共查询到20条相似文献，搜索用时 312 毫秒
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利用NASA提供的16天合成MODIS数据,以归一化植被指数(NDVI)作为植被覆盖特征指标,研究了2001~2008年那曲县NDVI变化特征,分析了温度、降水等气象因子与NDVI关系。结果显示:近年来那曲县最大NDVI、年均NDVI呈减小趋势;NDVI月变化与温度、降水显著正相关;年平均NDVI、植被生长季平均NDVI与气象因子相关性不明显;畜牧总量与植被生长季NDVI显著负相关。 相似文献
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内蒙古植被NDVI变化特征分析 总被引：2，自引：0，他引：2
对植被状况和植被覆盖的研究可以反映植被受环境条件影响产生的时空变化。文章根据GIMMS-NDVI数据集1982—2006年影像数据,分析内蒙古农田、森林、草原三种植被类型NDVI年内、年际的变化趋势以及植被覆盖变化特征的空间差异。各植被类型变化曲线都呈现4—7月NDVI激增,8—10月NDVI猛降,冬季农田、草原植被覆盖接近裸土的特点。农田夏季NDVI平均值的历年线性变化趋势通过显著性检验,森林夏季NDVI平均值呈现下降的趋势,草原夏季NDVI平均值呈现上升的趋势,但都不显著。 相似文献
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基于1982-2003年GIMMS NDVI遥感资料、气候资料和社会经济统计资料,利用主成分分析、逐步回归等方法,对黄淮海地区植被覆盖变化的驱动力和驱动机制进行了研究,从气候、社会经济两方面分析了区内6种植被类型区植被覆盖变化的驱动机制。结果发现,不同植被类型区,其驱动机制差别很大,但总体来说,区内各类植被类型区植被覆盖变化大都受到气候和人类活动的共同驱动,主要驱动力为气候因素,人类活动在局部区域能够产生较大作用,而大范围区域植被NDVI(归一化植被指数)的变化或改变,主要受气候变化的影响。在此基础上,分别建立了6种植被类型区年均NDVI变化驱动力模型。 相似文献
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黄淮海地区植被覆盖变化驱动力与驱动机制研究 总被引：2，自引：1，他引：2
基于1982-2003年GIMMS NDVI遥感资料、气候资料和社会经济统计资料,利用主成分分析、逐步回归等方法,对黄淮海地区植被覆盖变化的驱动力和驱动机制进行了研究,从气候、社会经济两方面分析了区内6种植被类型区植被覆盖变化的驱动机制.结果发现,不同植被类型区,其驱动机制差别很大,但总体来说,区内各类植被类型区植被覆盖变化大都受到气候和人类活动的共同驱动,主要驱动力为气候因素.人类活动在局部区域能够产生较大作用,而大范围区域植被NDVI(归一化植被指数)的变化或改变,主要受气候变化的影响.在此基础上,分别建立了6种植被类型区年均NDVI变化驱动力模型. 相似文献
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基于MODIS的广东省植被指数序列构建与应用 总被引：2，自引：0，他引：2
植被指数是衡量植被长势的重要指标,植被指数序列有助于准确地认知植被覆盖、土地利用和土壤水分的时空变化规律,以及进行干旱和植被生长监测.利用2004-2006年的MODIS数据,选择RVI、NDVI和EVI三种植被指数,采用最大值合成法进行广东省植被指数序列构建.按照不同植被覆盖对三种植被指数的年际变化规律进行分析,并通过NDVI进行植被覆盖度计算以及植被覆盖等级分类来分析植被的空间分布.结果表明,建立的植被指数序列能真实地反映植被生长规律,植被覆盖度和广东地区的植被实际分布状况一致.说明建立植被指数序列是动态监测广东省植被长势的及植被环境的变化的有效方法. 相似文献
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青藏高原不同时间尺度植被变化特征及其与气候因子的关系分析 总被引：1，自引：0，他引：1
利用1982-2006年GIMMS NDVI数据,以多种统计方法为基础,探讨了青藏高原(下称高原)不同时间尺度(年际、季节及月)植被变化的时空特征及其与气候因子的关系。结果表明:高原整体年平均NDVI变化呈波动上升趋势,其中夏季趋势最大,达0.004(10a)-1。不同覆盖度像元变化对总体植被变化的贡献不同,低植被覆盖像元变化对各季节总体植被变化贡献均较大,其中冬季最大;中等植被覆盖像元变化的贡献主要在秋季;高植被覆盖像元的贡献则夏季最明显。青藏高原植被变化存在显著的空间差异,其中夏季呈增加和减少趋势的面积均最大,分别达30.51%、10.52%,增加的区域主要位于高原东部,减少的区域主要在高原中部的藏北高原。进一步分析高原植被和气候因子的相关性表明,中等植被覆盖区植被与气候因子的相关性最高,其次是高植被覆盖区,低植被覆盖区的相关性则最低。在年际和季节尺度上,植被生长主要与温度和降水的累积效应有关,其中在植被生长较好的季节和区域更明显。而在月尺度上,中低植被覆盖区植被生长受短期降水事件影响较大,高植被覆盖区则仍是温度的累积效应占主导。 相似文献
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基于中等分辨率成像光谱仪(MODIS)8 d 500 m分辨率地表反射率数据生成归一化植被指数(NDVI)时间序列,利用线性回归、转折点检测和Mann-Kendall趋势分析方法,分析2000—2013年新疆地区植被覆盖时空变化格局,并结合Landsat数据分析典型区域植被变化。研究结果表明：近14 a来,新疆地区植被覆盖整体呈波动型上升的趋势,植被改善区面积占全区的34.02%,恶劣区的占3.20%,其中2000—2003年植被明显增长、2003—2009年的波动下降及2009—2013年的逐渐回升,植被增长显著的区域主要分布在准噶尔盆地南部和塔里木盆地北部绿洲;大多数植被类型NDVI呈增长趋势,其中增长率最高的是作物、开放灌丛和混交林,6种主要植被类型常绿针叶林、混交林、开放灌丛、多树草原、草原、作物呈现出相似的NDVI变化趋势;在植被覆盖变化显著的4个典型区,NDVI变化受土地覆盖类型变化的影响,荒漠、草地被开垦成农田导致NDVI增加,城市建成区扩张导致NDVI降低。 相似文献
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西北地区MODIS-NDVI指数饱和问题分析 总被引：6，自引：0，他引：6
为了了解西北地区MODIS-NDVI和MODIS-EVI两种植被指数的特点,本文利用美国NASA LP DAAC(Land Process Distributed Active Archive Center)2004年1~12月的250 m分辨率16天植被指数合成的MOD13 Q1数据集,对西北地区不同类型植被NDVI和EVI的特征进行分析,并对西北地区MODIS-NDVI饱和问题进行了初步研究。结果表明:NDVI和EVI对干旱—半干旱气候区植被覆盖度不高的植被类型描述能力相似,月际变化趋势一致。西北地区各种植被类型NDVI比EVI高,NDVI与EVI的差异总体上呈现从半荒漠、草原、农区到林区,随NDVI值的增加而增大的规律。对植被度覆盖度高的阔叶林和针叶林,在植被生长旺盛期,NDVI总在0.8附近波动,NDVI随植被的生长增加的很小,一直维持在一个高且平的范围内,不再能看出植被生长变化的现象,即饱和现象严重;而EVI表现良好,随着植被的生长而增加,能明显地反映出植被生长的季节变化。西北高寒草甸和陕西关中农业区NDVI也出现有不同程度的饱和,饱和时间因植被的不同从1~2月不等。0.8可作为NDVI饱和的阈值。NDVI饱和问题对卫星监测植被的研究和应用会产生误差,EVI能较好地解决NDVI的饱和问题。 相似文献
