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1.
基于MODIS-NDVI数据分析澜沧江流域生长季植被NDVI时空特征和变化趋势,结合地形数据、气象站点数据和植被类型数据,利用趋势分析和相关性分析法研究植被NDVI变化对气候因子的响应。结果表明:1)2000-2017年澜沧江流域生长季植被NDVI均值为0.592,整体呈现出由西北向东南波动增加趋势,增长速率为0.09%/10年;2) 2000-2017年澜沧江流域气温呈上升趋势,降水呈下降趋势,植被NDVII总体与平均气温的相关性高于累积降水量;3)澜沧江流域生长季植被NDVI驱动因子分析表明,气候驱动中以气温降水联合驱动为主,流域植被NDVI变化整体为非气候驱动。 相似文献
2.
Meng Qi Hu Fei Mao Han Sun Ying Yu Hou 《International Journal of Applied Earth Observation and Geoinformation》2011
Using NOAA/AVHRR 10-day composite NDVI data and 10-day meteorological data, including air temperature, precipitation, vapor pressure, wind velocity and sunshine duration, at 19 weather stations in the three-river-source region in the Qinghai–Tibetan Plateau in China from 1982 to 2000, the variations of NDVI and climate factors were analyzed for the purpose of studying the correlation between climate change and vegetation growth as represented by NDVI in this region. Results showed that the NDVI values in this region gradually grew from the west to the east, and the distribution was consistent with that of moisture status. The growing season came earlier due to climate warming, yet because of the reduction of precipitation, maximal NDVI during 1982–2000 did not show a significant change. NDVI related positively to air temperature, vapor pressure and precipitation, but negatively related to sunshine duration and wind velocity. Furthermore, the response of NDVI to climate change showed time lags for different climate factors. Water condition and temperature were found to be the most important factors effecting the variation of NDVI during the growing season in both the semi-arid and the semi-humid areas. In addition, NDVI had a better correlation with vapor pressure than with precipitation. The ratio of precipitation to evapotranspiration, representing water gain and loss, can be regarded as a comprehensive index to analyze NDVI and climate change, especially in areas where the water condition plays a dominant role. 相似文献
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针对鄂尔多斯高原植被覆盖变化受干旱胁迫的状况,该文结合降水和气温的协同变化,以2000-2012年生长季的MODIS-NDVI数据和同期降水、温度和帕尔默干旱指数为依据,采用线性趋势分析、标准偏差分析和相关性分析等方法,对鄂尔多斯高原植被与气候变化的相关关系和干旱异常变化对植被动态的影响进行了研究.结果表明:鄂尔多斯高原生长季及季节(春季、夏季和秋季)植被归一化植被指数主要受降水的控制和干旱的制约,秋季归一化植被指数更多地受到夏季干旱的影响.与气象因子的空间相关分析表明,春季温度上升有利于研究区北部归一化植被指数像元的增加.在荒漠草原和沙漠地区,夏季干旱与归一化植被指数的相关关系最强.秋季降水对典型草原归一化植被指数的提升显著. 相似文献
5.
A growing number of studies have focused on variations in vegetation phenology and their correlations with climatic factors. However, there has been little research on changes in spatial heterogeneity with respect to the end of the growing season (EGS) and on responses to climate change for alpine vegetation on the Qinghai–Tibetan Plateau (QTP). In this study, the satellite-derived normalized difference vegetation index (NDVI) and the meteorological record from 1982 to 2012 were used to characterize the spatial pattern of variations in the EGS and their relationship to temperature and precipitation on the QTP. Over the entire study period, the EGS displayed no statistically significant trend; however, there was a strong spatial heterogeneity throughout the plateau. Those areas showing a delaying trend in the EGS were mainly distributed in the eastern part of the plateau, whereas those showing an advancing trend were mostly scattered throughout the western part. Our results also showed that change in the vegetation EGS was more closely correlated with air temperature than with precipitation. Nonetheless, the temperature sensitivity of the vegetation EGS became lower as aridity increased, suggesting that precipitation is an important regulator of the response of the vegetation EGS to climate warming. These results indicate spatial differences in key environmental influences on the vegetation EGS that must be taken into account in current phenological models, which are largely driven by temperature. 相似文献
6.
