true spatial pattern of NDVI on the Loess Plateau in 2000 (a), the spatial patterns of NDVI predicted by the GWR (b) and OLS (c) models

图3 NDVI分布及预测值分布图:a.2000年黄土高原地区NDVI的分布格局;b.GWR预测结果;c.OLS预测结果

对比GWR模型与OLS模型的拟合优度(表1),以年均降水,年均温及两因子共同为自变量,采用GWR模型拟合结果均比OLS模型具有更低AICc值,更高的解释率.
Tab. 1 Comparison of model performance between GWR and OLS

表1 GWR与OLS 拟合结果比较

GWR OLS
变量 AICc R2 R2 adjusted AICc R2 R2 adjusted
AMP -6045.88 0.65 0.65 -4365.55 0.5 0.5
AMT -5339.95 0.59 0.59 -951.93 0.02 0.02
AMP and AMT -6246.84 0.66 0.66 -4366.20 0.51 0.51

注:GWR带宽为330 km.

3.2.2 GWR与OLS结果的残差比较 基于OLS模型的残差莫兰指数范围为0.73~0.81 (P<0.01),而基于GWR模型的残差莫兰指数范围为0.58~0.60 (P<0.01)(表2).可见OLS模型的残差结果具有很强的自相关性,表明GWR的拟合结果好于OLS.
Tab. 2 Comparison of Moran's I of residuals between OLS and GWR

表2 GWR与OLS模型残差的莫兰指数比较

GWR OLS
变量 Moran's I P Moran's I P
AMP 0.60 0.01 0.73 0.01
AMT 0.59 0.01 0.81 0.01
AMP and AMT 0.58 0.01 0.74 0.01

注:GWR带宽为330 km.

图4则更直观地展示出GWR模型与OLS模型的各自残差空间分布.GWR模型的残差基本呈现出均匀的随机分布,仅在少数部分地区,如河套(研究区北部),青海(研究区西部),宁夏贺兰山(研究区西北部)及山西中部(研究区东部)地区,其数值明显偏高(图4a);而OLS模型的残差则表现出存在较明显的空间格局,特别是在NDVI高值区与低值区(图4c).对GWR与OLS模型得到残差进行loess拟合,平滑参数均为0.75.GWR模型残差拟合结果的残差标准误为0.1269,OLS为0.1487.GWR模型的残差基本不存在明显趋势(图4b),而OLS模型结果残差随着NDVI值增加呈下降趋势,特别是在NDVI高值及低值处更为明显(图4d).
Fig. 4 Spatial distribution of simulated residuals from GWR and OLS model with loess fit for their residuals: GWR model (a, b) and OLS model (c, d)

图4 回归模型残差空间分布及残差Loess拟合结果:a和b为GWR;c和d为OLS

3.3 NDVI与气候因子关系的空间异质性

区域内AMP与AMT的回归系数空间分布差异较大,体现出NDVI与气候因子间的空间异质性.大部分区域AMP与NDVI间的回归系数为正值(图5a),约占样本数量的97.62%,表明降水量越大,NDVI值越大;AMT的回归系数负值约占样本数的58.58%,主要分布在研究区西南及东北部(图5b),表明该地区NDVI与温度间的关系更复杂.虽然截距对回归方程的作用较小,但其结果的空间分异也体现出较强的异质格局(图5c).Local R2的空间分布区域间差异较大(图5d),高值区主要沿着东北--西南方向呈带状分布,低值区主要位于高值区两侧,且分布较为聚集,西北部最低,东部次之.
Fig. 5 Spatial variation of regression outputs from the GWR model. The spatial patterns of GWR model coefficients beta AMP (a), beta AMT (b), intercepts (c), and correlation coefficients (d)

图5 基于GWR模型NDVI与气候因子的回归结果:a. AMP的回归系数,b. AMT的回归系数,c. 截距,d. Local R2

4 讨论

4.1 NDVI与气候因子间的空间尺度依存性

结果中NDVI与气候因子间的平稳性指数随带宽增加呈现下降趋势(图2),体现出拟合结果对空间尺度的敏感性.表明黄土高原地区二者间具有很强的空间尺度依存性,该结果虽然在以往研究中也已得到证实[25-27],但在建立二者间关系时未能消除尺度效应的影响.采用GWR模型,基于平稳性指数得到数据间达到空间平稳时对应的带宽(反映模型的空间尺度),基本能够消除空间尺度的干扰.
在AMP与AMT都未达空间平稳之前(图2),相同带宽下,AMP的SI均高于AMT.在农牧交错带以及青藏高原地区也存在此现象[13,14],均表明在相同的空间尺度下,AMP较AMT对NDVI影响的波动性更大.李本纲等指出NDVI与降水的相关系数较气温复杂得多,并且不同植被类型对降水的敏感性存在差异[28],支持了本研究结果.此外,许多研究发现降水是导致中国西北部地区植被变化最主要的自然因素[29].本文从降水对植被影响波动性的角度给出了解释,反映出相同空间尺度下,不同气候因子对NDVI影响的差异.

4.2 平稳性指数的指示作用

在获得平稳性指数基础上,依据交叉检验及AICc原则,得出建立黄土高原地区NDVI与气候因子间关系的带宽为330 km,其值介于青藏高原(156 km)[13]和北方农牧交错带(430 km)[14]之间.北方农牧交错带从暖温带落叶阔叶林区域向温带草原区域过渡,是落叶阔叶林和草甸--草原的大型镶嵌体[30].青藏高原地区则集中体现出高寒植被的特征[30],植被情况不如前者复杂.而黄土高原则位于上述二者之间,其植被情况具有明显的过渡性,反应出由东部森林地区向西部草原区的过渡特征.同时,还是内陆干旱气候带向东部季风气候及西部青藏高原向东部沿海平原的过渡区[31].这些均说明平稳性指数能够作为指示植被水平地带性特征的优良指标.具体来讲,不同地区间该指标反映出NDVI与气候因子间异质情况,异质性越大,则该数值越大.此外,在同一地区内,平稳性指数同样具有一定指示作用,它的变化能够指示两者间关系的变化情况.由此,基于空间尺度衍生出的指标能够为区域间植被--气候关系比较,以及评估某一地区植被--气候的变化提供参考.

4.3 气候因子对NDVI的影响

黄土高原大部分地区NDVI与AMP为正相关(约占样本数量的97.62%),与AMT之间的关系却未达显著水平(约占样本数量的41.42%).这与其他相关的研究结果类似[32],均体现出降水对该地植被的直接正向影响.Zhang等基于样地实验和过程模型也发现降水对该地区植被盖度,生产力存在直接作用[33].研究表明,温度是该地区植被生长的控制因素,但却不是植被夏季生长的限制因素[34].在干旱及半干旱地区水分为植物生长的主要生态限制条件[35].黄土高原地区十分缺水[36],该地区土壤侵蚀严重,保水性差,土壤含水量很低,并且主要分布在深层土壤[37],植物生长所需水分主要来自降水[38],使得降水在该地区植被地理分布中发挥着关键作用[39].因此,降水给该地植被带来直接的影响十分明显.