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利用1982-2002年Pathfinder NDVI遥感数据, 采用REOF和倾向度趋势分析方法, 研究了5～6月青藏高原地表植被变化区域特征及与全球变暖的关系。21年来高原区域春末夏初植被变化存在明显的空间差异, 且存在一个位于高原南北呈带状分布的植被显著变化区域。该区域内植被对全球气温变暖响应显著, 与前期5月北半球平均气温相关系数达到0.7675, 通过0.001显著性水平检验; 植被NDVI随气温升高呈现出显著一致的增加趋势, 增长速率超过10%/10 a, 是全球变暖响应的显著区和敏感区。进一步的分析表明, 对植被全球变暖响应显著的区域基本上处于高山山脉或半荒漠NDVI值低于0.12覆盖度较低的区域。不同植被类型对变暖响应的对比表明, 草地对全球变暖响应明显高于林地, 其植被NDVI 21年约增加10%。 相似文献
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基于遥感和GIS的中国植被指数变化的驱动因子分析及模型研究 总被引：39，自引：3，他引：36
在样带和典型区研究的基础上,采用相关分析和偏相关分析方法,对影响植被指数变化的因子（水、热和地表植被覆盖类型）进行了分析。结果表明：中国植被指数的时空变化极其复杂,虽受水、热和地表植被覆盖类型三个主导因子的影响和控制,但因时和因地而异,三者对植被指数影响和控制的主导地位也因时因地而不同;基于空间上的概念模型Indv=F(x,y,z)只能定性地描述以上三个主导因子时空变化同植被指数的相互关系。 相似文献
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The Influence of Vegetation Cover on Summer Precipitation in China： a Statistical Analysis of NDVI and Climate Data 总被引：18，自引：0，他引：18
This study provides new evidence for the feedback effects of vegetation cover on summer precipitation in different regions of China by calculating immediate (same season), and one-and two-season lagged correlations between the normalized difference vegetation index (NDVI) and summer precipitation. The results show that the correlation coefficients between NDVI in spring and the previous winter and precipitation in summer are positive in most regions of China, and they show significant difference between regions. The stronger one-and two-season lagged correlations occur in the eastern arid/semi-arid region, Central China,and Southwest China out of the eight climatic regions of China, and this implies that vegetation cover change has more sensitive feedback effects on summer precipitation in the three regions. The three regions are defined as sensitive regions. Spatial analyses of correlations between spring NDVI averaged over each sensitive region and summer precipitation of 160 stations suggest that the vegetation cover strongly affects summer precipitation not only over the sensitive region itself but also over other regions, especially the downstream region. 相似文献
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基于全球土地利用类型和覆盖度,利用生长季多年平均（1982～2015年）归一化植被指数（Normalized Difference Vegetation Index,NDVI）和气候平均态（气温、降水量）数据,讨论了全球植被格局与气候因子之间的关系,建立了两者之间的多元回归模型,并分析了植被对气温和降水气候态敏感性的特征。植被与气候因子在气候梯度上存在明显的对应关系,回归模型可较好拟合气候态NDVI的全球分布格局,拟合与观测NDVI的相关系数达0.90。其中,常绿阔叶林、混交林、常绿针叶林、落叶阔叶林、农田和木本稀树草原空间分布的拟合能力较好（r>0.8）。不同土地覆盖类型的NDVI对气温、降水气候态的空间敏感性特征不同。整体而言,植被对气温和降水的敏感性呈现反相关关系（r=-0.6）。不同土地覆盖类型对气温表现出正/负敏感性,寒带灌木对气温的敏感性最强,而农作物、草原、裸地对气温负敏感性较大;植被对降水的敏感性均表现出正敏感性,其中落叶针叶林、草原和稀树草原对降水的空间敏感性较强。 相似文献
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Fluctuation of farming-pastoral ecotone in association with changing East Asia monsoon climate 总被引：2，自引：0，他引：2
