基于遥感的中国北部植被NDVI和物候变化研究
|
摘要
植被是全球陆地生态系统的重要组成部分。植被与气象因子之间的相互关系研究是目前全球变化研究的热点问题。很多学者运用多种线性趋势分析方法研究植被的变化趋势,但由于植被的变化易受到气象因子的影响,从而表现为非线性变化,使用非线性的分段线性回归方法研究植被在不同阶段的变化可以很好的解释植被对于气象因子的响应。所以,开展不同季节植被变化及对气象因子的非线性响应研究变的很有必要。本研究选取中国北部地区,使用1982-2006年的GIMMS NDVI数据,从植被NDVI和物候两个角度研究中国北部植被变化及对气象因子的响应规律。主要结论如下：
1.GIMMS NDVI与MODIS NDVI数据在大部分地区具有较高的相关系数(0.9-1.0)且两数据的斜率均值在1.0附近,表明GIMMS NDVI数据具有较好的数据质量,所以GIMMS NDVI数据可用于后续植被NDVI和物候变化研究。
2.生长季降水是生长季NDVI变化的主要驱动力。生长季NDVI总体上以上升趋势为主；生长季NDVI在生长季降水转折点之前呈较快上升趋势,生长季NDVI在生长季降水转折点之后呈明显下降趋势。当生长季温度与生长季降水都呈增加趋势时,生长季NDVI上升趋势明显；但是当生长季温度增加,生长季降水减少时则会发生干旱,从而导致生长季NDVI下降。
3.春季温度是春季NDVI变化的主要驱动力；同时,局部地区也受到春季温度增加和春季降水减少导致干旱胁迫下春季NDVI下降。夏季降水是夏季NDVI变化的主要驱动力；当夏季温度与夏季降水都呈增加趋势时,夏季NDVI上升趋势明显；但是当夏季温度增加,夏季降水减少时则会发生干旱,从而导致夏季NDVI下降。秋季NDVI总体上呈上升趋势,在秋季温度转折点之前上升较快,在秋季温度转折点之后上升变缓。这是因为在秋季温度转折点之后秋季温度仍呈上升趋势而降水呈减少趋势的象元增多,从而在温度和降水共同影响下的干旱胁迫导致植被下降。
4.物候生长季始期总体上以延迟趋势为主；在物候生长季始期转折点之前,整个研究区主要呈提前趋势；在其转折点之后,整个研究区主要呈延迟趋势。物候生长季始期与温度具有较好的负相关且变化趋势具有较好的一致性。物候生长季末期总体上以延迟趋势为主；在物候生长季末期转折点之前,整个研究区主要呈延迟趋势；在其转折点之后,整个研究区呈微弱延迟趋势。物候生长季末期变化趋势受温度和降水共同作用下的干旱胁迫影响。物候生长季长度总体上以缩短趋势为主：在物候生长季长度转折点之前,整个研究区主要呈延长趋势；在其转折点之后,整个研究区主要呈缩短趋势。
本研究主要创新点如下：
1.使用PDSI干旱指数结合温度和降水数据综合分析中国北部生长季和季节性NDVI的非线性变化,与一元线性回归方法分时间段计算PDSI干旱指数结果相比,研究效果较好且为植被NDVI的多影响因素分析提供了新思路。
2.将分段线性回归方法应用于中国北部植被物候生长季末期和植被物候生长季长度研究,与一元线性回归方法分时间段计算结果相比,研究效果较好。
Vegetation is an important part of the global terrestrial ecosystems. The relationship between vegetation and climate factors has become the hot issue of global change research. A variety of linear trend analysis methods have been used by many scholars to study the trend of vegetation change. The performance of nonlinear changes for vegetation respond to climate factors, so the use of piecewise linear regression method to study the vegetation at different stages could be well explain the vegetation response to climate factors. Therefore, it is necessary to study vegetation change for different seasons and its nonlinear response to climate factors. The Northern China was selected, using GIMMS NDVI data from1982to2006, to study vegetation change and its response to climate factors in Northern China from two aspects of NDVI and vegetation phenology. The main conclusions are as follows:
1. GIMMS NDVI and MODIS NDVI data had a high correlation coefficient (0.9-1.0) and the mean slope of the two data around1.0in most areas, indicating that GIMMS NDVI data with better data quality, and then GIMMS NDVI data could be used for subsequent NDVI and phenological change research.
2. Growing season precipitation was the main driving force of the growing season NDVI change. Growing season NDVI was in general with an upward trend; growing season NDVI was rapidly upward trend before the turning point of growing season precipitation, and then significantly decreased after the turning point of growing season precipitation. When the growing season temperature and precipitation experienced an increasing trend in the growing season, the growing season NDVI rose significantly; however, when the growing season temperature increased with growing season precipitation reduced will occurred drought, resulting decline in growing season NDVI.
3. Spring temperature was the main driving force of the spring NDVI change, while spring NDVI decreased could be attributed to drought stress strengthened by increased spring warming and less spring precipitation in some areas. Summer precipitation was the main driving force of the summer NDVI change. Summer NDVI rose significantly with summer temperature and summer precipitation increased. But summer NDVI decreased could be attributed to drought stress strengthened by increased summer temperature and less summer precipitation. Autumn NDVI was in general with an upward trend; Autumn NDVI rose rapidly before the turning point of autumn temperature, while rose slowly after the turning point of autumn temperature. Autumn NDVI decreased after the turning point of autumn temperature could be attributed to drought stress strengthened by autumn warming and less autumn precipitation after the turning point of autumn temperature.
4. The start of the growing season (SOS) was in general delayed trend; the entire study area was in general advanced trend before the turning point of SOS; and the entire study area was delayed trend after the turning point of SOS. The SOS and temperature had a good negative correlation trend and better consistency. The end of the growing season (EOS) was in general delayed trend; the entire study area was in general delayed trend before the turning point of EOS; and the entire study area was weak delayed trend after the turning point of EOS. The EOS trend could be attributed to drought stress strengthened by combined effect of temperature and precipitation. The length of the growing season (LOS) overall shortened; the entire study area was extended trend before the turning point of LOS; and the entire study area was shortened trend after the turning point of LOS.
The main innovation of this study is as follows:
1. Compared PDSI drought index calculation results of a linear regression method with different time periods, PDSI drought index was used with a combination of temperature and precipitation data from a comprehensive analysis of nonlinear changes for growing season and seasonal NDVI in northern China for better research results.
2. Compared with the results of a linear regression method with different time periods, the piecewise linear regression method was applied to the end of growing season and the length of growing season in northern China for better research results.
1.GIMMS NDVI与MODIS NDVI数据在大部分地区具有较高的相关系数(0.9-1.0)且两数据的斜率均值在1.0附近,表明GIMMS NDVI数据具有较好的数据质量,所以GIMMS NDVI数据可用于后续植被NDVI和物候变化研究。
2.生长季降水是生长季NDVI变化的主要驱动力。生长季NDVI总体上以上升趋势为主；生长季NDVI在生长季降水转折点之前呈较快上升趋势,生长季NDVI在生长季降水转折点之后呈明显下降趋势。当生长季温度与生长季降水都呈增加趋势时,生长季NDVI上升趋势明显；但是当生长季温度增加,生长季降水减少时则会发生干旱,从而导致生长季NDVI下降。
3.春季温度是春季NDVI变化的主要驱动力；同时,局部地区也受到春季温度增加和春季降水减少导致干旱胁迫下春季NDVI下降。夏季降水是夏季NDVI变化的主要驱动力；当夏季温度与夏季降水都呈增加趋势时,夏季NDVI上升趋势明显；但是当夏季温度增加,夏季降水减少时则会发生干旱,从而导致夏季NDVI下降。秋季NDVI总体上呈上升趋势,在秋季温度转折点之前上升较快,在秋季温度转折点之后上升变缓。这是因为在秋季温度转折点之后秋季温度仍呈上升趋势而降水呈减少趋势的象元增多,从而在温度和降水共同影响下的干旱胁迫导致植被下降。
4.物候生长季始期总体上以延迟趋势为主；在物候生长季始期转折点之前,整个研究区主要呈提前趋势；在其转折点之后,整个研究区主要呈延迟趋势。物候生长季始期与温度具有较好的负相关且变化趋势具有较好的一致性。物候生长季末期总体上以延迟趋势为主；在物候生长季末期转折点之前,整个研究区主要呈延迟趋势；在其转折点之后,整个研究区呈微弱延迟趋势。物候生长季末期变化趋势受温度和降水共同作用下的干旱胁迫影响。物候生长季长度总体上以缩短趋势为主：在物候生长季长度转折点之前,整个研究区主要呈延长趋势；在其转折点之后,整个研究区主要呈缩短趋势。
本研究主要创新点如下：
1.使用PDSI干旱指数结合温度和降水数据综合分析中国北部生长季和季节性NDVI的非线性变化,与一元线性回归方法分时间段计算PDSI干旱指数结果相比,研究效果较好且为植被NDVI的多影响因素分析提供了新思路。
2.将分段线性回归方法应用于中国北部植被物候生长季末期和植被物候生长季长度研究,与一元线性回归方法分时间段计算结果相比,研究效果较好。
Vegetation is an important part of the global terrestrial ecosystems. The relationship between vegetation and climate factors has become the hot issue of global change research. A variety of linear trend analysis methods have been used by many scholars to study the trend of vegetation change. The performance of nonlinear changes for vegetation respond to climate factors, so the use of piecewise linear regression method to study the vegetation at different stages could be well explain the vegetation response to climate factors. Therefore, it is necessary to study vegetation change for different seasons and its nonlinear response to climate factors. The Northern China was selected, using GIMMS NDVI data from1982to2006, to study vegetation change and its response to climate factors in Northern China from two aspects of NDVI and vegetation phenology. The main conclusions are as follows:
1. GIMMS NDVI and MODIS NDVI data had a high correlation coefficient (0.9-1.0) and the mean slope of the two data around1.0in most areas, indicating that GIMMS NDVI data with better data quality, and then GIMMS NDVI data could be used for subsequent NDVI and phenological change research.
2. Growing season precipitation was the main driving force of the growing season NDVI change. Growing season NDVI was in general with an upward trend; growing season NDVI was rapidly upward trend before the turning point of growing season precipitation, and then significantly decreased after the turning point of growing season precipitation. When the growing season temperature and precipitation experienced an increasing trend in the growing season, the growing season NDVI rose significantly; however, when the growing season temperature increased with growing season precipitation reduced will occurred drought, resulting decline in growing season NDVI.
3. Spring temperature was the main driving force of the spring NDVI change, while spring NDVI decreased could be attributed to drought stress strengthened by increased spring warming and less spring precipitation in some areas. Summer precipitation was the main driving force of the summer NDVI change. Summer NDVI rose significantly with summer temperature and summer precipitation increased. But summer NDVI decreased could be attributed to drought stress strengthened by increased summer temperature and less summer precipitation. Autumn NDVI was in general with an upward trend; Autumn NDVI rose rapidly before the turning point of autumn temperature, while rose slowly after the turning point of autumn temperature. Autumn NDVI decreased after the turning point of autumn temperature could be attributed to drought stress strengthened by autumn warming and less autumn precipitation after the turning point of autumn temperature.