4.4 NDVI与气候因子关系的空间异质性

GWR模型拟合结果(回归系数,Local R2及残差)的差异,反映出NDVI与气候之间关系的高异质性.GWR模型Local R2的空间分布格局较明显地展示出该地区森林--草原过渡区,草原--荒漠过渡区及温带阔叶林植被分区界限[40].NDVI与气温,降水在森林--草原区最相关,温带阔叶林区次之,草原--荒漠区最弱.这与罗隆诚的结果相似[19],暗示了森林--草原地带的植被过渡性在反映气候变化方面更为敏感.此外,上述格局在研究区南部较北部更明晰,这可能由于北部受人类活动的影响更强[41].长期以来,由于受农业耕垦,伐木的影响,使得这些地区植被盖度较低,导致NDVI与气候因子的关系不明显.此外,虽然GWR拟合结果残差基本呈现随机分布,但其数值在河套,青海,宁夏贺兰山及山西中部等地区明显偏高.在山西中部汾河谷地,农作物种植虽然亦受降水的影响,但人工灌溉的影响则更为直接;在河套平原地区,虽然降水较少,但地下水补给丰富,灌溉条件便利,受灌溉的影响更大;在贺兰山和青海东部,海拔较高,常形成山地地形雨,地形的影响更为密切.因此,Local R2及残差结果是NDVI与气候间关系格局的真实展现,反映出了除气候之外,人类活动,地形等其他因素对NDVI的影响.

5 结论

(1)黄土高原地区NDVI与气候因子间具有很强的空间尺度依存性;在相同的空间尺度下,年均降水较年均温对NDVI影响的波动性更大.
(2)黄土高原地区NDVI与气候因子间的非平稳性使得二者间空间异质性较高;与OLS回归模型相比,GWR模型考虑了变量的空间非平稳性及尺度依存性特征,能够更准确地展现二者间格局.
(3)基于GWR模型,黄土高原地区NDVI与气候因子间沿东北--西南方向的带状趋势,反映出不同植被--气候区的差异特征;二者间的异质情况还反映出除气候外,人类活动,地形等其他因素的影响.
(4)地区间NDVI与气候因子平稳性指数差异反映出了植被水平地带性特征,该指标能够为区域间植被--气候关系比较,以及评估某一地区植被--气候的变化提供参考.

The authors have declared that no competing interests exist.

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Zhao Z Q, Gao J B, Wang Y L, et al.Exploring spatially variable relationships between NDVI and climatic factors in a transition zone using geographically weighted regression. Theoretical and Applied Climatology, 2015, 120(3-4): 507-519.At landscape scale, the normalized difference vegetation index (NDVI) can be used to indicate the vegetation's dynamic characteristics and has been widely employed to develop correlated and dependent relationships with the climatic and environmental factors. However, studies show that NDVI-environment relationships always emerge with complex features such as nonlinearity, scale dependency, and nonstationarity, especially in highly heterogeneous areas. In this study, we used geographically weighted regression (GWR), a local modeling technique to estimate regression models with spatially varying relationships, to investigate the spatially nonstationaly relationships between NDVI and climatic factors at multiple scales in North China. The results indicate that all GWR models with appropriate bandwidth represented significant improvements of model performance over the ordinary least squares (OLS) models. The spatial relationships between NDVI and climatic factors varied significantly over space and were more significant and sensitive in the ecogeographical transition zone. Clear spatial patterns of slope parameters and local coefficient of determination (R-2) were found from the results of the GWR models. Moreover, the spatial patterns of the local R-2 of NDVI-precipitation are much clearer than the R-2 of NDVI-temperature in the semi-arid and subhumid areas, which mean that precipitation has more significant influence on vegetation in these areas. In conclusion, the study revealed detailed site information on the variable relationships in different parts of the study area, especially in the ecogeographical transition zone, and the GWR model can improve model ability to address spatial, nonstationary, and scale-dependent problems in landscape ecology.

DOI

[15]
郭铌, 朱燕君, 王介民, 等. 近22年来西北不同类型植被NDVI变化与气候因子的关系. 植物生态学报, 2008, 32(2): 319-327.<p>为了研究气候变化对西北地区不同类型植被的影响，利用NASA GIMMS 1982～2003年逐月归一化植被指数（Normalized difference vegetation index, <em>NDVI</em>）数据集和西北地区138个气象站点同期的气温和降水资料，计算了各站22年月平均气温和降水与<em>NDVI</em>的相关系数。同时, 选西北地区森林、草原、绿洲和雨养农业4类有代表性的植被类型为研究区，对各类植被<em>NDVI</em>与气温和降水的相关关系进行分析。研究结果表明：除无植被的戈壁沙漠地区外，西北地区<em>NDVI</em>与气温和降水均有较好的相关性。除祁连山中部地区外，西北地区<em>NDVI</em>与气温的相关系数大于降水。天山、阿尔泰山和秦岭的<em>NDVI</em>与气温相关系数最高，而青海东北部<em>NDVI</em>与降水相关系数最高。西北地区各种类型植被对气候变化反映敏感。其敏感度因植被类型不同和同类植被所处的地理位置不同而有差异；纬度较高的新疆林区与温度相关性最高，高寒草甸次之。在植被生长最旺盛的夏季（6～8月），22年来西北地区各林区的<em>NDVI</em>均呈下降趋势。其中西北东部林区下降趋势显著，与这些地区的降水减少和气温增加有关。草原区植被以上升趋势为主，高寒草甸和盐生草甸上升趋势最为显著，气温升高是这些地区植被生长加速的原因 之一。西北绿洲是<em>NDVI</em>增加极为显著的地区，以新疆绿洲<em>NDVI</em>上升趋势最大。气候变暖是近年绿洲<em>NDVI</em>增加的主要驱动力之一，绿洲面积扩大、种植结构调整和种植品种变化等人为因素对绿洲<em>NDVI</em>增加的作用不可忽视，这种作用在新疆表现的尤为突出。雨养农业区<em>NDVI</em>年际 间波动较大，各区域间变化不太一致。<em>NDVI</em>的波动与降水变化有很好的正相关，与气温变化有很好的负相关，近年来西北东部气温升高和降水的减少是雨养农业区<em>NDVI</em>下降的原因，农业措施的实施也改变了植被生长对气候条件的依赖性。</p>

DOI

[Guo Ni, Zhu Yanjun, Wang Jiemin, et al.The relationship between NDVI and climate elements for 22 years in different vegetation areas of northwest China. Journal of Plant Ecology, 2008, 32(2): 319-327.]

[16]
陈安安, 孙林, 胡北, 等. 近10a黄土高原地区NDVI变化及其对水热因子响应分析. 水土保持通报, 2011, 31(5): 215-219.植被变化及其对气候的响应是当前全球变化研究的关键领域之一。基 于SPOT-VGT NDVI数据集和黄土高原气象资料,应用最大化合成法和Kriging插值等地理空间分析方法,对黄土高原地区植被变化特征及其对气温和降水的响应过程进 行了多时间尺度分析。结果表明,1999—2008年期间黄土高原地区植被覆盖整体呈上升趋势,线性增速为9.9%/10a,NDVI在旬、月和季尺度的 变化曲线均呈单峰型,8月份达到最大值,2月为全年的最低值。研究黄土高原地区植被NDVI对气温和降水变化响应的最优尺度为月尺度。黄土高原地区 NDVI在旬、月尺度上与温度的相关程度强于降水,而季尺度上与降水的相关程度强于气温。

[Chen Anan, Sun Lin, Hu Bei, et al.Changes of NDVI and its responses to temperature and precipitation on Loess Plateau over last ten years. Bulletin of Soil and Water Conservation, 2011, 31(5): 215-219.]

