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GEOGRAPHICAL RESEARCH >

2018 , Vol. 37 >Issue 12: 2433 - 2446

DOI: https://doi.org/10.11821/dlyj201812006

Articles

Vegetation change and its topographic effects in the karst mountainous areas of Guizhou and Guangxi

  • LIU Liangmeizi , 1, 2 ,
  • ZHAN Chesheng , 1 ,
  • HU Shi 1 ,
  • DONG Yuxuan 3
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  • 1. Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • 2. University of Chinese Academy of Sciences, Beijing 100049, China
  • 3. College of Water Sciences, Beijing Normal University, Beijing 100875, China

Received date: 2018-06-14

  Request revised date: 2018-09-16

  Online published: 2018-12-20

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《地理研究》编辑部 所有
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Abstract

Rocky desertification is one of the most severe ecological issues that restrict the sustainable development of karst area in southwestern China. Compared with other ecosystems, mountain ecosystem is more sensitive to climate change due to its complex topography. Understanding the variation of vegetation growth associated to topographic factors is critical to promote ecological management in karst mountainous areas. Based on the Moderate Resolution Imaging Spectroradiometer Normalized Difference Vegetation Index (MODIS NDVI) data from 2000 to 2016, the spatial-temporal variation of NDVI in the karst mountainous area of Guizhou and Guangxi was analyzed. The topographical factors, including altitude, slope gradient, aspect and relief amplitude were introduced to examine the response of vegetation variation to topographical factors. The results showed that NDVI in the middle of karst mountainous area was higher than that in the northwest and southeast. Averaged NDVI during growing season showed a single-peak curve distribution with altitude, with the largest value (0.67) at an elevation of 400-600 m. However, no significant difference was found along the slope and aspect gradient. A greening trend occurred in the karst mountainous area, with an averaged increasing rate of 0.0018 yr-1, illustrating that the vegetation restoration in recent years tended to be better. More than 75% of the study area showed an increasing trend of NDVI, and about 20% of the study area, distributed in the western and southeastern parts of the region (southwest Guizhou and central Guangxi), performed a significant increase. Pixels with a decreasing trend of NDVI were only observed in the northeast and middle-eastern parts. The percentage of pixels with a significant increasing trend increased with the elevation gradient. The increased rate is higher at high altitude than that at low altitude, indicating that the ecological construction of vegetation at low altitude with gentle slope should be strengthened. These conclusions provide a scientific basis for the comprehensive treatment of rocky desertification and improvement of fragile ecological environment in the karst mountainous area in a certain sense.

Key words： NDVI; vegetation changes; topographic effects; karst mountainous area

Cite this article

LIU Liangmeizi , ZHAN Chesheng , HU Shi , DONG Yuxuan . Vegetation change and its topographic effects in the karst mountainous areas of Guizhou and Guangxi[J]. GEOGRAPHICAL RESEARCH, 2018 , 37(12) : 2433 -2446 . DOI: 10.11821/dlyj201812006

石漠化是中国西南喀斯特山区最严重的生态问题[1]。如何对喀斯特山区植被实行保护与恢复,有效遏制石漠化、控制水土流失,已成为改善喀斯特生态环境的重要内容[2]。
植被是陆地生态系统中的重要成分,反应区域石漠化变化的重要信息[3]。地形因子是影响植被形成、覆盖的最主要因素之一[4]。其中,海拔高度影响土壤的垂直地带性[5];坡度和坡向能够影响地表径流、日照时长、湿度、温度等[6];地形起伏度也会影响区域小气候。各地形要素之间相互作用,共同影响植被的生长条件进而影响植被覆盖[7]。已有大量研究分析地形因子与植被覆盖[4]、植被生产力[8]、植被多样性[6]的关系。在不同的研究区,影响植被分布的地形因子各不相同[7]。如在巴西东南部的大西洋热带雨林,海拔高度和坡度是影响植被分布的主要因素[9];以色列北加利利山的植被分布格局受坡度和坡向影响[10]。此外,同一地形因子对植被分布的影响在不同地区也不尽相同,如在北京百花山,海拔1500~1800 m内,植被丰富度最高[6];而在祁连山,受降水增多和温度升高的影响,植被覆盖在2700~3600 m范围内呈现显著增加趋势[11]。在美国俄勒冈州东南部,坡度是影响植被多样性的唯一非土壤因子[12],但在中国西南地区的干热河谷,坡度对植被覆盖的影响十分微弱[13];在新墨西哥北部的雷东多山,由于北坡接收的太阳辐射少于东坡,抑制了植被生长,使得北坡的森林覆盖度低于东坡[14]。而在北半球干旱条件下则得到相反的结论,阴坡因为日照时数较阳坡短,蒸发过程弱,水分较好,植被长势也更为良好[15]。在喀斯特山区,由于地形差异导致的能量分配[14]、土壤性质[16]不同,会影响区域植被分布格局的差异。因此,探索喀斯特山区近年来的植被变化情况及其受地形的控制效应,对未来国家石漠化山区生态保护政策的制定具有科学指导意义。
遥感影像由于空间尺度大、时间序列长、间隔周期短的特点,已成为大尺度植被动态变化研究的重要数据源之一[17]。其中,运用归一化植被指数（The Normalized Difference Vegetation Index,NDVI）对植被生长的动态监测在全球尺度、洲际尺度和区域尺度均较为广泛[18]。但目前国内有关植被动态变化的研究重点区域是西北、东北以及包括青藏高原、蒙古高原、黄土高原在内的三大高原[19],有关西南喀斯特山区的研究虽有所涉及,也大多以省域县域为研究单元[20,21],鲜有以自然地貌划分的研究区,此外,以往的研究大多聚焦于气候变化和人类活动对植被变化的影响[22,23,24],但在生境脆弱、地形复杂的喀斯特山区,除气候因素和人类活动之外,植被变化也受特殊地形影响[2]。本文针对喀斯特山区这一独特地形,同时从海拔高度、坡度、坡向、地形起伏度四个重要的地形因子出发,以栅格为基本计算单元,探寻喀斯特山区植被的时空变化规律及其与地形因子的相互关系,提出可能的驱动因子,明确植被恢复显著区以及仍需加强生态治理的区域,为喀斯特山区石漠化综合治理,以及脆弱生态环境的改善提供科学依据。

1 研究方法与数据来源

1.1 研究区概况

黔桂喀斯特山区（22°05′N~28°15′N、104°15′E~110°25′E）,位于中国西南地区,包括贵州中南部和广西中西部,具体含贵阳、六盘水、安顺和河池的全部地区,黔西南、黔南、毕节、百色、柳州、来宾、贵港、崇左和南宁的大部份地区,以及铜仁、遵义和黔东南的小部份地区,共107个县,总面积252769.21 km2。东接湖南、西邻云南、北连四川,地势自西北向东南逐渐降低,最高海拔为2800 m（图1a）,山地众多,平原较少。属于亚热带季风气候,年平均气温多在15 ℃以上,年降水超过1200 mm,雨季明显,受季风影响多集中在4-10月。
Fig. 1 Elevation and land cover types in the karst mountainous areas

图1 研究区高程及土地覆盖类型

1.2 数据来源及处理

本文中的基础数据主要包括地理数据和遥感数据。其中,遥感数据来源于MODIS NDVI16天最大化合成的MOD13Q1数据（http://modis.gsfc.nasa.gov/data/dataprod/mod13.php）,空间分辨率250 m。所有的遥感数据均利用SG滤波法对数据进行降噪,将NDVI绝对值（最大年NDVI值-最小年NDVI值）小于0.1和不在0~1范围内的网格赋空值,因为这些格网分别主要是建设用地和水域。
文中使用的地理数据主要包括数字高程模型（DEM）和土地利用的数据。DEM数据通过中国科学院计算机网络信息中心国际科学与技术数据镜像站点（http://www.gscloud.cn）获得,空间分辨率为90 m,为与MODIS NDVI数据精度一致,重采样转换为250 m,同时提取喀斯特山区的坡度、坡向信息,地形起伏度的提取基于变点分析法[25,26,27]。文中的海拔以200 m一个间隔,由于2000 m以上格点较少,在NDVI显著变化格点沿海拔梯度分布规律的分析时可能造成结果的不合理,因此将其合并为一个等级,共11级。地形起伏度按100 m间隔划分,起伏度700 m以上的格点并为一类,共8类。坡度的分级与海拔、地形起伏度相似,以2.5°等间隔划分,25°以上合并,计11类。坡向按4方向分类法分为阳坡、阴坡、半阳坡和半阴坡[28]。
土地利用类型数据（LUCC）由中国科学院遥感与数字地球研究所基于MODIS生态系统分类标准进行遥感解译和分类得到,空间分辨率为30 m。本文选取其2010年最新的分类数据进行分析,为保证各类型数据精度的一致性,按各土地利用类型最大面积占比将30 m的数据重采样至250 m。喀斯特山区的植被覆盖类型主要包括以下8种：常绿阔叶林、落叶阔叶林、常绿针叶林、针阔混交林、灌木林、草地、水田、旱地,占比极小的植被类型,包括稀疏林、稀疏草地、落叶阔叶灌木林、灌木绿地等全部归入“其他植被”类,不作后续分析。文中所有数据的统一投影坐标为兰勃特方位等积投影。