As a monsoon climate dominated region, East Asia has a high rate of climate variation. Previous studies demonstrated that the East Asian monsoon had weakened since the end of 1970’s; however, contrary to the climatic trend, a common scenario of advancing farming-pastoral ecotone (FPE) has been proposed. The objective of this study is to analyze land surface changes in association with monsoon climate variability over past 25 years in East Asia. A combination of intensive ground survey of vegetation and land use, meteorological data, and remote sensing are used to quantify the relationship between vegetation and climate and to analyze the FPE fluctuations associated with changing climate. Field precipitation data from 1981 to 2005, are used to represent climate variations and to delineate the FPE boundary. NDVI data are used to evaluate greenness-precipitation linkages by vegetation type and to create land cover maps depicting spatial pattern fluctuations of the FPE. This study demonstrates that: (1) There was no persistent northwest shifting trend of either the FPE boundary or vegetation cover during last 25 years. (2) Time integrated NDVI (TI-NDVI) varies with precipitation, and the maximum or minimum NDVI may be only sensitive to precipitation for areas with mean annual precipitation lower than approximately 200 mm. (3) A significant relationship exists between NDVI and precipitation variations for areas with mean annual precipitation greater than approximately 300 mm, especially the ecotone with a ΔNDVI of 0.122?±?0.032. (4) The “advances” of FPE closely mimic fluctuations of precipitation in East Asia. 相似文献
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Interannual variability and correlation of vegetation cover and precipitation in Eastern China 总被引：5，自引：1，他引：4
Dejuan Jiang Hua Zhang Yong Zhang Kun Wang 《Theoretical and Applied Climatology》2014,118(1-2):93-105
Based on the SPOT/VEGETATION Normalized Difference Vegetation Index (NDVI) data and daily precipitation data of 357 meteorological stations, the spatial and temporal variability of vegetation cover, measured by NDVI, and precipitation as well as their relationships are investigated in Eastern China, which is portioned into three subregions (regions I, II, and III), for the period 1998–2010. The results show that high NDVI values appear mainly in Northeastern China and in August while high precipitation (PRETOT) occurs in Southeastern China and in July (June for Southern China). Extreme precipitation days (RD95p) and amount (EPRETOT) coincide well with PRETOT. Extreme precipitation intensity (RINTEN) has a similar spatial variability to PRETOT but with a smaller seasonal variation than PRETOT. Growing season NDVI is positively correlated with PRETOT in 11.7 % of the study area (mostly in arid to subhumid regions of Northern China), where precipitation is a limiting factor for vegetation growth. In contrast, a negative correlation between growing season NDVI and PRETOT is found in 4.8 % of the study area, mostly in areas around the Yangtze River and deep Northeastern China. No significant correlations between these two variables are found for the other regions because vegetation response to precipitation is affected by other factors such as temperature, radiation, and human