[17]
程杰. 黄土高原草地植被分布与气候响应特征. 咸阳: 西北农林科技大学博士学位论文, 2011.针对黄土高原生态环境建设的需要及草原学、生态学与环境科学研究的前沿性问题,在总结前人相关领域研究的基础上,以可覆盖黄土高原地区的草甸草原、典型草原、荒漠草原和灌丛草原类型区的草地植被分布与气候响应为研究对象,通过对105县有关资料收集、野外样地调查与采样和室内实验与统计分析及科学推断等相结合的研究方法,从系统分析黄土高原不同经度草地植被与气候变化特征入手,研究不同草地植被类型退化与恢复的水分、养分时空变化过程,揭示不同植被地带指示种群与气候变化的响应趋势及空间变异特征,提出黄土高原不同气候带植被恢复建设的调控措施,为实现黄土高原植被生产力的不断提高与持续稳定发展提供基础数据和理论依据,为维持黄土高原生态平衡和人与自然和谐及西部生态环境建设工程提供科学依据和实践指导。主要研究结论如下: (1)研究了黄土高原典型区域主要气候因子与不同植被地带指示种的变化趋势。表明50年来黄土高原半干旱区年降水量总体上呈现出明显减少的趋势, 51年降水量共减少40.31 mm,降幅为7.9 mm/10 a,近10年(1999～2008年)平均降水量仅为392.85mm,比51年平均值减少47.86 mm,下降10.86%,使草原植被破坏已达极限;30年平均温度上升1.2℃,增温幅度为0.4℃/10 a。因受气候暖干化影响,典型指示植物个体分化明显,并向不同地带延伸,使一些优势种逐渐退化为伴生种。 (2)揭示了黄土高原草地植被土壤水分的变异特征。在黄土高原经度100°～114°之间,0～100cm土壤水分变异幅度,草甸草原为17.28～24.68%;典型草原为11.7～21.84%;荒漠草原为5.5～17.0%;灌丛草原为13.96～21.26%。草地土壤剖面水分垂直分布趋势总体为:0～30cm受降雨量影响为速变层;30～60cm受降雨强度和土壤容重的影响,为水分利用亏缺层;60cm～100cm受土壤水库的影响,为缓慢回升层。 (3)分析了黄土高原草地植被土壤养分的变化状况。在黄土高原不同草原地带土壤养分排序均为草甸草原典型草原灌丛草原荒漠草原地带;各地带草地受封禁年限与不同退化程度的影响,植被生长与土壤养分的变化差异显著,在4种类型草原地带土壤养分均随封禁年限的延长而提高,随退化程度的加重及土层的加深而降低。 (4)探讨了黄土高原不同地带草地生产力与气候响应关系。黄土高原从西向东随经度的变化,年降水量相应上升,在经度100°～114°之间,降水量平均由410mm上升到660mm,4种草原类型的生产力随降雨量提高均呈逐渐增强的趋势,且呈极显著的相关性,同时还存在累加效应,这与牧草的生长和需水规律相一致,表明在黄土高原的经度范围,水分是影响草原生产力的首要驱动因子。 (5)揭示了黄土高原典型种群与气候变化响应特征。近年来受全球气候变化的影响,草地种群对气候反应较为敏感,其分布幅度在逐渐扩大。草甸草原以白羊草为代表的4个典型种群,已由该地带建群种扩展为典型草原优势种。典型草原10个种群可分为3种类型,以禾本科为主的旱生中旱生植物,从草甸草原到典型草原均有分布;以菊科为主的旱生及旱中生植物,已由典型草原地带向草甸草原和荒漠草原地带扩展;以豆科和其它科为主的中旱生植物,不仅为典型草原地带的建群种,且已延伸到荒漠草原地带,表明气候暖干化的变化趋势在加剧。荒漠草原4个典型种群不仅成为该地带的建群种,且已延伸到草原化荒漠地带与极干旱植物驴驴蒿等混生组成群落。灌丛草原7个种群,适宜草甸草原生长的白刺花等种群已扩展到典型草原以优势种出现;典型草原地带生长的柠条锦鸡儿等种群已扩展到荒漠草原地带以优势种出现;荒漠草原地带的杠柳等种群已伸展到典型草原与荒漠草原交错区以伴生种或偶见种出现。以上种群分布均为气候变化的指示信号和重要标志,为我国气候变化与物种多样性及种群分布格局的研究提供了重要科学依据。 (6)研究发现黄土高原草地植被地带迁移趋势明显。根据植被地理分布、植物区系成分、环境条件以及目前植被分布状况,结合黄土高原植被调查研究与文献资料考证,由于现代气候具有向暖干化发展趋势,加之人类活动对植被的重复破坏,致使森林草原地带的分界线向南退缩,典型草原地带分界线在不断扩大,向南迁移直接进入森林草原地带,而荒漠草原也在不断南移,伸入到典型草原地带,出现了目前黄土高原森林草原地带、典型草原地带和荒漠草原地带镶嵌分布的植被群落类型表现较为明显。

[Cheng Jie.Response of grassland vegetations distribution to climate in Loess Plateau. Xianyang: Doctoral Dissertation of Northwest Agriculture and Forest University, 2011.]

[18]
李双双, 延军平, 万佳. 近10年陕甘宁黄土高原区植被覆盖时空变化特征. 地理学报, 2012, 67(7): 960-970.基于2000-2009 年MODIS-NDVI 植被覆盖指数, 采用线性趋势分析、Hurst 指数和偏相关系数等数理分析方法, 对陕甘宁地区&ldquo;退耕还林还草&rdquo;实施10a 来植被覆盖时空变化特征、影响因素及其未来变化趋势进行分析。结果表明:① 2000-2009 年陕甘宁地区植被覆盖呈现明显增加趋势0.032/10a, 远快于三北防护林工程区1982-2006 年植被覆盖平均增速0.007/10a;② 陕甘宁地区植被恢复具有阶段性, 整体呈&ldquo;S&rdquo;型增长, 具有两次明显的植被高恢复期;③ 陕甘宁地区植被恢复以轻微改善为主, 中度改善次之, 呈退化趋势区域比重较小(2.38%), 零星分布于宁南八县、定边东部、甘肃陇东的环县和镇原;④ 陕甘宁地区植被覆盖度逐年提高、生态环境持续改善是人类活动和气候变化共同驱动, 其中人类经济活动作用明显;⑤ 陕甘宁地区植被恢复具有一定的持续性, 未来大部分区域将持续改善, 退化区集中分布于陕北中东部、&ldquo;彭阳&mdash;镇原&rdquo;南部以及盐池北部。

DOI

[Li shuangshuang, Yan Junping, Wan jia. The spatial-temporal changes of vegetation restoration on Loess Plateau in Shaanxi-Gansu-Ningxia region. Acta Geographic Sinica, 2012, 67(7): 960-970.]