1.3 研究方法

1.3.1 遥感数据预处理 由于冰雪、气溶胶等干扰,NDVI数据值可能出现缺失或异常。因此,文中使用的NDVI数据经过滤波平滑处理,以消除大气带来的噪音。本文采用的是Chen等改进的SG滤波方法[29],在该算法中引入了拟合影响因子Fk,通过比较前后相邻计算得到的Fk,确定拟合是否达到最佳而停止。Fk是第k次平滑的拟合因子,它是对观测值与真值间接近程度的刻画,当它达到局部最小时（即满足公式1时）,标志这一序列点的拟合值与真值达到了最接近的程度,计算终止。
F k - 1 ≥ F k ≤ F k + 1 （1）
Fk的计算如下：
F k = ∑ i = 1 n N i k + 1 - N i 0 × W i （2）
式中： N i k + 1 是第i个遥感数据值第K次平滑之后的值,其计算如式（3）所示;Wi是第i个遥感数据的权重,计算如式（4）所示：
N i k + 1 = N i 0 , N i 0 ≥ N i tr N i tr , N i 0 < N i tr （3）
W i = 1 , N i 0 ≥ N i tr 1 - d i d max , N i 0 < N i tr （4）
式中：Ni是第i个遥感数据的原始值; N i tr 是利用SG滤波平滑之后的遥感数据;di是原始遥感数据和平滑之后数据之间的差值,即 d i = N i 0 - N i tr ;dmax是原始遥感数据和平滑之后数据之间的最大差值。
1.3.2 一元线性回归分析法 为了拟合喀斯特山区2000-2016年归一化植被指数（NDVI）的变化趋势,采用一元线性回归分析方法[30],即最小二乘法,基于栅格尺度分析植被覆盖的年际变化。
斜率θ的计算公式如下：
θ = n × ∑ i = 1 n i × NDV I i - ∑ i = 1 n i ∑ i = 1 n NDV I i n × ∑ i = 1 n i 2 - ∑ i = 1 n i 2 （5）
式中：i表示年份序号;NDVIi表示第i年的NDVI值;得到的θ表示时间序列上NDVI的变化趋势。若θ>0,近17年NDVI增加,区域植被有绿化趋势;若θ<0,区域植被有退化趋势。
NDVI变化趋势的显著性检验以F检验为基础进行,统计量F的计算公式如下：
F = U Q × ( n - 2 ) U = ∑ i = 1 n ( y ˆ i - y ̅ ) 2 Q = ∑ i = 1 n ( y i - y ˆ i ) 2 （6）
式中：U表示误差平方和,反映自变量时间对因变量NDVI的作用程度;Q表示回归平方和,又叫剩余平方和或残差平方和,反映其他因素的作用引起的因变量NDVI的波动程度;yi表示年份i的NDVI观测值; y ˆ i 和 y ̅ 分别为NDVI的回归值和平均值;n为年份数。
后续统计分析中,不同植被类型随海拔显著变化格点面积占比指的是各海拔范围内各植被类型显著变化的格点与该植被类型在该海拔所有格点数的比值（地形起伏度、坡度、坡向同）。

2 结果分析

2.1 NDVI的空间格局

2.1.1 年均NDVI的空间格局 黔桂喀斯特山区多年平均NDVI为0.63（图2）,略高于贵州省年均值（0.57）[31],呈现中部高,西北、东南低的格局。NDVI值大于0.7的地区大约占研究区总面积的十分之一,主要分布于海拔较低的广西西北部附近（河池市、百色市）,植被类型以常绿阔叶林为主;而在贵州中部、广西南部、东部极少部分区域,NDVI值小于0.4,不足研究区总面积的千分之一。
Fig. 2 Spatial distribution of annual NDVI in karst mountainous areas from 2000 to 2016

图2 2000-2016年喀斯特山区NDVI的空间分布

2.1.2 平均NDVI与海拔高度、地形起伏度 NDVI变化随海拔高度和地形起伏度呈单峰曲线,峰值分别在400~600 m和400~500 m左右,不同植被类型NDVI随海拔高度、地形起伏度的变化趋势一致,森林植被的NDVI值较其他植被类型高（图3、图4）。地形起伏度400~500 m的区域大多位于海拔400~600 m范围内,海拔400~600 m处,地势相对平坦,以常绿阔叶林、常绿针叶林和针阔混交林为主,植被的热量、光照、水分等条件均比较充足[32],且地处广西境内的山区,城镇化速率缓慢,植物的生长环境良好,植被覆盖率较大,NDVI较高[33]。随着海拔升高,地势变陡,水热条件相对较差,植被生长受到抑制,NDVI降低。当海拔高于2400 m时,植被生长受山顶效应影响,由于光照强,风速大,蒸散发强烈,且土层瘠薄,植被一旦遭到破坏,恢复极难。
Fig. 3 The distribution of NDVI at different altitudes

图3 NDVI在不同海拔上的分布状况

Fig.4 The distribution of NDVI at different relief amplitudes

图4 NDVI在不同地形起伏度上的分布状况

2.1.3 平均NDVI与坡度坡向 平均NDVI的坡度、坡向差异均不明显（图5）。随坡度的增加,人类活动逐渐减少,平均NDVI有上升趋势,但并不明显。平均NDVI在不同坡向上几乎无异。一般而言,在干旱和半干旱区,水分是植被生长的主要限制因子[34],阴坡蒸发较少,土壤水分压力较阳坡小,植被长势较阳坡更为茂盛;在北半球高海拔地区,温度限制植被生长[35],阳坡由于接收到更多的太阳辐射,植被生长更为良好,喀斯特山区水热条件优异,太阳辐射和水分耗散两者共同作用,使得NDVI随坡向变化并不明显。
Fig. 5 NDVI of different vegetation types on different slopes and aspects

图5 不同植被类型在不同坡度、坡向上的NDVI

2.2 NDVI时空变化特征

2.2.1 NDVI的时相变化 2000-2016年喀斯特山区平均NDVI呈上升趋势（图6）,这与Piao等在全国范围[36]、蒙吉军等在西南地区[37]以及童晓伟等在喀斯特山区[2]的研究结果一致。
Fig. 6 Annual NDVI changing trend from 2000 to 2016

图6 2000-2016年年均NDVI变化趋势

NDVI的变化大体可以分为四个阶段：2000-2004年为增长期;2006年为NDVI的极小值点（0.59）,这是由于2003年以来中国南方地区处于枯水期[38],且2006年研究区内平均温度较高,喀斯特山区溶蚀作用明显,降水沿溶蚀漏斗流入地下,难以被植被有效利用,植被生长受到抑制;2006-2009年为增长期;2010-2016年NDVI呈振荡上升的趋势。
冬季对NDVI年际变化的贡献最大（图7）,平均变化率约为0.0036 yr-1,这可能与喀斯特山区近年的气候变化有关。
Fig. 7 Interannual changing rate of NDVI in each season from 2000 to 2016

图7 2000-2016年各季节NDVI年际变化率

2.2.2 NDVI变化趋势的空间格局 NDVI多年动态变化趋势（图8a、图8b）显示：2000-2016年,喀斯特山区73.4%的区域NDVI年均值呈增长趋势,其中21.4%的区域为显著增长（P<0.05）,约3%的地区明显下降,NDVI的平均增长率约为0.0018 yr-1。说明在喀斯特山区,近年来的植树造林、退耕还林等一系列生态建设工程所带来的生态效益已有所呈现,植被绿度呈增加趋势,喀斯特山区的生态环境正趋于好转。
Fig. 8 Spatial pattern of annual NDVI variation in karst mountainous area from 2000 to 2016

图8 2000-2016年喀斯特山区NDVI变化趋势的空间格局

NDVI变化具有明显的空间异质性,其中较大的绿化趋势出现在喀斯特山区西部和东南部（0.007 yr-1~0.024 yr-1）,包括六盘水、安顺、毕节、来宾、贵港等地（黔西南和桂中地区）。这些地区植被覆盖度较低,人口密度和载畜量水平也相对低,植被受人类活动影响较少,因此植被恢复良好。由于城市快速发展和人口积聚效应导致大量的人类活动如辟林放牧、兴建城镇等,呈下降趋势的区域主要位于东北部和中东部的城市周围（包括贵阳、遵义、铜仁、柳州等）,下降幅度在-0.04 yr-1~-0.001 yr-1之间。

2.3 NDVI时空变化特征的地形效应

2.3.1 NDVI变化与海拔高度 不同的海拔高度上NDVI以增加为主,显著减少的面积占比极小,最大值仅为7%（图9）。
Fig. 9 The percentage of pixels with significant tendency along elevations (P<0.05)

图9 NDVI显著性变化格点占比随海拔高度的变化趋势（P<0.05）

虽然不同植被类型的增长比例具有一定的海拔差异,但总体而言,喀斯特地区NDVI显著增加格点占比随海拔增加而增加,显著降低格点占比呈相反的变化趋势（图9）。其中在海拔1800 m左右针阔混交林增加显著,海拔2000 m以上,旱地增加显著,而海拔2300 m左右,低矮的草甸增多导致草地NDVI增加显著。相反的,低海拔（<600 m）植被减少显著,尤其是针叶林和阔叶林,说明低海拔地区受人类活动影响较强,大部分针叶林和阔叶林转化为建设用地,使总体植被NDVI值降低。
海拔400 m以下,植被显著增加格点占比与显著减少格点占比均呈现下降趋势,表明该海拔范围内植被变化的波动较大,在外界干扰时植被结构更不稳定[2]。海拔2000 m以上显著增加格点面积占比与显著减少格点面积占比差值最大,植被增加最为显著,主要表现在旱地和草地NDVI增长明显。这表明在高海拔地区,由于土地资源更为稀缺,人类向高海拔进行土地资源开发的程度更大,开荒的耕地和稀疏的草丛增多[38]。此外,封山育林等政策的实施也有利于高海拔地区的植被结构稳定[2]。
2.3.2 NDVI变化与地形起伏度 在不同的地形起伏度范围内NDVI以增加为主,显著减少的部分极少（图10）。其中,显著增加格点占比随地形起伏度先减少后增加,谷值位于200~300 m范围内,在起伏度300 m以上,由于草地和耕地急剧增加,显著增加格点占比逐步增加。表明在喀斯特山区坡耕地耕种并未停止[2],另一方面,草地的显著增加趋势也说明一系列生态工程在喀斯特山区已发挥作用。NDVI显著降低格点面积占比随地形起伏度增加呈下降趋势,地形起伏度300 m以下,受森林植被和耕地减少影响,显著降低格点面积占比快速下降。
Fig. 10 The percentage of pixels with significant tendency along relief amplitudes (P<0.05)