《地理信息系统科学与遥感》2013,50(3):371-393
This study uses a multiple linear regression method to composite standard Normalized Difference Vegetation Index (NDVI) time series (1982-2009) consisting of three kinds of satellite NDVI data (AVHRR, SPOT, and MODIS). This dataset was combined with climate data and land cover maps to analyze growing season (June to September) NDVI trends in northeast Asia. In combination with climate zones, NDVI changes that are influenced by climate factors and land cover changes were also evaluated. This study revealed that the vegetation cover in the arid, western regions of northeast Asia is strongly influenced by precipitation, and with increasing precipitation, NDVI values become less influenced by precipitation. Spatial changes in the NDVI as influenced by temperature in this region are less obvious. Land cover dynamics also influence NDVI changes in different climate zones, especially for bare ground, cropland, and grassland. Future research should also incorporate higher-spatial-resolution data as well as other data types (such as greenhouse gas data) to further evaluate the mechanisms through which these factors interact. 相似文献
7.
This paper investigated spatiotemporal dynamic pattern of vegetation, climate factor, and their complex relationships from seasonal to inter-annual scale in China during the period 1982–1998 through wavelet transform method based on GIMMS data-sets. First, most vegetation canopies demonstrated obvious seasonality, increasing with latitudinal gradient. Second, obvious dynamic trends were observed in both vegetation and climate change, especially the positive trends. Over 70% areas were observed with obvious vegetation greening up, with vegetation degradation principally in the Pearl River Delta, Yangtze River Delta, and desert. Overall warming trend was observed across the whole country (>98% area), stronger in Northern China. Although over half of area (58.2%) obtained increasing rainfall trend, around a quarter of area (24.5%), especially the Central China and most northern portion of China, exhibited significantly negative rainfall trend. Third, significantly positive normalized difference vegetation index (NDVI)–climate relationship was generally observed on the de-noised time series in most vegetated regions, corresponding to their synchronous stronger seasonal pattern. Finally, at inter-annual level, the NDVI–climate relationship differed with climatic regions and their long-term trends: in humid regions, positive coefficients were observed except in regions with vegetation degradation; in arid, semiarid, and semihumid regions, positive relationships would be examined on the condition that increasing rainfall could compensate the increasing water requirement along with increasing temperature. This study provided valuable insights into the long-term vegetation–climate relationship in China with consideration of their spatiotemporal variability and overall trend in the global change process. 相似文献
8.
基于MODIS-NDVI的内蒙古植被变化遥感监测 总被引：2，自引：0，他引：2
本文利用2002-2006年5-8月的MODIS 1B数据,建立NDVI时间序列,并结合气象数据中的月均温、月降水量、滞后1月和滞后2月累计降水量对内蒙古地区植被生长季NDVI的月际、年际变化规律以及NDVI变化同气候因子的相关性进行了分析。结果表明:月际变化上,5-8月NDVI不断增加,NDVI变化率5-6月>6-7月>7-8月;年际变化上,2002-2006年间,草地的波动性最大;在与气候因子的相关性上:滞后2月降水>滞后1月降水>月均温>月降水量;对于林地和草地来说,各种相关系数高纬高于低纬,对于农耕地来说各种相关系数基本相当;对于沙地来说,各种相关系数均不高,这与其植被稀少且几乎无变化有关。 相似文献
9.
Abstract Land cover is an important component of the earth system. Human induced surface alteration can affect earth systems directly, through loss or degradation of ecosystems, or indirectly through impact on the climate and biogeochemical cycles necessary to sustain life on earth. The significance of the earth's surface has made land use/land cover change an important issue in global change research. Alteration of land cover occurs at a variety of spatial scales, but as with many environmental change issues, the impacts of surface changes are often conceptualized at the global scale. In this study, we investigate the effects of land cover change on total reflected radiation and the Normalized Difference Vegetation Index (NDVI) in a 10,000 km2 local area in the High Plains of southwestern Kansas. Landsat MSS data from five years of record within the twenty‐year period 1973 to 1992 were classified into cool season crop, warm season crop, and pasture/prairie. Mean values of summer reflectance and NDVI from each cover type and for the study area as a whole were then analyzed for systematic change over the study period. Both reflectivity and vegetation index increased during the study period, although causes for the increase appear to be different. Results suggest that changes in mean surface reflectance in the study site are strongly influenced by land cover change, whereas changes in NDVI are more closely linked to 50‐day antecedent precipitation. 相似文献
10.