disturbance. On a monthly scale, there is a positive correlation between NDVI and PRETOT in May (for region II) and September (all subregions except region I). NDVI variations lag 1 month behind PRETOT in June (for region I) and October. Correlations between NDVI and RD95p, EPRETOT are similar to that with PRETOT, but the relationships between NDVI and RINTEN are relatively weaker than with PRETOT. This study provides the technical basis for agriculture development and ecological construction in Eastern China. 相似文献
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Assessment of vegetation dynamics and their response to variations in precipitation and temperature in the Tibetan Plateau 总被引：10，自引：1，他引：9
The Tibetan Plateau is a region sensitive to climate change, due to its high altitude and large terrain. This sensitivity can be measured through the response of vegetation patterns to climate variability in this region. Time series analysis of Normalized Difference Vegetation Index (NDVI) imagery and correlation analyses are effective tools to study land cover changes and their response to climatic variations. This is especially important for regions like the Tibetan Plateau, which has a complex ecosystem but lacks a lot of detailed in-situ observation data due to its remoteness, vastness and the severity of its climatic conditions. In this research a time series of 315 SPOT VEGETATION scenes, covering the period between 1998 and 2006, has been processed with the Harmonic ANalysis of Time Series (HANTS) algorithm in order to reveal the governing spatiotemporal pattern of variability. Results show that the spatial distribution of NDVI values is in agreement with the general climate pattern in the Tibetan Plateau. The seasonal variation is greatly influenced by the Asian monsoon. Interannual analysis shows that vegetation density (recorded here by the NDVI values) in the entire Tibetan Plateau has generally increased. Using a 1 km resolution land cover map from GLC2000, seven meteorological stations, presenting monthly data on near surface air temperature and precipitation, were selected for correlation analysis between NDVI and climate conditions in this research. A time lag response has also been found between NDVI and climate variables. Except in desert grassland (Shiquanhe station), the NDVI of all selected sites showed strong correlation with air temperature and precipitation, with variations in correlation according to the different land cover types at different locations. The strongest relationship was found in alpine and subalpine plain grass, the weakest in desert grassland. 相似文献
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选取西藏藏北高原西部高寒草原植被、中部高寒草甸植被及东南部高寒灌丛草甸植被 3 种藏北地区最典型的植被类型, 结合临近 3 个气象观测站的资料, 分析这 3 种典型植被类型地区 1999—2001 年旬平均气温、旬总降水量和 SPOT VEGETATION 卫星 10 d 最大值合成归一化植被指数 (NDVI) 变化特征以及 3 种典型植被基于 SPOT VEGETATION NDVI 的生长变化对旬平均气温和旬总降水量两个主要气候要素变化的响应关系。 结果表明: 藏北地区降水资源的空间分布特点是东南部向西北部逐渐减少, 气温则由南向北逐渐递减, 与降水资源分布相反, 蒸发量西部高, 东部低; SPOT VEGETATION NDVI 能够较为准确地反映 3 种典型植被生长变化特征, 所反映的植被返青期和枯黄期等重要植被生长阶段与由积温计算的植被生长特征基本一致; 藏北地区基于 SPOT VEGETATION NDVI 的植被生长变化与气温的相关系数明显高于与降水的相关系数 , 其中以那曲为代表的高寒草甸植被的 NDVI 与旬气温和旬降水总量的相关系数最大, 分别为 0.81 和 0.68 , 表明藏北地区由于海拔高, 气候寒冷, 气温对该地区植被生长的影响明显高于降水的影响, 即该地区植被生长变化对气温的响应程度明显高于对降水的响应程度 , 是植被生长的限制性因素; 不同植被类型对气温和降水两个要素的响应程度大小依次是高寒草甸、高寒灌丛草甸和高寒草原。 相似文献