图10 NDVI显著性变化格点占比随地形起伏度的变化趋势（P<0.05）

2.3.3 NDVI变化与坡度 不同的坡度范围内植被以恢复为主（图11）。显著增长格点占比基本稳定在21%左右,且随坡度变化波动较大,10°达到峰值后下降,直到坡度大于25°时,由于草地以及耕地（包括水田和旱地）显著增加,显著增长格点面积占比有一个“陡升”的趋势。由于地少人多,喀斯特山区陡坡耕种大量存在,其中25°以上坡度垦殖占比13.14%[39],使得坡度大于25°时NDVI增长迅速。
Fig.11 The percentage of pixels with significant tendency along slopes (P<0.05)

图11 NDVI显著性变化格点占比随坡度的变化趋势（P<0.05）

在坡度小于10°时,NDVI显著下降格点占比随坡度增加显著减小,超过10°后趋于稳定（约为1.5%）。坡度10°以下NDVI显著减小的区域主要为耕地,由于城市化进程加快使得建筑用地面积激增,建筑用地多分布于缓坡处,喀斯特山区缓坡（0°~5°）内耕地占43.89%[40],因此,建筑用地的扩张导致耕地面积迅速减少[41]。
2.3.4 NDVI变化与坡向 NDVI变化的坡向差异不大（图12）。不同坡向上,NDVI值以增加为主,然而显著变化格点的占比变化不显著。其中,耕地受坡向影响较为显著。NDVI上升格点有向半阳坡（60°~120°）倾向的趋势,降低格点主要分布在330°~0°的阴坡范围内。由此可以看出,由阴坡转向阳坡时,一开始由于太阳辐射增强,植被恢复趋势先增强,而后由半阳坡转至阳坡,人类活动影响增强,土壤养分减少,植被恢复有减弱趋势,但变化幅度较小[42]。
Fig. 12 The percentage of pixels with significant tendency along aspects (P<0.05)

图12 NDVI显著性变化格点占比随坡向的变化趋势（P<0.05）

3 讨论

NDVI是指示植被的密度以及动态变化[24]的重要因子,与植被的覆盖密度呈正相关关系[43]。在过去的20年间,已有大量研究运用长时间序列的NDVI数据对全球、洲际和区域尺度的植被动态的年际变化进行探讨[44,45]。中国的植被覆盖有逐渐绿化的趋势[46,47]。针对喀斯特山区,据中国石漠化公报显示[48],经实地估算,2005-2011年,广西石漠化土地减少面积最多（4.53×109 m2）,贵州减少2.92×109 m2;Tong等通过集成长时间序列光学、微波遥感影像、生态系统模型、气候变化及生态工程投入与治理地面核查等数据,阐明在西南喀斯特地区,植被恢复与生态工程的实施具有良好的一致性[49];也有不同研究者运用不同的遥感数据源（MODIS、AVHRR、Landsat TM、SPOT等）,从不同空间尺度（县域—省域—西南部）[37,50,51]和多时间尺度[52]（3年、6年、14年、32年）出发,分析得出：由于退耕还林还草等一系列生态工程以及全球气候的变化[22,23,24],喀斯特山区植被覆盖也有所增加,生态环境趋于好转。NDVI的平均增长率（0.0018 yr-1）与Piao 等[36]（1982-1999年间为0.0018 yr-1）一致,略低于Tian等[31]贵州省NDVI增长率0.0028 yr-1,略高于Hou等[53]中国西南地区NDVI增长率0.0015 yr-1。
对山区而言,降水量随海拔升高而增加,直到最大降水高度（降水量最大时对应的高程）,而后随海拔上升而减少。最大降水高度主要发生在温暖潮湿的水流上升的区域。而气温随海拔升高呈明显下降趋势。因此,往往在海拔中段水热条件最为优越[54]。在喀斯特山区,海拔400~600 m处是植被NDVI的峰值。除优越的水热条件外,该海拔范围内地势平坦,植被类型以森林植被为主,地处广西境内的山区,城镇化速率缓慢[33],故NDVI值较高。
不同地形条件下植被变化差异明显。随海拔升高NDVI增加显著,起伏度300 m以上和陡坡（>25°）处植被恢复显著,高海拔、大起伏度、陡坡处的植被变化主要受耕地和灌丛草地影响。这表明喀斯特区域人类活动的干扰空间在扩大,趋向于高海拔和陡坡地区[55]。同时,封山育林等生态工程使得高山的灌丛、草地受人为扰动小,利于植被的恢复。而在低海拔地区,由于人类活动剧烈,针叶林、阔叶林转变为诸如建筑用地等,导致植被NDVI降低[40]。一般来说,朝南的坡面较朝北的坡面获取更多的太阳辐射,从而增强植物生长的光合作用。然而,较多的太阳辐射也会导致蒸散耗水增多,土壤水储量减少[14]。这两种影响在区域尺度上可以相互抵消,其综合效应导致坡向对NDVI变化的影响不显著。此外,由于土地利用图和遥感数据的空间分辨率的限制,不可避免地会忽略一些细节信息,这也削弱了坡向的影响。因此,今后还需要在多空间尺度上进一步进行研究。未来黔桂喀斯特山区植被生态建设与恢复应多重视低海拔、缓坡、阳坡处的植被生态治理。

4 结论

基于订正后的2000-2016年MODIS NDVI遥感数据以及黔桂喀斯特山区DEM、LUCC地理数据,结合GIS方法,探究了该喀斯特山区2000-2016年植被生长的变化趋势和垂直分布特征,得到以下结论：
（1）喀斯特山区多年平均NDVI介于0.1~0.9之间,均值约0.63,植被分布总体呈现中部高,西北、东南低的趋势。年均NDVI随海拔和地形起伏度变化呈单峰曲线,峰值分别在400~600 m和400~500 m左右,随坡度和坡向的变化并不明显。
（2）近年来喀斯特山区植被绿化情况转好,冬季对植被变化的影响最大。2000-2016年NDVI的平均增长率约为0.0018 yr-1（P<0.05）。75%左右的区域植被呈现增长趋势,其中超过20%的区域显著增长,不到5%的地区明显下降。较大的绿化趋势出现在喀斯特山区西部和东南部,包括黔西南和桂中地区。呈显著下降趋势的区域主要位于东北部和中东部,包括贵阳、遵义、铜仁、柳州等。
（3）喀斯特2000-2016年间的植被变化受地形因子影响,尤其是海拔高度。年均NDVI呈增长趋势的比例随海拔的增加而增加,低海拔及地形起伏度较小处,人类活动的干扰导致植被恢复慢;坡度10°左右时植被绿化趋势较为显著,得益于坡耕地耕种以及草地的自然恢复,大地形起伏度（>300 m）和陡坡（>25°）处植被恢复呈快速增长趋势;NDVI随坡向的变化不明显,但当坡向由阴坡转向阳坡,植被恢复呈先增强后减弱的趋势,未来喀斯特山区应进一步加强低海拔、缓坡、阳坡处的植被生态治理。

The authors have declared that no competing interests exist.

References

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[11]
Deng Shaofu, Yang Taibao, Zeng Biao, et al.Vegetation cover variation in the Qilian mountains and its response to climate change in 2000-2011. Journal of Mountain Science, 2013, 10(6): 1050-1062.An understanding of variations in vegetation cover in response to climate change is critical for predicting and managing future terrestrial ecosystem dynamics. Because scientists anticipate that mountain ecosystems will be more sensitive to future climate change compared to others, our objectives were to investigate the impacts of climate change on variation in vegetation cover in the Qilian Mountains (QLM), China, between 2000 and 2011. To accomplish this, we used linear regression techniques on 250-m MODIS Normalized Difference Vegetation Index (NDVI) datasets and meteorological records to determine spatiotemporal variability in vegetation cover and climatic factors (i.e. temperature and precipitation). Our results showed that temperatures and precipitation have increased in this region during our study period. In addition, we found that growing season mean NDVI was mainly distributed in the vertical zone from 2,700 m to 3,600 m in elevation. In the study region, we observed significant positive and negative trends in vegetation cover in 26.71% and 2.27% of the vegetated areas. Correlation analyses indicated that rising precipitation from May to August was responsible for increased vegetation cover in areas with positive trends in growing season mean NDVI. However, there was no similar significant correlation between growing season mean NDVI and precipitation in regions where vegetation cover declined throughout our study period. Using spatial statistics, we found that vegetation cover frequently declined in areas within the 2,500 3,100 m vertical zone, where it has steep slope, and is on the sunny side of mountains. Here, the positive influences of increasing precipitation could not offset the drier conditions that occurred through warming trends. In contrast, in higher elevation zones (3,900 4,500 m) on the shaded side of the mountains, rising temperatures and increasing precipitation improved conditions for vegetation growth. Increased precipitation also facilitated vegetation growth in areas experiencing warming trends at lower elevations (2,000 2,400 m) and on lower slopes where water was more easily conserved. We suggest that spatial differences in variation in vegetation as the result of climate change depend on local moisture and thermal conditions, which are mainly controlled by topography (e.g. elevation, aspect, and slope), and other factors, such as local hydrology.

