首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献，搜索用时 131 毫秒
1.
Vegetation greenness is a key indicator of terrestrial vegetation activity. To under-stand the variation in vegetation activity in spring across eastern China (EC), we analysed the variation in the Normalised Difference Vegetation Index (NDVI) from April to May during 1982-2006. The regional mean NDVI across EC increased at the rate of 0.02/10yr (r2=0.28; p=0.024) prior to 1998; the increase ceased, and the NDVI dropped to a low level thereafter. However, the processes of variation in the NDVI were different from one region to another. In the North China Plain, a cultivated area, the NDVI increased (0.03/10yr; r2=0.52; p<0.001) from 1982 to 2006. In contrast, the NDVI decreased (-0.02/10yr; r2=0.24; p=0.014) consecu-tively from 1982 to 2006 in the Yangtze River and Pearl River deltas, two regions of rapid urbanisation. In the eastern region of the Inner Mongolian Plateau and the lower reaches of the Yangtze River in East China, the NDVI increased prior to 1998 and decreased thereafter. In the Hulun Buir area and the southern part of the Yangtze River Basin, the NDVI increased prior to 1998 and remained static thereafter. The NDVI in the grasslands and croplands in the semi-humid and semi-arid areas showed a significant positive correlation with precipitation, while the NDVI in the woodlands in the humid to semi-humid areas showed a significant positive correlation with temperature. As much as 60% of the variation in the NDVI was ex-plained by either precipitation or temperature.  相似文献   

2.
Though many studies have focused on the causes of shifts in trend of temperature, whether the response of vegetation growth to temperature has changed is still not very clear. In this study, we analyzed the spatial features of the trend changes of temperature during the growing season and the response of vegetation growth in China based on observed climatic data and the normalized difference vegetation index(NDVI) from 1984 to 2011. An obvious warming to cooling shift during growing season from the period 1984–1997 to the period 1998–2011 was identified in the northern and northeastern regions of China, whereas a totally converse shift was observed in the southern and western regions, suggesting large spatial heterogeneity of changes of the trend of growing season temperature throughout China. China as a whole, a significant positive relationship between vegetation growth and temperature during 1984 to 1997 has been greatly weakened during 1998–2011. This change of response of vegetation growth to temperature has also been confirmed by Granger causality test. On regional scales, obvious shifts in relationship between vegetation growth and temperature were identified in temperate desert region and rainforest region. Furthermore, by comprehensively analyzing of the relationship between NDVI and climate variables, an overall reduction of impacts of climate factors on vegetation growth was identified over China during recent years, indicating enhanced influences from human associated activities.  相似文献   

3.
30年来呼伦贝尔地区草地植被对气候变化的响应(英文)   总被引：8，自引：3，他引：5  
Global warming has led to significant vegetation changes especially in the past 20 years. Hulun Buir Grassland in Inner Mongolia, one of the world’s three prairies, is undergoing a process of prominent warming and drying. It is essential to investigate the effects of climatic change (temperature and precipitation) on vegetation dynamics for a better understanding of climatic change. NDVI (Normalized Difference Vegetation Index), reflecting characteristics of plant growth, vegetation coverage and biomass, is used as an indicator to monitor vegetation changes. GIMMS NDVI from 1981 to 2006 and MODIS NDVI from 2000 to 2009 were adopted and integrated in this study to extract the time series characteristics of vegetation changes in Hulun Buir Grassland. The responses of vegetation coverage to climatic change on the yearly, seasonal and monthly scales were analyzed combined with temperature and precipitation data of seven meteorological sites. In the past 30 years, vegetation coverage was more correlated with climatic factors, and the correlations were dependent on the time scales. On an inter-annual scale, vegetation change was better correlated with precipitation, suggesting that rainfall was the main factor for driving vegetation changes. On a seasonal-interannual scale, correlations between vegetation coverage change and climatic factors showed that the sensitivity of vegetation growth to the aqueous and thermal condition changes was different in different seasons. The sensitivity of vegetation growth to temperature in summers was higher than in the other seasons, while its sensitivity to rainfall in both summers and autumns was higher, especially in summers. On a monthly-interannual scale, correlations between vegetation coverage change and climatic factors during growth seasons showed that the response of vegetation changes to temperature in both April and May was stronger. This indicates that the temperature effect occurs in the early stage of vegetation growth. Correlations between vegetation growth and precipitation of the month before the current month, were better from May to August, showing a hysteresis response of vegetation growth to rainfall. Grasses get green and begin to grow in April, and the impacts of temperature on grass growth are obvious. The increase of NDVI in April may be due to climatic warming that leads to an advanced growth season. In summary, relationships between monthly-interannual variations of vegetation coverage and climatic factors represent the temporal rhythm controls of temperature and precipitation on grass growth largely.  相似文献   