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西南地区植被变化与气温及降水关系的初步分析 总被引：7，自引：0，他引：7
利用卫星遥感植被归一化指数(NDVI)资料和西南地区96个实测台站的月平均气温以及降水资料,初步分析了西南地区植被变化与气温及降水的关系。结果表明:近20年来西南地区植被覆盖状况较好,其中夏季植被覆盖最好,冬季植被分布空间差异最大;西南地区植被整体呈增加趋势,同时也存在较明显的季节和区域差异:春季西南大部分地区植被以增加为主,夏季、秋季全区以减少为主,冬季则以增加为主且存在明显的东西反向特征,东部减少西部增加。时滞互相关分析表明:西南地区11~2月份的植被对超前其1~2个月的气温以及夏季的植被对春季气温的敏感性比较大,3~4月的植被生长对上年夏季的降水敏感性比较大;同期时,1~3月植被和气温为正相关关系,6~9月的植被生长和降水为明显的负相关关系;在植被超前气候的条件下,1~2月的植被和滞后1~2个月的气温呈正相关关系,与滞后1个月的降水有明显的负相关关系。 相似文献
20.
V. Krishna Prasad K. V. S. Badarinath Anuradha Eaturu 《Theoretical and Applied Climatology》2007,89(1-2):95-107
Summary Leaf phenology describes the seasonal cycle of leaf functioning and is essential for understanding the interactions between
the biosphere, the climate and the atmosphere. In this study, we characterized the spatial patterns in phenological variations
in eight contrasting forest types in an Indian region using coarse resolution NOAA AVHRR satellite data. The onset, offset
and growing season length for different forest types has been estimated using normalized difference vegetation index (NDVI).
Further, the relationship between NDVI and climatic parameters has been assessed to determine which climatic variable (temperature
or precipitation) best explain variation in NDVI. In addition, we also assessed how quickly and over what time periods does
NDVI respond to different precipitation events. Our results suggested strong spatial variability in NDVI metrics for different
forest types. Among the eight forest types, tropical dry deciduous forests showed lowest values for summed NDVI (SNDVI), averaged
NDVI (ANDVI) and integrated NDVI (I-NDVI), while the tropical wet evergreen forests of Arunachal Pradesh had highest values.
Within the different evergreen forest types, SNDVI, ANDVI and INDVI were highest for tropical wet evergreen forests, followed
by tropical evergreen forests, tropical semi-evergreen forests and were least for tropical dry evergreen forests. Differences
in the amplitude of NDVI were quite distinct for evergreen forests compared to deciduous ones and mixed deciduous forests.
Although, all the evergreen forests studied had a similar growing season length of 270 days, the onset and offset dates were
quite different. Response of vegetative greenness to climatic variability appeared to vary with vegetation characteristics
and forest types. Linear correlations between mean monthly NDVI and temperature were found to yield negative relationships
in contrast to precipitation, which showed a significant positive response to vegetation greenness. The correlations improved
much for different forest types when the log of cumulative rainfall was correlated against mean monthly NDVI. Of the eight
forest types, the NDVI for six forest types was positively correlated with the logarithm of cumulative rainfall that was summed
for 3–4 months. Overall, this study identifies precipitation as a major control for vegetation greenness in tropical forests,
more so than temperature. 相似文献