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1.
Spatiotemporal variations of Chinese Loess Plateau vegetation cover during 1981–2006 have been investigated using GIMMS and SPOT VGT NDVI data and the cause of vegetation cover changes has been analyzed, considering the climate changes and human activities. Vegetation cover changes on the Loess Plateau have experienced four stages as follows: (1) vegetation cover showed a continued increasing phase during 1981–1989; (2) vegetation cover changes came into a relative steady phase with small fluctuations during 1990–1998; (3) vegetation cover declined rapidly during 1999–2001; and (4) vegetation cover increased rapidly during 2002–2006. The vegetation cover changes of the Loess Plateau show a notable spatial difference. The vegetation cover has obviously increased in the Inner Mongolia and Ningxia plain along the Yellow River and the ecological rehabilitated region of Ordos Plateau, however the vegetation cover evidently decreased in the hilly and gully areas of Loess Plateau, Liupan Mountains region and the northern hillside of Qinling Mountains. The response of NDVI to climate changes varied with different vegetation types. NDVI of sandy land vegetation, grassland and cultivated land show a significant increasing trend, but forest shows a decreasing trend. The results obtained in this study show that the spatiotemporal variations of vegetation cover are the outcome of climate changes and human activities. Temperature is a control factor of the seasonal change of vegetation growth. The increased temperature makes soil drier and unfavors vegetation growth in summer, but it favors vegetation growth in spring and autumn because of a longer growing period. There is a significant correlation between vegetation cover and precipitation and thus, the change in precipitation is an important factor for vegetation variation. The improved agricultural production has resulted in an increase of NDVI in the farmland, and the implementation of large-scale vegetation construction has led to some beneficial effect in ecology. Supported by the National Natural Science Foundation of China (Grant No. 40671019) and the Knowledge Innovation Project of the Institute of Geographical Sciences and Natural Resources Research of Chinese Academy of Sciences  相似文献   

2.
The Mongolian Plateau (MP) steppe is one of the largest steppe environments in the world. To monitor the terrestrial vegetation dynamics on the MP and to ascertain what the driving forces, this study examined the vegetation dynamics in Republic of Mongolia (M) and the Inner Mongolia Autonomous Region (IM) of China from the period 1982 to 2011, based on the satellite-derived GIMMS NDVI3g (Normalized Difference Vegetation Index) data across three biomes (desert, grassland and forest). The results are as followed: (1) Vegetation coverage in IM was generally greater than that in M. Before 2002, time series of NDVI over the MP increased at an average rate of 0.05% yr−1. Additionally, after 2002, the NDVI increased at a rate of 0.21% yr−1. From 1982 to 2011, the area of IM and M with positive anomalies in the NDVI increased at a separate rate of 1.82% yr−1 and 1.76% yr−1, respectively. (2) At the biome scale, the inter-annual forest NDVI variation in IM and desert NDVI for the entire MP had a significant increasing trend (0.06% yr−1 and 0.04% yr−1, respectively). (3) Climate forcing was a dominant controlling factor affecting the vegetation, and the anthropogenic behavior exhibited no significant value in the whole region. However, overgrazing was the most important reason for the regional degradation, particularly in IM. (4) In the future, the forest biome will go to recovery, whereas both the grassland and desert biomes are predicted to degrade continuously.  相似文献   