4.
To understand the variations in vegetation and their correlation with climate factors in the upper catchments of the Yellow River, China, Normalized Difference Vegetation Index（NDVI） time series data from 2000 to 2010 were collected based on the MOD13Q1 product. The coefficient of variation, Theil–Sen median trend analysis and the Mann–Kendall test were combined to investigate the volatility characteristic and trend characteristic of the vegetation. Climate data sets were then used to analyze the correlation between variations in vegetation and climate change. In terms of the temporal variations, the vegetation in this study area improved slightly from 2000 to 2010, although the volatility characteristic was larger in 2000–2005 than in 2006–2010. In terms of the spatial variation, vegetation which is relatively stable and has a significantly increasing trend accounts for the largest part of the study area. Its spatial distribution is highly correlated with altitude, which ranges from about 2000 to 3000 m in this area. Highly fluctuating vegetation and vegetation which showed a significantly decreasing trend were mostly distributed around the reservoirs and in the reaches of the river with hydropower developments. Vegetation with a relatively stable and significantly decreasing trend and vegetation with a highly fluctuating and significantly increasing trend are widely dispersed. With respect to the response of vegetation to climate change, about 20–30% of the vegetation has a significant correlation with climatic factors and the correlations in most areas are positive： regions with precipitation as the key influencing factor account for more than 10% of the area; regions with temperature as the key influencing factor account for less than 10% of the area; and regions with precipitation and temperature as the key influencing factors together account for about 5% of the total area. More than 70% of the vegetation has an insignificant correlation with climatic factors.  相似文献   

5.
The Qinling Mountains, located at the junction of warm temperate and subtropical zones, serve as the boundary between north and south China. Exploring the sensitivity of the response of vegetation there to hydrothermal dynamics elucidates the dynamics and mechanisms of the main vegetation types in the context of changes in temperature and moisture. Importance should be attached to changes in vegetation in different climate zones. To reveal the sensitivity and areal differentiation of vegetation responses to hydrothermal dynamics, the spatio-temporal variation characteristics of the normalized vegetation index(NDVI) and the standardized precipitation evapotranspiration index(SPEI) on the northern and southern slopes of the Qinling Mountains from 2000 to 2018 are explored using the meteorological data of 32 meteorological stations and the MODIS NDVI datasets. The results show that: 1) The overall vegetation coverage of the Qinling Mountains improved significantly from 2000 to 2018. The NDVI rise rate and area ratio on the southern slope were higher than those on the northern slope, and the vegetation on the southern slope improved more than that on the northern slope. The Qinling Mountains showed an insignificant humidification trend. The humidification rate and humidification area of the northern slope were greater than those on the southern slope. 2) Vegetation on the northern slope of the Qinling Mountains was more sensitive to hydrothermal dynamics than that on the southern slope. Vegetation was most sensitive to hydrothermal dynamics from March to June on the northern slope, and from March to May(spring) on the southern slope. The vegetation on the northern and southern slopes was mainly affected by hydrothermal dynamics on a scale of 3–7 months, responding weakly to hydrothermal dynamics on a scale of 11–12 months. 3) Some 90.34% of NDVI and SPEI was positively correlated in the Qinling Mountains. Spring humidification in most parts of the study area promoted the growth of vegetation all the year round. The sensitivity of vegetation responses to hydrothermal dynamics with increasing altitude increased first and then decreased. Elevations of 800 to 1200 m were the most sensitive range for vegetation response to hydrothermal dynamics. The sensitivity of the vegetation response at elevations of 1200–3000 m decreased with increasing altitude. As regards to vegetation type, grass was most sensitive to hydrothermal dynamics on both the northern and southern slopes of the Qinling Mountains; but most other vegetation types on the northern slope were more sensitive to hydrothermal dynamics than those on the southern slope.  相似文献   