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[12]
Davies K W, Bates J D, Miller R F.Environmental and vegetation relationships of the Artemisia tridentata, spp wyomingensis, alliance. Journal of Arid Environments, 2007, 70(3): 478-494.The Artemisia tridentata spp. wyomingensis (Beetle & A. Young) S.L. Welsh alliance is the most extensive of the big sagebrush complex in the Intermountain West and is characterized by a wide range of environments and vegetation heterogeneity. The purpose of this study was to identify environmental factors driving variation in plant species composition and determine the potential for using environmental factors to explain vegetation characteristics of the A. tridentata spp. wyomingensis alliance. Seventeen environmental factors and seven vegetation response variables were measured on 107 relatively undisturbed, late seral A. tridentata spp. wyomingensis sites across southeastern Oregon and northern Nevada. Non-metric multidimensional scaling (NMS) was used to identify environmental factors correlated with plant species composition as indexed by canopy cover. Stepwise multiple linear regressions were used to develop models correlating plant cover and structural characteristics with environmental factors. Vegetation composition variation appears to be driven by soil characteristics. Canopy cover of perennial grasses and forbs was moderately correlated with direct incident radiation and soil characteristics, particularly soil texture in the upper 15 cm of the profile. Total herbaceous cover variation was better explained by environmental factors (soil water-holding capacity, incident radiation, depth to Bt horizon, and percent sand in the upper 15 cm of the soil profile) ( P<0.0001, R 2=0.52) than any other vegetation characteristic. Vegetation structural characteristics (e.g. sagebrush height, canopy volume and canopy cover, density, and plant visual obstruction) exhibited weak or no relationships with measured environmental variables. Limited correlation among environmental factors and some vegetation characteristics was likely due to the large ecological amplitudes and ecotypic variations expressed by many of the plant species in the sagebrush steppe. This study expands our understanding of the A. tridentata spp. wyomingensis alliance and elucidates the complexity of environmental 搗egetation relationships.

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[13]
Dong Yifan, Xiong Donghong, Su Zhengan, et al.The distribution of and factors influencing the vegetation in a gully in the Dry-hot Valley of southwest China. Catena, 2014, 116(1): 60-67.61Dry-hot valley in southwest China with a fragile ecology and serious gully erosion.61The vegetation-soil-topography relationship in the gully area.61The vegetation distribution on the gully sidewall and the gully bed.

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[14]
Zapata-Rios X, Brooks P D, Troch P A, et al.Influence of terrain aspect on water partitioning, vegetation structure and vegetation greening in high-elevation catchments in northern New Mexico. Ecohydrology, 2015, 9(5): 782-795.

[15]
常学礼, 吕世海, 冯朝阳, 等. 地形对草甸草原植被生产力分布格局的影响. 生态学报, 2015, 35(10): 3339-3348.草原植被生产力在陆地生态系统碳平衡分析中扮演重要角色,而地形作为影响植被生产力(NPP)分布格局的重要环境因子在已有的草原遥感监测研究中没有被充分重视。以USGS和GLCF共享MODIS和DEM数据为数据源,选取呼伦贝尔辉河湿地保护区草甸草原核心区为研究对象,在地面光谱生物量模型构建的基础上,采用ARCGIS的空间分析功能对呼伦贝尔草甸草原2000-2012年的NPP分布格局进行了分析。研究结果表明,地形对草甸草原植被生产力分布格局有显著的影响。在海拔高度、坡度和坡向等3个地形因子中,海拔高度引起的NPP变化幅度最大,坡度次之,坡向最小。在总体特征上,海拔高度每升高10m,生产力增加4.78 g/m<sup>2</sup>;坡度每增加1&#176;生产力增加-1.42 g/m<sup>2</sup>;N坡向植被生产力水平最高(184.8 g/m<sup>2</sup>),西南(SW)坡向最低(173.3 g/m<sup>2</sup>)。从不同地形因子的分布面积特点判断,地形对草甸草原NPP的影响尺度介于土壤环境异质性和草场类型异质性之间。不同生产力水平年份对生产力分布格局的影响趋势一致,但变化幅度不同,在中等生产力水平年份NPP变幅最大。

DOI

[Chang Xueli, Lyu Shihai, Feng Zhaoyang, et al.Impact of topography on the spatial distribution pattern of net primary productivity in a meadow. Acta Ecologica Sinica, 2015, 35(10): 3339-3348.]

[16]
Li Jingjing, Peng Shouzhang, Li Zhi, et al.Detecting and attributing vegetation changes on China's Loess Plateau. Agricultural & Forest Meteorology, 2017, 247: 260-270.

[17]
Liu Rui, Xiao Linlin, Liu Zhe, et al.Quantifying the relative impacts of climate and human activities on vegetation changes at the regional scale. Ecological Indicators, 2018, 93: 91-99.Understanding human and climate-induced vegetation changes could benefit regional ecological management. In this paper, a framework was established to quantify the relative contribution rates of human and climate factors to vegetation changes in Chongqing, China, from 2000 to 2015. MODIS NDVI time series data were collected, and land use data were produced using Landsat TM/OLI images. A combined analysis of land use and vegetation changes was conducted, and the residual trends method (RESTREND) was explored in the framework. The results showed that Chongqing experienced a significant vegetation increase from 2000 to 2015. The relative contribution rates of human activities and climate to the vegetation changes were 90.96% and 9.04%, respectively. These results indicate that human activities had a dominant role in vegetation restoration in Chongqing in 2000 2015. Throughout the study period, extensive land use changes occurred in Chongqing. During the study period, persistent forested land, farmland-forested land (a land use conversion type), persistent farmland, and grassland-forested land were the four most important land use (changed and unchanged) types attributed to the growing season NDVI (GSN) increases in Chongqing from 2000 to 2015. The contributions of these four land use types were 45.03%, 21.19%, 16.79% and 12.60%, respectively. The farmland-forested land was characterized as the most effective land use conversion type for vegetation restoration. The proposed framework allows for human and climate-induced vegetation changes to be quantitatively distinguished at the regional scale and provides the contribution rates of each changed and unchanged land use type. The framework is expected to be useful for regional ecological management and research.

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[18]
马明国, 王建, 王雪梅. 基于遥感的植被年际变化及其与气候关系研究进展. 遥感学报, 2006, 10(3): 421-431.植被具有明显的年际变化和季节变化特点,对植被的动态监测可以从一定程度上反映气候变化的趋势,因此监测植被动态变化以及分析这种变化与气候的关系已经成为全球变化研究的一个重要领域.随着遥感卫星获得长时间系列逐日观测数据,许多国际组织和机构制定了全球卫星数据接收、处理和生成数据集计划,所产生的标准数据集则极大地促进了该项研究.大量研究在全球尺度、洲际尺度（北美洲和欧亚大陆）以及区域尺度上广泛开展.在阅读国内外大量文献的基础上,比较分析了常用于植被监测的卫星传感器和主要数据集,汇总了植被年际变化及其与气候关系研究的主要研究方法和研究结果.结果表明近20年来全球植被活动明显增强,表现为北半球普遍存在增加的趋势,南半球干旱半干旱区出现降低的植被光合作用,但这些变化因空间位置不同和研究尺度不一样体现出不同的动态变化特征.气温和降水是影响植被变化的最主要的因素.

DOI

[Ma Mingguo, Wang Jian, Wang Xuemei.Advance in the inter-annual variability of vegetation and its relation to climate based on remote sensing. Journal Of Remote Sensing, 2006, 10(3): 421-431.]

[19]
杨雪梅, 杨太保, 刘海猛, 等. 气候变暖背景下近30a北半球植被变化研究综述. 干旱区研究, 2016, 33(2): 379-391.归一化植被指数(NDVI)目前广泛应用于全球和区域尺度植被变化研究,成为揭示气候变化的重要指标。基于NDVI变化以及NDVI提取的植被物候变化2个方面(植被生长季开始时间SOG,植被生长季结束时间EOG),对近30 a气候变暖背景下北半球植被变化的有关研究结论进行回顾总结。结果显示:1近30 a北半球植被生长季NDVI整体呈增加趋势,森林植被NDVI增长速率大于其他植被类型;20世纪90年代NDVI增加趋势较80年代显著,从21世纪初开始,出现NDVI增长速率减缓现象;2近30 a北半球SOG整体呈提前趋势,近10 a SOG提前趋势减缓;欧亚地区SOG提前趋势可能较北美显著,非洲植被物候变化规律不清晰;北半球植被物候变化表现出明显的纬度地带性,55°~65°N纬度带SOG提前趋势与45°~55°N纬度带EOG推迟趋势相对显著;3除森林退化严重外,近30 a青藏高原植被整体上以增加为主,NDVI增长趋势北部显著,中部和东部微弱,南部呈下降趋势;高原东部和藏北SOG提前趋势显著,而中部、西部和西南部有推迟现象。

DOI

[Yang Xuemei, Yang Taibao, Liu Haimeng, et al.Vegetation variation in the north hemisphere under climate warming in the last 30 years. Arid Zone Research, 2016, 33(2): 379-391.]