3.
Spatiotemporal variations of Chinese Loess Plateau vegetation cover during 1981-2006 have been investigated using GIMMS and SPOT VGT NDVI data and the cause of vegetation cover changes has been analyzed, considering the climate changes and human activities. Vegetation cover changes on the Loess Plateau have experienced four stages as follows: (1) vegetation cover showed a continued increasing phase during 1981―1989; (2) vegetation cover changes came into a relative steady phase with small fluctuations during 1990―1998; (3) vegetation cover declined rapidly during 1999―2001; and (4) vegetation cover increased rapidly during 2002―2006. The vegetation cover changes of the Loess Plateau show a notable spatial difference. The vegetation cover has obviously increased in the Inner Mongolia and Ningxia plain along the Yellow River and the ecological rehabilitated region of Ordos Plateau, however the vegetation cover evidently decreased in the hilly and gully areas of Loess Plateau, Liupan Mountains region and the northern hillside of Qinling Mountains. The response of NDVI to climate changes varied with different vegetation types. NDVI of sandy land vegetation, grassland and cultivated land show a significant increasing trend, but forest shows a decreasing trend. The results obtained in this study show that the spatiotemporal variations of vegetation cover are the outcome of climate changes and human activities. Temperature is a control factor of the seasonal change of vegetation growth. The increased temperature makes soil drier and unfavors vegetation growth in summer, but it favors vegetation growth in spring and autumn because of a longer growing period. There is a significant correlation between vegetation cover and precipitation and thus, the change in precipitation is an important factor for vegetation variation. The improved agricultural production has resulted in an increase of NDVI in the farmland, and the implementation of large-scale vegetation construction has led to some beneficial effect in ecology.  相似文献   

4.
Jing Fu  Jun Niu  Bellie Sivakumar 《水文研究》2018,32(12):1814-1827
Vegetation cover plays an important role in linking the atmosphere, water, and land and is deemed as a key indicator in the terrestrial ecological system. Therefore, it is of great importance to monitor vegetation dynamics and understand the mechanisms of vegetation change, including that driven by climate change. This study examines (a) the evolution of vegetation dynamics over the Heihe River Basin in the typical arid zone in north‐western China using nonparametric Mann–Kendall test and Thiel Sen's slope; (b) the relationships between remotely sensed vegetation indices (normalized difference vegetation index [NDVI] and enhanced vegetation index [EVI]) and hydroclimatic variables based on correlation analysis; and (c) the prediction of vegetation anomalies using a multiple linear regression model. For the analysis, the Moderate Resolution Imaging Spectroradiometer NDVI/EVI product and the gridded daily meteorological data at a spatial resolution of 0.125° over the period 2001–2010 are considered. The results indicate that vegetation cover improved over a large proportion during 2001–2010, with a significant trend towards warm and wet, characterized by an increase in average annual temperature and precipitation by 0.042 °C/year and 5.8 mm/year, respectively. We test the feasibility of NDVI and EVI in quantifying the responses of vegetation anomaly to climate change and develop a statistical model to predict vegetation dynamics in the basin. The NDVI‐based model is found to be more reliable than the EVI‐based model, partly due to the vegetation characteristics and geomorphologic properties of the study region. The proposed model performs well when there is no lag time between meteorological factors and vegetation indices for grassland and cropland, whereas 1‐month lead time prediction is found to be best for forest. The soil water content is introduced as an extra explanatory variable, which effectively improves the prediction accuracy for different land use types. In general, the predictive ability of the proposed model is stable and satisfactory, and the model can provide useful early warning information for regional water resources management under changing climate.  相似文献   

5.
杜明  赵鹏 《地球》2012,(11):104-109
干旱是影响社会发展和农业生产的重要因素之一。本文基于EOS/MODIS卫星遥感资料,选取江西省2001-2006年的NDVI时间序列数据,分析了NDVI对干旱的响应规律。计算了NDVI与气温、降水之间的关系。并提取植被状态指数(VCI),分析VCI与气温距平、降水距平的空间分布规律。结果表明:2003年江西夏季旱灾以高温少雨天气为主。这一时期的NDVI数值明显低于其他年份同一时期的NDVI值。气温温度越高,NDVI值越大;日照时数时间越长,NDVI值越大;降水量越高,NDVI值越大;降水距平百分率越高,VCI值越高;平均温度距平越小,VCI值越高。说明气候因素对NDVI指数和VCI指数有很大影响。研究表明,基于MODIS的植被指数可以反映旱灾的时空分布规律。  相似文献   