[19]
罗隆诚. 黄土高原植被覆盖变化及其对气候的多尺度响应. 西安: 西北大学硕士学位论文, 2012.作为重要的生态因子,植被既是 气候变化的承受者,又对气候变化产生积极的反馈作用。因此,研究植被覆盖变化及其与气温和降水等气候因子的响应关系已成为当前全球变化研究的重要领域之 一。文章基于黄土高原地区1999年-2008年的SPOT归一化植被指数(NDVI)数据和相关气象台站的气候数据,应用GIS空间分析、时滞分析等方 法,分析了黄土高原地区植被覆盖及气候因子(气温、降水量)的空间分布特征和变化规律,同时对黄土高原植被变化对气候的多时空尺度响应过程与机制进行了研 究。主要结论如下： (1)黄土高原地区1999年-2008年间植被NDVI呈上升趋势,过去10年累计增幅为10.5%。从季节上看,秋季增幅最大,夏季次之,冬季增幅最 小；从空间上看,陕北黄土高原及其周边地区增幅最为明显。而同期黄土高原地区的气温略微呈现下降趋势,降水量呈现波动增多趋势。 (2)黄土高原地区植被NDVI与气候因子(气温和降水量)显著的相关关系。在不同时间尺度下比较,旬尺度上黄土高原地区NDVI对气温的响应滞后1旬, 对降水量的响应滞后3旬,且与气温的相关性大于与降水量的相关性；在月尺度上黄土高原地区NDVI对气温和降水量的滞后1月时相关性最好,且对气温的相关 性大于对降水的相关性；在季尺度上黄土高原地区NDVI与气温和降水的最好的相关性均在当季,即时滞期为0,且对降水量的相关性大于对气温的相关性。 (3)在不同的空间尺度下,首先,将黄土高原地区划分为温带阔叶林植被区(Ⅰ区)、森林-草原过渡区(Ⅱ区)、草原-荒漠过渡区(Ⅲ区)共3个区,在旬时 间尺度上,温带阔叶林区和森林草原区植被NDVI对气温和降水量的响应特征具有一致性(为2旬),草原荒漠区响应的最大时滞期更长(为3旬)；在月时间尺 度上,3个分区NDVI对气温和降水的最大时滞期均为1月；在季时间尺度上,除草原荒漠区NDVI对降水的最大时滞期为1季以外,其余的最大时滞期均为当 季。然后,再选取两个区域尺度的典型样区：陕北黄土高原地区(自然地理分区)和宁夏回族自治区(行政边界分区),以及一个典型样点(甘肃省榆中县)进行分 析,结果表明植被NDVI寸气温和降水量的响应特征具有一定相似性,但其最大相关系数所处的时滞期各有差异。 (4)通过对黄土高原地区不同时空尺度下植被NDVI与气温、降水量时滞分析结果的对比分析,表明黄土高原地区植被NDVI对气温响应的最大相关系数整体 上高于对降水量响应的最大相关系数,且在旬、月、季时间尺度上的最大时滞期具有一定的一致性,而在不同的空间尺度下则相似性和差异性并存。

[Luo Longcheng.The vegetation cover change and its response to climate of multi-scale in Loess Plateau. Xi'an: Master Dissertation of Northwest University, 2012.]

[20]
张建香. 黄土高原植被景观格局变化的多尺度分析及其影响因素研究. 兰州: 西北师范大学硕士学位论文, 2013.黄土高原长期受人类活动影响， 区内自然植被大多被人工植被替代，植被景观格局时空变化复杂多样。动态监测黄土高原不同尺度下植被景观格局的时空演变，深入研究植被与地形、气候以及人类 活动之间的相互关系，对于揭示区域环境状况的演化与变迁等具有重要的现实意义。 本文应用景观生态学的理论和方法，结合遥感（RS）和地理信息系统（GIS）技术，利用不同时期不同分辨率的植被类型数据和植被指数数据，分别采用基于 Fragstats的景观指数法和基于小波分析的空间统计学方法，研究不同时期黄土高原植被景观格局的多尺度变化特征，同时从自然和人为因素两方面分析了 不同时期影响黄土高原植被景观格局变化的主导因素。 分析结果表明：（1）黄土高原植被景观1982-2011年期间发生了阶段性变化。根据黄土高原生长季（4-10月）归一化植被指数（GIMMS NDVI和MODIS NDVI）的波动性变化，发现植被覆盖情况总体趋好，但在整个研究时段内发生了阶段性变化。其中：1982-1990年为植被恢复阶段，河套平原东南部， 晋、陕中北部和陇中地区植被恢复最为显著；1990-2001年为植被退化阶段，鄂尔多斯高原东部，晋、陕中部地区植被退化最严重；2001-2011年 为植被恢复阶段，晋、陕的中北部，陇中、陇东的南部地区植被明显恢复。在所有时段中，以延河流域植被景观的变化最为复杂，作为典型的植被变化区，为小尺度 上研究黄土高原植被景观格局的变化做了准备。（2）无论是整个黄土高原区，还是黄土高原典型区延河流域，植被景观的基质始终是草原和农作物，针叶林、阔叶 林、荒漠、建设用地和水域等其他景观类型镶嵌分布其中。从时间上看，植被景观的破碎化程度逐渐加深，而且在2000年以后加深速度更快，以灌丛、草原和农 作物最为典型。在不同的空间尺度上，破碎化程度随着尺度的增大逐渐减小，并且当空间尺度增大到一定程度时，其随时间变化的特征逐渐被掩盖。聚集度和分离度 随时间变化不明显，在小尺度上聚集度较高，尤其是斑块面积较小的针叶林、居民地和水域，随着尺度的增大，聚集度减小分离度逐渐增加，针叶林、灌丛和草原最 具代表性。植被景观要素的丰度和优势度对空间粒度的大小不敏感，但受空间幅度的影响，在小尺度和大中尺度上表现出不同的变化规律。斑块形状的复杂度随着景 观尺度的增大，呈先减后增的趋势，其中草原的这种变化最为显著。植被景观总体上趋于多样化，当研究区大小或幅度一定时，景观多样性随空间粒度的增大略有减 小，而当幅度和粒度同时增大时，多样性会逐渐增大。（3）植被NDVI的空间异质性主要体现在480m、960m、1920m、3840m、16km、 32km、64km、128km的尺度上。植被景观的异质性与数据获取的时间、数据分辨率和空间位置均有关。植被指数越高、数据分辨率越高，植被景观的空 间异质性就越大，而且，沿经度方向植被NDVI的空间差异性和破碎化程度和大于纬度方向。

[Zhang jiangxiang. Impacts of vegetation landscape structure change in Loess Plateau based on multi-scale analysis. Lanzhou: Master Dissertation of Northwest Normal University, 2013.]

[21]
Hijmans R J, Cameron S E, Parra J L, et al.Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 2005, 25(15): 1965-1978.ABSTRACT We developed interpolated climate surfaces for global land areas (excluding Antarctica) at a spatial resolution of 30 arc s (often referred to as 1-km spatial resolution). The climate elements considered were monthly precipitation and mean, minimum, and maximum temperature. Input data were gathered from a variety of sources and, where possible, were restricted to records from the 1950-2000 period. We used the thin-plate smoothing spline algorithm implemented in the ANUSPLIN package for interpolation, using latitude, longitude, and elevation as independent variables. We quantified uncertainty arising from the input data and the interpolation by mapping weather station density, elevation bias in the weather stations, and elevation variation within grid cells and through data partitioning and cross validation. Elevation bias tended to be negative (stations lower than expected) at high latitudes but positive in the tropics. Uncertainty is highest in mountainous and in poorly sampled areas. Data partitioning showed high uncertainty of the surfaces on isolated islands, e.g. in the Pacific. Aggregating the elevation and climate data to 10 arc min resolution showed an enormous variation within grid cells, illustrating the value of high-resolution surfaces. A comparison with an existing data set at 10 arc min resolution showed overall agreement, but with significant variation in some regions. A comparison with two high-resolution data sets for the United States also identified areas with large local differences, particularly in mountainous areas. Compared to previous global climatologies, ours has the following advantages: the data are at a higher spatial resolution (400 times greater or more); more weather station records were used; improved elevation data were used; and more information about spatial patterns of uncertainty in the data is available. Owing to the overall low density of available climate stations, our surfaces do not capture of all variation that may occur at a resolution of 1 km, particularly of precipitation in mountainous areas. In future work, such variation might be captured through knowledge-based methods and inclusion of additional co-variates, particularly layers obtained through remote sensing.