4. The start of the growing season (SOS) was in general delayed trend; the entire study area was in general advanced trend before the turning point of SOS; and the entire study area was delayed trend after the turning point of SOS. The SOS and temperature had a good negative correlation trend and better consistency. The end of the growing season (EOS) was in general delayed trend; the entire study area was in general delayed trend before the turning point of EOS; and the entire study area was weak delayed trend after the turning point of EOS. The EOS trend could be attributed to drought stress strengthened by combined effect of temperature and precipitation. The length of the growing season (LOS) overall shortened; the entire study area was extended trend before the turning point of LOS; and the entire study area was shortened trend after the turning point of LOS.
The main innovation of this study is as follows:
1. Compared PDSI drought index calculation results of a linear regression method with different time periods, PDSI drought index was used with a combination of temperature and precipitation data from a comprehensive analysis of nonlinear changes for growing season and seasonal NDVI in northern China for better research results.
2. Compared with the results of a linear regression method with different time periods, the piecewise linear regression method was applied to the end of growing season and the length of growing season in northern China for better research results.
引文
[1]Ahmed M, Anchukaitis K J, Asrat A, Borgaonkar H P, Braida M, Buckley B M, Buntgen U, Chase B M, Christie D A, Cook E R. Continental-scale temperature variability during the past two millennia. Nature geoscience [J].2013,6:339-346.
[2]Altermatt F. Temperature-related shifts in butterfly phenology depend on the habitat. Global Change Biology [J].2012,18 (8):2429-2438.
[3]Bisigato A, Campanella M, Pazos G. Plant phenology as affected by land degradation in the arid Patagonian Monte, Argentina:A multivariate approach. Journal of Arid Environments [J].2013,91:79-87.
[4]Boschetti M, Nutini F, Brivio P A, Bartholome E, Stroppiana D, Hoscilo A. Identification of environmental anomaly hot spots in West Africa from time series of NDVI and rainfall. ISPRS Journal of Photogrammetry and Remote Sensing [J].2013,78:26-40.
[5]Brown J C, Kastens J H, Coutinho A C, Victoria D D C, Bishop C R. Classifying multiyear agricultural land use data from Mato Grosso using time-series MODIS vegetation index data. Remote Sensing of Environment [J].2013,130:39-50.
[6]Brown M E, de Beurs K, Vrieling A. The response of African land surface phenology to large scale climate oscillations. Remote Sensing of Environment [J].2010,114 (10):2286-2296.
[7]Buermann W, Bikash P R, Jung M, Burn D H, Reichstein M. Earlier springs decrease peak summer productivity in North American boreal forests. Environmental Research Letters [J].2013,8 (2):024027.
[8]Buyantuyev A, Wu J. Urbanization diversifies land surface phenology in arid environments: interactions among vegetation, climatic variation, and land use pattern in the Phoenix metropolitan region, USA. Landscape and Urban Planning [J].2012,105 (1):149-159.
[9]Chen X, Xu L. Temperature controls on the spatial pattern of tree phenology in China's temperate zone. Agricultural and Forest Meteorology [J].2012,154-155:195-202.
0] Ciais P, Reichstein M, Viovy N, Granier A, Ogee J, Allard V, Aubinet M, Buchmann N, Bernhofer C, Carrara A. Europe-wide reduction in primary productivity caused by the heat and drought in 2003. Nature [J].2005,437 (7058):529-533.
1] Cihlar J, Tcherednichenko I, Latifovic R, Li Z, Chen J. Impact of variable atmospheric water vapor content on AVHRR data corrections over land. IEEE Transactions on Geoscience and Remote Sensing [J].2001,39 (1):173-180.
2] Clark M L, Aide T M, Grau H R, Riner G. A scalable approach to mapping annual land cover at 250 m using MODIS time series data:A case study in the Dry Chaco ecoregion of South America. Remote Sensing of Environment [J].2010,114 (11):2816-2832.
3] Cleland E E, Chiariello N R, Loarie S R, Mooney H A, Field C B. Diverse responses of phenology to global changes in a grassland ecosystem. Proceedings of the National Academy of Sciences [J].2006,103 (37):13740-13744.
4] Cong N, Piao S, Chen A, Wang X, Lin X, Chen S, Han S, Zhou G, Zhang X. Spring vegetation green-up date in China inferred from SPOT NDVI data:a multiple model analysis. Agricultural and Forest Meteorology [J].2012,165:104-113.
5] Cong N, Wang T, Nan H, Ma Y, Wang X, Myneni R B, Piao S. Changes in satellite-derived spring vegetation green-up date and its linkage to climate in China from 1982 to 2010:a multimethod analysis. Global change biology [J].2013,19 (3):881-891.
6] Cook J, Nuccitelli D, Green S A, Richardson M, Winkler B, Painting R, Way R, Jacobs P, Skuce A. Quantifying the consensus on anthropogenic global warming in the scientific literature. Environmental Research Letters [J].2013,8 (2):024024.
7] Coops N C, Wulder M A, Iwanicka D. Large area monitoring with a MODIS-based Disturbance Index (DI) sensitive to annual and seasonal variations. Remote Sensing of Environment [J].2009,113 (6):1250-1261.
8] Cotton P A. Avian migration phenology and global climate change. Proceedings of the National Academy of Sciences [J].2003,100 (21):12219-12222.
9] Dai A. Characteristics and trends in various forms of the Palmer Drought Severity Index during 1900-2008. Journal of Geophysical Research:Atmospheres (1984-2012) [J].2011, 116:D12115.
[20]Dall'Olmo G, Karnieli A. Monitoring phenological cycles of desert ecosystems using NDVI and LST data derived from NOAA-AVHRR imagery. International Journal of Remote Sensing [J].2002,23 (19):4055-4071.
[21]De Jong R, de Bruin S, de Wit A, Schaepman M E, Dent D L. Analysis of monotonic greening and browning trends from global NDVI time-series. Remote Sensing of Environment [J].2011,115 (2):692-702.
[22]De Jong R, Verbesselt J, Zeileis A, Schaepman M E. Shifts in Global Vegetation Activity Trends. Remote Sensing [J].2013,5 (3):1117-1133.
[23]Dragoni D, Rahman A F. Trends in fall phenology across the deciduous forests of the Eastern USA. Agricultural and Forest Meteorology [J].2012,157:96-105.
[24]Dutrieux L P, Bartholomeus H, Herold M, Verbesselt J. Relationships between declining summer sea ice, increasing temperatures and changing vegetation in the Siberian Arctic tundra from MODIS time series (2000-11). Environmental Research Letters [J].2012,7 (4):044028.
[25]Epstein H E, Myers-Smith I, Walker D A. Recent dynamics of arctic and sub-arctic vegetation. Environmental Research Letters [J].2013,8 (1):015040.
[26]Fensholt R, Langanke T, Rasmussen K, Reenberg A, Prince S D, Tucker C, Scholes R J, Le Q B, Bondeau A, Eastman R. Greenness in semi-arid areas across the globe 1981-2007-An Earth Observing Satellite based analysis of trends and drivers. Remote Sensing of Environment [J].2012,121:144-158.
[27]Fensholt R, Proud S R. Evaluation of earth observation based global long term vegetation trends-Comparing GIMMS and MODIS global NDVI time series. Remote sensing of Environment [J].2012,119:131-147.
[28]Gao J, Liu Y. Climate warming and land use change in Heilongjiang Province, Northeast China. Applied Geography [J].2011,31 (2):476-482.
[29]Gillett N P, Arora V K, Zickfeld K, Marshall S J, Merryfield W J. Ongoing climate change following a complete cessation of carbon dioxide emissions. Nature Geoscience [J].2011,4 (2):83-87.
[30]Goetz S J, Bunn A G, Fiske G J, Houghton R A. Satellite-observed photosynthetic trends across boreal North America associated with climate and fire disturbance. Proceedings of the National Academy of Sciences of the United States of America [J].2005,102 (38):13521-13525.
[31]Gong D Y, Ho C H. Detection of large-scale climate signals in spring vegetation index (normalized difference vegetation index) over the Northern Hemisphere. Journal of Geophysical Research:Atmospheres [J].2003,108 (D16):4498.
[32]Han S, Yang Z. Cooling effect of agricultural irrigation over Xinjiang, Northwest China from 1959 to 2006. Environmental Research Letters [J].2013,8 (2):024039.
[33]H?gda K A, T?mmervik H, Karlsen S R. Trends in the Start of the Growing Season in Fennoscandia 1982-2011. Remote Sensing [J].2013,5 (9):4304-4318.
[34]Holland D M, Thomas R H, De Young B, Ribergaard M H, Lyberth B. Acceleration of Jakobshavn Isbrae triggered by warm subsurface ocean waters. Nature Geoscience [J].2008, 1 (10):659-664.
[35]Huete A, Didan K, Miura T, Rodriguez E P, Gao X, Ferreira L G. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote sensing of environment [J].2002,83 (1):195-213.
[36]Hufkens K, Friedl M A, Keenan T F, Sonnentag O, Bailey A, O'Keefe J, Richardson A D. Ecological impacts of a widespread frost event following early spring leaf-out. Global Change Biology [J].2012,18 (7):2365-2377.
[37]IPCC. Climate Change 2013. The Physical Science Basis [M]. Cambridge University Press, Cambridge, UK,2013.
[38]Ivits E, Cherlet M, Sommer S, Mehl W. Addressing the complexity in non-linear evolution of vegetation phenological change with time-series of remote sensing images. Ecological Indicators [J].2013,26:49-60.
[39]James M, Kalluri S N. The Pathfinder AVHRR land data set:An improved coarse resolution data set for terrestrial monitoring. International Journal of Remote Sensing [J].1994,15 (17):3347-3363.
[40]Jeong S J, Ho C H, Gim H J, Brown M E. Phenology shifts at start vs. end of growing season in temperate vegetation over the Northern Hemisphere for the period 1982-2008. Global Change Biology [J].2011,17 (7):2385-2399.
[41]Jeong S J, Ho C H, Kim B M, Feng S, Medvigy D. Non-linear response of vegetation to coherent warming over northern high latitudes. Remote Sensing Letters [J].2013,4 (2):123-130.
[42]Jiang B, Liang S. Improved vegetation greenness increases summer atmospheric water vapor over Northern China. Journal of Geophysical Research:Atmospheres [J].2013,118 (15):8129-8139.
[43]Jiang Z, Huete A R, Didan K, Miura T. Development of a two-band enhanced vegetation index without a blue band. Remote Sensing of Environment [J].2008,112 (10):3833-3845.
