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1.
中国东部植被NDVI对气温和降水的时空响应(英文) 总被引：8，自引：4，他引：4
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 maxi... 相似文献
2.
LIU Xianfeng ZHANG Jinshui ZHU Xiufang PAN Yaozhong LIU Yanxu ZHANG Donghai LIN Zhihui 《地理学报(英文版)》2014,24(2):288-302
The Three-River Headwaters Region （TRHR）, which is the source area of the Yangtze River, Yellow River, and Lancang River, is of key importance to the ecological secu- rity of China. Because of climate changes and human activities, ecological degradation oc- curred in this region. Therefore, ＂The nature reserve of Three-River Sou,＇ce Regions＂ was established, and ＂The project of ecological protection and construction for the Three-River Headwaters Nature Reserve＂ was implemented by the Chinese government. This study, based on MODIS-NDVI and climate data, aims to analyze the spatiotemporal changes in vegetation coverage and its driving factors in the TRHR between 2000 and 2011, from three dimensions. Linear regression, Hurst index analysis, and partial correlation analysis were employed. The results showed the following： （1） In the past 12 years （2000-2011）, the NDVI of the study area increased, with a linear tendency being 1.2%/10a, of which the Yangtze and Yellow River source regions presented an increasing trend, while the Lancang River source region showed a decreasing trend. （2） Vegetation coverage presented an obvious spatial difference in the TRHR, and the NDVI frequency was featured by a bimodal structure. （3） The area with improved vegetation coverage was larger than the degraded area, being 64.06% and 35.94%, respectively during the study period, and presented an increasing trend in the north and a decreasing trend in the south. （4） The reverse characteristics of vegetation cov- erage change are significant. In the future, degradation trends will be mainly found in the Yangtze River Basin and to the north of the Yellow River, while areas with improving trends are mainly distributed in the Lancang River Basin. （5） The response of vegetation coverage to precipitation and potential evapotranspiration has a time lag, while there is no such lag in the case of temperature. （6） The increased vegetation coverage is mainly attributed to the warm-wet climate change and the implementation of the ecological protection project. 相似文献
3.
The Three-River Headwaters Region(TRHR), which is the source area of the Yangtze River, Yellow River, and Lancang River, is of key importance to the ecological security of China. Because of climate changes and human activities, ecological degradation occurred in this region. Therefore, "The nature reserve of Three-River Source Regions" was established, and "The project of ecological protection and construction for the Three-River Headwaters Nature Reserve" was implemented by the Chinese government. This study, based on MODIS-NDVI and climate data, aims to analyze the spatiotemporal changes in vegetation coverage and its driving factors in the TRHR between 2000 and 2011, from three dimensions. Linear regression, Hurst index analysis, and partial correlation analysis were employed. The results showed the following:(1) In the past 12 years(2000–2011), the NDVI of the study area increased, with a linear tendency being 1.2%/10a, of which the Yangtze and Yellow River source regions presented an increasing trend, while the Lancang River source region showed a decreasing trend.(2) Vegetation coverage presented an obvious spatial difference in the TRHR, and the NDVI frequency was featured by a bimodal structure.(3) The area with improved vegetation coverage was larger than the degraded area, being 64.06% and 35.94%, respectively during the study period, and presented an increasing trend in the north and a decreasing trend in the south.(4) The reverse characteristics of vegetation coverage change are significant. In the future, degradation trends will be mainly found in the Yangtze River Basin and to the north of the Yellow River, while areas with improving trends are mainly distributed in the Lancang River Basin.(5) The response of vegetation coverage to precipitation and potential evapotranspiration has a time lag, while there is no such lag in the case of temperature.(6) The increased vegetation coverage is mainly attributed to the warm-wet climate change and the implementation of the ecological protection project. 相似文献
4.