DOI

[22]
Fotheringham S, Brunsdon C, Charlton M.Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Newcastle: John Wiley & Sons Ltd, 2002.No abstract is available for this item.

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[23]
Brunsdon C, Fotheringham S, Charlton M.Geographically weighted regression modelling spatial non-stationarity. Journal of the Royal Statistical Society, 1998, 47(2): 431-443.In regression models where the cases are geographical locations, sometimes regression coefficients do not remain fixed over space. A technique for exploring this phenomenon, geographically weighted regression is introduced. A related Monte Carte significance test for spatial non-stationarity is also considered. Finally, an example of the method is given, using limiting long term illness data from the 1991 UK census.

DOI

[24]
Osborne P E, Foody G M, Suárez-Seoane S.Non-stationarity and local approaches to modelling the distributions of wildlife. Diversity and Distributions, 2007, 13(3): 313-323.London ED, Connolly RJ, Szikszay M, Wamsley JK.

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[25]
李斌, 张金屯. 黄土高原地区植被与气候的关系. 生态学报, 2003, 23(1): 82-89.利用地理信息系统技术结合典范对应分析和数量区划的方法 ,研究了黄土高原地区植被与气候之间的关系。排序结果表明 :CCA的第一轴代表黄土高原植被和气候梯度的纬向性变化 ,水分梯度是决定植被分布的最主要气候因子 ,热量梯度中的全年月平均最低气温、月平均最高气温、年均温也对植被的纬向性分布有较大的影响 ,黄土高原植被与气候梯度表现出明显的纬向性 ;CCA的第二轴代表黄土高原植被和气候梯度的经向性变化 ,热量梯度是决定植被经向性分布的最主要气候因子 ,水分梯度中的全年最大蒸散量对植被的经向性分布有较大的影响。黄土高原植被与气候梯度表现出明显的经向分布规律性。

[Li Bin, Zhang Jintun.Analysis of relationships between vegetation and climate variables in Loess Plateau. Acta Ecologica Sinica, 2003, 23(1): 82-89.]

[26]
宋怡, 马明国. 基于GIMMS AVHRR NDVI数据的中国寒旱区植被动态及其与气候因子的关系. 遥感学报, 2008, 12(3): 499-505.本文基于遥感和地理信息系统技术,用气象数据对中国的寒旱区作了初步的定义.利用GIMMS AVHRR NDVI (Normalized Difference Vegetation Index)数据对中国寒旱区植被覆盖的情况进行了动态监测.采用最大化合成植被指数SINDVI,一元线性回归趋势分析和偏差分析得出寒旱区植被变化特征,并且结合各个气象台站的年平均气温和年总降水数据采用相关分析方法,分析植被动态对气候对气候变化的响应.得出结论:东北的长白山、大小兴安岭、山西的太行山、新疆的准格尔盆地和阿尔泰山的部分地区植被呈现明显退化趋势;而天山、喜马拉雅山、祁连山、阴山、蒙古高原、东北平原及大巴山的高山区,植被呈现改善趋势.中国寒旱区大部分区域植被变化与降水和温度均呈现正相关关系.

DOI

[Song Yi, Ma Minguo.Variation of AVHRR NDVI and its relationship with climate in Chinese arid and cold regions. Journal of Remote Sensing, 2008, 12(3): 499-505.]

[27]
蒲蕾, 任志远. 陕西省不同地区NDVI变化与气候因子的关系及响应研究. 水土保持通报, 2013, 33(2): 265-269, 275.利用SPOT VEGETATION数据分别研究了陕西省近10 a植被空间分布和动态变化,比较了陕南、关中和陕北地区植被NDVI的年际变化和月变化.结果表明,陕西省植被覆盖总体较好,各地区植被总体轻微改善.这 3个地区的植被NDVI年均值均逐年增加,并且增长速度表现为:陕南＞关中＞陕北,不同地区植被夏季生长最好.通过对不同地区植被NDVI与气温、降水、 日照时数的年际和年内相关关系及其响应的研究得出,不同地区植被NDVI与气温、降水、日照时数的年际相关性不大,而年内相关性显著.研究了不同地区植被 NDVI对气温、降水、日照时数的滞后效应得出,陕南地区植被NDVI对气温降水的响应不具有滞后性,对日照时数的响应具有滞后性.关中和陕北地区植被 NDVI对气温、日照时数的响应具有滞后性,对降水的响应具有即时性.

[Pu lei, Ren Zhiyuan. Changes of NDVI in different areas of Shaanxi province and its responses to climate factor. Bulletin of Soil and Water Conservation, 2013, 33(2): 265-269, 275.]

[28]
李本纲, 陶澍. AVHRR NDVI与气候因子的相关分析. 生态学报, 2000, 20(5): 898-902.对中国 1 60个气象站 1 0 a的连续 AVHRR NDVI数据、气象观测数据进行相关分析 ,并结合植被覆盖类型资料深入探讨了 AVHRR NDVI/气温和 AVHRR NDVI/降水相关系数的地区差异及其随植被类型变化规律。研究结果表明 ,对中国的大部分地区 ,气温对植被的影响超过降水。就自然植被而言 ,其对降水的敏感性趋势为草本植被大于灌木植被 ,灌木植被大于乔木植被。就农作物而言 ,降水影响取决于耕作制度、作物种类、降水季节分配、灌溉方式等因素。在华中、新疆等灌溉农业区 ,降水对植被的直接影响相对较弱 ;而在东北、华北、四川盆地等地区 ,降水对农作物的生长起决定性作用。

[Li Bengang, Tao Shu.Correlation between AVHRR NDVI and climate factors. Acta Ecoligica Sinica, 2000, 20(5): 898-902.]

[29]
Zhao X, Tan K, Zhao S, et al.Changing climate affects vegetation growth in the arid region of the northwestern China. Journal of Arid Environments, 2011, 75(10): 946-952.<h2 class="secHeading" id="section_abstract">Abstract</h2><p id="abspara0010">The northwestern China is a typical dry-land region of Inner Asia, where significant climate change has been observed over the past several decades. How the regional vegetation, particularly the grassland-oasis-desert complex, responds to such climatic change is poorly understood. To address this question, we investigated spatio-temporal changes in vegetation growth and their responses to a changing climate by biome and bioregion, using satellite-sensed Normalized Difference Vegetation Index (NDVI) data from 1982 to 2003, along with corresponding climate data. Over the past 22 years, about 30% of the total vegetated area showed an annual increase of 0.7% in growing season NDVI. This trend occurred in all biomes and all bioregions except Sawuer, a subregion of the study area with no significant climate change. Further analyses indicated that NDVI change was highly correlated with the current precipitation and evapotranspiration in growing season but was not associated with temperature. We also found that NDVI was positively correlated with the preceding winter precipitation. These findings suggest that precipitation may be the key cause of vegetation growth in this area, even for mountain forests and grasslands, whose growth are often regarded to be limited by low temperate in winter and early spring.</p><h4 id="secGabs_N1e1e0030N73746a28">Highlights</h4><p>? We proposed that significant climate change may lead to changes in vegetation growth in arid northwestern China. ? NDVI-indicated vegetation growth shows an overall increase in the whole area, all biomes and most bioregions. ? Precipitation may be the key cause of vegetation growth in this area, even for mountain forests and grasslands.</p>

DOI

[30]
武吉华, 张绅, 江源, 等. 植物地理学(第四版). 北京: 高等教育出版社, 2004.