《International Journal of Digital Earth》2013,6(11):1098-1117
ABSTRACTDetecting changes in vegetation, distinguishing the persistence of changes, and seeking their causes during multiple periods are important to gaining a deeper understanding of vegetation dynamics. Using the Global Inventory Modeling and Mapping Studies Normalized Difference Vegetation Index (NDVI) version NDVI3g dataset in the Tibetan Plateau, the trends in the seasonal components of NDVI and their linkage with climatic factors were analyzed over 14 asymptotic periods of 18–31 years since 1982. Dynamic trends in vegetation experienced an obvious increase at regional scale, but the increases of vegetation activity mostly tended to stall or slow down as the studied time period was extended. At pixel scale, areas with significant browning significantly expanded over 14 periods for all seasons, but for significant greening significantly increased only in autumn. The changes of vegetation activity in spring were the most drastic among three seasons. Increased increments of NDVI in summer, spring, and autumn took turns being the main reason for the enhanced vegetation activity in the growing season in the nested 14 periods. Vegetation activity was mainly regulated by a thermal factor, and the dominant climatic drivers of vegetation growth varied across different seasons and regions. We speculate that the increase of NDVI will continue but the increments will decline in all seasons except autumn. 相似文献
11.
Boniface O Oindo Rolf A de By Andrew K Skidmore 《International Journal of Applied Earth Observation and Geoinformation》2000,2(3-4)
Species richness, or simply the number of species in a given area, is commonly used as an important indicator of biological diversity. Spatial variability in species richness has been postulated to depend upon environmental factors such as climate and climatic variability, which in turn may affect net primary productivity. The Advanced Very High Resolution Radiometer (AVHRR) derived Normalized Difference Vegetation Index (NDVI) has been shown to be correlated with climatic variables including rainfall, actual evapotranspiration and net primary productivity. To determine factors favoring high species richness, we examined the relationship between interannual NDVI variables and species richness of birds at a quarter degree scale (55 × 55 km). Results revealed a strong positive correlation between species richness and maximum average NDVI. Conversely, species richness showed negative correlation with standard deviation of maximum NDVI and the coefficient of variation. Though these relationships are indirect, they apparently operate through the green vegetation cover. Understanding such relationships can help in mapping and monitoring biological diversity, as well as in estimating changes in species richness in response to global climatic change. 相似文献
12.
Phenology is a sensitive and critical feature of vegetation and is a good indicator for climate change studies. The global inventory modelling and mapping studies (GIMMS) normalized difference vegetation index (NDVI) has been the most widely used data source for monitoring of the vegetation dynamics over large geographical areas in the past two decades. With the release of the third version of the NDVI (GIMMS NDVI3g) recently, it is important to compare the NDVI3g data with those of the previous version (NDVIg) to link existing studies with future applications of the NDVI3g in monitoring vegetation phenology. In this study, the three most popular satellite start of vegetation growing season (SOS) extraction methods were used, and the differences between SOSg and SOS3g arising from the methods were explored. The amplitude and the peak values of the NDVI3g are higher than those of the NDVIg curve, which indicated that the SOS derived from the NDVIg (SOSg) was significantly later than that derived from the NDVI3g (SOS3g) based on all the methods, for the whole northern hemisphere. In addition, SOSg and SOS3g both showed an advancing trend during 1982–2006, but that trend was more significant with SOSg than with SOS3g in the results from all three methods. In summary, the difference between SOSg and SOS3g (in the multi-year mean SOS, SOS change slope and the turning point in the time series) varied among the methods and was partly related to latitude. For the multi-year mean SOS, the difference increased with latitude intervals in the low latitudes (0–30°N) and decreased in the mid- and high-latitude intervals. The GIMMS NDVI3g data-sets seemed more sensitive than the GIMMS NDVIg in detecting information about the ground, and the SOS3g data were better correlated both with the in situ observations and the SOS derived from the Moderate Resolution Imaging Spectroradiometer NDVI. For the northern hemisphere, previous satellite measures (SOS derived from GIMMS NDVIg) may have overestimated the advancing trend of the SOS by an average of 0.032 d yr–1. 相似文献
13.