6.
To understand the variations in vegetation and their correlation with climate factors in the upper catchments of the Yellow River, China, Normalized Difference Vegetation Index(NDVI) time series data from 2000 to 2010 were collected based on the MOD13Q1 product. The coefficient of variation, Theil–Sen median trend analysis and the Mann–Kendall test were combined to investigate the volatility characteristic and trend characteristic of the vegetation. Climate data sets were then used to analyze the correlation between variations in vegetation and climate change. In terms of the temporal variations, the vegetation in this study area improved slightly from 2000 to 2010, although the volatility characteristic was larger in 2000–2005 than in 2006–2010. In terms of the spatial variation, vegetation which is relatively stable and has a significantly increasing trend accounts for the largest part of the study area. Its spatial distribution is highly correlated with altitude, which ranges from about 2000 to 3000 m in this area. Highly fluctuating vegetation and vegetation which showed a significantly decreasing trend were mostly distributed around the reservoirs and in the reaches of the river with hydropower developments. Vegetation with a relatively stable and significantly decreasing trend and vegetation with a highly fluctuating and significantly increasing trend are widely dispersed. With respect to the response of vegetation to climate change, about 20–30% of the vegetation has a significant correlation with climatic factors and the correlations in most areas are positive: regions with precipitation as the key influencing factor account for more than 10% of the area; regions with temperature as the key influencing factor account for less than 10% of the area; and regions with precipitation and temperature as the key influencing factors together account for about 5% of the total area. More than 70% of the vegetation has an insignificant correlation with climatic factors.  相似文献   

7.
The normalized difference vegetation index （NDVI） is used extensively to describe vegetation cover and ecological environ- ment change. The purpose of this study was to contrast the response of different tree species growing in the same habitat to climate change and retrieve past NDVI using tree-ring width data from tree cores collected from the transitional zone of Pinus tabulaeformis and Picea crassifolia in the Luoshan Mountains in the middle arid region of Ningxia. Correlation analysis indi- cated that radial growth ofP tabulaeJbrmis is more sensitive to precipitation and temperature change than that ofP crassifolia. Natural factors such as water availability and heat at this elevation are more suited to the growth ofP crassifolia, and are more advantageous to its renewal and succession. P. crassifolia is probably the better of the two species for protecting the forest ecosystem and conserving water in the Luoshan desertification area. Ring width of P. crassifolia correlates significantly with average NDVI for April-May （r =0.641, p 〈0.01）, and both of them are influenced positively by precipitation in April-May. The reconstructed NDVI for 1923-2007 shows the relatively low vegetation cover occurred in the 1920s-1930s, the 1960s-1970s, and the early 21 st century. The reconstructed NDVI better reflected the drought climate in the study area.  相似文献   

8.
The vegetation coverage dynamics and its relationship with climate factors on different spatial and temporal scales in Inner Mongolia during 2001-2010 were analyzed based on MODIS-NDVI data and climate data.The results indicated that vegetation coverage in Inner Mongolia showed obvious longitudinal zonality,increasing from west to east across the region with a change rate of 0.2/10°N.During 2001-2010,the mean vegetation coverage was 0.57,0.4 and 0.16 in forest,grassland and desert biome,respectively,exhibiting evident spatial heterogeneities.Totally,vegetation coverage had a slight increasing trend during the study period.Across Inner Mongolia,the area of which the vegetation coverage showed extremely significant and significant increase accounted for 11.25% and 29.13% of the area of whole region,respectively,while the area of which the vegetation coverage showed extremely significant and significant decrease accounted for 7.65% and 26.61%,respectively.On inter-annual time scale,precipitation was the dominant driving force of vegetation coverage for the whole region.On inter-monthly scale,the change of vegetation coverage was consistent with both the change of temperature and precipitation,implying that the vegetation growth within a year is more sensitive to the combined effects of water and heat rather than either single climate factor.The vegetation coverage in forest biome was mainly driven by temperature on both inter-annual and inter-monthly scales,while that in desert biome was mainly influenced by precipitation on both the two temporal scales.In grassland biome,the yearly vegetation coverage had a better correlation with precipitation,while the monthly vegetation coverage was influenced by both temperature and precipitation.In grassland biome,the impacts of precipitation on monthly vegetation coverage showed time-delay effects.  相似文献   