[20]
李燕丽, 潘贤章, 王昌昆, 等. 2000-2011年广西植被净初级生产力时空分布特征及其驱动因素. 生态学报, 2014, 34(18): 5220-5228.受人类活动及自然环境影响，广西土壤酸化、水土流失及石漠化等问题比较严重，生态环境面临巨大压力。NPP能有效反映植物群落在自然环境中的生产能力，是评价生态服务功能的重要指标。利用2000-2011年MODIS归一化植被指数（NDVI）数据，基于光能利用率模型对广西植被净初级生产力（NPP）进行估算，分析其时空变化规律，探讨气象因子、植被类型、土壤类型、海拔高度及人类活动的影响。研究表明：近12年广西全区NPP总体呈增加趋势，在西南部地区上升较为明显，而在桂林、柳州等地区呈缓慢下降趋势。广西NPP与降水呈显著正相关关系，与温度相关性不显著；NPP值随海拔高度升高而增加；NPP时空变化特征随植被类型和土壤类型的不同而不同，其中栽培植被NPP不断上升，显示人类活动逐渐成为影响NPP变化的主要因素。

DOI

[Li Yanli, Pan Xianzhang, Wang Changkun, et al.Changes of vegetation net primary productivity and its driving factors from 2000 to 2011 in Guangxi, China. Acta Ecologica Sinica, 2014, 34(18): 5220-5228.]

[21]
张勇荣, 周忠发, 马士彬, 等. 基于NDVI的喀斯特地区植被对气候变化的响应研究: 以贵州省六盘水市为例. 水土保持通报, 2014, 34(4): 114-117.利用1999-2010年SPOT-VGT NDVI数据,采用基于像元的相关分析方法,分析了贵州省典型喀斯特区域植被对气候变化的响应.结果表明,1999-2010年研究区气候变化呈冷干趋势,植被NDVI呈恢复趋势;从区域尺度分析,研究区植被NDVI与气候要素间呈不显著相关关系;从像元尺度分析,植被NDVI与年均气温和降水量均具有较强的负相关性,且年均气温的影响力大于年降水量;由于植被NDVI与气候要素存在负相关,所以气候冷干的变化趋势有利于区域整体植被NDVI的恢复;植被NDVI与气候要素的相关性在空间上存在较强的地域性,进一步证明了植被NDVI对气候变化的响应受到地形的强烈影响.

[Zhang Yongrong, Zhou Zhongfa, Ma Shibin, et al.A study on response of vegetation to climate change base on NDVI in Karst region: A case study at Liupanshui city in Guizhou province. Bulletin of Soil and Water Conservation, 2014, 34(4): 114-117.]

[22]
Liao Chujie, Yue Yuemin, Wang Kelin, et al.Ecological restoration enhances ecosystem health in the karst regions of southwest China. Ecological Indicators, 2018, 90: 416-425.Within the past decades, the karst region in the Guangxi province in southwest China has been in the focus of large scale ecological restoration projects. In this study, we adapt the pressure-state-response (PSR) framework (which includes measures for human pressure, the current state of the ecosystem and the human response) and propose a remote sensing based ecosystem health (ESH) index (0–1; 25062m spatial resolution), evaluating the pressure and state of the fragile karst ecosystem. We further apply inventory data of recovery actions (restoration areas at county level resolution) as response to ongoing degradation to test the impact of ecological restoration on the ESH. Our analysis was conducted for the years 2000, 2010 and 2016, and the results showed that 73% of the study area experienced an increase in the ESH (from 2000 to 2016) which was related to the improvements in vegetation vigor, organization, resilience, ecosystem service provisioning which offset a deterioration in fragmentation and population density. From 2000 to 2016, areas of increase in ESH were slightly larger in karst than in non-karst (37.5% and 35.1%, respectively), but also larger areas of decrease in ESH were observed in karst as compared to non-karst (16% and 11%, respectively). The results further showed that the share of areas with a high ESH (greater than 0.7) had increased by 653% (from 67.16% to 70.21%) during the 1762years period. At county level, we found a clear relationship between increases in ESH and ecological restoration areas ( r 62=620.58 , p 62=620.004), with a high recovery rate (ratio between areas with increased ESH and restoration areas in a county) in karst than in non-karst. We conclude that restoration projects have caused a large scale transformation of farmland into forested areas (65550062km 2 ), which has caused a general improvement in ecosystem parameters related to ESH.

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[23]
Zhang Mingyang, Wang Kelin, Liu Huiyu, et al.Effect of ecological engineering projects on ecosystem services in a karst region: A case study of northwest Guangxi, China. Journal of Cleaner Production, 2018, 183: 831-842.]Ecological efficiencies of rocky desertification control measures at the regional scale remain unclear. It is urgent and challenging to determine the influences of ecological engineering on the variations of ecosystem services, and to evaluate the ecological benefit of rocky desertification control measures. In this study, variations of three kinds of ecosystem services (water regulation, soil conservation, and carbon sequestration) were analysed in a typical karst region of Northwest Guangxi China during the period from 2000 to 2010. The relative importance of the main factors that influence these three ecosystem services were analysed using radial basis function network, Kaiser eyer lkin (KMO), and principal component analysis. The results showed that over half of the study area has experienced an increase in water regulation (50.39%) and soil conservation (58.53%), and approximately 28.24% of the study region has undergone increased carbon sequestration. Environmental factors had a substantial impact on the ecosystem services, and the order of relative importance was as follows: geology > soil > vegetation > temperature > precipitation. Anthropogenic activities have played an important role in the changes to the ecosystem services. In addition to the significant conversion of other land types to woodland (approximately 46.80% of the total transfer area), the vegetation species, shape, and fraction, which are greatly influenced by human activities, contributed 79.05% to the variance. This resulted in a high KMO value of 0.912 (>0.9, represents very suitable), and the Bartlett test was significant (Sig. 0.00). These results showed that although natural environmental factors remained basic influences on the pattern of ecosystem services, anthropogenic activities of ecological engineering projects also had important and positive influences on the ecosystem services. This study also indicated that satellite images and new methods should be applied to deal with the relative lack of existing datasets.

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[24]
Wang Jing, Wang Kelin, Zhang Mingyang, et al.Impacts of climate change and human activities on vegetation cover in hilly southern China. Ecological Engineering, 2015, 81: 451-461.Vegetation cover is a commonly used indicator to evaluate terrestrial environmental conditions. Changes in the spatiotemporal patterns of vegetation alter the structures and functions of the landscape, thereby affecting ecological processes. Hilly southern China is an important ecological restoration area, in which the vegetation cover and land use has changed significantly. However, very few studies have considered vegetation changes due to multiple factors in this region. We investigated the spatiotemporal variations in vegetation cover using a Normal Difference Vegetation Index (NDVI) time-series data set obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) and climate data from 2000 to 2010. Our results indicate that the NDVI during the growing season had increased by 0.03% during the 11-year period. Patterns of change in vegetation cover differed among locations, with 58.7% of the study area displaying increased NDVI values, and in 7.3% of the study area, within an ecological restoration zone, the increase was significant. Effective ecological restoration programs, such as Grain for Green and hill closure for afforestation, have improved the environmental conditions. The spatiotemporal variations in vegetation cover were likely to be a synergistic impact of climate change (fluctuations in temperature and precipitation) and human activities. A residual analysis of the changes in the NDVI indicated that human activities had either improved or degraded vegetation cover in some parts of southern China. Specifically, the negative effects of extreme weather events in 2009 and 2010 offset the positive benefits of ecological reconstruction programs in the western part of the study area. This indicates that extreme weather events should be considered in the design and planning of future ecological reconstruction. Drought-resistant plant species might be considered for future ecological projects. However, an eco-risk assessment should be conducted when introducing drought-resistant plant species.

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[25]
封志明, 唐焰, 杨艳昭, 等. 中国地形起伏度及其与人口分布的相关性. 地理学报, 2007, 62(10): 1073-1082.基于人居环境自然评价的需要,运用GIS技术,采用窗口分析等方法,提取了基于栅格尺度(10km×10km)的中国地形起伏度,并从比例结构、空间分布和高度特征3个方面系统分析了中国地形起伏度的分布规律及其与人口分布的相关性。研究表明:中国的地形起伏度以低值为主,63%的区域低于1(相对高差≤500m);空间分布呈现西高东低、南高北低的格局;随着经度和纬度增高,地形起伏度呈逐渐下降趋势,28oN、35oN、42oN纬线和85oE、102oE、115oE经线上的地形起伏度符合中国三大阶梯的地貌特征;随着海拔高度增加,地形起伏度呈现逐渐升高趋势。实证分析表明:中国的地形起伏度与人口密度有较好的对数拟合关系,拟合度高达0.91;全国85%以上的人口居住在地形起伏度小于1的地区,在地形起伏度大于3的地区居住的人口总数只占全国0.57%。中国地形起伏度与人口分布的相关性区域差异显著,东北、华北、华中和华南等地相关性显著,内蒙古与青藏地区几乎不存在相关性。

DOI

[Feng Zhiming, Tang Yan, Yang Yanzhao, et al.The relief degree of land surface in China and its correlation with population distribution. Acta Geographica Sinica, 2007, 62(10): 1073-1082.]

[26]
韩海辉, 高婷, 易欢, 等. 基于变点分析法提取地势起伏度: 以青藏高原为例. 地理科学, 2012, 32(1): 101-104.Choosing scientific method to extract and express relief amplitude has become the critical factor to improve the effectiveness and practicality in relief research.Based on SRTM3-DEM,the relief amplitude with increasing grid window method in the Tibetan Plateau was extracted,and then the best window area by the mean change point method was calculated.The result shows that 1.17km could be the best window area,the relief amplitude can be divided into eight classes,and the most widely distributed class is low rolling mountain.The relief amplitude is generally more violent at the edge of the plateau.It is mainly due to the intensive tectonic movement and river headward erosion.While the terrain is relatively flat in hinterland of the plateau,the erosion and removal caused by glaciation and unfreezing may be the greater impact on the relief amplitude.