6.
In this study, the vegetation dynamics and their correlations with climate variability in northern China were evaluated based on the normalized difference vegetation index (NDVI) and meteorological datasets from 1982 to 2006. The NDVI showed that vegetation cover had a tiny increasing trend for whole study area in the past 25 years. However, the interannual changes of NDVI were different in each season. The part of spring and autumn NDVI values increased significantly, while the summer NDVI increased no significantly. And the interannual variations of the NDVI showed obvious spatial differentiations. The annual max NDVI increased were mainly distributed in most areas of grassland and farmland, whereas the annual max NDVI decreased were mainly distributed in forest areas. The annual NDVI and temperature had more important relationships. Thus, as compared to precipitation, the correlation between NDVI with temperature was stronger than the precipitation in northern China. NDVI and climatic variables were different in each season. The NDVI trends exhibited a close correspondence to climatological variations in region and season. In Addition, human activities also had profound effect to the NDVI trends in some regions. All these findings will make humans know more about the knowledge of the natural forces that influence vegetation change and supply a scientific basic resource to for the environmental management in northern China.  相似文献   

7.
Investigating the spatial and temporal variance in productivity along natural precipitation gradients is one of the most efficient approaches to improve understanding of how ecosystems respond to climate change. In this paper, by using the natural precipitation gradient of the Inner Mongolian Plateau from east to west determined by relatively long-term observations, we analyzed the temporal and spatial dynamics of aboveground net primary productivity (ANPP) of the temperate grasslands covering this region. Across this grassland transect, ANPP increased exponentially with the increase of mean annual precipitation (MAP) (ANPP=24.47e0.005MAP, R2=0.48). Values for the three vegetation types desert steppe, typical steppe, and meadow steppe were: 60.86 gm-2a-1, 167.14 gm-2a-1 and 288.73 gm-2a-1 respectively. By contrast, temperature had negative effects on ANPP. The moisture index (K ), which takes into ac- count both precipitation and temperature could explain the spatial variance of ANPP better than MAP alone (ANPP=2020.34K1.24, R2=0.57). Temporally, we found that the inter-annual variation in ANPP (cal- culated as the coefficient of variation, CV) got greater with the increase of aridity. However, this trend was not correlated with the inter-annual variation of precipitation. For all of the three vegetation types, ANPP had greater inter-annual variation than annual precipitation (PPT). Their difference (ANPP CV/PPT CV) was greatest in desert steppe and least in meadow steppe. Our results suggest that in more arid regions, grasslands not only have lower productivity, but also higher inter-annual variation of production. Climate change may have significant effects on the productivity through changes in precipitation pattern, vegetation growth potential, and species diversity.  相似文献   

8.
This study investigated the influence of climatic variables on the spatio-temporal variation of vegetation growth using normalized difference vegetation index (NDVI) data and climate data from 2000 to 2013 in the Northeast China Transect. Partial correlation and linear regression methods were applied to quantify the response of the growing season NDVI to climatic variables. Gradient analysis was used to investigate how the response changes across the precipitation gradient over the transect. The results show that, at the spatial scale, NDVI increases with precipitation in grassland, and the spatial sensitivity is 0.001/mm. At the temporal scale, grassland NDVI is less correlated with precipitation in wet areas where precipitation exceeds a threshold of 250 mm. The temporal sensitivity of grassland NDVI to precipitation is 0.0003–0.0006/mm. Positive correlations between NDVI and temperature dominate in forest areas, and forest NDVI is sensitive to temperature by 0.06–0.12/°C.  相似文献   

9.
The temporal evolution of vegetation activity on various land cover classes in the Spanish Pyrenees was analyzed. Two time series of the normalized difference vegetation index (NDVI) were used, corresponding to March (early spring) and August (the end of summer). The series were generated from Landsat TM and Landsat ETM+ images for the period 1984–2007. An increase in the NDVI in March was found for vegetated areas, and the opposite trend was found in both March and August for degraded areas (badlands and erosion risk areas). The rise in minimum temperature and the time variation of the cloud cover during the study period appears to be the most important factors explaining increased NDVI in the vegetated areas. In degraded areas, no climatic or topographic variable was associated with the negative NDVI trend, which may be related to erosion processes taking place in these regions. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