There is a lack of simple ways to predict the vegetation responses to the East Asian Monsoon(EAM) variability in China due to the complexity of the monsoon system. In this study, we found the variation of the Western Pacific Subtropical High(WPSH), which is one of the major components of the EAM, has a profound influence on the vegetation growth in China. When the WPSH is located more to the west of its climate average, the eastern and northwestern parts experience increased yearly-averaged normalized difference vegetation index(NDVI) and gross primary productivity(GPP) by 0.3%–2.2%, and 0.2%–2.2%, respectively. In contrast, when the WPSH is located more to the east of its climate average, the above areas experience decreased yearly-averaged NDVI and GPP by 0.4% to 1.6%, and 1.3% to 4.5%, respectively. The WPSH serves as a major circulation index to predict the response of vegetation to monsoon. 相似文献
5.
江河源区NDVI时空变化及其与气候因子的关系(英文) 总被引：5，自引：3，他引：2
The source regions of the Yangtze and Yellow rivers are important water conservation areas of China. In recent years, ecological deterioration trend of the source regions caused by global climate change and unreasonable resource development increased gradually. In this paper, the spatial distribution and dynamic change of vegetation cover in the source regions of the Yangtze and Yellow rivers are analyzed in recent 10 years based on 1-km resolution multitemporal SPOTVGT-DN data from 1998 to 2007. Meanwhile, the correlation relationships between air temperature, precipitation, shallow ground temperature and NDVI, which is 3×3 pixel at the center of Wudaoliang, Tuotuohe, Qumalai, Maduo, and Dari meteorological stations were analyzed. The results show that the NDVI values in these two source regions are increasing in recent 10 years. Spatial distribution of NDVI which was consistent with hydrothermal condition decreased from southeast to northwest of the source regions. NDVI with a value over 0.54 was mainly distributed in the southeastern source region of the Yellow River, and most NDVI values in the northwestern source region of the Yangtze River were less than 0.22. Spatial changing trend of NDVI has great difference and most parts in the source regions of the Yangtze and Yellow rivers witnessed indistinct change. The regions with marked increasing trend were mainly distributed on the south side of the Tongtian River, some part of Keqianqu, Tongtian, Chumaer, and Tuotuo rivers in the source region of the Yangtze River and Xingsuhai, and southern Dari county in the source region of the Yellow River. The regions with very marked increasing tendency were mainly distributed on the south side of Tongtian Rriver and sporadically distributed in hinterland of the source region of the Yangtze River. The north side of Tangula Range in the source region of the Yangtze River and Dari and Maduo counties in the source region of the Yellow River were areas in which NDVI changed with marked decreasing tendency. The NDVI change was980 Journal of Geographical Sciences positively correlated with average temperature, precipitation and shallow ground temperature. Shallow ground temperature had the greatest effect on NDVI change, and the second greatest factor influencing NDVI was average temperature. The correlation between NDVI and shallow ground temperature in the source regions of the Yangtze and Yellow rivers increased significantly with the depth of soil layer. 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.
Inter-annual variations in vegetation and their response to climatic factors in the upper catchments of the Yellow River from 2000 to 2010 总被引：1，自引：0，他引：1
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
8.
Based on the drought/flood grades of 90 meterological stations over eastern China and summer average sea-level pressure (SLP) during 1850–2008 and BPCCA statistical methods, the coupling relationship between the drought/flood grades and the East Asian summer SLP is analyzed. The East Asian summer monsoon index which is closely related with interdecadal variation of drought/flood distribution over eastern China is defined by using the key areas of SLP. The impact of the interdecadal variation of the East Asian summer monsoon on the distribution of drought/flood over eastern China in the last 159 years is researched. The results show that there are four typical drought and flood spatial distribution patterns in eastern China, i.e. the distribution of drought/flood in southern China is contrary to the other regions, the distribution of drought/flood along the Huanghe River–Huaihe River Valley is contrary to the Yangtze River Valley and regions south of it, the distribution of drought/flood along the Yangtze River Valley and Huaihe River Valley is contrary to the other regions, the distribution of drought/flood in eastern China is contrary to the western. The main distribution pattern of SLP in summer is that the strength of SLP is opposite in Asian continent and West Pacific. It has close relationship between the interdecadal variation of drought/flood distribution patterns over eastern China and the interdecadal variation of the East Asian summer monsoon which was defined in this paper, but the correlation is not stable and it has a significant difference in changes of interdecadal phase. When the East Asian summer monsoon was stronger (weaker), regions north of the Yangtze River Valley was more susceptible to drought (flood), the Yangtze River Valley and regions south of it were more susceptible to flood (drought) before the 1920s; when the East Asian summer monsoon was stronger (weaker), the regions north of the Yangtze River Valley was prone to flood (drought), the Yangtze River Valley and regions south of it were prone to drought (flood) after the 1920s. It is indicated that by using the data of the longer period could get much richer results than by using the data of the last 50–60 years. The differences in the interdecadal phase between the East Asian summer monsoon and the drought/flood distributions in eastern China may be associated with the nonlinear feedback, which is the East Asian summer monsoon for the extrinsic forcing of solar activity. 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.