9.
In Northeast Thailand, the climate change has resulted in erratic rainfall and tem- perature patterns. The region has experienced both periods of drought and seasonal floods with the increasing severity. This study investigated the seasonal variation of vegetation greenness based on the Normalized Difference Vegetation Index （NDVI） in major land cover types in the region. An assessment of the relationship between climate patterns and vegeta- tion conditions observed from NDVI was made. NDVI data were collected from year 2001 to 2009 using multi-temporal Terra MODIS Vegetation Indices Product （MOD13Q1）. NDVI pro- files were developed to measure vegetation dynamics and variation according to land cover types. Meteorological information, i.e. rainfall and temperature, for a 30 year time span from 1980 to 2009 was analyzed for their patterns. Furthermore, the data taken from the period of 2001-2009, were digitally encoded into GIS database and the spatial patterns of monthly rainfall and temperature maps were generated based on kriging technique. The results showed a decreasing trend in NDVI values for both deciduous and evergreen forests. The highest productivity and biomass were observed in dry evergreen forests and the lowest in paddy fields. Temperature was found to be increasing slightly from 1980 to 2009 while no significant trends in rainfall amounts were observed. In dry evergreen forest, NDVI was not correlated with rainfall but was significant negatively correlated with temperature. These re- sults indicated that the overall productivity in dry evergreen forest was affected by increasing temperatures. A vegetation greenness model was developed from correlations between NDVI and meteorological data using linear regression. The model could be used to observe the change in vegetation greenness and dynamics affected by temperature and rainfall.  相似文献   

10.
Different government departments and researchers have paid considerable attention at various levels to improving the eco-environment in ecologically fragile areas. Over the past decade, large numbers of people have emigrated from rural areas as a result of the rapid urbanization in Chinese society. The question then remains: to what extent does this migration affect the regional vegetation greenness in the areas that people have moved from Based on normalized difference vegetation index(NDVI) data with a resolution of 1 km, as well as meteorological data and socio-economic data from 2000 to 2010 in Inner Mongolia, the spatio-temporal variation of vegetation greenness in the study area was analyzed via trend analysis and significance test methods. The contributions of human activities and natural factors to the variation of vegetation conditions during this period were also quantitatively tested and verified, using a multi-regression analysis method. We found that:(1) the vegetation greenness of the study area increased by 10.1% during 2000–2010. More than 28% of the vegetation greenness increased significantly, and only about 2% decreased evidently during the study period.(2) The area with significant degradation showed a banded distribution at the northern edge of the agro-pastoral ecotone in central Inner Mongolia. This indicates that the eco-environment is still fragile in this area, which should be paid close attention. The area where vegetation greenness significantly improved showed a concentrated distribution in the southeast and west of Inner Mongolia.(3) The effect of agricultural labor on vegetation greenness exceeded those due to natural factors(i.e. precipitation and temperature). The emigration of agricultural labor improved the regional vegetation greenness significantly.  相似文献   