[Han Haihui, Gao Ting, Yi Huan, et al.Extraction of relief amplitude based on change point method: A case study on the Tibetan Plateau. Scientia Geographica Sinica, 2012, 32(1): 101-104.]

[27]
李史干, 周慧杰, 朱杰, 等. 湿热岩溶山区植被覆盖度与地形因子的相关性研究: 以广西红水河流域为例. 湖南农业科学, 2018, (1): 55-59.

[Li Shigan, Zhou Huijie, Zhu Jie, et al.Correlation between vegetation coverage and terrain factors in Damp Hot Karst Mountainous Areas of Hongshui River Basin. Hunan Agricultural Sciences, 2018, (1): 55-59.]

[28]
Yan Yuehong, He Zuxia, Hu Yuan, et al.The ecological response of fern diversity to different slopes in Gudoushan nature reserve, Guangdong. Biodiversity Science, 2011, 19(1): 41-47.

DOI

[29]
Chen J, Jönsson P, Tamura M, et al.A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky-Golay filter. Remote Sensing of Environment, 2004, 91(3-4): 332-344.Although the Normalized Difference Vegetation Index (NDVI) time-series data, derived from NOAA/AVHRR, SPOT/VEGETATION, TERRA or AQUA/MODIS, has been successfully used in research regarding global environmental change, residual noise in the NDVI time-series data, even after applying strict pre-processing, impedes further analysis and risks generating erroneous results. Based on the assumptions that NDVI time-series follow annual cycles of growth and decline of vegetation, and that clouds or poor atmospheric conditions usually depress NDVI values, we have developed in the present study a simple but robust method based on the Savitzky olay filter to smooth out noise in NDVI time-series, specifically that caused primarily by cloud contamination and atmospheric variability. Our method was developed to make data approach the upper NDVI envelope and to reflect the changes in NDVI patterns via an iteration process. From the results obtained by applying the newly developed method to a 10-day MVC SPOT VGT-S product, we provide optimized parameters for the new method and compare this technique with the BISE algorithm and Fourier-based fitting method. Our results indicate that the new method is more effective in obtaining high-quality NDVI time-series.

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[30]
Stow D, Daeschner S, Hope A, et al.Variability of the seasonally integrated normalized difference vegetation index across the north slope of Alaska in the 1990s. International Journal of Remote Sensing, 2003, 24(5): 1111-1117.The interannual variability and trend of above-ground photosynthetic activity of Arctic tundra vegetation in the 1990s is examined for the north slope region of Alaska, based on the seasonally integrated normalized difference vegetation index (SINDVI) derived from local area coverage (LAC) National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) data. Smaller SINDVI values occurred during the three years (1992-1994) following the volcanic eruption of Mt Pinatubo. Even after implementing corrections for this stratospheric aerosol effect and adjusting for changes in radiometric calibration coefficients, an apparent increasing trend of SINDVI in the 1990s is evident for the entire north slope. The most pronounced increase was observed for the foothills physiographical province.

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[31]
Tian Yichao, Bai Xiaoyong, Wang Shijie, et al.Spatial-temporal changes of vegetation cover in Guizhou province, southern China. Chinese Geographical Science, 2017, 27(1): 25-38.Guizhou Province is an important karst area in the world and a fragile ecological area in China. Ecological risk assessment is very necessary to be conducted in this region. This study investigates different characteristics of the spatial-temporal changes of vegetation cover in Guizhou Province of Southern China using the data set of SPOT VEGETATION (1999 2015) at spatial resolution of 1-km and temporal resolution of 10-day. The coefficient of variation, the Theil-Sen median trend analysis, and the Mann-Kendall test are used to investigate the spatial-temporal change of vegetation cover and its future trend. Results show that: 1) the spatial distribution pattern of vegetation cover in Guizhou Plateau is high in the east whereas low in the west. The average annual normalized difference vegetation index (NDVI) from west to east is higher than that from south to north. 2) Average annual NDVI improved obviously in the past 17 years. The growth rate of average annual NDVI is 0.028/10 yr, which is slower than that of vegetation in the country (0.048/10 yr) from 1998 to 2007. Average annual NDVI in karst area is lower than that in non-karst area. However, the growing rate of average annual NDVI in karst area (0.030/10 yr) is faster than that in non-karst area (0.023/10 yr), indicating that vegetation coverage increases more rapidly in karst area. 3) Vegetation coverage in the study area is stable overall, but fluctuates in the local scales. 4) Vegetation coverage presents a continuous increasing trend. The Hurst exponent of NDVI in different vegetation types has an obvious threshold in various elevations. 5) The proportion of vegetation cover with sustainable increase is higher than that of vegetation cover with sustainable decrease. The improvement in vegetation cover may expand to most parts of the study area.

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[32]
喻素芳, 佘光辉, 罗叶红, 等. 基于MODIS-NDVI数据广西植被覆盖变化特征分析. 湖北农业科学, 2015, 54(2): 321-325.利用月合成MODIS-NDVI时间序列数据、气象数据、DEM等数据,分析研究了2001-2010年广西省10年间植被覆盖变化的特征.结果表明,广西植被覆盖率较高且总体呈上升趋势,从区域角度分析,桂南地区增加趋势最显著,其次是桂中地区;从海拔梯度角度分析,海拔200 m以下的区域植被覆盖增加趋势最显著,但此区域的植被覆盖率较低,NDVI最高分布在海拔400～800 m的区域.植被覆盖变化受气温、降水及人类活动影响较大,植被覆盖梯度变化除受这些因素影响外,也与植被垂直地理分布特征相关.

DOI

[Yu Sufang, She Guanghui, Luo Yehong, et al.Analysis of characteristics of vegetation cover change in Guangxi province based on MODIS-NDVI. Hubei Agricultural Sciences, 2015, 54(2): 321-325.]

[33]
韦振锋, 任志远, 张翀. 近12年广西植被覆盖与降水和气温的时空响应特征. 水土保持研究, 2013, 20(5): 33-38.植被是生态系统中比较活跃的成员,分析其与降水和气温之间年际动态变化特征,已经成为当前国内外研究生态环境的发展趋势。基于植被归一化(NDVI)数据和气象数据,以一元线性回归方法分析1999—2010年间植被变化趋势,同时通过相关分析和偏相关分析方法初步探讨12年NDVI与降水和气温之间的相关程度。结果表明:(1)广西植被覆盖变化趋势总体是良好的,桂南和桂西北植被覆盖变化趋势表现较显著,其他地区相对变化不显著。(2)广西主要植被类型中,显著增加的植被主要有稀疏灌丛、密集灌丛、常绿阔叶林和常绿针叶林,其他植被类型变化不显著。(3)研究区域内,降水对植被的响应相对气温对植被的响应较弱,相关强度呈由桂西南向桂东北递减的规律。(4)气温对整个研究区域的植被覆盖响应呈正相关,中部相关较强,而四周相对较弱。综上,植被覆盖与降水和气温的时空响应特征,与研究区域的气候变化和地形概况相一致。

[Wei Zhenfeng, Ren Zhiyuan, Zhang Chong.Research on vegetation response to temperature and precipitation in Guangxi in recent 12 years. Research of Soil and Water Conservation, 2013, 20(5): 33-38.]

[34]
Kawabata A, Ichii K, Yamaguchi Y.Global monitoring of interannual changes in vegetation activities using NDVI and its relationships to temperature and precipitation. International Journal of Remote Sensing, 2001, 22(7): 1377-1382.Interannual trends in annual and seasonal vegetation activities from 1982 to 1990 on a global scale were analysed using the Pathfinder AVHRR Land NDVI data set corrected by utilising desert and high NDVI areas. Climate effects on interannual variations in NDVI were also investigated using temperature and precipitation data compiled from stational observations. In the northern middlehigh latitudes, vegetation activities increased over broad regions because of a gradual rise in temperature. NDVI increases were also detected in the tropical regions, such as western Africa and south-eastern Asia. Plant photosynthetic activities on the other hand, decreased remarkably in some arid and semi-arid areas in the Southern Hemisphere, because annual rainfall decreased during this period.

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[35]
Zhou L, Tucker C J, Kaufmann R K, et al.Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999. Journal of Geophysical Research Atmospheres, 2001, 106(D17): 20069-20084.

DOI

[36]
Piao Shilong, Fang Jingyun, Zhou Liming, et al.Interannual variations of monthly and seasonal normalized difference vegetation index (NDVI) in China from 1982 to 1999. Journal of Geophysical Research Atmospheres, 2003, 108(D14): 4401.1] In this paper, we analyzed interannual variations of normalized difference vegetation index (NDVI) and their relationships with climatic variables (temperature and precipitation) and human activity in China between 1982 and 1999. Monthly and seasonal NDVI increased significantly at both the country and biome scales over the study period. NDVI shows the largest increase (14.4% during the 18 years and a trend of 0.0018 yr0908081) over 85.9% of the total study area in spring and the smallest increase (5.2% with a trend of 0.0012 yr0908081) over 72.2% of the area in summer. The NDVI trends show a marked heterogeneity corresponding to regional and seasonal variations in climates. There is about a 3-month lag for the period between the maximum trend in temperature (February) and that in NDVI (April or May) at the country and biome scales. Human activity (urbanization and agricultural practices) also played an important role in influencing the NDVI trends over some regions. Rapid urbanization resulted in a sharp decrease in NDVI in the Yangtze River and Pearl River deltas, while irrigation and fertilization may have contributed to the increased NDVI in the North China plain.

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[37]
蒙吉军, 王钧. 20世纪80年代以来西南喀斯特地区植被变化对气候变化的响应. 地理研究, 2007, 26(5):857-865.