[Wu Jihua, Zhang Kun, Jiang Yuan, et al.Plant Geography (4th edition). Beijing: Higher Education Press, 2004.]

[31]
郑景云, 尹云鹤, 李炳元. 中国气候区划新方案. 地理学报, 2010, 65(1): 3-12.lt;p>根据全国609个气象站1971-2000年的日气象观测资料,遵循地带性与非地带性相结合、发生同一性与区域气候特征相对一致性相结合、综合性和主导因素相结合、自下而上和自上而下相结合、空间分布连续性与取大去小等5个基本原则,在充分吸纳已有气候区划基本理论与区划方法的基础上,参照中国科学院《中国自然地理》编辑委员会制定的气候区划三级指标体系,对我国气候进行重新区划;结果将我国划分为12个温度带、24个干湿区、56个气候区。与先前区划方案相比发现:20世纪70年代以来,中国气候带、区的总体格局并未发生明显变化,但一些重要的气候分界线却出现了一定程度的移动。其中亚热带北界与暖温带北界均出现了北移,北方地区的半湿润与半干旱分界线也出现了不同程度的东移与南扩,同时中温带、暖温带、北亚热带和中亚热带的三级气候区也出现了一定程度的变动;这种变化可能主要是因为20世纪80年代以后我国大多数地区出现不同程度的增暖及北方一些区域出现干旱化而引起的;且与本区划所采用的资料站点和部分区划原则有一定更新有关。</p>

[Zheng Jingyun, Yin Yuehe, Li Bingyua.A new scheme for climate regionalization in China. Acta Geographica Sinica, 2010, 65(1): 3-12.]

[32]
郭敏杰. 基于NDVI的黄土高原地区植被覆盖度对气候变化响应及定量分析. 北京: 中国科学院大学硕士学位论文, 2014.本文主要采用1982-2006年的NOAA/AVHRR NDVI8 km数据和黄土高原及周边地区82个气象站点的降水、气温数据，探讨了黄土高原地区植被覆盖、主要气候因子的时、空变化特征，以及之间的响应规律，并通过 残差分析法分析了人类活动及气候变化对区域植被改善的影响贡献程度。论文主要结论如下:<br>　　1)1982-2006年，黄土高原地区 植被覆盖度呈不显著上升趋势，植被覆盖度波动较低。四季平均植被覆盖度线性趋势均为正。未变化的植被覆盖度面积占85.29％以上，为中低植被覆盖水平， 植被覆盖改善面积占9.17％，退化面积占5.54％。重心演变分析发现，中低和高植被覆盖面积重心...

[Guo Minjie.Responses of vegetation coverage to climate change on the Loess Plateau based on AVHRR/NDVI and its quantitative analysis. Beijing: Master Dissertation of University of Chinese Academy of Sciences, 2014.]

[33]
Zhang Y, Huang M B, Lian J J, et al.Spatial distributions of optimal plant coverage for the dominant tree and shrub species along a precipitation gradient on the central Loess Plateau. Agricultural and Forest Meteorology, 2015, 206:69-84.The Loess Plateau in China has the most severe soil erosion in the world. Increasing plant coverage can effectively control soil erosion; however, low water availability in this region limits plant growth. The objective of this study was to determine the optimal plant coverage for the two non-native plants mainly used in vegetation restoration ( Robinia pseudoacacia and Hippophae rhamnoides ) on the Loess Plateau. We analyzed the spatial distribution of the mean actual evapotranspiration (AET), net primary productivity (NPP) and maximum leaf area index (LAI) along a precipitation gradient transect on the central Loess Plateau. The modified Biome-BGC model was used to simulate the dynamics of AET, NPP, and LAI for the two plants. The model was assessed by using the only available parameter that had been continuously determined in the field (i.e., AET) that pertained to the two plants growing at two sites that had validated physiological parameters. The validated model was subsequently used to simulate the dynamics of AET, NPP and maximum LAI for the two plants at 75 representative sites along the transect. The results indicated that annual NPP and maximum LAI did not present significant trends over time for either plant. Spatial distributions of the mean AET, NPP, and LAI exhibited decreases along the southeast to northwest precipitation gradient on the Loess Plateau, which was consistent with the spatial distribution pattern of the mean annual precipitation (MAP) in the studied area. In the non-native tree zone where MAP was greater than 550聽mm, the optimal plant coverage (given by the mean maximum LAI value) ranged from 2.5 to 3.5. In the non-native shrub zone where MAP ranged from 250 to 350聽mm, the optimal plant coverage ranged from 0.8 to 1.5. In the mixed zones of non-native trees and shrubs where MAP ranged from 350 to 550聽mm, the optimal plant coverage ranged from 1.5 to 2.5. These quantitative findings giving optimal plant coverages for different precipitation regions should be useful for guiding non-native vegetation restoration on the Loess Plateau.

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[34]
Zhang Q, Zhang L, Huang J, et al.Spatial distribution of surface energy fluxes over the Loess Plateau in China and its relationship with climate and the environment. Science China Earth Sciences, 2014, 57(9): 2135-2147.China's Loess Plateau is located at the edge of the Asian summer monsoon in a transition zone of climate and ecology. In the Loess Plateau, climate and environments change along with space, which has an obvious impact on the spatial distribution of surface energy fluxes. Because of scarce land-surface observation sites and short observation time in this area, previous studies have failed to fully understand the land-surface energy balance characteristics over the entire the Loess Plateau and their effect mechanisms. In this paper, we first test the simulation ability of the Community Land Model(CLM) model by comparing its simulated data with observed data. Based on the simulation data for the Loess Plateau over the past thirty years, we then analyze the spatial distribution of surface energy fluxes and compare the pattern differences between the area averages for the driest year and wettest year. Furthermore, we analyze the relationship between the spatial distribution of the components of the surface energy balance with longitude, latitude, altitude, precipitation and temperature. The main results are as follows: the spatial distribution of surface energy fluxes are significantly different, with the surface net radiation and sensible heat flux increasing from south to north and latent heat flux and soil heat flux decreasing from southeast to northwest. The sensible heat flux at the driest point is nearly twice as high as that at the wettest point, whereas the latent heat flux and soil heat flux at the driest point are half as much as that at the wettest point. The impact of variations of annual precipitation on the components of the surface energy balance is also obvious, and the maximum magnitude of the changes to the sensible heat flux and latent heat flux is nearly 30%. To a certain extent, geographical factors(including longitude, latitude, and altitude) and climate factors(including temperature and precipitation) affect the surface energy fluxes. However, the surface net radiation is more closely related to latitude and altitude, sensible heat flux is more closely related to the monsoon rainfall and latitude, and latent heat flux and soil heat flux are more closely related to the monsoon rainfall.