10.
Vegetation indices derived from remote sensing data still remain to be used for analysing the relationship between climatic factors and vegetation seasonal phenology in middle latitudes with subtropical conditions forests such as the Canarian laurel forest. The Garajonay National Park, located in the La Gomera Island, protects one of the best preserved examples of the Macaronesian laurel forest, due to the cloud banks produced by trade winds, with rainfall and temperature field data showing a clear Mediterranean climatic pattern. We have analysed seasonal vegetation indices trend for different types of forest inside the Garajonay National Park using normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) products derived from moderate resolution imaging spectrometer (MODIS) Aqua data for two hydrological years (October 2003 to September 2005) in relationship with the existing field climatic data: rainfall, net fog water and temperature. Maximum annual EVI maps show the highest vegetation indices in the laurel forest of La Gomera that occur during the dry season, mainly in late spring to early summer, with EVI temporal profiles showing that valley‐bottom laurel forest areas have the most clear seasonal trend. Difference maps of EVI values between months with the lowest and highest rainfall of each hydrological year clearly confirm the highest photosynthetic activity in the laurel forest during the dry season. In addition, these forests show a significative temporal correlation between EVI values and the temperature in the forest (p < 0·001). Our results prove the absence of summer drought stress in the laurel forest implying that the fog drip income is high enough to maintain enough soil moisture to allow the forest fully transpire when temperatures are higher. As the laurel forest of La Gomera occurs in the main recharge area of the island's aquifer system, our analysis of EVI data suggests that fog drip constitutes a key hydrological factor. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

11.
The Bosten Lake watershed investigated in this study has seen significant land cover and climate change. The spatiotemporal relationship between evapotranspiration (ET) and environmental factors remain unclear. In this study, trend analysis and correlation methods are applied to analyze the spatiotemporal characteristics of ET and the relationship between ET and its driving factors using remotely sensed ET data and measured climate data between 2001 and 2018. During the study period, high values of ET primarily occurr in the wetlands of the plain area and the mid‐elevation mountain areas. The ET values show a significantly increasing trend in the different vegetation types due to climate change and other factors. The ET change trend in the study area is in the range of ?13.4 to ≈35.9 mm per year; the desert area exhibits a significant decrease and most of the mountain areas show a significantly increasing trend. ET is significantly correlated with land surface temperature, normalized difference vegetation index (NDVI), and solar radiation. The dominant factor affecting ET is NDVI, accounting for 15.2% of the study area. The results of this study highlight the need for appropriate land‐use strategies for managing water resources in arid land ecosystems.  相似文献   

12.
Spatiotemporal dynamic simulation of grassland carbon storage in China   总被引:1,自引:0,他引:1  
Based on the Terrestrial Ecosystem Model(TEM 5.0), together with the data of climate(temperature, precipitation and solar radiation) and environment(grassland vegetation types, soil texture, altitude, longitude and latitude, and atmospheric CO2 concentration data), the spatiotemporal variations of carbon storage and density, and their controlling factors were discussed in this paper. The results indicated that:(1) the total carbon storage of China's grasslands with a total area of 394.93×104 km2 was 59.47 Pg C. Among them, there were 3.15 Pg C in vegetation and 56.32 Pg C in soil carbon. China's grasslands covering 7.0–11.3% of the total world's grassland area had 1.3–11.3% of the vegetation carbon and 9.7–22.5% of the soil carbon in the world grasslands. The total carbon storage increased from 59.13 to 60.16 Pg C during 1961–2013 with an increasing rate of 19.4 Tg C yr~(-1).(2) The grasslands in the Qinghai-Tibetan Plateau contributed most to the total carbon storage during 1961–2013, accounting for 63.2% of the total grassland carbon storage, followed by Xinjiang grasslands(15.8%) and Inner Mongolia grasslands(11.1%).(3) The vegetation carbon storage showed an increasing trend, with the average annual growth rate of 9.62 Tg C yr~(-1) during 1961–2013, and temperature was the main determinant factor, explaining approximately 85% of its variation. The vegetation carbon storage showed an increasing trend in most grassland regions, however, a decreasing trend in the central grassland in the southern China, the western and central parts of the Inner Mongolian grasslands as well as some parts on the Qinghai-Tibetan Plateau. The soil carbon storage showed a significantly increasing trend with a rate of 7.96 Tg C yr~(-1), which resulted from the interaction of more precipitation and low temperature in the 1980 s and 1990 s. Among them, precipitation was the main determinant factor of increasing soil carbon increases of China's grasslands.  相似文献   