[Meng Jijun, Wang Jun.The response of vegetation dynamics to climate change in the southwestern karst region of China since the early 1980s. Geographical Research, 2007, 26(5): 857-865.]

[38]
黄晓云, 林德根, 王静爱, 等. 气候变化背景下中国南方喀斯特地区NPP时空变化. 林业科学, 2013, 49(5):10-16.基于中国南方8省区喀斯特地区卫星遥感和地面气象观测资料,分析气候变化背景下中国南方喀斯特地区2000—2011年间的NPP时空变化规律,及不同土地利用类型NPP变化。结果表明: 在气候变化背景下, 2000—2005年间,研究区NPP值总体呈上升趋势,在2005年发生转折, 2006—2011年间,NPP值总体呈下降趋势; 喀斯特地区NPP的变化幅度明显大于非喀斯特区; 农田、低密度灌木林、混合用地等土地利用类型对石漠化反应敏感。

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[Huang Xiaoyun, Lin Degen, Wang Jingai, et al.Temporal and spatial NPP variation in the karst region in south China under the background of climate change. Scientia Silvae Sinicae, 2013, 49(5): 10-16.]

[39]
李瑞玲, 王世杰, 熊康宁, 等. 贵州省岩溶地区坡度与土地石漠化空间相关分析. 水土保持通报, 2006, 26(4): 82-86.喀斯特石漠化从本质上来讲是喀斯特地区的成土速率远小于水土流失的速率而造成的土地生产力的 退化过程。坡度起伏决定着地表现代侵蚀作用的强弱，影响着水土流失的强度；坡度越大，地表物质的不稳定性就越强，土壤越容易遭受侵蚀而变薄。在前期工作 中，构筑了贵州省岩溶地区1：500000坡度分级图和石漠化分布图，对岩溶地区坡度图和石漠化图进行空间叠加分析，研究坡度与石漠化形成的相关关系。贵 州省岩溶地区坡度主要集中于10°～25°之间，不同程度石漠化分布最集中的地区是〉25°的坡地区；在坡度〉18°的地区，石漠化的发生率基本随着坡度 的增大而增大，强度石漠化的表现尤为明显；〈18°的坡地区石漠化程度主要以轻度和中度为主。

DOI

[Li Ruilin, Wang Shijie, Xiong Kangning, et al.Correlation between rocky desertification and slope degree in karst area of Guizhou. Bulletin of Soil and Water Conservation, 2006, 26(4): 82-86.]

[40]
张红旗, 尚二萍, 于竹筱. 基于地形分异指数的黔桂喀斯特山地土地利用垂直分布特征. 资源科学, 2017, 39(10): 1964-1974.

[Zhang Hongqi, Shang Erping, Yu Zhuxiao.Vertical distribution characteristics of land use in Guizhou and Guangxi karst mountainous region based on terrain differentiation indicators. Resources Science, 2017, 39(10): 1964-1974.]

[41]
张跃红, 安裕伦, 马良瑞, 等. 1960-2010年贵州省喀斯特山区陡坡土地利用变化. 地理科学进展, 2012, 31(7): 878-884.基于GIS 与RS技术, 以贵州省喀斯特山区坡度大于25&deg;的区域为研究对象, 利用1960 年1:50000 地形图、1990 年Landsat TM遥感影像以及2010 年的环境减灾卫星(HJ-1A/1B)影像, 解译获取1960、1990、2010 年3 个时间点的土地利用数据, 并结合贵州省水文地质图、坡度图进行陡坡土地利用变化分析。结果表明:①1960-1990 年的30 年间, 有林地、灌木林、水体呈减少趋势, 其中灌木林减少的最多, 其次是有林地;而草地、建设用地、裸岩和耕地呈持续增长趋势, 其中草地增加的最多, 其次是耕地。②1990-2010 年的20 年间, 灌木林、裸岩、耕地呈减少趋势, 其中耕地减少的最多;而有林地、疏林地、草地、水体呈增长趋势, 其中疏林地增加的最多。③随坡度增加覆盖比例呈降低趋势的土地利用类型为有林地、疏林地、水体、建设用地和耕地;随坡度增加覆盖比例呈增加趋势的土地利用为灌木林、草地和裸岩。

DOI

[Zhang Yuehong, An Yulun, Ma Liangrui, et al.Land use change of slope land in karst mountainous regions, Guizhou province during 1960-2010. Progress in Geography, 2012, 31(7): 878-884.]

[42]
宋同清, 彭晚霞, 曾馥平, 等. 木论喀斯特峰丛洼地森林群落空间格局及环境解释. 植物生态学报, 2010, 34(3): 298-308.lt;FONT face=Verdana>基于广西壮族自治区木论国家级自然保护区典型峰丛洼地景观尺度内不同微生境条件和植物群落类型50个样地(20 m × 20 m)的系统取样调查, 用二元物种指示方法(TWINSPAN)对样地内胸径(<EM>DBH</EM>) ≥ 1 cm的木本植物进行分类, 选择10个土壤环境因子和5个空间因子, 利用除趋势典范对应分析(DCCA)研究了森林群落分布的土壤环境与空间格局, 并给予定量化的合理解释。结果如下: 1) TWINSPAN将森林群落划分为11组, 在三级水平上分为4类生态群落类型。2) DCCA第一排序轴集中了排序的大部分信息, 突出反映了各森林群落所在的坡向和土壤主要养分梯度, 沿第一轴从左到右, 坡向由阴转阳,岩石裸露率越来越高, 土壤主要养分逐渐降低, 森林群落分别出现了由原生性和耐阴性强逐步向阳性先锋树种为主的次生林和人工林变化的格局。3)因子分离分析结果表明, 土壤环境因子对森林群落分布格局的解释能力为39.16%, 其中21.02%单纯由土壤环境因子所引起, 空间因子的解释能力为31.34%, 其中13.16%独立于土壤环境的变化, 18.15%是土壤环境和空间因子相互耦合作用的结果, 不可解释部分达47.66%, 表明喀斯特峰丛洼地森林群落的物种共存受生态位分化理论和中性理论双重控制。</FONT>

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[Song Tongqing, Peng Wanxia, Zeng Fuping, et al.Spatial pattern of forest communities and environmental interpretation in Mulun National Nature Reserve, karst cluster-peak depression region. Chinese Journal of Plant Ecology, 2010, 34(3): 298-308.]

[43]
Sun Hongyu, Wang Changyao, Niu Zheng.Analysis of the vegetation cover change and the relationship between NDVI and environmental factors by using NOAA time series data. Journal of Remote Sensing, 1998, 266(2): 153-161.Key Words】：

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[44]
Zhao Lin, Dai Aiguo, Dong Bo.Changes in global vegetation activity and its driving factors during 1982-2013. Agricultural & Forest Meteorology, 2018, 249: 198-209.Precipitation over the contiguous United States exhibits large multi-decadal oscillations since the early twentieth century, and they often lead to dry (e.g., 1946–1976 and 1999-present) and wet (e.g., 1977–1998) periods and apparent precipitation trends (e.g., from the 1950s to 1990s) over most of the western and central US. The exact cause of these inter-decadal variations is not fully... [Show full abstract]

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[45]
Chen Baozhang, Xu Guang, Coops N C, et al.Changes in vegetation photosynthetic activity trends across the Asia-Pacific region over the last three decades. Remote Sensing of Environment, 2014, 144: 28-41.61The mechanism for vegetation dynamics in the Asia–Pacific (AP) region was detected.61The AP region increased NDVI at a rate of 0.13%yr611 over the last three decades.61The turning points were 2008 and 1987 for the AA and NA subareas, respectively.61The vegetation greening rate was an order larger after 2008 than before in AA.61The vegetation greened very quickly before 1987 and then plateaued after 1987.

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[46]
Xu Guang, Zhang Huifang, Chen Baozhang, et al.Changes in vegetation growth dynamics and relations with climate over China's landmass from 1982 to 2011. Remote Sensing, 2014, 6(4): 3263-3283.Understanding how the dynamics of vegetation growth respond to climate change at different temporal and spatial scales is critical to projecting future ecosystem dynamics and the adaptation of ecosystems to global change. In this study, we investigated vegetated growth dynamics (annual productivity, seasonality and the minimum amount of vegetated cover) in China and their relations with climatic factors during 1982 2011, using the updated Global Inventory Modeling and Mapping Studies (GIMMS) third generation global satellite Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) dataset and climate data acquired from the National Centers for Environmental Prediction (NCEP). Major findings are as follows: (1) annual mean NDVI over China significantly increased by about 0.0006 per year from 1982 to 2011; (2) of the vegetated area in China, over 33% experienced a significant positive trend in vegetation growth, mostly located in central and southern China; about 21% experienced a significant positive trend in growth seasonality, most of which occurred in northern China (gt;35 N); (3) changes in vegetation growth dynamics were significantly correlated with air temperature and precipitation (p lt; 0.001) at a region scale; (4) at the country scale, changes in NDVI was significantly and positively correlated with annual air temperature (r = 0.52, p lt; 0.01) and not associated with annual precipitation (p gt; 0.1); (5) of the vegetated area, about 24% showed significant correlations between annual mean NDVI and air temperature (93% positive and remainder negative), and 12% showed significant correlations of annual mean NDVI with annual precipitation (65% positive and 35% negative). The spatiotemporal variations in vegetation growth dynamics were controlled primarily by temperature and secondly by precipitation. Vegetation growth was also affected by human activities; and (6) monthly NDVI was significantly correlated with the preceding month temperature and precipitation in western, central and northern China. The effects of a climate lag of more than two months in southern China may be caused mainly by the abundance of precipitation. These findings suggest that continuing efforts to monitor vegetation changes (in situ and satellite observations) over time and at broad scales are greatly needed, and are critical for the management of ecosystems and adapting to global climatic changes. It is likewise difficult to predict well future vegetation growth without linking these observations to mechanistic terrestrial ecosystem processes models that integrate all the satellite and in situ observations.