[44]John R, Chen J, Lu N, Wilske B. Land cover/land use change in semi-arid Inner Mongolia: 1992-2004. Environmental Research Letters [J].2009,4 (4):045010.
[45]Jones M O, Jones L A, Kimball J S, McDonald K C. Satellite passive microwave remote sensing for monitoring global land surface phenology. Remote Sensing of Environment [J].2011,115 (4):1102-1114.
[46]Jones M O, Kimball J S, Jones L A, McDonald K C. Satellite passive microwave detection of North America start of season. Remote Sensing of Environment [J].2012,123:324-333.
[47]Jong R, Verbesselt J, Schaepman M E, Bruin S. Trend changes in global greening and browning:contribution of short-term trends to longer-term change. Global Change Biology [J].2012,18 (2):642-655.
[48]Joshi M, Sutton R, Lowe J, Frame D. Projections of when temperature change will exceed 2 [deg] C above pre-industrial levels. Nature Climate Change [J].2011,1 (8):407-412.
[49]Katsman C, van Oldenborgh G J. Tracing the upper ocean's "missing heat". Geophysical Research Letters [J].2011,38 (14):L14610.
[50]Keenlyside N, Latif M, Jungclaus J, Kornblueh L, Roeckner E. Advancing decadal-scale climate prediction in the North Atlantic sector. Nature [J].2008,453 (7191):84-88.
[51]Koltunov A, Ustin S L, Asner G P, Fung I. Selective logging changes forest phenology in the Brazilian Amazon:Evidence from MODIS image time series analysis. Remote Sensing of Environment [J].2009,113 (11):2431-2440.
[52]Kosaka Y, Xie S-P. Recent global-warming hiatus tied to equatorial Pacific surface cooling. Nature [J].2013,501 (7467):403-407.
[53]Lane J E, Kruuk L E, Charmantier A, Murie J O, Dobson F S. Delayed phenology and reduced fitness associated with climate change in a wild hibernator. Nature [J].2012,489 (7417):554-557.
[54]Liu H, Tian F, Hu H, Hu H, Sivapalan M. Soil moisture controls on patterns of grass green-up in Inner Mongolia:an index based approach. Hydrology & Earth System Sciences [J].2013,17 (2):805-815.
[55]Loarie S R, Lobell D B, Asner G P, Mu Q, Field C B. Direct impacts on local climate of sugar-cane expansion in Brazil. Nature Climate Change [J].2011,1 (2):105-109.
[56]Lucht W, Prentice I C, Myneni R B, Sitch S, Friedlingstein P, Cramer W, Bousquet P, Buermann W, Smith B. Climatic Control of the High-Latitude Vegetation Greening Trend and Pinatubo Effect. Science [J].2002,296 (5573):1687-1689.
[57]Ma Z, Peng C, Zhu Q, Chen H, Yu G, Li W, Zhou X, Wang W, Zhang W. Regional drought-induced reduction in the biomass carbon sink of Canada's boreal forests. Proceedings of the National Academy of Sciences [J].2012,109 (7):2423-2427.
[58]Macias-Fauria M, Forbes B C, Zetterberg P, Kumpula T. Eurasian Arctic greening reveals teleconnections and the potential for structurally novel ecosystems. Nature Climate Change [J].2012,2(8):613-618.
[59]Mao D, Wang Z, Luo L, Ren C. Integrating AVHRR and MODIS data to monitor NDVI changes and their relationships with climatic parameters in Northeast China. International Journal of Applied Earth Observation and Geoinformation [J].2012,18:528-536.
[60]Mao J, Shi X, Thornton P E, Piao S, Wang X. Causes of spring vegetation growth trends in the northern mid-high latitudes from 1982 to 2004. Environmental Research Letters [J].2012, 7(1):014010.
[61]Meehl G A, Covey C, Taylor K E, Delworth T, Stouffer R J, Latif M, McAvaney B, Mitchell J F. The WCRP CMIP3 multimodel dataset:A new era in climate change research. Bulletin of the American Meteorological Society [J].2007,88 (9):1383-1394.
[62]Melaas E K, Friedl M A, Zhu Z. Detecting interannual variation in deciduous broadleaf forest phenology using Landsat TM/ETM+data. Remote Sensing of Environment [J].2013, 132:176-185.
[63]Mildrexler D J, Zhao M, Running S W. Testing a MODIS global disturbance index across North America. Remote Sensing of Environment [J].2009,113 (10):2103-2117.
[64]Mohammat A, Wang X, Xu X, Peng L, Yang Y, Zhang X, Myneni R B, Piao S. Drought and spring cooling induced recent decrease in vegetation growth in Inner Asia. Agricultural and Forest Meteorology [J].2013,178-179:21-30.
[65]Myneni R B, Keeling C, Tucker C, Asrar G, Nemani R. Increased plant growth in the northern high latitudes from 1981 to 1991. Nature [J].1997,386 (6626):698-702.
[66]Neil K L, Landrum L, Wu J. Effects of urbanization on flowering phenology in the metropolitan Phoenix region of USA:Findings from herbarium records. Journal of arid environments [J].2010,74 (4):440-444.
[67]Nemani R R, Keeling C D, Hashimoto H, Jolly W M, Piper S C, Tucker C J, Myneni R B, Running S W. Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science [J].2003,300 (5625):1560-1563.
[68]Neuheimer A, Thresher R, Lyle J, Semmens J. Tolerance limit for fish growth exceeded by warming waters. Nature Climate Change [J].2011,1 (2):110-113.
[69]Otto A, Otto F E, Boucher O, Church J, Hegerl G, Forster P M, Gillett N P, Gregory J, Johnson G C, Knutti R. Energy budget constraints on climate response. Nature Geoscience [J].2013,6:415-416.
[70]Pan Y, Li L, Zhang J, Liang S, Zhu X, Sulla-Menashe D. Winter wheat area estimation from MODIS-EVI time series data using the Crop Proportion Phenology Index. Remote Sensing of Environment [J].2012,119:232-242.
[71]Park H S, Sohn B J. Recent trends in changes of vegetation over East Asia coupled with temperature and rainfall variations. Journal of Geophysical Research:Atmospheres [J].2010, 115:D14101.
[72]Pearson R G, Phillips S J, Loranty M M, Beck P S, Damoulas T, Knight S J, Goetz S J. Shifts in Arctic vegetation and associated feedbacks under climate change. Nature Climate Change [J].2013,3 (7):673-677.
[73]Peng S, Chen A, Xu L, Cao C, Fang J, Myneni R B, Pinzon J E, Tucker C J, Piao S. Recent change of vegetation growth trend in China. Environmental Research Letters [J].2011,6 (4):044027.
[74]Peng S, Piao S, Ciais P, Fang J, Wang X. Change in winter snow depth and its impacts on vegetation in China. Global change biology [J].2010,16 (11):3004-3013.
[75]Peng S, Piao S, Ciais P, Friedlingstein P, Zhou L, Wang T. Change in snow phenology and its potential feedback to temperature in the Northern Hemisphere over the last three decades. Environmental Research Letters [J].2013,8 (1):014008.
[76]Piao S, Ciais P, Friedlingstein P, Peylin P, Reichstein M, Luyssaert S, Margolis H, Fang J, Barr A, Chen A. Net carbon dioxide losses of northern ecosystems in response to autumn warming. Nature [J].2008,451 (7174):49-52.
[77]Piao S, Cui M, Chen A, Wang X, Ciais P, Liu J, Tang Y. Altitude and temperature dependence of change in the spring vegetation green-up date from 1982 to 2006 in the Qinghai-Xizang Plateau. Agricultural and Forest Meteorology [J].2011a,151 (12):1599-1608.
[78]Piao S, Fang J, Zhou L, Ciais P, Zhu B. Variations in satellite-derived phenology in China's temperate vegetation. Global Change Biology [J].2006a,12 (4):672-685.
[79]Piao S, Fang J, Zhou L, Guo Q, Henderson M, Ji W, Li Y, Tao S. Interannual variations of monthly and seasonal normalized difference vegetation index (NDVI) in China from 1982 to 1999. Journal of Geophysical Research:Atmospheres (1984-2012) [J].2003,108:D144401.
[80]Piao S, Fang J, Zhou L, Zhu B, Tan K, Tao S. Changes in vegetation net primary productivity from 1982 to 1999 in China. Global Biogeochemical Cycles [J].2005,19 (2):GB2027.
[81]Piao S, Friedlingstein P, Ciais P, Zhou L, Chen A. Effect of climate and CO2 changes on the greening of the Northern Hemisphere over the past two decades. Geophysical Research Letters [J].2006b,33 (23):L23402.
[82]Piao S, Wang X, Ciais P, Zhu B, Wang T, Liu J. Changes in satellite-derived vegetation growth trend in temperate and boreal Eurasia from 1982 to 2006. Global Change Biology [J].2011b,17 (10):3228-3239.
[83]Pinzon J E, Brown M E, Tucker C J (2005) Hilbert-Huang transform and its applications[M]. In N.E. Huang (Ed.), Interdisciplinary mathematical sciences v.5 (pp. xii,311 p.). Singapore; Hackensack, NJ; London:World Scientific.
[84]Pongratz J, Lobell D, Cao L, Caldeira K. Crop yields in a geoengineered climate. Nature Climate Change [J].2012,2 (2):101-105.
[85]Pope K S, Dose V, Da Silva D, Brown P H, Leslie C A, DeJong T M. Detecting nonlinear response of spring phenology to climate change by Bayesian analysis. Global change biology [J].2013,19(5):1518-1525.
[86]Post E, Bhatt U S, Bitz C M, Brodie J F, Fulton T L, Hebblewhite M, Kerby J, Kutz S J, Stirling I, Walker D A. Ecological consequences of sea-ice decline. Science [J].2013,341 (6145):519-524.
[87]Pringle M, Denham R, Devadas R. Identification of cropping activity in central and southern Queensland, Australia, with the aid of MODIS MOD13Q1 imagery. International Journal of Applied Earth Observation and Geoinformation [J].2012,19:276-285.
[88]Reed B C, Brown J F, VanderZee D, Loveland T R, Merchant J W, Ohlen D O. Measuring phenological variability from satellite imagery. Journal of Vegetation Science [J].1994,5 (5):703-714.
[89]Roemmich D, Gould W J, Gilson J.135 years of global ocean warming between the Challenger expedition and the Argo Programme. Nature Climate Change [J].2012,2 (6):425-428.
[90]Rowlands D J, Frame D J, Ackerley D, Aina T, Booth B B, Christensen C, Collins M, Faull N, Forest C E, Grandey B S. Broad range of 2050 warming from an observationally constrained large climate model ensemble. Nature Geoscience [J].2012,5 (4):256-260.
[91]Sakamoto T, Gitelson A A, Arkebauer T J. MODIS-based corn grain yield estimation model incorporating crop phenology information. Remote Sensing of Environment [J].2013, 131:215-231.