13.
The aim of this research is to provide a detailed characterization of spatial patterns and temporal trends in the regional and local dust source areas within the desert of the Alashan Prefecture (Inner Mongolia, China). This problem was approached through multi‐scale remote sensing analysis of vegetation changes. The primary requirements for this regional analysis are high spatial and spectral resolution data, accurate spectral calibration and good temporal resolution with a suitable temporal baseline. Landsat analysis and field validation along with the low spatial resolution classifications from MODIS and AVHRR are combined to provide a reliable characterization of the different potential dust‐producing sources. The representation of intra‐annual and inter‐annual Normalized Difference Vegetation Index (NDVI) trend to assess land cover discrimination for mapping potential dust source using MODIS and AVHRR at larger scale is enhanced by Landsat Spectral Mixing Analysis (SMA). The combined methodology is to determine the extent to which Landsat can distinguish important soils types in order to better understand how soil reflectance behaves at seasonal and inter‐annual timescales. As a final result mapping soil surface properties using SMA is representative of responses of different land and soil cover previously identified by NDVI trend. The results could be used in dust emission models even if they are not reflecting aggregate formation, soil stability or particle coatings showing to be critical for accurately represent dust source over different regional and local emitting areas. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

14.
植被覆盖状况影响中国地表气温变化的观测事实   总被引:3,自引:0,他引:3       下载免费PDF全文
利用NOAA/AVHRR归一化植被指数(NDVI)及观测气温与再分析地表气温的差值(Observation Minus Reanalysis, OMR)分析了植被覆盖状况对中国地表气温变化的影响.结果表明,地表气温OMR趋势值与NDVI在空间上呈现出显著的负相关关系,植被覆盖状况差(NDVI小于0.1)的区域地表升温较为显著,气温OMR趋势值超过0.2℃/10a,而植被覆盖度高(NDVI大于0.5)的区域气温OMR趋势值则变化不大,甚至出现降温.气温OMR趋势值对植被的季节变化还有着敏感的响应.不同区域植被覆盖状况的差异可能导致中国地表气温变化对全球变暖的响应不同,预测中国未来气候变化需要考虑植被覆盖状况及其动态变化的影响.  相似文献   

15.
For better prediction and understanding of land-atmospheric interaction, in-situ observed meteorological data acquired from the China Meteorological Administration (CMA) were assimilated in the Weather Research and Forecasting (WRF) model and the monthly Green Vegetation Coverage (GVF) data, which was calculated using the Normalized Difference Vegetation Index (NDVI) of the Earth Observing System Moderate-Resolution Imaging Spectroradiometer (EOS-MODIS) and Digital Elevation Model (DEM) data of the Shuttle Radar Topography Mission (SRTM) system. Furthermore, the WRF model produced a High-Resolution Assimilation Dataset of the water-energy cycle in China (HRADC). This dataset has a horizontal resolution of 25 km for near surface meteorological data, such as air temperature, humidity, wind vectors and pressure (19 levels); soil temperature and moisture (four levels); surface temperature; downward/upward short/long radiation; 3-h latent heat flux; sensible heat flux; and ground heat flux. In this study, we 1) briefly introduce the cycling 3D-Var assimilation method and 2) compare results of meteorological elements, such as 2 m temperature and precipitation generated by the HRADC with the gridded observation data from CMA, and surface temperature and specific humidity with Global Land Data Assimilation System (GLDAS) output data from the National Aeronautics and Space Administration (NASA). We find that the simulated results of monthly 2 m temperature from HRADC is improved compared with the control simulation and has effectively reproduced the observed patterns. The simulated special distribution of ground surface temperature and specific humidity from HRADC are much closer to GLDAS outputs. The spatial distribution of root mean square errors (RMSE) and bias of 2 m temperature between observations and HRADC is reduced compared with the bias between observations and the control run. The monthly spatial distribution of surface temperature and specific humidity from HRADC is consistent with the GLDAS outputs over China. This study could improve the land surface parameters by utilizing remote sensing data and could further improve atmospheric elements with a data assimilation system. This work provides an effective attempt at combining multi-source data with different spatial and temporal scales into numerical simulations, and the simulated results could be used in further research on the long-term climatic effects and characteristics of the water-energy cycle over China.  相似文献   