近5年青海省植被覆盖变化的遥感监测 总被引：3，自引：2，他引：1
This paper used five years （2001-2006） time series of MODIS NDVI images with a 1-km spatial resolution to produce a land cover map of Qinghai Province in China. A classification approach for different land cover types with special emphasis on vegetation, especially on sparse vegetation, was developed which synthesized Decision Tree Classification, Supervised Classification and Unsupervised Classification. The spatial distribution and dynamic change of vegetation cover in Qinghai from 2001 to 2006 were analyzed based on the land cover classification map and five grade elevation belts derived from Qinghai DEM. The result shows that vegetation cover in Qinghai in recent five years has been some improved and the area of vegetation was increased from 370,047 km^2 in 2001 to 374,576 km^2 in 2006. Meanwhile, vegetation cover ratio was increased by 0.63%. Vegetation cover ratio in high mountain belt is the largest （67.92%） among the five grade elevation belts in Qinghai Province. The second largest vegetation cover ratio is in middle mountain belt （61.80%）. Next, in the order of the decreasing vegetation cover ratio, the remaining grades are extreme high mountain belt （38.98%）, low mountain belt （25.55%） and flat region belt （15.46%）. The area of middle density grassland in high mountain belt is the biggest （94,003 km^2）, and vegetation cover ratio of dense grassland in middle mountain belt is the highest （32.62%）, and the increased area of dense grassland in high mountain belt is the greatest （1280 km^2）. In recent five years the conversion from sparse grass to middle density grass in high mountain belt has been the largest vegetation cover variation and the converted area is 15931 km^2. 相似文献
11.
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
12.
陕甘宁地区植被恢复对气候变化和人类活动的响应(英文) 总被引：5，自引：2，他引：3
The "Grain for Green Project" initiated by the governments since 1999 were the dominant contributors to the vegetation restoration in the agro-pastoral transitional zone of northern China. Climate change and human activities are responsible for the improvement and degradation to a certain degree. In order to monitor the vegetation variations and clarify the causes of rehabilitation in the Shaanxi-Gansu-Ningxia Region, this paper, based on the MODIS-NDVI and climate data during the period of 2000-2009, analyzes the main charac-teristics, spatial-temporal distribution and reasons of vegetation restoration, using methods of linear regression, the Hurst Exponent, standard deviation and other methods. Results are shown as follows. (1) From 2000 to 2009, the NDVI of the study area was improved progres-sively, with a linear tendency being 0.032/10a, faster than the growth of the Three-North Shelter Forest Program (0.007/10a) from 1982 to 2006. (2) The vegetation restoration is characterized by two fast-growing periods, with an "S-shaped" increasing curve. (3) The largest proportion of the contribution to vegetation restoration was observed in the slightly improved area, followed by the moderate and the significantly improved area; the degraded area is distributed sporadically over southern part of Ningxia Hui Autonomous Region as well as eastern Dingbian of Shaanxi province, Huanxian and Zhengyuan of Gansu province. (4) Climate change and human activities are two driving forces in vegetation restoration; more-over anthropogenic factors such as "Grain for Green Project" were the main causes leading to an increasing trend of NDVI on local scale. However, its influencing mechanism remains to be further investigated. (5) The Hurst Exponent of NDVI time series shows that the vegetation restoration was sustainable. It is expected that improvement in vegetation cover will expand to the most parts of the region. 相似文献
13.