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[47]
Peng Shushi, Chen Anping, Xu Liang, et al.Recent change of vegetation growth trend in China. Environmental Research Letters, 2011, 6(4): 044027.Using satellite-derived normalized difference vegetation index (NDVI) data, several previous studies have indicated that vegetation growth significantly increased in most areas of China during the period 1982-99. In this letter, we extended the study period to 2010. We found that at the national scale the growing season (April-October) NDVI significantly increased by 0.0007 yrfrom 1982 to 2010, but the increasing trend in NDVI over the last decade decreased in comparison to that of the 1982-99 period. The trends in NDVI show significant seasonal and spatial variances. The increasing trend in April and May (AM) NDVI (0.0013 yr) is larger than those in June, July and August (JJA) (0.0003 yr) and September and October (SO) (0.0008 yr). This relatively small increasing trend of JJA NDVI during 1982-2010 compared with that during 1982-99 (0.0012 yr) (Piao et al 2003 J. Geophys. Res. tmos. 108 4401) implies a change in the JJA vegetation growth trend, which significantly turned from increasing (0.0039 yr) to slightly decreasing ( - 0.0002 yr) in 1988. Regarding the spatial pattern of changes in NDVI, the growing season NDVI increased (over 0.0020 yr) from 1982 to 2010 in southern China, while its change was close to zero in northern China, as a result of a significant changing trend reversal that occurred in the 1990s and early 2000s. In northern China, the growing season NDVI significantly increased before the 1990s as a result of warming and enhanced precipitation, but decreased after the 1990s due to drought stress strengthened by warming and reduced precipitation. Our results also show that the responses of vegetation growth to climate change vary across different seasons and ecosystems.

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[48]
中国石漠化状况公报. , 2012-06-18.

[Bulletin of China's Rocky Desertification (State Forestry Administration of China). , 2012-06-18.]

[49]
Tong Xiaowei, Martin Brandt, Yue Yuemin, et al.Increased vegetation growth and carbon stock in China karst via ecological engineering. Nature Sustainability, 2018, 1: 44-50.article{bb436f78-8d6d-4909-bc4f-d1d560af7d3e, author = {Tong, Xiaowei and Brandt, Martin and Yue, Yuemin and Horion, Stephanie and Wang, Kelin and Keersmaecker, Wanda De and Tian, Feng and Schurgers, Guy and Xiao, Xiangming and Luo, Yiqi and Chen, Chi and Myneni, Ranga and Shi, Zheng and Chen, Hongsong and Fensholt, Rasmus}, language = {eng}, month = {01}, number = {1}, pages = {44--50}, series = {Nature Sustainability}, title = {Increased vegetation growth and carbon stock in China karst via ecological engineering}, url = {http://dx.doi.org/}, volume = {1}, year = {2018}, }

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[50]
Cai Hongyan, Yang Xiaohuan, Wang Kejing, et al.Is forest restoration in the Southwest China karst promoted mainly by climate change or human-induced factors?. Remote Sensing, 2014, 6(10): 9895-9910.The Southwest China Karst, the largest continuous karst zone in the world, has suffered serious rock desertification due to the large population pressure in the area. Recent trend analyses have indicated general greening trends in this region. The region has experienced mild climate change, and yet significant land use changes, such as afforestation and reforestation. In addition, out-migration has occurred. Whether climate change or human-induced factors, i.e., ecological afforestation projects and out-migration have primarily promoted forest restoration in this region was investigated in this study, using Guizhou Province as the study area. Based on Moderate-Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data, we found general greening trends of the forest from 2000 to 2010. About 89% of the forests have experienced an increase in the annual NDVI, and among which, about 41% is statistically significant. For the summer season, more than 65% of the forests have increases in summer NDVI, and about 16% of the increases are significant. The strongest greening trends mainly occurred in the karst areas. Meanwhile, annual average and summer average temperature in this region have increased and the precipitation in most of the region has decreased, although most of these changes were not statistically significant (p gt; 0.1). A site-based regression analysis using 19 climate stations with minimum land use changes showed that a warming climate coupled with a decrease in precipitation explained some of the changes in the forest NDVI, but the results were not conclusive. The major changes were attributed to human-induced factors, especially in the karst areas. The implications of an ecological afforestation project and out-migration for forest restoration were also discussed, and the need for further investigations at the household level to better understand the out-migration nvironment relationship was identified.

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[51]
李昊, 蔡运龙, 陈睿山, 等. 基于植被遥感的西南喀斯特退耕还林工程效果评价: 以贵州省毕节地区为例. 生态学报, 2011, 31(12): 3255-3264.中国西南喀斯特地区生态环境脆弱,人口压力和不合理的土地利用方式使得土地退化问题严峻。2000年以来,国家开始在该地区推行退耕还林等一系列生态工程。需要评估这些工程的效果,以期为进一步的生态建设工程决策提供科学依据。以贵州省毕节地区为例,利用SPOT-VGT <em>NDVI</em>遥感数据,以大规模开展退耕还林工程前的1998-2001年为基准,建立<em>NDVI</em>-气候响应模型,在此基础上结合残差法来分析2002-2008年以退耕还林工程为主的人为因素在当地生态恢复中的作用。结果表明,近年来开展的生态工程使得整个毕节地区植被条件得到了明显的改善,但在东部大方、黔西一些区域土地退化的趋势仍未扭转,需要今后进一步的政策引导和开展后续生态工程。

[Li Hao, Cai Yunlong, Chen Ruishan, et al.Effect assessment of the project of grain for green in the karst region in southwestern China: A case study of Bijie prefecture. Acta Ecologica Sinica, 2011, 31(12): 3255-3264.]

[52]
Liu Huiyu, Zhang Mingyang, Lin Zhenshan, et al. Spatial heterogeneity of the relationship between vegetation dynamics and climate change and their driving forces at multiple time scales in Southwest China. Agricultural & Forest Meteorology, 2018, 256/257: 10-21.Under global climate change, relationship between vegetation dynamics and climate change is vital for vegetation conservation and restoration in fragile ecological system. However, the relationships at multiple time scales are unclear. Based on the Ensemble empirical mode decomposition method (EEMD), we revealed the spatial heterogeneity of vegetation dynamics and its relationship with climate change at multiple time scales in Southwest China during 1982 2015. Vegetation dynamics can be divided into 3-, 6-, 14-, and 32-year time scale oscillations with an increasing trend. Hereinto, the 3-year time scale and the increasing trend are dominant. In Guangxi and north of Guizhou provinces, vegetation dynamics was dominated by the long-term trend, whereas in the other areas it was dominated by the 3-year time scale. With increasing time scale, the impact of climate change became more pronounced. The relationship between vegetation dynamics and temperature in growing season was determined by elevation and vegetation type at the 3- and 6-year time scales, but only by vegetation type over the long-term trend. The relationship between vegetation dynamics and precipitation was driven by karst landform and vegetation type at the 3-year time scale, by precipitation amount at the 6-year time scale, and by karst landform and elevation over the long-term trend. Based on multivariate regression analysis with multiple time scale analysis, climate change had a good and significant interpretation on vegetation dynamics in 54.1% of the study area. Specifically, in Guangxi and north of Guizhou provinces, the impact of climate change on vegetation dynamics was greater than that of human activities. Our findings showed that multiple time scale analysis might facilitate a better understanding of the mechanisms of vegetation dynamics, and provide scientific knowledge on vegetation restoration and conservation in fragile ecosystems.

DOI

[53]
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[Wang Ling.Impacts of orientations of slopes and elevation on rainfall in mountainous regions. Scientia Geographica Sinica, 1996, 16(2): 150-158.]

[55]
许月卿, 罗鼎, 冯艳, 等. 西南喀斯特山区土地利用/覆被变化研究: 以贵州省猫跳河流域为例. 资源科学, 2010, 32(9): 1752-1760.我国西南喀斯特山区山高坡陡，地形破碎，生态环境非常脆弱，是土地利用变化的敏感区域，也是全球环境变化响应比较突出的区域。本文根据贵州省猫跳河流域1973年MSS影像数据、1990年、2002年和2007年的Landsat -TM影像数据，利用遥感、GIS技术和数理统计方法，系统地分析了该流域土地利用/覆被变化的时空格局和特征，为喀斯特其它地区土地利用变化的研究和区域土地可持续利用政策的制定提供了参考和依据。结果表明：近30年来，流域内土地利用/覆被发生了剧烈变化。1973年-1990年, 由于陡坡开荒以及城镇化发展，流域内旱地、裸岩地和城镇建设用地增加，水田、灌木林、其它林地、灌草地均在减少;1990年以后，由于生态建设相关政策和项目的实施，流域内旱地和裸岩地大幅度减少，林地大幅度增加，城镇用地、农村居民点和交通工矿用地呈持续增加趋势;1973年-2007年，各地类土地利用类型转化与土地利用强度存在较大差异，主要表现为灌木林、灌草地、有林地、其它林地、旱地和裸岩地之间的转化，土地利用强度表现为先增大后减小;流域内绝大多数地类分部的平均海拔高程和坡度呈增加趋势，说明流域内人类活动对土地的干扰空间在扩大，趋向于高海拔和陡坡地区。

[Xu Yueqing, Luo Ding, Feng Yan, et al.A study on land use and land cover change in karst mountainous areas in southwestern China: A case study of the Maotiao River Watershed, Guizhou province. Resources Science, 2010, 32(9): 1752-1760.]

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