16.
The ecotone between alpine steppe and meadow in the central Tibetan Plateau is sensitive to climate changes. Here we used the pollen records from three lakes in this region to reconstruct the evolution of local vegetation and climate since 8200 cal. yr BP. The history of temperature and precipitation was reconstructed quantitatively with multi-bioclimatic indexes and a transfer function from pollen records. Results show that the steppe/meadow dominated during the period of 8200–6500 cal. yr BP, especially 8200–7200 cal. yr BP, indicating the central Tibetan Plateau was controlled by strong monsoon. The steppe dominated during the periods of 6000–4900, 4400–3900, and 2800–2400 cal. yr BP. The steppe decreased gradually and the meadow expanded during the period of 4900–4400 cal. yr BP. Three century-scale drought events occurred during 5800–4900, 4400–3900 and 2800 cal. yr BP, respectively. The first time when the regional climate shifted to the present level was at 6500 cal. yr BP in the central Plateau. Since 3000 cal. yr BP, the temperature and precipitation have decreased gradually to the present level. However, the cold climate between 700–300 cal. yr BP likely corresponds to the Little Ice Age. Supported by Chinese Academy of Sciences 100 Talents Project (Grant No. 29082762), National Natural Science Foundation of China (Grant Nos. 40671196, 40372085, 49371068, 49871078), and U.S. National Science Foundation (Grant Nos. ATM-9410491, ATM-008194)  相似文献   

17.
The age of past lava flows is crucial information for evaluating the hazards and risks posed by effusive volcanoes, but traditional dating methods are expensive and time‐consuming. This study proposes an alternative statistical dating method based on remote sensing observations of tropical volcanoes by exploiting the relationship between lava flow age and vegetation cover. First, the factors controlling vegetation density on lava flows, represented by the normalized difference vegetation index (NDVI), were investigated. These factors were then integrated into pixel‐based multi‐variable regression models of lava flow age to derive lava flow age maps. The method was tested at a pixel scale on three tropical African volcanoes with considerable recent effusive activity: Nyamuragira (Democratic Republic of Congo), Mt Cameroon (Cameroon) and Karthala (the Comoros). Due to different climatic and topographic conditions, the parameters of the spatial modeling are volcano‐specific. Validation suggests that the obtained statistical models are robust and can thus be applied for estimating the age of unmodified undated lava flow surfaces for these volcanoes. When the models are applied to fully vegetated lava flows, the results should be interpreted with caution due to the saturation of NDVI. In order to improve the accuracy of the models, when available, spatial data on temperature and precipitation should be included to directly represent climatic variation. Copyright © 2017 John Wiley & Sons, Ltd.  相似文献   