《地理学报(英文版)》2019,(9)
The Heihe River Basin is located in the arid and semi-arid regions of Northwest China. Here, the terrestrial ecosystem is vulnerable, making it necessary to identify the factors that could affect the ecosystem. In this study, MODIS-NDVI data with a 250-m resolution were used as a proxy for the terrestrial ecosystem. By combining these with environmental factors, we were able to explore the spatial features of NDVI and identify the factors influencing the NDVI distribution in the Heihe River Basin during the period of 2000–2016. A geographical detector(Geodetector) was employed to examine the spatial heterogeneity of the NDVI and to explore the factors that could potentially influence the NDVI distribution. The results indicate that:(1) the NDVI in the Heihe River Basin appeared high in the southeast while being low in the north, showing spatial heterogeneity with a q-statistic of 0.38. The spatial trend of the vegetation in the three sub-basins generally increased in the growing seasons from 2000 to 2016;(2) The results obtained by the Geodetector(as denoted by the q-statistic as well as the degree of spatial association between the NDVI and environmental factors) showed spatial heterogeneity in the associations between the NDVI and the environmental factors for the overall basin as well as the sub-basins. Precipitation was the dominant factor for the overall basin. In the upper basin, elevation was found to be the dominant factor. The dominant factor in the middle basin was precipitation, closely followed by the soil type. In the lower basin, the dominant factor was soil type with a lower q-statistic of 0.13, and the dominant interaction between the elevation and soil type was nonlinearly enhanced(q-statistic = 0.22). 相似文献
14.
There is growing concern over the effects of climate change on glacier melt and hydrology. In this article, we used two natural small-scale basins, Tuotuo River and Buqu River in the source region of the Yangtze River, China, to show the impacts of glacier melt on stream flow. Changes in the extent of glaciers and ice volume in 1970, 1992 and 2009 are evaluated using remote sensing images. Changes to the glacier surface area over the same time interval are estimated through the delineation of glacier outlines and positions using Landsat TM/ETM＋ imagery. By 2009, the glacier surface area had decreased by 20.83% and 34.81% of the 1970 values in Tuotuo River and Baqu River basins respectively. The total meltwater supply in each basin is estimated to be 2.56×10^9 m^3/yr and 1.24×10^9 m^3/yr respectively. Mass balance calculations show that glaciers in the study area suffered a constant mass loss of snow and ice, accumulatively approximately -24 m over the past 40 years. The annual and summer stream flow tended to increase in Tuotuo River basin from 1970 to 2009 while a negative trend of change was shown in Buqu River basin during 1970-1986. Glaciers became shorter, narrower and thinner under the effect of atmospheric warming. Streamflow increase has been recorded at Tuotuo River station in response to increased glacier and permafrost melt. However, streamflow decrease has been recorded at Yanshiping station on Buqu River, where glacier melt has lagged behind atmospheric warming. These results show a close but variable linkage among climate change, glacier melting and water resources in the source region of the Yangtze River. 相似文献
15.