[92]Saleska S R, Didan K, Huete A R, Da Rocha H R. Amazon forests green-up during 2005 drought. Science [J].2007,318 (5850):612-612.
[93]Sankey J B, Wallace C S, Ravi S. Phenology-based, remote sensing of post-burn disturbance windows in rangelands. Ecological Indicators [J].2013,30:35-44.
[94]Savitzky A, Golay M J. Smoothing and differentiation of data by simplified least squares procedures. Analytical chemistry [J].1964,36 (8):1627-1639.
[95]Shen M, Tang Y, Chen J, Zhu X, Zheng Y. Influences of temperature and precipitation before the growing season on spring phenology in grasslands of the central and eastern Qinghai-Tibetan Plateau. Agricultural and Forest Meteorology [J].2011,151 (12):1711-1722.
[96]Sjostrom M, Ardo J, Arneth A, Boulain N, Cappelaere B, Eklundh L, De Grandcourt A, Kutsch W, Merbold L, Nouvellon Y. Exploring the potential of MODIS EVI for modeling gross primary production across African ecosystems. Remote sensing of environment [J].2011,115 (4):1081-1089.
[97]Solano R, Didan K, Jacobson A, Huete A. MODIS vegetation indices (MOD 13) C5 user's guide. [J].2010, (Available at:):http://vip.arizona.edu/MODIS_UsersGuide.php.
[98]Song Q, Lin H, Zhang Y, Tan Z, Zhao J, Zhao J, Zhang X, Zhou W, Yu L, Yang L. The effect of drought stress on self-organisation in a seasonal tropical rainforest. Ecological Modelling [J].2013,265:136-139.
[99]Song Y, Achberger C, Linderholm H W. Rain-season trends in precipitation and their effect in different climate regions of China during 1961-2008. Environmental Research Letters [J].2011,6(3):034025.
[100]Soudani K, Hmimina G, Delpierre N, Pontailler J-Y, Aubinet M, Bonal D, Caquet B, De Grandcourt A, Burban B, Flechard C. Ground-based Network of NDVI measurements for tracking temporal dynamics of canopy structure and vegetation phenology in different biomes. Remote Sensing of Environment [J].2012,123:234-245.
[101]Stefanon M, Drobinski P, D'Andrea F, Noblet-Ducoudre N. Effects of interactive vegetation phenology on the 2003 summer heat waves. Journal of Geophysical Research: Atmospheres (1984-2012) [J].2012,117:D24103.
[102]Steven M D, Malthus T J, Baret F, Xu H, Chopping M J. Intercalibration of vegetation indices from different sensor systems. Remote Sensing of Environment [J].2003,88 (4):412-422.
[103]Sun Y, Gu L, Dickinson R E, Zhou B. Forest greenness after the massive 2008 Chinese ice storm:integrated effects of natural processes and human intervention. Environmental Research Letters [J].2012,7 (3):035702.
[104]Sutton R T, Dong B. Atlantic Ocean influence on a shift in European climate in the 1990s. Nature Geoscience [J].2012,5 (11):788-792.
[105]Toms J D, Lesperance M L. Piecewise regression:a tool for identifying ecological thresholds. Ecology [J].2003,84 (8):2034-2041.
[106]Tucker C J, Pinzon J E, Brown M E, Slayback D A, Pak E W, Mahoney R, Vermote E F, El Saleous N. An extended AVHRR 8-km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data. International Journal of Remote Sensing [J].2005,26 (20):4485-4498.
[107]Van Mantgem P J, Stephenson N L, Byrne J C, Daniels L D, Franklin J F, Fule P Z, Harmon M E, Larson A J, Smith J M, Taylor A H. Widespread increase of tree mortality rates in the western United States. Science [J].2009,323 (5913):521-524.
8] Verbesselt J, Hyndman R, Zeileis A, Culvenor D. Phenological change detection while accounting for abrupt and gradual trends in satellite image time series. Remote Sensing of Environment [J].2010,114 (12):2970-2980.
9] Walker D A, Epstein H E, Raynolds M K, Kuss P, Kopecky M A, Frost G V, Daniels F J A, Leibman M O, Moskalenko N G, Matyshak G V, Khitun O V, Khomutov A V, Forbes B C, Bhatt U S, Kade A N, Vonlanthen C M, Tichy L. Environment, vegetation and greenness (NDVI) along the North America and Eurasia Arctic transects. Environmental Research Letters [J].2012,7 (1):015504.
0] Walker J, De Beurs K, Wynne R, Gao F. Evaluation of Landsat and MODIS data fusion products for analysis of dryland forest phenology. Remote Sensing of Environment [J].2012, 117:381-393.
1] Wang H, Ma M, Wang X, Yuan W, Song Y, Tan J, Huang G. Seasonal variation of vegetation productivity over an alpine meadow in the Qinghai-Tibet Plateau in China: modeling the interactions of vegetation productivity, phenology, and the soil freeze-thaw process. Ecological research [J].2013,28 (2):271-282.
2] Wang X, Piao S, Ciais P, Li J, Friedlingstein P, Koven C, Chen A. Spring temperature change and its implication in the change of vegetation growth in North America from 1982 to 2006. Proceedings of the National Academy of Sciences [J].2011,108 (4):1240-1245.
3] Warren R, VanDerWal J, Price J, Welbergen J, Atkinson I, Ramirez-Villegas J, Osborn T, Jarvis A, Shoo L, Williams S. Quantifying the benefit of early climate change mitigation in avoiding biodiversity loss. Nature Climate Change [J].2013,3:678-682.
4] White M A, Thornton P E, Running S W. A continental phenology model for monitoring vegetation responses to interannual climatic variability. Global biogeochemical cycles [J].1997,11 (2):217-234.
5] Wu C, Munger J W, Niu Z, Kuang D. Comparison of multiple models for estimating gross primary production using MODIS and eddy covariance data in Harvard Forest. Remote Sensing of Environment [J].2010,114(12):2925-2939.
[116]Wu X, Liu H. Consistent shifts in spring vegetation green-up date across temperate biomes in China,1982-2006. Global change biology [J].2013,19 (3):870-880.
[117]Wu Z, Wu J, Liu J, He B, Lei T, Wang Q. Increasing terrestrial vegetation activity of ecological restoration program in the Beijing-Tianjin sand source region of China. Ecological Engineering [J].2013,52:37-50.
[118]Xiao X, Braswell B, Zhang Q, Boles S, Frolking S, Moore III B. Sensitivity of vegetation indices to atmospheric aerosols:continental-scale observations in Northern Asia. Remote Sensing of Environment [J].2003,84 (3):385-392.
[119]Xu X, Piao S, Wang X, Chen A, Ciais P, Myneni R B. Spatio-temporal patterns of the area experiencing negative vegetation growth anomalies in China over the last three decades. Environmental Research Letters [J].2012,7 (3):035701.
[120]Xue Y, Liu S, Zhang L, Hu Y. Integrating fuzzy logic with piecewise linear regression for detecting vegetation greenness change in the Yukon River Basin, Alaska. International Journal of Remote Sensing [J].2013,34 (12):4242-4263.
[121]Yu F, Price K P, Ellis J, Shi P. Response of seasonal vegetation development to climatic variations in eastern central Asia. Remote Sensing of Environment [J].2003,87 (1):42-54.
[122]Yu H, Xu J, Okuto E, Luedeling E. Seasonal response of grasslands to climate change on the Tibetan Plateau. PloS one [J].2012,7 (11):e49230.
[123]Yu Z, Liu S, Wang J, Sun P, Liu W, Hartley D S. Effects of seasonal snow on the growing season of temperate vegetation in China. Global change biology [J].2013,19 (7):2182-2195.
[124]Zeng H, Jia G, Epstein H. Recent changes in phenology over the northern high latitudes detected from multi-satellite data. Environmental Research Letters [J].2011,6 (4):045508.
[125]Zeng H, Jia G, Forbes B C. Shifts in Arctic phenology in response to climate and anthropogenic factors as detected from multiple satellite time series. Environmental Research Letters [J].2013,8 (3):035036.
126] Zhang K, Kimball J S, Hogg E H, Zhao M, Oechel W C, Cassano J J, Running S W. Satellite-based model detection of recent climate-driven changes in northern high-latitude vegetation productivity. Journal of Geophysical Research:Biogeosciences [J].2008,113 (G3):G03033.
127] Zhang L, Xiao J, Li J, Wang K, Lei L, Guo H. The 2010 spring drought reduced primary productivity in southwestern China. Environmental Research Letters [J].2012,7 (4):045706.
128] Zhang X, Friedl M A, Schaaf C B, Strahler A H, Hodges J C, Gao F, Reed B C, Huete A. Monitoring vegetation phenology using MODIS. Remote sensing of environment [J].2003, 84 (3):471-475.
129] Zhang X, Goldberg M, Tarpley D, Friedl M A, Morisette J, Kogan F, Yu Y. Drought-induced vegetation stress in southwestern North America. Environmental Research Letters [J].2010,5 (2):024008.
130] Zhang X, Tang Q, Zheng J, Ge Q. Warming/cooling effects of cropland greenness changes during 1982-2006 in the North China Plain. Environmental Research Letters [J].201.3,8 (2):024038.
131] Zhang Y, Gao J, Liu L, Wang Z, Ding M, Yang X. NDVI-based vegetation changes and their responses to climate change from 1982 to 2011:A case study in the Koshi River Basin in the middle Himalayans. Global and Planetary Change [J].2013,108:139-148.
132] Zhao M, Running S W. Drought-induced reduction in global terrestrial net primary production from 2000 through 2009. Science [J].2010,329 (5994):940-943.
133] Zhou L, Kaufinann R, Tian Y, Myneni R, Tucker C. Relation between interannual variations in satellite measures of northern forest greenness and climate between 1982 and 1999. Journal of Geophysical Research [J].2003,108 (D1):4004.
134] Zhou L, Tucker C J, Kaufmann R K, Slayback D, Shabanov N V, Myneni R B. Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999. Journal of Geophysical Research:Atmospheres (1984-2012) [J].2001,106 (D17):20069-20083.
[135]Zhu W, Tian H, Xu X, Pan Y, Chen G, Lin W. Extension of the growing season due to delayed autumn over mid and high latitudes in North America during 1982-2006. Global Ecology and Biogeography [J].2012,21 (2):260-271.
[136]安佑志,刘朝顺,施润和,高炜,殷杰.基于MODIS时序数据的长江三角洲地区植被覆盖时空变化分析.生态环境学报[J].2012,21(12)：1923-1927.
[137]边金虎,李爱农,宋孟强,马利群,蒋锦刚.MODIS植被指数时间序列Savitzky-Golay滤波算法重构.遥感学报[J].2010,14(4)：725-741.
[138]陈军,王玉辉.1956-2009年内蒙古苏尼特左旗荒漠草原的降水格局.生态学报[J].2012,32(22)：6925-6935.