Baozhang Chen Guang Xu Nicholas C. Coops Philippe Ciais Ranga B. Myneni 《International Journal of Digital Earth》2016,9(11):1055-1076
The Asia-Pacific (AP) region has experienced faster warming than the global average in recent decades and has experienced more climate extremes, however little is known about the response of vegetation growth to these changes. The updated Global Inventory Modeling and Mapping Studies third-generation global satellite Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index dataset and gridded reanalysis climate data were used to investigate the spatiotemporal changes in both trends of vegetation dynamic indicators and climatic variables. We then further analyzed their relations associated with land cover across the AP region. The main findings are threefold: (1) at continental scales the AP region overall experienced a gradual and significant increasing trend in vegetation growth during the last three decades, and this NDVI trend corresponded with an insignificant increasing trend in temperature; (2) vegetation growth was negatively and significantly correlated with the Pacific Decadal Oscillation index and the El Niño/Southern Oscillation (ENSO) in AP; and (3) at pixel scales, except for Australia, both vegetation growth and air temperature significantly increased in the majority of study regions and vegetation growth spatially correlated with temperature; In Australia and other water-limited regions vegetation growth positively correlated with precipitation. 相似文献
14.
In this paper, we apply lagged correlation analysis to study the effects of vegetation cover on the summer climate in different zones of China, using NOAA/AVHRR normalized difference vegetation index (NDVI) data during the time period from 1982 to 2001 and climate data of 365 meteorological stations across China (precipitation from 1982 to 2001 and temperature from 1982 to 1998). The results show that there are positive correlations between spring NDVI and summer climate (temperature and precipitation) in most zones of China; these suggest that, when the vegetation cover increases, the summer precipitation will increase, and the lagged correlations show a significant difference between zones. The stronger correlations between NDVI in previous season and summer climate occur in three zones (Mid-temperate zone, Warm-temperate zone and Plateau climate zone), and this implies that vegetation changes have more sensitive feedback effects on climate in the three zones in China. 相似文献
15.
利用MERIS数据植被指数分析福建省植被长势季节变化 总被引：1，自引：0，他引：1
监测植被长势动态变化可以提供生态系统状况有价值的信息,可以检测到人类或气候作用引起的变化。本研究利用2004—2005年间10期MERIS影像数据,以福建省为例,探讨MERIS数据在区域植被长势季节变化监测中的应用效果;分析了MERIS数据用于区域植被季节变化监测时的数据处理方法;比较了MERIS数据几种植被指数,提出了利用10和8波段组合改进MERISNDVI的建议;利用多时相合成的NDVI简单分析了2004年夏季—2005年夏季三个季节的植被长势状况。结果表明,MERIS植被指数的时空变化有效反映了气候变化对植被长势的影响。 相似文献
16.
Rahul Nigam Bimal Kumar Bhattacharya Keshav R. Gunjal N. Padmanabhan N. K. Patel 《Journal of the Indian Society of Remote Sensing》2012,40(1):1-9
To study impact of climate change on vegetation time series vegetation index has a vital role to know the behaviour of vegetation
dynamics over a time period. INSAT 3A CCD (Charged Couple Device) is the only geostationary sensor to acquire regular coverage
of Asia continent at 1 km × 1 km spatial resolution with high temporal frequency (half-an-hour). A formulation of surface
reflectances in red, near infrared (NIR), short wave infrared (SWIR) and NDVI from INSAT 3A CCD has been defined and integrated
in the operational chain. The atmospheric correction of at-sensor reflectances using SMAC (Simple Model for Atmospheric Correction)
model improved the NDVI by 5–40% and also increased its dynamic range. The temporal dynamics of 16-day NDVI composite at 0500
GMT for a growing year (June 2008–March 2009) showed matching profiles with reference to global products (MODIS TERRA) over
known land targets. The root mean square deviation (RMSD) between the two was 0.14 with correlation coefficient (r) 0.84 from
200 paired datasets. This inter-sensor cross-correlation would help in NDVI calibration to add continuity in long term NDVI
database for climate change studies. 相似文献
17.