11.
CUI Linli  SHI Jun 《地理学报》2010,20(2):163-176
Temporal and spatial response characteristics of vegetation NDVI to the variation of temperature and precipitation in the whole year, spring, summer and autumn was analyzed from April 1998 to March 2008 based on the SPOT VGT–NDVI data and daily temperature and precipitation data from 205 meteorological stations in eastern China. The results indicate that as a whole, the response of vegetation NDVI to the variation of temperature is more pronounced than that of precipitation in eastern China. Vegetation NDVI maximally responds to the variation of temperature with a lag of about 10 days, and it maximally responds to the variation of precipitation with a lag of about 30 days. The response of vegetation NDVI to temperature and precipitation is most pronounced in autumn, and has the longest lag in summer. Spatially, the maximum response of vegetation NDVI to the variation of temperature is more pronounced in the northern and middle parts than in the southern part of eastern China. The maximum response of vegetation NDVI to the variation of precipitation is more pronounced in the northern part than in the middle and southern parts of eastern China. The response of vegetation NDVI to the variation of temperature has longer lag in the northern and southern parts than in the middle part of eastern China. The response of vegetation NDVI to the variation of precipitation has the longest lag in the southern part, and the shortest lag in the northern part of eastern China. The response of vegetation NDVI to the variation of temperature and precipitation in eastern China is mainly consistent with other results, but the lag time of vegetation NDVI to the variation of temperature and precipitation has some differences with those results of the monsoon region of eastern China.  相似文献   

12.
中国东部植被NDVI对气温和降水的旬响应特征   总被引：31，自引：2，他引：29  
利用中国东部SPOT VGT-NDVI数据和气象站点的日平均气温和降水资料,分析了1998-2007年中国东部植被NDVI在全年、春季、夏季和秋季对气温和降水变化的旬时空响应特征.结果表明,中国东部植被总体上对气温变化的响应大于降水,植被对气温变化的最大响应滞后1旬左右,对降水变化的最大响应滞后3旬左右.秋季植被NDVI对气温和降水变化响应最大,夏季NDVI对气温和降水响应的滞后期较长.在空间上,植被对气温变化的最大响应总体表现为北部和中部大于南部,对降水变化的最大响应表现为北部大于中部和南部.植被对气温变化最大响应的滞后期呈现出北部较长-中部短-南部最长的空间分布,对降水变化最大响应的滞后期则随着纬度降低由北到南逐渐延长.  相似文献   

13.
本文基于1982-2006年连续25年的GIMMS AVHRR NDVI植被覆盖指数,采用了最大化NDVI均值法、与气温及降水变化的相关性和一元线性回归趋势分析法,对中国三北防护林工程区连续25年的植被覆盖时空变化特征进行了动态变化研究。结果表明:(1)近25年来,研究区植被NDVI平均值总体呈缓慢上升趋势,增速为每10年0.007;(2)研究区植被和气温、降水整体呈正相关关系,植被与降水正相关面积明显大于植被与气温正相关面积,说明降水是研究区植被生长的关键因子;(3)1982-2006年,研究区植被覆盖增加的区域主要分布在大兴安岭中、南部,小兴安岭中部,长白山东北段,燕山,辽西低山丘陵区,阿尔泰山,天山,祁连山东段,西北荒漠区东部和黄土高原丘陵沟壑区南部等;植被覆盖减少的区域主要是在大兴安岭两侧,呼伦贝尔高原西部,三江平原北部,科尔沁沙地南端,西北荒漠区南部和黄土高原丘陵沟壑区北部等。  相似文献   

14.
The temporal and spatial changes of NDVI on the Tibetan Plateau, as well as the relationship between NDVI and precipitation, were discussed in this paper, by using 8-km resolution multi-temporal NOAA AVHRR-NDVI data from 1982 to 1999. Monthly maximum NDVI and monthly rainfall were used to analyze the seasonal changes, and annual maximum NDVI, annual effective precipitation and growing season precipitation (from April to August) were used to discuss the interannual changes. The dynamic change of NDVI and the corre-lation coefficients between NDVI and rainfall were computed for each pixel. The results are as follows: (1) The NDVI reached the peak in growing season (from July to September) on the Tibetan Plateau. In the northern and western parts of the plateau, the growing season was very short (about two or three months); but in the southern, vegetation grew almost all the year round. The correlation of monthly maximum NDVI and monthly rainfall varied in different areas. It was weak in the western, northern and southern parts, but strong in the central and eastern parts. (2) The spatial distribution of NDVI interannual dynamic change was different too. The increase areas were mainly distributed in southern Tibet montane shrub-steppe zone, western part of western Sichuan-eastern Tibet montane coniferous forest zone, western part of northern slopes of Kunlun montane desert zone and southeastern part of southern slopes of Himalaya montane evergreen broad-leaved forest zone; the decrease areas were mainly distributed in the Qaidam montane desert zone, the western and northern parts of eastern Qinghai-Qilian montane steppe zone, southern Qinghai high cold meadow steppe zone and Ngari montane desert-steppe and desert zone. The spatial distribution of correlation coeffi-cient between annual effective rainfall and annual maximum NDVI was similar to the growing season rainfall and annual maximum NDVI, and there was good relationship between NDVI and rainfall in the meadow and grassland with medium vegetation cover, and the effect of rainfall on vegetation was small in the forest and desert area.  相似文献   