[139]陈莉,方丽娟,李帅.东北地区近50年农作物生长季干旱趋势研究.灾害学[J].2010,25(4)：5-10.
[140]陈效逑,喻蓉.1982～1999年我国东部暖温带植被生长季节的时空变化.地理学报[J].2007,62(1)：41-51.
[141]戴君虎,王焕炯,葛全胜.近50年中国温带季风区植物花期春季霜冻风险变化.地理学报[J].2013,68(5)：593-601.
[142]方精云,朴世龙,贺金生,马文红.近20年来中国植被活动在增强.中国科学(C辑)[J].2003,33(6)：554-565.
[143]葛全胜,王芳,王绍武,程邦波.对全球变暖认识的七个问题的确定与不确定性.中国·人口资源与环境[J].2014,24(1)：1-6.
[144]郭江勇,林纾,万莉莉.500hPa高度场对西北地区秋季降水的影响分析.资源科学[J].2009,31(10)：1749-1754.
[145]国志兴,张晓宁,王宗明,方伟华.东北地区植被物候对气候变化的响应.生态学杂志[J].2010,29(3)：578-585.
[146]何月,张小伟,李仁忠,樊高峰,蔡菊珍.浙江省作物多熟种植制度遥感反演及其时空格局.生态学杂志[J].2011,30(12)：2827-2835.
[147]黄森旺,李晓松,吴炳方,裴亮.近25年三北防护林工程区土地退化及驱动力分析.地理学报[J].2012,67(5)：589-598.
[148]李杭燕,马明国,谭俊磊.时序NDVI数据集重建综合方法研究.遥感技术与应用[J].2010,25(6)：891-896.
[149]李洪权,范广洲,周定文,华维,刘雅勤,李学敏.青藏高原春季植被变化特征及其对夏季气温的影响.地理科学[J].2008,28(2)：259-265.
[150]李敏敏,延军平.华北段农牧交错带气候变化特征及其响应.干旱区资源与环境[J].2013,27(5)：100-106.
[151]李明,吴正方,杜海波,宗盛伟,孟祥君,张莲芝.基于遥感方法的长白山地区植被物候期变化趋势研究.地理科学[J].2011,31(10)：1242-1248.
[152]李荣平,周广胜.1980-2005年中国东北木本植物物候特征及其对气温的响应.生态学杂志[J].2010,29(12)：2317-2326.
[153]李月臣,宫鹏,刘春霞,陈晋,于德永.北方13省1982-1999年植被变化及其与气候因子的关系.资源科学[J].2006,28(2)：109-117.
[154]梁爽,彭书时,林鑫,丛楠.1982-2010年全国草地生长时空变化.北京大学学报(自然科学版)[J].2013,49(2)：311-320.
[155]刘海文，周天军,朱玉祥,林一骅.东亚夏季风自20世纪90年代初开始恢复增强.科学通报[J].2012,57(9)：765-769.
[156]刘抗,李照荣,张宇.1971-2010年中国西北地区秋季降水变化特征.中国沙漠[J].2014,34(3¨-9.
[157]刘丽娟,庞勇,范文义,李增元,李明泽.基于时间序列MODISEVI数据的森林生长异常监测.林业科学[J].2012,48(2)：54-62.
[158]刘玲玲,刘良云,胡勇.1982-2006年欧亚大陆植被生长季开始时间遥感监测分析.地理科学进展[J].2012,31(11)：1433-1442.
[159]刘亚南,潘志华,李超,安萍莉,潘学标.近50年北方农牧交错带气候月季变化和空间分布规律.中国农业大学学报[J].2012,17(4)：96-102.
[160]马建勇,潘婕,许吟隆,姜江SRESAIB情景下东北地区未来干旱趋势预估.干旱区研究[J].2013,30(2)：329-335.
[161]毛睿,龚道溢,Chen D欧亚大陆春季植被状况与东亚夏季大气环流的显著联系.气象学报 [J].2008,66(4)：592-598.
[162]潘耀忠,李乐,张锦水,梁顺林,侯东.基于典型物候特征的MODIS-EVI时间序列数据农作物种植面积提取方法一小区域冬小麦实验研究.遥感学报[J].2011,15(3)：578-594.
[163]朴世龙,方精云.1982-1999年我国陆地植被活动对气候变化响应的季节差异.地理学报[J].2003,58(1)：119-125.
[164]邱海军,曹明明.基于SPOT VEGETATION数据的中国植被覆盖时空变化分析.资源科学[J].2011,33(2)：335-340.
[165]沈柏竹,廉毅,杨涵洧,张世轩.中国东北夏季温度年代际变化特征.地理科学[J].2012,32(6)：739-745.
[166]施雅风,沈永平,李栋梁,张国威,丁永建,胡汝骥,康尔泗.中国西北气候由暖干向暖湿转型的特征和趋势探讨.第四纪研究[J].2003,23(2)：152-164.
[167]孙华生,黄敬峰,彭代亮.利用MODIS数据识别水稻关键生长发育期.遥感学报[J].2009,13(6)：1122-1137.
[168]孙艳玲,郭鹏.1982-2006年华北植被覆盖变化及其与气候变化的关系.生态环境学报[J].2012,21(1)：7-12.
[169]王宏,李晓兵,李霞,莺歌,符娜.基于NOAANDVI和MSAVⅠ研究中国北方植被生长季变化.生态学报[J].2007,27(2)：504-515.
[170]王焕炯,戴君虎,葛全胜.1952～2007年中国白蜡树春季物候时空变化分析.中国科学：地球科学[J].2012,42(5)：701-710.
[171]王少鹏,王志恒,朴世龙,方精云.我国40年来增温时间存在显著的区域差异.科学通报[J].2010,55(16)：1538-1543.
[172]王晓爽,胡卓玮,赵文吉,刘洪岐.基于EVI植被指数的大尺度草地多源信息综合分类研究.草业科学[J].2011,28(1)：10.
[173]王宗明,国志兴,宋开山,罗玲,张柏,刘殿伟,黄妮,任春颖.中国东北地区植被NDVI对气候变化的响应.生态学杂志[J].2009,28(6)：1041-1048.
[174]吴文斌,杨鹏,唐华俊,周清波,张莉,唐鹏钦.过去20年中国耕地生长季起始期的时空变化.生态学报[J].2009,29(4)：1777-1786.
[175]武永峰,李茂松,刘布春,白文波,蒋卫国.基于NOAA NDVI的中国植被绿度始期变化.地理科学进展[J].2008,27(6)：32-40.
[176]袭祝香,杨雪艳,刘实,纪玲玲.东北地区夏季干旱风险评估与区划.地理科学[J].2013,33(6)：735-740.
[177]信忠保,许炯心,郑伟.气候变化和人类活动对黄土高原植被覆盖变化的影响.中国科学(D辑)[J]-007,37(11)：1504-1514.
[178]徐岩岩,张佳华,Limin Y.基于MODIS-EVI数据和Symlet11小波识别东北地区水稻主要物候期.生态学报[J].2012,32(7)：2091-2098.
[179]闫峰,王艳姣,吴波.近50年河北省干旱时空分布特征.地理研究[J].2010,29(3)：423-430.
[180]闫慧敏,肖向明,黄河清.黄淮海多熟种植农业区作物历遥感检测与时空特征.生态学报[J].2010,30(9)：2416-2423.
[181]闫娜,李登科,杜继稳,延军平.基于MODIS产品LST/NDVI/EVI的陕西旱情监测.自然灾害学报[J].2010,19(4)：178-182.
[182]颜梅春,张先聪，胡莎,王元超.基于MODIS数据的京津唐地区干旱监测研究.地理与地理信息科学[J].2012,28(2)：94-103.
[183]杨金虎,江志红,裴永成.欧亚大陆春季植被对同年中国西北夏季大气环流和气候的影响研究.冰川冻土[J].2011,33(5)：1014-1021.
[184]殷贺,李正国,王仰麟,蔡福.基于时间序列植被特征的内蒙古荒漠化评价.地理学报[J].2011,66(5)：653-661.
[185]于信芳,庄大方.基于MODIS NDVI数据的东北森林物候期监测.资源科学[J].2006,28(4)：111-117.
[186]张戈丽,陶健,董金玮,徐兴良.1960年-2010年内蒙古东部地区生长季变化分析.资源科学[J].2011a,33(12)：2323-2332.
[187]张戈丽,徐兴良,周才平,张宏斌,欧阳华.近30年来呼伦贝尔地区草地植被变化对气候变化的响应.地理学报[J].2011b,66(1)：47-58.
[188]张金龙,刘学锋,于长文.河北省干旱分布特征和变化规律分析.干旱区研究[J].2012,29(1)：41-46.
[189]张井勇,董文杰,叶笃正,符淙斌.中国植被覆盖对夏季气候影响的新证据.科学通报[J].2003,48(1)：91-95.
[190]张明伟,周清波,陈仲新,周勇,刘佳,蔡崇法.基于物候模型的作物种植面积变化监测方法.农业工程学报[J].2006,22(10)：139-144.
[191]张生军,王涛,王天明,卢爱刚,葛剑平.新疆不同植被NDVI的变化及其与气候因子的关系.草业科学[J].2009,26(5)：26-31.
[192]张钛仁,柴秀梅,李自珍.中国北方植被覆盖度特征及其与沙尘暴关系.高原气象[J].2010,29(1)：137-145.
[193]张伟,闫敏华,陈泮勤.松嫩平原近50年来生长季降水资源特征分析.干旱区资源与环境[J].2007,21(10)：73-78.
[194]张学珍,戴君虎,葛全胜.1982-2006年中国东部春季植被变化的区域差异.地理学报[J].2012,67(1)：53-61.
[195]张学珍,郑景云,何凡能,戴君虎.1982-2006年中国东部秋季植被覆盖变化过程的区域差异.自然资源学报[J].2013,28(1)：28-37.
[196]张延伟,魏文寿,姜逢清,刘明哲,王雯雯,白磊,韩茜,洪雯,陆恒,李雪梅.近50年新疆气温和降水量变化及其与NAO指数的交叉小波谱分析.高原气象[J].2012,31(4)：974-982.
[197]赵霞,谭琨,方精云.1982-2006年新疆植被活动的年际变化及其季节差异.干旱区研究[J].2011,28(1)：10-16.
[198]郑景云,葛全胜,郝志新.气候增暖对我国近40年植物物候变化的影响.科学通报[J].2002,47(20)：1582-1587.
[199]周峰,许有鹏,吕慧华.基于MODIS-EVI数据的长江三角洲地区植被变化的特征.长江流域资源与环境[J].2012,21(11)：1363-1369.
[200]朱大威,金之庆.气候及其变率变化对东北地区粮食生产的影响.作物学报[J].2008,34(9)：1588-1597.
[201]宗海锋,陈烈庭,张庆云ENSO与中国夏季降水年际变化关系的不稳定性特征.大气科学[J].2010,34(1)：184-192
[2]Altermatt F. Temperature-related shifts in butterfly phenology depend on the habitat. Global Change Biology [J].2012,18 (8):2429-2438.