18.
Using SPOT-VEGETATION Normal Difference Vegetation Index (SPOT/NDVI) data from 1998 to 2011 and climate data obtained from 223 weather stations in or near North China, vegetation variation characteristics within North China were analyzed. Vegetation variation characteristics under the influence of climate variations and human activities were distinguished through a residual analysis. Based on the results of that analysis, the relative roles of climate variations and human activities in vegetation variation were calculated. The results showed that NDVI observed by remote sensing (SPOT/NDVI) increased from 1998 to 2011. The relative roles of climate variations and human activities in vegetation increase were 30.82% and 69.18%, respectively, indicating that human activities played a major role. And observed NDVI showed an increasing trend for different land cover types overall. While NDVI increase in shrub was mainly caused by climate variations, NDVI increases in forest, grassland, farmland, deserts and urban were all primarily caused by human activities. For areas with increasing vegetation, as identified by remote sensing observations in North China, the relative roles of climate variations and human activities in vegetation change were calculated at 14.85% and 85.15% respectively, again indicating that human activities played an important role in vegetation increase. For areas of decreasing vegetation, as identified by remote sensing observations in North China, the relative roles of climate variations and human activities in vegetation change were calculated at 87.72% and 12.28% respectively, indicating that climate variations had large negative effects on vegetation condition. In addition, the relative roles of climate variations and human activities on vegetation variation have obvious spatial differences in North China. Human activities played a positive role in vegetation growth in North China. However, we cannot ignore the function of human destruction on vegetation variation in some areas.  相似文献   

19.
The weakening relationship between inter-annual temperature variability and vegetation activity in the Northern Hemisphere over the last three decades has been reported by a recent study. However, how and to what extent vegetation activity responds to climate change in China is still unclear. We applied the Pearson correlation and partial correlation methods with a moving 15-y window to the GIMMS NDVI dataset from NOAA/AVHRR and observed climate data to examine the variation in the relationships between vegetation activity and climate variables. Results showed that there was an expanding negative response of vegetation growth to climate warming and a positive role of precipitation. The change patterns between NDVI and climate variables over vegetation types during the past three decades pointed an expending negative correlation between NDVI and temperature and a positive role of precipitation over most of the vegetation types (meadow, grassland, shrub, desert, cropland, and forest). Specifically, correlation between NDVI and temperature (PNDVI-T) have shifted from positive to negative in most of the station of temperature-limited areas with evergreen broadleaf forests, whereas precipitation-limited temperate grassland and desert were characterized by a positive PNDVI-P. This study contributes to ongoing investigations of the effects of climate change on vegetation activity. It is also of great importance for designing forest management strategies to cope with climate change.  相似文献   

20.
流域植被覆盖状况对于水源地生态环境保护具有重要的指示作用.当前的水质目标管理不仅要着眼于湖库水质参数控制,更应该从整个流域的角度维系生态平衡.在此背景下,依托长时间序列MODIS遥感数据对千岛湖流域2001-2013年植被覆盖状况进行监测,采用最小二乘法趋势分析和Mann-Kendall显著性检验方法分析了千岛湖流域植被的空间分布特征、时间变化特征与长期变化趋势.研究表明该方法能够有效地监测流域植被覆盖的时空动态变化:1)从空间分布上来看,千岛湖流域植被覆盖状况整体较好,但同时也发现受人为干扰较大的地域如河、湖附近的城镇建设用地、农业用地以及园地,其NDVI值明显低于自然林地;2)从时间变化特征上看,2001-2013年千岛湖流域植被年际NDVI在0.69~0.73之间波动,且近年来有增长趋势,年内季节性NDVI动态分析表明高时间分辨率的MODIS数据能够用来区分常绿植被与落叶植被的物候特征,以分析不同植被类型对流域氮、磷流失的风险差异;3)从变化趋势上看,2001-2013年植被覆盖状况改善的区域远大于退化的区域,其中改善区域约占流域面积的55.90%,呈现出一定退化状态的区域约占29.60%(严重退化区域仅占3.97%),而相对稳定不变区域约占14.51%.经与气温与降水等气候因子进行相关性分析表明,植被NDVI与气温呈显著正相关,而降水则不敏感,说明气温是研究区植被生长的主导气候因子.同时发现,人类活动对局部植被变化影响较大.研究结果可为流域水资源与生态环境保护提供空间数据支撑.  相似文献   

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