Impact of Climate Change on Runoff of the Major River Basins of India Using Global Circulation Model (HadCM3) Projected Data 总被引：1，自引：0，他引：1
Praveen K. Gupta Sushma Panigrahy Jai Singh Parihar 《Journal of the Indian Society of Remote Sensing》2011,39(3):337-344
The effects of climate change on hydrological regimes have become a priority area for water and catchment management strategies.
The terrestrial hydrology driven by monsoon rainfall plays a crucial role in shaping the agriculture, surface and ground water
scenario in India. Thus, it is imperative to assess the impact of the changing climatic scenario projected under various climate
change scenario towards the hydrological aspects for India. Runoff is one of the key parameters used as an indicator of hydrological
process. A study was taken up to analyse the climate change impact on the runoff of river basins of India. The global circulation
model output of Hadley centre (HADCM3) projected climate change data was used. Scenario for 2080 (A2 scenario indicating more
industrial growth) was selected. The runoff was modeled using the curve number method in spatial domain using satellite derived
current landuse/cover map. The derived runoff was compared with the runoff using normal climatic data (1951–1980). The results
showed that there is a decline in the future climatic runoff in most of the river basins of India compared to normal climatic
runoff. However, significant reduction was observed for the river basins in the eastern region viz: lower part of Ganga, Bahamani-Baitrani,
Subarnrekha and upper parts of the Mahanadi. The mean projected runoff reduction during monsoon season (June–September) were
18 Billion Cubic Meter (BCM), 3.2 BCM, 3.5 BCM and 5.9 BCM for Brahmaputra-Barak Subarnrekha, Subarnarekha and Brahmini-Baitrani
basin, respectively in comparison to normal climatic runoff. Overall reduction in seasonal runoff was high for Subarnrekha
basin (54.1%). Rainfall to runoff conversion was high for Brahmaputra-Barak basin (72%), whereas coefficient of variation
for runoff was more for Mahanadi basin (1.88) considering the monsoon season. Study indicates that eastern India agriculture
may be affected due to shortage of surface water availability. 相似文献
18.
基于获取的塔河流域2000~2014年历年4~10月间逐月MODIS植被指数产品,采用时间序列谐波分析法(HANTS)对最大值合成的逐月NDVI时间序列数据进行了重建,用趋势线分析法对塔河流域近15年生长季(4~10月)MODIS NDVI的时间变化进行计算,用一元线性回归趋势法计算得到了塔河流域近15年生长季(4~10月)NDVI变化趋势的空间分布。结合植被类型分布图对计算得到的实验结果进行了研究分析,总结了塔河流域多年植被覆盖的时空分布及其变化规律,成果可为塔河流域综合治理及生态环境评价提供依据。 相似文献
19.
Multitemporal NOAA/AVHRR NDVI images and monthly temperature and precipitation data were obtained across Yangtze River basin
covering the period 1981–2001. The spatial and temporal patterns of NDVI are the same, while spatial analysis shows that the
NDVI is influenced by the vegetation types growing in the study regions, and NDVI presents an increasing trend during the
study period in the whole basin. The climate indicators play an important role in the changes of vegetation cover in the river
basin. In the two Indicators, temperature has a significant effect on the NDVI values than precipitation in the whole basin.
However, in the 11 subbasins, the different rules are shown in different subbasins. 相似文献
20.
In this paper, we apply lagged correlation analysis to study the effects of vegetation cover on the summer climate in different
zones of China, using NOAA/AVHRR normalized difference vegetation index (NDVI) data during the time period from 1982 to 2001
and climate data of 365 meteorological stations across China (precipitation from 1982 to 2001 and temperature from 1982 to
1998). The results show that there are positive correlations between spring NDVI and summer climate (temperature and precipitation)
in most zones of China; these suggest that, when the vegetation cover increases, the summer precipitation will increase, and
the lagged correlations show a significant difference between zones. The stronger correlations between NDVI in previous season
and summer climate occur in three zones (Mid-temperate zone, Warm-temperate zone and Plateau climate zone), and this implies
that vegetation changes have more sensitive feedback effects on climate in the three zones in China.
Supported by the National 973 Program of China (No.2006CB701300), the National Natural Science Foundation of China (No.40721001),
the Sino-Germany Joint Project (No. 2006DFB91920), the Open Fund of Shanghai Leading Academic Discipline Project (T0102) and
the Open Fund of LIESMARS, Wuhan University. 相似文献