[3]Bisigato A, Campanella M, Pazos G. Plant phenology as affected by land degradation in the arid Patagonian Monte, Argentina:A multivariate approach. Journal of Arid Environments [J].2013,91:79-87.
[4]Boschetti M, Nutini F, Brivio P A, Bartholome E, Stroppiana D, Hoscilo A. Identification of environmental anomaly hot spots in West Africa from time series of NDVI and rainfall. ISPRS Journal of Photogrammetry and Remote Sensing [J].2013,78:26-40.
[5]Brown J C, Kastens J H, Coutinho A C, Victoria D D C, Bishop C R. Classifying multiyear agricultural land use data from Mato Grosso using time-series MODIS vegetation index data. Remote Sensing of Environment [J].2013,130:39-50.
[6]Brown M E, de Beurs K, Vrieling A. The response of African land surface phenology to large scale climate oscillations. Remote Sensing of Environment [J].2010,114 (10):2286-2296.
[7]Buermann W, Bikash P R, Jung M, Burn D H, Reichstein M. Earlier springs decrease peak summer productivity in North American boreal forests. Environmental Research Letters [J].2013,8 (2):024027.
[8]Buyantuyev A, Wu J. Urbanization diversifies land surface phenology in arid environments: interactions among vegetation, climatic variation, and land use pattern in the Phoenix metropolitan region, USA. Landscape and Urban Planning [J].2012,105 (1):149-159.
[9]Chen X, Xu L. Temperature controls on the spatial pattern of tree phenology in China's temperate zone. Agricultural and Forest Meteorology [J].2012,154-155:195-202.
0] Ciais P, Reichstein M, Viovy N, Granier A, Ogee J, Allard V, Aubinet M, Buchmann N, Bernhofer C, Carrara A. Europe-wide reduction in primary productivity caused by the heat and drought in 2003. Nature [J].2005,437 (7058):529-533.
1] Cihlar J, Tcherednichenko I, Latifovic R, Li Z, Chen J. Impact of variable atmospheric water vapor content on AVHRR data corrections over land. IEEE Transactions on Geoscience and Remote Sensing [J].2001,39 (1):173-180.
2] Clark M L, Aide T M, Grau H R, Riner G. A scalable approach to mapping annual land cover at 250 m using MODIS time series data:A case study in the Dry Chaco ecoregion of South America. Remote Sensing of Environment [J].2010,114 (11):2816-2832.
3] Cleland E E, Chiariello N R, Loarie S R, Mooney H A, Field C B. Diverse responses of phenology to global changes in a grassland ecosystem. Proceedings of the National Academy of Sciences [J].2006,103 (37):13740-13744.
4] Cong N, Piao S, Chen A, Wang X, Lin X, Chen S, Han S, Zhou G, Zhang X. Spring vegetation green-up date in China inferred from SPOT NDVI data:a multiple model analysis. Agricultural and Forest Meteorology [J].2012,165:104-113.
5] Cong N, Wang T, Nan H, Ma Y, Wang X, Myneni R B, Piao S. Changes in satellite-derived spring vegetation green-up date and its linkage to climate in China from 1982 to 2010:a multimethod analysis. Global change biology [J].2013,19 (3):881-891.
6] Cook J, Nuccitelli D, Green S A, Richardson M, Winkler B, Painting R, Way R, Jacobs P, Skuce A. Quantifying the consensus on anthropogenic global warming in the scientific literature. Environmental Research Letters [J].2013,8 (2):024024.
7] Coops N C, Wulder M A, Iwanicka D. Large area monitoring with a MODIS-based Disturbance Index (DI) sensitive to annual and seasonal variations. Remote Sensing of Environment [J].2009,113 (6):1250-1261.
8] Cotton P A. Avian migration phenology and global climate change. Proceedings of the National Academy of Sciences [J].2003,100 (21):12219-12222.
9] Dai A. Characteristics and trends in various forms of the Palmer Drought Severity Index during 1900-2008. Journal of Geophysical Research:Atmospheres (1984-2012) [J].2011, 116:D12115.
[20]Dall'Olmo G, Karnieli A. Monitoring phenological cycles of desert ecosystems using NDVI and LST data derived from NOAA-AVHRR imagery. International Journal of Remote Sensing [J].2002,23 (19):4055-4071.
[21]De Jong R, de Bruin S, de Wit A, Schaepman M E, Dent D L. Analysis of monotonic greening and browning trends from global NDVI time-series. Remote Sensing of Environment [J].2011,115 (2):692-702.
[22]De Jong R, Verbesselt J, Zeileis A, Schaepman M E. Shifts in Global Vegetation Activity Trends. Remote Sensing [J].2013,5 (3):1117-1133.
[23]Dragoni D, Rahman A F. Trends in fall phenology across the deciduous forests of the Eastern USA. Agricultural and Forest Meteorology [J].2012,157:96-105.
[24]Dutrieux L P, Bartholomeus H, Herold M, Verbesselt J. Relationships between declining summer sea ice, increasing temperatures and changing vegetation in the Siberian Arctic tundra from MODIS time series (2000-11). Environmental Research Letters [J].2012,7 (4):044028.
[25]Epstein H E, Myers-Smith I, Walker D A. Recent dynamics of arctic and sub-arctic vegetation. Environmental Research Letters [J].2013,8 (1):015040.
[26]Fensholt R, Langanke T, Rasmussen K, Reenberg A, Prince S D, Tucker C, Scholes R J, Le Q B, Bondeau A, Eastman R. Greenness in semi-arid areas across the globe 1981-2007-An Earth Observing Satellite based analysis of trends and drivers. Remote Sensing of Environment [J].2012,121:144-158.
[27]Fensholt R, Proud S R. Evaluation of earth observation based global long term vegetation trends-Comparing GIMMS and MODIS global NDVI time series. Remote sensing of Environment [J].2012,119:131-147.
[28]Gao J, Liu Y. Climate warming and land use change in Heilongjiang Province, Northeast China. Applied Geography [J].2011,31 (2):476-482.
[29]Gillett N P, Arora V K, Zickfeld K, Marshall S J, Merryfield W J. Ongoing climate change following a complete cessation of carbon dioxide emissions. Nature Geoscience [J].2011,4 (2):83-87.
[30]Goetz S J, Bunn A G, Fiske G J, Houghton R A. Satellite-observed photosynthetic trends across boreal North America associated with climate and fire disturbance. Proceedings of the National Academy of Sciences of the United States of America [J].2005,102 (38):13521-13525.
[31]Gong D Y, Ho C H. Detection of large-scale climate signals in spring vegetation index (normalized difference vegetation index) over the Northern Hemisphere. Journal of Geophysical Research:Atmospheres [J].2003,108 (D16):4498.
[32]Han S, Yang Z. Cooling effect of agricultural irrigation over Xinjiang, Northwest China from 1959 to 2006. Environmental Research Letters [J].2013,8 (2):024039.
[33]H?gda K A, T?mmervik H, Karlsen S R. Trends in the Start of the Growing Season in Fennoscandia 1982-2011. Remote Sensing [J].2013,5 (9):4304-4318.
[34]Holland D M, Thomas R H, De Young B, Ribergaard M H, Lyberth B. Acceleration of Jakobshavn Isbrae triggered by warm subsurface ocean waters. Nature Geoscience [J].2008, 1 (10):659-664.
[35]Huete A, Didan K, Miura T, Rodriguez E P, Gao X, Ferreira L G. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote sensing of environment [J].2002,83 (1):195-213.
[36]Hufkens K, Friedl M A, Keenan T F, Sonnentag O, Bailey A, O'Keefe J, Richardson A D. Ecological impacts of a widespread frost event following early spring leaf-out. Global Change Biology [J].2012,18 (7):2365-2377.
[37]IPCC. Climate Change 2013. The Physical Science Basis [M]. Cambridge University Press, Cambridge, UK,2013.
[38]Ivits E, Cherlet M, Sommer S, Mehl W. Addressing the complexity in non-linear evolution of vegetation phenological change with time-series of remote sensing images. Ecological Indicators [J].2013,26:49-60.
[39]James M, Kalluri S N. The Pathfinder AVHRR land data set:An improved coarse resolution data set for terrestrial monitoring. International Journal of Remote Sensing [J].1994,15 (17):3347-3363.
[40]Jeong S J, Ho C H, Gim H J, Brown M E. Phenology shifts at start vs. end of growing season in temperate vegetation over the Northern Hemisphere for the period 1982-2008. Global Change Biology [J].2011,17 (7):2385-2399.
[41]Jeong S J, Ho C H, Kim B M, Feng S, Medvigy D. Non-linear response of vegetation to coherent warming over northern high latitudes. Remote Sensing Letters [J].2013,4 (2):123-130.
[42]Jiang B, Liang S. Improved vegetation greenness increases summer atmospheric water vapor over Northern China. Journal of Geophysical Research:Atmospheres [J].2013,118 (15):8129-8139.
[43]Jiang Z, Huete A R, Didan K, Miura T. Development of a two-band enhanced vegetation index without a blue band. Remote Sensing of Environment [J].2008,112 (10):3833-3845.
[44]John R, Chen J, Lu N, Wilske B. Land cover/land use change in semi-arid Inner Mongolia: 1992-2004. Environmental Research Letters [J].2009,4 (4):045010.
[45]Jones M O, Jones L A, Kimball J S, McDonald K C. Satellite passive microwave remote sensing for monitoring global land surface phenology. Remote Sensing of Environment [J].2011,115 (4):1102-1114.
[46]Jones M O, Kimball J S, Jones L A, McDonald K C. Satellite passive microwave detection of North America start of season. Remote Sensing of Environment [J].2012,123:324-333.
[47]Jong R, Verbesselt J, Schaepman M E, Bruin S. Trend changes in global greening and browning:contribution of short-term trends to longer-term change. Global Change Biology [J].2012,18 (2):642-655.
[48]Joshi M, Sutton R, Lowe J, Frame D. Projections of when temperature change will exceed 2 [deg] C above pre-industrial levels. Nature Climate Change [J].2011,1 (8):407-412.
[49]Katsman C, van Oldenborgh G J. Tracing the upper ocean's "missing heat". Geophysical Research Letters [J].2011,38 (14):L14610.
[50]Keenlyside N, Latif M, Jungclaus J, Kornblueh L, Roeckner E. Advancing decadal-scale climate prediction in the North Atlantic sector. Nature [J].2008,453 (7191):84-88.
[51]Koltunov A, Ustin S L, Asner G P, Fung I. Selective logging changes forest phenology in the Brazilian Amazon:Evidence from MODIS image time series analysis. Remote Sensing of Environment [J].2009,113 (11):2431-2440.
[52]Kosaka Y, Xie S-P. Recent global-warming hiatus tied to equatorial Pacific surface cooling. Nature [J].2013,501 (7467):403-407.