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[35]
Wang S, Fu B J, Gao G Y, et al.Soil moisture and evapotranspiration of different land cover types in the Loess Plateau, China. Hydrology and Earth System Sciences, 2012, 16(8): 2883-2892.We studied the impacts of re-vegetation on soil moisture dynamics and evapotranspiration (ET) of five land cover types in the Loess Plateau in northern China. Soil moisture and temperature variations under grass (Andropogon), subshrub (Artemisia scoparia), shrub (Spiraea pubescens), plantation forest (Robinia pseudoacacia), and crop (Zea mays) vegetation were continuously monitored during the growing season of 2011. There were more than 10 soil moisture pulses during the period of data collection. Surface soil moisture of all of the land cover types showed an increasing trend in the rainy season. Soil moisture under the corn crop was consistently higher than the other surfaces. Grass and subshrubs showed an intermediate moisture level. Grass had slightly higher readings than those of subshrub most of the time. Shrubs and plantation forests were characterized by lower soil moisture readings, with the shrub levels consistently being slightly higher than those of the forests. Despite the greater post-rainfall loss of moisture under subshrub and grass vegetation than forests and shrubs, subshrub and grass sites exhibit a higher soil moisture content due to their greater soil retention capacity in the dry period. The daily ET trends of the forests and shrub sites were similar and were more stable than those of the other types. Soils under subshrubs acquired and retained soil moisture resources more efficiently than the other cover types, with a competitive advantage in the long term, representing an adaptive vegetation type in the study watershed. The interactions between vegetation and soil moisture dynamics contribute to structure and function of the ecosystems studied.

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[36]
Shi H, Shao M G.Soil and water loss from the Loess Plateau in China. Journal of Arid Environments, 2000, 45(1): 9-20.Physical, geological, climatic and land forming factors in north China are described and the effect of human activities on soil and water erosion are discussed. The proposed measures for the control of soil and water loss are: engineering and biological strategies for reducing runoff, changes in land use, improved grassland and forestry management practices, construction of dams, terraces and s...

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[37]
Wang Y Q, Shao M A, Zhang C C, et al.Choosing an optimal land-use pattern for restoring eco-environments in a semiarid region of the Chinese Loess Plateau. Ecological Engineering, 2015, 74(5): 213-222.The natural environments in the semiarid regions of the Chinese Loess Plateau (CLP) are fragile due to the serious soil erosion and the weak ecological services of the plants. To ascertain and then evaluate a sustainable land-use pattern in these regions, we selected six typical land-use patterns (i.e., a farmland, a natural grassland, a homogeneous shrubland (S), a mix of shrubland and cultivated grassland (S–Alf), a mix of shrubland and orchard (S–O) and a mix of shrubland and grassland (S–G)) on the plateau and then measured the soil water, related soil properties and plant root indices to a depth of 1800cm. We also measured the aboveground net primary productivities (ANPPs). The mean soil water content (SWC) within the 0–1800cm profile was significantly highest (15.2%) in farmland, followed by grassland (11.4%) and S–Alf (8.0%). The available water (AW), the ratio between AW and AW capacity, and the thickness of the dried soil layers also demonstrated that farmland had the best conditions of soil water, followed by grassland and shrubland. The aboveground biomasses of grassland in both non-growing (140gm 612 ) and growing (370gm 612 ) seasons were significantly higher than those of shrublands. The ANPPs of the grassland (2.0gm 612 d 611 ) demonstrated a similar trend. The patterns of land use (including the mixtures of different plant species) greatly affected the patterns of vertical distribution and quantities of soil water within the 1800-cm profile. The data for the soil–water regime and the ANPP further indicated that grassland would be an optimal use of the land for these semiarid regions. This information should be useful to the ecological scientists and policy makers for developing strategies for the sustainable management of vegetation on the CLP and possibly other water-limited regions around the world.

DOI PMID

[38]
艾宁, 魏天兴, 朱清科. 陕北黄土高原不同植被类型下降雨对坡面径流侵蚀产沙的影响. 水土保持学报, 2013, 27(2): 26-30, 35.通过对陕北黄土高原吴起县退耕 地5个不同植被类型径流小区降雨对径流产沙影响的分析,研究退耕还林后不同植被类型的水土保持效应。结果表明:(1)降雨量与雨强对径流量的影响显著;小 区建立初期5个径流小区的产流状况从大到小为油松草地沙棘+油松(Ⅱ)沙棘+油松(Ⅰ)沙棘;随着植被生长,产流从大到小为草地沙棘+油松(Ⅱ)沙棘油松 沙棘+油松(Ⅰ)。随着林分郁闭度的增大,降雨与径流量的相关性在减少。(2)径流量与雨强对产沙量的影响显著;小区建立初期5个径流小区的产沙量从大到 小顺序为油松沙棘+油松(Ⅱ)草地沙棘沙棘+油松(Ⅰ);随着植被生长,产沙量从大到小为草地油松沙棘沙棘+油松(Ⅱ)沙棘+油松(Ⅰ)。随着植被生长, 产沙量基本趋于稳定。(3)坡度对径流产沙的影响显著。同一场降雨,植被类型相同,坡度大的径流量大、产沙量也大;坡度相近的小区,小区建立初期径流产沙 量从大到小为油松沙棘+油松(Ⅱ)草地沙棘沙棘+油松(Ⅰ);随着植被生长,径流产沙从大到小为草地油松沙棘沙棘+油松(Ⅱ)沙棘+油松(Ⅰ)。因此,退 耕还林后,林草植被恢复有效减少了水土流失,在造林初期,沙棘纯林的水土保持效果最为显著,随着植被生长,(沙棘+油松)混合林地的水土保持效应效果最 佳。

[Ai Ning, Wei Tianxing, Zhu Qingke.The effect of rainfall for runoff-erosion-sediment yield under the different vegetation types in Loess Plateau of northern shannxi province. Journal of Soil and Water Conservation, 2013, 27(2): 26-30, 35.]

[39]
Xin Z B, Xu J X, Zheng W, et al. Spatiotemporal variations of vegetation cover on the Chinese Loess Plateau (1981-2006): Impacts of climate changes and human activities. Science in China Series D: Earth Sciences. 2008, 51(1): 67-78.Spatiotemporal variations of Chinese Loess Plateau vegetation cover during 1981-2006 have been investigated using GIMMS and SPOT VGT NDVI data and the cause of vegetation cover changes has been analyzed, considering the climate changes and human activities. Vegetation cover changes on the Loess Plateau have experienced four stages as follows: (1) vegetation cover showed a continued increasing phase during 1981―1989; (2) vegetation cover changes came into a relative steady phase with small fluctuations during 1990―1998; (3) vegetation cover declined rapidly during 1999―2001; and (4) vegetation cover increased rapidly during 2002―2006. The vegetation cover changes of the Loess Plateau show a notable spatial difference. The vegetation cover has obviously increased in the Inner Mongolia and Ningxia plain along the Yellow River and the ecological rehabilitated region of Ordos Plateau, however the vegetation cover evidently decreased in the hilly and gully areas of Loess Plateau, Liupan Mountains region and the northern hillside of Qinling Mountains. The response of NDVI to climate changes varied with different vegetation types. NDVI of sandy land vegetation, grassland and cultivated land show a significant increasing trend, but forest shows a decreasing trend. The results obtained in this study show that the spatiotemporal variations of vegetation cover are the outcome of climate changes and human activities. Temperature is a control factor of the seasonal change of vegetation growth. The increased temperature makes soil drier and unfavors vegetation growth in summer, but it favors vegetation growth in spring and autumn because of a longer growing period. There is a significant correlation between vegetation cover and precipitation and thus, the change in precipitation is an important factor for vegetation variation. The improved agricultural production has resulted in an increase of NDVI in the farmland, and the implementation of large-scale vegetation construction has led to some beneficial effect in ecology.