15.
青藏高原植被覆盖变化与降水关系   总被引：15，自引：6，他引：9  
The temporal and spatial changes of NDVI on the Tibetan Plateau, as well as the relationship between NDVI and precipitation, were discussed in this paper, by using 8-km resolution multi-temporal NOAA AVHRR-NDVI data from 1982 to 1999. Monthly maximum NDVI and monthly rainfall were used to analyze the seasonal changes, and annual maximum NDVI, annual effective precipitation and growing season precipitation (from April to August) were used to discuss the interannual changes. The dynamic change of NDVI and the corre- lation coefficients between NDVI and rainfall were computed for each pixel. The results are as follows: (1) The NDVI reached the peak in growing season (from July to September) on the Tibetan Plateau. In the northern and western parts of the plateau, the growing season was very short (about two or three months); but in the southern, vegetation grew almost all the year round. The correlation of monthly maximum NDVI and monthly rainfall varied in different areas. It was weak in the western, northern and southern parts, but strong in the central and eastern parts. (2) The spatial distribution of NDVI interannual dynamic change was different too. The increase areas were mainly distributed in southern Tibet montane shrub-steppe zone, western part of western Sichuan-eastern Tibet montane coniferous forest zone, western part of northern slopes of Kunlun montane desert zone and southeastern part of southern slopes of Himalaya montane evergreen broad-leaved forest zone; the decrease areas were mainly distributed in the Qaidam montane desert zone, the western and northern parts of eastern Qinghai-Qilian montane steppe zone, southern Qinghai high cold meadow steppe zone and Ngari montane desert-steppe and desert zone. The spatial distribution of correlation coeffi- cient between annual effective rainfall and annual maximum NDVI was similar to the growing season rainfall and annual maximum NDVI, and there was good relationship between NDVI and rainfall in the meadow and grassland with medium vegetation cover, and the effect of rainfall on vegetation was small in the forest and desert area.  相似文献   

16.
应用遥感数据研究中国植被生态系统与气候的关系   总被引：48，自引：2，他引：48  
应用1982-1994年NOAA/AVHRR的归一化植被指数（NDVI）资料和587个气象台站的数据对我国不同类型植被生态系统和气候的关系进行研究，首先将我国的植被类型划分为21类，在此基础上分别研究了不同时间尺度下我国不同区域，不同植被类型和气候的关系。结果表明：在多年平均状态下，植被生态系统NDVI水平主要受水分条件的影响；年内变化上，温度对植被生态系统季相变化化起着比降水略大的作用，年降水量造成了植被季相响应的差异，在年际变化上，分别研究了4个季节和整个生长期尺度上的关系，一般情形为温度和降水对植被的年际波动起着大致相反的作用，不同植被类型在不同的生长时期（季节）对气候的变化响应方式也不同，发现在植被的生长期，我国南方和北方的植被生态系统对温度和降水的响应方式相反；同时存在2个植被-气候敏感区，分别为我国北方的典型草原到森林的过渡区和云南中部部分区域。  相似文献   