[53]Lane J E, Kruuk L E, Charmantier A, Murie J O, Dobson F S. Delayed phenology and reduced fitness associated with climate change in a wild hibernator. Nature [J].2012,489 (7417):554-557.
[54]Liu H, Tian F, Hu H, Hu H, Sivapalan M. Soil moisture controls on patterns of grass green-up in Inner Mongolia:an index based approach. Hydrology & Earth System Sciences [J].2013,17 (2):805-815.
[55]Loarie S R, Lobell D B, Asner G P, Mu Q, Field C B. Direct impacts on local climate of sugar-cane expansion in Brazil. Nature Climate Change [J].2011,1 (2):105-109.
[56]Lucht W, Prentice I C, Myneni R B, Sitch S, Friedlingstein P, Cramer W, Bousquet P, Buermann W, Smith B. Climatic Control of the High-Latitude Vegetation Greening Trend and Pinatubo Effect. Science [J].2002,296 (5573):1687-1689.
[57]Ma Z, Peng C, Zhu Q, Chen H, Yu G, Li W, Zhou X, Wang W, Zhang W. Regional drought-induced reduction in the biomass carbon sink of Canada's boreal forests. Proceedings of the National Academy of Sciences [J].2012,109 (7):2423-2427.
[58]Macias-Fauria M, Forbes B C, Zetterberg P, Kumpula T. Eurasian Arctic greening reveals teleconnections and the potential for structurally novel ecosystems. Nature Climate Change [J].2012,2(8):613-618.
[59]Mao D, Wang Z, Luo L, Ren C. Integrating AVHRR and MODIS data to monitor NDVI changes and their relationships with climatic parameters in Northeast China. International Journal of Applied Earth Observation and Geoinformation [J].2012,18:528-536.
[60]Mao J, Shi X, Thornton P E, Piao S, Wang X. Causes of spring vegetation growth trends in the northern mid-high latitudes from 1982 to 2004. Environmental Research Letters [J].2012, 7(1):014010.
[61]Meehl G A, Covey C, Taylor K E, Delworth T, Stouffer R J, Latif M, McAvaney B, Mitchell J F. The WCRP CMIP3 multimodel dataset:A new era in climate change research. Bulletin of the American Meteorological Society [J].2007,88 (9):1383-1394.
[62]Melaas E K, Friedl M A, Zhu Z. Detecting interannual variation in deciduous broadleaf forest phenology using Landsat TM/ETM+data. Remote Sensing of Environment [J].2013, 132:176-185.
[63]Mildrexler D J, Zhao M, Running S W. Testing a MODIS global disturbance index across North America. Remote Sensing of Environment [J].2009,113 (10):2103-2117.
[64]Mohammat A, Wang X, Xu X, Peng L, Yang Y, Zhang X, Myneni R B, Piao S. Drought and spring cooling induced recent decrease in vegetation growth in Inner Asia. Agricultural and Forest Meteorology [J].2013,178-179:21-30.
[65]Myneni R B, Keeling C, Tucker C, Asrar G, Nemani R. Increased plant growth in the northern high latitudes from 1981 to 1991. Nature [J].1997,386 (6626):698-702.
[66]Neil K L, Landrum L, Wu J. Effects of urbanization on flowering phenology in the metropolitan Phoenix region of USA:Findings from herbarium records. Journal of arid environments [J].2010,74 (4):440-444.
[67]Nemani R R, Keeling C D, Hashimoto H, Jolly W M, Piper S C, Tucker C J, Myneni R B, Running S W. Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science [J].2003,300 (5625):1560-1563.
[68]Neuheimer A, Thresher R, Lyle J, Semmens J. Tolerance limit for fish growth exceeded by warming waters. Nature Climate Change [J].2011,1 (2):110-113.
[69]Otto A, Otto F E, Boucher O, Church J, Hegerl G, Forster P M, Gillett N P, Gregory J, Johnson G C, Knutti R. Energy budget constraints on climate response. Nature Geoscience [J].2013,6:415-416.
[70]Pan Y, Li L, Zhang J, Liang S, Zhu X, Sulla-Menashe D. Winter wheat area estimation from MODIS-EVI time series data using the Crop Proportion Phenology Index. Remote Sensing of Environment [J].2012,119:232-242.
[71]Park H S, Sohn B J. Recent trends in changes of vegetation over East Asia coupled with temperature and rainfall variations. Journal of Geophysical Research:Atmospheres [J].2010, 115:D14101.
[72]Pearson R G, Phillips S J, Loranty M M, Beck P S, Damoulas T, Knight S J, Goetz S J. Shifts in Arctic vegetation and associated feedbacks under climate change. Nature Climate Change [J].2013,3 (7):673-677.
[73]Peng S, Chen A, Xu L, Cao C, Fang J, Myneni R B, Pinzon J E, Tucker C J, Piao S. Recent change of vegetation growth trend in China. Environmental Research Letters [J].2011,6 (4):044027.
[74]Peng S, Piao S, Ciais P, Fang J, Wang X. Change in winter snow depth and its impacts on vegetation in China. Global change biology [J].2010,16 (11):3004-3013.
[75]Peng S, Piao S, Ciais P, Friedlingstein P, Zhou L, Wang T. Change in snow phenology and its potential feedback to temperature in the Northern Hemisphere over the last three decades. Environmental Research Letters [J].2013,8 (1):014008.
[76]Piao S, Ciais P, Friedlingstein P, Peylin P, Reichstein M, Luyssaert S, Margolis H, Fang J, Barr A, Chen A. Net carbon dioxide losses of northern ecosystems in response to autumn warming. Nature [J].2008,451 (7174):49-52.
[77]Piao S, Cui M, Chen A, Wang X, Ciais P, Liu J, Tang Y. Altitude and temperature dependence of change in the spring vegetation green-up date from 1982 to 2006 in the Qinghai-Xizang Plateau. Agricultural and Forest Meteorology [J].2011a,151 (12):1599-1608.
[78]Piao S, Fang J, Zhou L, Ciais P, Zhu B. Variations in satellite-derived phenology in China's temperate vegetation. Global Change Biology [J].2006a,12 (4):672-685.
[79]Piao S, Fang J, Zhou L, Guo Q, Henderson M, Ji W, Li Y, Tao S. Interannual variations of monthly and seasonal normalized difference vegetation index (NDVI) in China from 1982 to 1999. Journal of Geophysical Research:Atmospheres (1984-2012) [J].2003,108:D144401.
[80]Piao S, Fang J, Zhou L, Zhu B, Tan K, Tao S. Changes in vegetation net primary productivity from 1982 to 1999 in China. Global Biogeochemical Cycles [J].2005,19 (2):GB2027.
[81]Piao S, Friedlingstein P, Ciais P, Zhou L, Chen A. Effect of climate and CO2 changes on the greening of the Northern Hemisphere over the past two decades. Geophysical Research Letters [J].2006b,33 (23):L23402.
[82]Piao S, Wang X, Ciais P, Zhu B, Wang T, Liu J. Changes in satellite-derived vegetation growth trend in temperate and boreal Eurasia from 1982 to 2006. Global Change Biology [J].2011b,17 (10):3228-3239.
[83]Pinzon J E, Brown M E, Tucker C J (2005) Hilbert-Huang transform and its applications[M]. In N.E. Huang (Ed.), Interdisciplinary mathematical sciences v.5 (pp. xii,311 p.). Singapore; Hackensack, NJ; London:World Scientific.
[84]Pongratz J, Lobell D, Cao L, Caldeira K. Crop yields in a geoengineered climate. Nature Climate Change [J].2012,2 (2):101-105.
[85]Pope K S, Dose V, Da Silva D, Brown P H, Leslie C A, DeJong T M. Detecting nonlinear response of spring phenology to climate change by Bayesian analysis. Global change biology [J].2013,19(5):1518-1525.
[86]Post E, Bhatt U S, Bitz C M, Brodie J F, Fulton T L, Hebblewhite M, Kerby J, Kutz S J, Stirling I, Walker D A. Ecological consequences of sea-ice decline. Science [J].2013,341 (6145):519-524.
[87]Pringle M, Denham R, Devadas R. Identification of cropping activity in central and southern Queensland, Australia, with the aid of MODIS MOD13Q1 imagery. International Journal of Applied Earth Observation and Geoinformation [J].2012,19:276-285.
[88]Reed B C, Brown J F, VanderZee D, Loveland T R, Merchant J W, Ohlen D O. Measuring phenological variability from satellite imagery. Journal of Vegetation Science [J].1994,5 (5):703-714.
[89]Roemmich D, Gould W J, Gilson J.135 years of global ocean warming between the Challenger expedition and the Argo Programme. Nature Climate Change [J].2012,2 (6):425-428.
[90]Rowlands D J, Frame D J, Ackerley D, Aina T, Booth B B, Christensen C, Collins M, Faull N, Forest C E, Grandey B S. Broad range of 2050 warming from an observationally constrained large climate model ensemble. Nature Geoscience [J].2012,5 (4):256-260.
[91]Sakamoto T, Gitelson A A, Arkebauer T J. MODIS-based corn grain yield estimation model incorporating crop phenology information. Remote Sensing of Environment [J].2013, 131:215-231.
[92]Saleska S R, Didan K, Huete A R, Da Rocha H R. Amazon forests green-up during 2005 drought. Science [J].2007,318 (5850):612-612.
[93]Sankey J B, Wallace C S, Ravi S. Phenology-based, remote sensing of post-burn disturbance windows in rangelands. Ecological Indicators [J].2013,30:35-44.
[94]Savitzky A, Golay M J. Smoothing and differentiation of data by simplified least squares procedures. Analytical chemistry [J].1964,36 (8):1627-1639.
[95]Shen M, Tang Y, Chen J, Zhu X, Zheng Y. Influences of temperature and precipitation before the growing season on spring phenology in grasslands of the central and eastern Qinghai-Tibetan Plateau. Agricultural and Forest Meteorology [J].2011,151 (12):1711-1722.
[96]Sjostrom M, Ardo J, Arneth A, Boulain N, Cappelaere B, Eklundh L, De Grandcourt A, Kutsch W, Merbold L, Nouvellon Y. Exploring the potential of MODIS EVI for modeling gross primary production across African ecosystems. Remote sensing of environment [J].2011,115 (4):1081-1089.
[97]Solano R, Didan K, Jacobson A, Huete A. MODIS vegetation indices (MOD 13) C5 user's guide. [J].2010, (Available at:):http://vip.arizona.edu/MODIS_UsersGuide.php.
[98]Song Q, Lin H, Zhang Y, Tan Z, Zhao J, Zhao J, Zhang X, Zhou W, Yu L, Yang L. The effect of drought stress on self-organisation in a seasonal tropical rainforest. Ecological Modelling [J].2013,265:136-139.