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[40]
中国科学院黄土高原综合考察队. 黄土高原地区综合治理开发分区研究. 北京: 中国经济出版社, 1990.本文在介绍了黄土高原的基本概 况与建设成就之后,详细剖析了黄土高原地区存在的问题及其产生的原因,总结了其中的经验教训.文中还着重分析了该地区的自然资源及农林牧副各业生产潜力, 提出了资源合理利用与综合经营的具体意见。在此基础上,制定了5个地带25个区域的分区综合治理方案.为了保证这个方案的实施,本文在最后一部分提出了 10条必需的保证措施.

[Loess Plateau Comprehensive Scientifical Survey Group, CAS. Comprehensive Development of the Loess Plateau Region And Their Rational Distribution. Beijing: China Economic Publishing House, 1990.]

[41]
王晗生. 黄土高原植被建设中若干关键问题的研究. 咸阳: 西北农林科技大学博士学位论文, 2002.生态环境建设是实现社会和经济可持续发展的重大问题。黄土高原以严重的水土流失闻名于世，水土保持工作长期以来受到人们的高度关注，然而，迄今，从整体上 说，黄土高原生态环境建设并未达到预期的效果，其中防蚀植被作为重要建设内容，依然是最为薄弱的环节。在我国实施西部大开发战略的新的历史时期，为取得植 被建设实质性的成效，不能不使人们对黄土高原长期造林种草的实践进行反思和总结。 本文从广义植被(包括农作物)的角度出发，通过广泛搜集资料以及野外考察，采取分析与综合、归纳与演绎相结合的方法，对该地区植被建造中存在的根本性关键 问题，如植被建造依据及技术与模式、植被作用下的土壤干化、景观生态建设等进行了探讨。 首先，讨论了植被结构与其防止土壤侵蚀作用的关系，结果表明，植被盖度或郁闭度的大小并不一定就是防蚀有效植被的充分条件，植被保持水土功能还与覆盖层的 高度密切相关，覆盖层高度大并不有利于植被保持水土。贴地面覆盖层的发育程度(盖度或厚度)是防蚀有效植被的充分必要条件，贴地面覆盖因而也是其更为一般 的基本本质特征。植被保持水土重要的是应具有贴地面的覆盖层，促进贴地面覆盖层的发育或关注贴地面覆盖层的变化是植被保持水土的关键。 在上述结论的基础上，本文通过指出现有防蚀植被定义的缺陷，论述了其涵义，认为防蚀植被应当是在侵蚀地区，以防止土壤侵蚀或以固沙为目的，植物充分占据地 面空间，一般具紧密结构，或者显著具有有机体(枯落物以及生物量)贴地面覆盖特征的植被。进一步的分析表明防蚀植被就是发育良好的自然植被或者接近自然的 人工植被，与纯粹追求经济目标的人工植被相比，不仅在结构上，而且在演替、经营等方面是不同的。据此，通过对荒坡问题的讨论，认为应当将灌苹坡，尤其草坡 与真正的荒坡区别开来而对待。 为因地制宜地建造植被，本文还分析了黄土高原植被屈性的有关观点，以及生物气候条件在不同地域之间的分异性和植被地带性特征，说明黄土高原可表征为森林、 草原等地带，不能认为黄土高原不具有森林发育的地带性环境。相对于森林地带北界森林线，森林草原地带北界应为树木线。植被建造不应局限于一种土地利用模 式，如朱显谟“28字方略”，不能无视疏林及稀疏灌丛在森林草原地带的客观存在。 在阐述植被建造依据之后，本文讨论了植被建造的技术与模式，表明典型水土保持植物是建造水土保持植被的首选植物。在分析人工林经营存在问题的基础上，将水 土保持林划分为公益性和公益及商品兼顾林两类，并论述了其成林过程、途径等方面的性质，表明人工水土保持林接近自然的属性是保证其质量的重要特征；使得林 木在一个世代内保持其稳定性而不早衰，或者演替为地带性顶极植被而产生的稳定性，则奠定了其功能持续的基础：较短时期内形成良好的贴地面覆盖是其快速有效 性的前提。鉴于造林的一般立地特征，黄十高原除建造森林植被外，更应高度重视草灌的水土保持作用。在一定情况下，可不必全面造林种草，如植被带状种植形 式，可以较少的占地面积，就能达到良好的水工保持目的。植被带状种植在逐步退耕还林还草中也有着特殊 的意义。一般地，水土保持林内可以间种牧草．但粮、药、菜等间作形式欠妥。商品林虽然通常 也被称其为“林”，但它绝非一般意义上的森林，可以说，两品林属于作物栽培范畴也有一定的 根据。“杂草”概念及其控制具有相对性。 本文接着又讨论了植被土壤水分状况及其与经营的关系，表明在气候干旱少雨，蒸发又强烈 的条件下，黄土高原由于地下水埋藏深，土壤于化是植被作用下易于发生的现象，是人为营造大 片耗水性强的植被类型，高密度以及追求高生本量的必然结果。这种植物生长用水与环境供水之 间的矛盾表现，对人工林草植被的稳定性构成亚重威胁，并对植被衰败后的深根性植物的生长发 育起到显著的抑制作用。显然，植被作用下的土壤干化，对追求经济目标来说是不利的，但对于 防止土壤侵蚀并不一定就产生负面影响。植被作用下土壤干化的显现，表明森林涵养水源的功能 址以实现，水源涵养林是水土保持林，但水土呆待林不一定就是水源涵养林。人为可以将植被作 用下的上壤干化现象加以调节和控制，如局部带状或团块状种植、疏伐、轮作、休闲等。何况， 土壤干化并不是黄土高原植被建造的必然结果。因此，不能以此为由或者根据植被减少流域年总 径流量的结果，怀疑甚至否定黄土高原林草植波的建造。植被作用下的土壤干化现象说明，在贯 彻适地适种原则的基础上，还需选择耗水量少的抗旱节水植物和可维持土壤水库水平的密度或盖 度，这是保证植被稳定持久值得重视的又一重翌方面。从有利于流域水资源状况的改善，在满足 水土保持目标的前提下，人工林草植被的发展也应该适度规模。公益性植被建造不能根据作物栽 培的水分利用原则，极尽将降雨转化为生物产量。 最后，本文由景观生态学的观点理解生态环境建设，分析了“山川秀美”的涵义，讨论了黄 士高原生态环境建设的目标、重点、原则、途径等。基本农田建设在一定程度上关系到生态环境

[Wang Hansheng.Research into several key problems existing in vegetation in construction in Loess Plateau. Xianyang: Doctoral Dissertation of Northwest Agriculture and Forest University, 2002.]

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