The quantity and spatial pattern of farmland has changed in China, which has led to a major change in the production potential under the influence of the national project of ecological environmental protection and rapid economic growth during 1990–2010. In this study, the production potential in China was calculated based on meteorological, terrain elevation, soil and land-use data from 1990, 2000 and 2010 using the Global Agro-ecological Zones model. Then, changes in the production potential in response to farmland changes from 1990 to 2010 were subsequently analyzed. The main conclusions were the following. First, the total production potential was 1.055 billion tons in China in 2010. Moreover, the average production potential was 7614 kg/ha and showed tremendous heterogeneity in spatial pattern. Total production in eastern China was high, whereas that in northwestern China was low. The regions with high per unit production potential were mainly distributed over southern China and the middle and lower reaches of the Yangtze River. Second, the obvious spatiotemporal heterogeneity in farmland changes from 1990 to 2010 had a significant influence on the production potential in China. The total production potential decreased in southern China and increased in northern China. Furthermore, the center of growth of the production potential moved gradually from northeastern China to northwestern China. The net decrease in the production potential was 2.97 million tons, which occupied 0.29% of the national total actual production in 2010. Third, obvious differences in the production potential in response to farmland changes from 1990 to 2000 and from 2000 to 2010 were detected. The net increase in the production potential during the first decade was 10.11 million tons and mainly distributed in the Northeast China Plain and the arid and semi-arid regions of northern China. The net decrease in the production potential during the next decade was 13.08 million tons and primarily distributed in the middle and lower reaches of the Yangtze River region and the Huang-Huai-Hai Plain. In general, the reason for the increase in the production potential during the past two decades might be due to the reclamation of grasslands, woodlands and unused land, and the reason for the decrease in the production potential might be urbanization that occupied the farmland and Green for Grain Project, which returned farmland to forests and grasslands. 相似文献
16.
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
17.
《地理学报(英文版)》2017,(7)
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
18.
This study analyzed the spatial and temporal variations in the Normalized Difference Vegetation Index(NDVI) on the Mongolian Plateau from 1982–2013 using Global Inventory Modeling and Mapping Studies(GIMMS) NDVI3 g data and explored the effects of climate factors and human activities on vegetation. The results indicate that NDVI has slight upward trend in the Mongolian Plateau over the last 32 years. The area in which NDVI increased was much larger than that in which it decreased. Increased NDVI was primarily distributed in the southern part of the plateau, especially in the agro-pastoral ecotone of Inner Mongolia. Improvement in the vegetative cover is predicted for a larger area compared to that in which degradation is predicted based on Hurst exponent analysis. The NDVI-indicated vegetation growth in the Mongolian Plateau is a combined result of climate variations and human activities. Specifically, the precipitation has been the dominant factor and the recent human effort in protecting the ecological environments has left readily detectable imprints in the NDVI data series. 相似文献
19.
The leaf area index(LAI) shows a significant increasing trend from global to regional scales, which is known as greening. Greening will further enhance photosynthesis, but it is unclear whether the contribution of greening has exceeded the CO2 fertilization effect and become the dominant factor in the gross primary productivity(GPP) variation. We took the Yangtze River Delta(YRD) of China, where cropland and natural vegetation are significantly greening, as an example. Based on the bo... 相似文献
20.
《地理学报(英文版)》2019,(4)
The 1998–2012 global warming hiatus has aroused great public interest over the past several years. Based on the air temperature measurements from 622 meteorological stations in China, the temperature response to the global warming hiatus was analyzed at national and regional scales. We found that air temperature changed –0.221℃/10 a during 1998–2012, which was lower than the long-term trend for 1960–1998 by 0.427℃/10 a. Therefore, the warming hiatus in China was more pronounced than the global mean. Winter played a dominant role in the nationwide warming hiatus, contributing 74.13%, while summer contributed the least among the four seasons. Furthermore, the warming hiatus was spatial heterogeneous across different climate conditions in China. Comparing the three geographic zones, the monsoon region of eastern China, arid region of northwestern China, and high frigid region of the Tibetan Plateau, there was significant cooling in eastern and northwestern China. In eastern China, which contributed 53.79%, the trend magnitudes were 0.896℃/10 a in winter and 0.134℃/10 a in summer. In the Tibetan Plateau, air temperature increased by 0.204℃/10 a, indicating a lack of a significant warming hiatus. More broadly, the warming hiatus in China may have been associated with the negative phase of PDO and reduction in sunspot numbers and total solar radiation. Finally, although a warming hiatus occurred in China from 1998 to 2012, air temperature rapidly increased after 2012 and will likely to continuously warm in the next few years. 相似文献