17.
利用1982-2000年NOAA/AVHRR卫星的NDVI数据(时间分辨率旬,空间分辨率8 km×8 km),结合同时期的气温和降水资料,基于时滞互相关方法和GIS工具,分析了青藏高原植被覆盖对水、热条件年内变化的时滞响应及其空间特征。结果如下:①除高寒荒漠、森林外,青藏高原植被NDVI与同期旬均温和旬降水相关性均呈高度正相关。其中,中等覆盖度的植被受水、热影响表现更为强烈。②青藏高原植被NDVI对气温和降水有滞后效应,且滞后水平存在空间差异,高原北部(柴达木盆地、昆仑山北冀)和高原南部植被对降水、和温度的响应比较迟缓,而高原中、东部地区植被对温度和降水的响应比较敏感。③不同植被类型对水热条件的响应程度也存在差异,由高到低依次是草甸、草原、灌丛、高寒垫状植被、荒漠,最后是森林。  相似文献   

18.
基于1982~2006年GIMMS NDVI数据集和地面气象台站观测数据,分析了青藏高原整个区域及各生态地理分区年均NDVI的变化趋势,并通过偏相关分析研究不同生态地理分区植被覆被变化对气温和降水响应的空间分异特征。研究表明:(1)近25年来,高原植被覆盖变化整体上趋于改善;高原东北部、东中部以及西南部湿润半湿润及部分半干旱地区植被趋于改善,植被覆盖较差的北部、西部半干旱和干旱地区呈现退化趋势;(2)高原植被变化与气温变化的相关性明显高于与降水变化的相关性,说明高原植被年际变化对温度变化更为敏感;(3)高原植被年际变化与气温和降水的相关性具有明显的区域差异,植被覆盖中等区域全年月NDVI与气温和降水的相关性最强,相关性由草甸向草原、针叶林逐步减弱,荒漠区相关性最弱。生长季植被覆盖变化与气温的相关性和全年相关性较一致,降水则不同,生长季期间高原大部分地区植被变化与降水相关性不显著。  相似文献   

19.
长白山区植被生长季NDVI时空变化及其对气候因子敏感性   总被引：7，自引：1，他引：6  
本文利用长白山区SPOT/VGT NDVI 数据和气象数据,分析该区不同植被类型NDVI时空变化特征以及与气候因子的相关关系,并探讨了植被对气候变化响应的滞后性。结果表明：①2000-2009 年,长白山区植被NDVI 逐年变化总体呈增长趋势,增长区域的面积占全区面积的83.91%,在空间上主要集中在北坡和西坡,NDVI减少区域集中在南坡;②NDVI变化率随季节和植被类型变化而不同,NDVI增长主要集中在5 月和9 月,而7 月NDVI变化较小,甚至出现下降趋势;③植被NDVI与温度和降水存在着显著的正相关性（p<0.01）,且NDVI与温度的相关性高于与降水的相关性,且随海拔升高,NDVI与温度相关性增强;④NDVI对气温和降水变化的响应存在滞后期, 不同植被类型,滞后期存在差异。苔原NDVI对温度和降水响应的滞后期大约10 天,而针阔混交林和针叶林NDVI 对温度和降水响应的滞后期约为20 天。  相似文献   

20.
2000-2012年祁连山植被覆盖变化及其与气候因子的相关性   总被引：5，自引：1，他引：4  
研究祁连山地区植被覆盖变化及其与气候因子的响应关系对这一地区土地利用总体特征以及对区域及全球气候和环境变化都将产生深远的意义。利用2000-2012年美国国家航空航天局提供的MODIS NDVI数据并结合相应的气候资料,通过对逐像元信息的提取和分析,运用均值法、斜率分析法、相关分析法,研究了2000-2012年不同季节祁连山植被覆盖的时空变化及其与气候因子的相关性。结果表明:13 a来祁连山植被覆盖整体上呈增加趋势,其中春季植被改善最为明显,秋季次之;植被覆盖变化在不同季节都存在明显的空间差异;不同季节植被与气温、降水的时滞效应不尽相同;祁连山春季大部分地区NDVI与气温呈显著正相关,夏季NDVI与降水呈显著正相关,秋、冬季NDVI与降水、气温的相关性不明显。  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号