[99]Song Y, Achberger C, Linderholm H W. Rain-season trends in precipitation and their effect in different climate regions of China during 1961-2008. Environmental Research Letters [J].2011,6(3):034025.
[100]Soudani K, Hmimina G, Delpierre N, Pontailler J-Y, Aubinet M, Bonal D, Caquet B, De Grandcourt A, Burban B, Flechard C. Ground-based Network of NDVI measurements for tracking temporal dynamics of canopy structure and vegetation phenology in different biomes. Remote Sensing of Environment [J].2012,123:234-245.
[101]Stefanon M, Drobinski P, D'Andrea F, Noblet-Ducoudre N. Effects of interactive vegetation phenology on the 2003 summer heat waves. Journal of Geophysical Research: Atmospheres (1984-2012) [J].2012,117:D24103.
[102]Steven M D, Malthus T J, Baret F, Xu H, Chopping M J. Intercalibration of vegetation indices from different sensor systems. Remote Sensing of Environment [J].2003,88 (4):412-422.
[103]Sun Y, Gu L, Dickinson R E, Zhou B. Forest greenness after the massive 2008 Chinese ice storm:integrated effects of natural processes and human intervention. Environmental Research Letters [J].2012,7 (3):035702.
[104]Sutton R T, Dong B. Atlantic Ocean influence on a shift in European climate in the 1990s. Nature Geoscience [J].2012,5 (11):788-792.
[105]Toms J D, Lesperance M L. Piecewise regression:a tool for identifying ecological thresholds. Ecology [J].2003,84 (8):2034-2041.
[106]Tucker C J, Pinzon J E, Brown M E, Slayback D A, Pak E W, Mahoney R, Vermote E F, El Saleous N. An extended AVHRR 8-km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data. International Journal of Remote Sensing [J].2005,26 (20):4485-4498.
[107]Van Mantgem P J, Stephenson N L, Byrne J C, Daniels L D, Franklin J F, Fule P Z, Harmon M E, Larson A J, Smith J M, Taylor A H. Widespread increase of tree mortality rates in the western United States. Science [J].2009,323 (5913):521-524.
8] Verbesselt J, Hyndman R, Zeileis A, Culvenor D. Phenological change detection while accounting for abrupt and gradual trends in satellite image time series. Remote Sensing of Environment [J].2010,114 (12):2970-2980.
9] Walker D A, Epstein H E, Raynolds M K, Kuss P, Kopecky M A, Frost G V, Daniels F J A, Leibman M O, Moskalenko N G, Matyshak G V, Khitun O V, Khomutov A V, Forbes B C, Bhatt U S, Kade A N, Vonlanthen C M, Tichy L. Environment, vegetation and greenness (NDVI) along the North America and Eurasia Arctic transects. Environmental Research Letters [J].2012,7 (1):015504.
0] Walker J, De Beurs K, Wynne R, Gao F. Evaluation of Landsat and MODIS data fusion products for analysis of dryland forest phenology. Remote Sensing of Environment [J].2012, 117:381-393.
1] Wang H, Ma M, Wang X, Yuan W, Song Y, Tan J, Huang G. Seasonal variation of vegetation productivity over an alpine meadow in the Qinghai-Tibet Plateau in China: modeling the interactions of vegetation productivity, phenology, and the soil freeze-thaw process. Ecological research [J].2013,28 (2):271-282.
2] Wang X, Piao S, Ciais P, Li J, Friedlingstein P, Koven C, Chen A. Spring temperature change and its implication in the change of vegetation growth in North America from 1982 to 2006. Proceedings of the National Academy of Sciences [J].2011,108 (4):1240-1245.
3] Warren R, VanDerWal J, Price J, Welbergen J, Atkinson I, Ramirez-Villegas J, Osborn T, Jarvis A, Shoo L, Williams S. Quantifying the benefit of early climate change mitigation in avoiding biodiversity loss. Nature Climate Change [J].2013,3:678-682.
4] White M A, Thornton P E, Running S W. A continental phenology model for monitoring vegetation responses to interannual climatic variability. Global biogeochemical cycles [J].1997,11 (2):217-234.
5] Wu C, Munger J W, Niu Z, Kuang D. Comparison of multiple models for estimating gross primary production using MODIS and eddy covariance data in Harvard Forest. Remote Sensing of Environment [J].2010,114(12):2925-2939.
[116]Wu X, Liu H. Consistent shifts in spring vegetation green-up date across temperate biomes in China,1982-2006. Global change biology [J].2013,19 (3):870-880.
[117]Wu Z, Wu J, Liu J, He B, Lei T, Wang Q. Increasing terrestrial vegetation activity of ecological restoration program in the Beijing-Tianjin sand source region of China. Ecological Engineering [J].2013,52:37-50.
[118]Xiao X, Braswell B, Zhang Q, Boles S, Frolking S, Moore III B. Sensitivity of vegetation indices to atmospheric aerosols:continental-scale observations in Northern Asia. Remote Sensing of Environment [J].2003,84 (3):385-392.
[119]Xu X, Piao S, Wang X, Chen A, Ciais P, Myneni R B. Spatio-temporal patterns of the area experiencing negative vegetation growth anomalies in China over the last three decades. Environmental Research Letters [J].2012,7 (3):035701.
[120]Xue Y, Liu S, Zhang L, Hu Y. Integrating fuzzy logic with piecewise linear regression for detecting vegetation greenness change in the Yukon River Basin, Alaska. International Journal of Remote Sensing [J].2013,34 (12):4242-4263.
[121]Yu F, Price K P, Ellis J, Shi P. Response of seasonal vegetation development to climatic variations in eastern central Asia. Remote Sensing of Environment [J].2003,87 (1):42-54.
[122]Yu H, Xu J, Okuto E, Luedeling E. Seasonal response of grasslands to climate change on the Tibetan Plateau. PloS one [J].2012,7 (11):e49230.
[123]Yu Z, Liu S, Wang J, Sun P, Liu W, Hartley D S. Effects of seasonal snow on the growing season of temperate vegetation in China. Global change biology [J].2013,19 (7):2182-2195.
[124]Zeng H, Jia G, Epstein H. Recent changes in phenology over the northern high latitudes detected from multi-satellite data. Environmental Research Letters [J].2011,6 (4):045508.
[125]Zeng H, Jia G, Forbes B C. Shifts in Arctic phenology in response to climate and anthropogenic factors as detected from multiple satellite time series. Environmental Research Letters [J].2013,8 (3):035036.
126] Zhang K, Kimball J S, Hogg E H, Zhao M, Oechel W C, Cassano J J, Running S W. Satellite-based model detection of recent climate-driven changes in northern high-latitude vegetation productivity. Journal of Geophysical Research:Biogeosciences [J].2008,113 (G3):G03033.
127] Zhang L, Xiao J, Li J, Wang K, Lei L, Guo H. The 2010 spring drought reduced primary productivity in southwestern China. Environmental Research Letters [J].2012,7 (4):045706.
128] Zhang X, Friedl M A, Schaaf C B, Strahler A H, Hodges J C, Gao F, Reed B C, Huete A. Monitoring vegetation phenology using MODIS. Remote sensing of environment [J].2003, 84 (3):471-475.
129] Zhang X, Goldberg M, Tarpley D, Friedl M A, Morisette J, Kogan F, Yu Y. Drought-induced vegetation stress in southwestern North America. Environmental Research Letters [J].2010,5 (2):024008.
130] Zhang X, Tang Q, Zheng J, Ge Q. Warming/cooling effects of cropland greenness changes during 1982-2006 in the North China Plain. Environmental Research Letters [J].201.3,8 (2):024038.
131] Zhang Y, Gao J, Liu L, Wang Z, Ding M, Yang X. NDVI-based vegetation changes and their responses to climate change from 1982 to 2011:A case study in the Koshi River Basin in the middle Himalayans. Global and Planetary Change [J].2013,108:139-148.
132] Zhao M, Running S W. Drought-induced reduction in global terrestrial net primary production from 2000 through 2009. Science [J].2010,329 (5994):940-943.
133] Zhou L, Kaufinann R, Tian Y, Myneni R, Tucker C. Relation between interannual variations in satellite measures of northern forest greenness and climate between 1982 and 1999. Journal of Geophysical Research [J].2003,108 (D1):4004.
134] Zhou L, Tucker C J, Kaufmann R K, Slayback D, Shabanov N V, Myneni R B. Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999. Journal of Geophysical Research:Atmospheres (1984-2012) [J].2001,106 (D17):20069-20083.
[135]Zhu W, Tian H, Xu X, Pan Y, Chen G, Lin W. Extension of the growing season due to delayed autumn over mid and high latitudes in North America during 1982-2006. Global Ecology and Biogeography [J].2012,21 (2):260-271.
[136]安佑志,刘朝顺,施润和,高炜,殷杰.基于MODIS时序数据的长江三角洲地区植被覆盖时空变化分析.生态环境学报[J].2012,21(12)：1923-1927.
[137]边金虎,李爱农,宋孟强,马利群,蒋锦刚.MODIS植被指数时间序列Savitzky-Golay滤波算法重构.遥感学报[J].2010,14(4)：725-741.
[138]陈军,王玉辉.1956-2009年内蒙古苏尼特左旗荒漠草原的降水格局.生态学报[J].2012,32(22)：6925-6935.
[139]陈莉,方丽娟,李帅.东北地区近50年农作物生长季干旱趋势研究.灾害学[J].2010,25(4)：5-10.
[140]陈效逑,喻蓉.1982～1999年我国东部暖温带植被生长季节的时空变化.地理学报[J].2007,62(1)：41-51.
[141]戴君虎,王焕炯,葛全胜.近50年中国温带季风区植物花期春季霜冻风险变化.地理学报[J].2013,68(5)：593-601.
[142]方精云,朴世龙,贺金生,马文红.近20年来中国植被活动在增强.中国科学(C辑)[J].2003,33(6)：554-565.
[143]葛全胜,王芳,王绍武,程邦波.对全球变暖认识的七个问题的确定与不确定性.中国·人口资源与环境[J].2014,24(1)：1-6.
[144]郭江勇,林纾,万莉莉.500hPa高度场对西北地区秋季降水的影响分析.资源科学[J].2009,31(10)：1749-1754.
[145]国志兴,张晓宁,王宗明,方伟华.东北地区植被物候对气候变化的响应.生态学杂志[J].2010,29(3)：578-585.
[146]何月,张小伟,李仁忠,樊高峰,蔡菊珍.浙江省作物多熟种植制度遥感反演及其时空格局.生态学杂志[J].2011,30(12)：2827-2835.
[147]黄森旺,李晓松,吴炳方,裴亮.近25年三北防护林工程区土地退化及驱动力分析.地理学报[J].2012,67(5)：589-598.
[148]李杭燕,马明国,谭俊磊.时序NDVI数据集重建综合方法研究.遥感技术与应用[J].2010,25(6)：891-896.
[149]李洪权,范广洲,周定文,华维,刘雅勤,李学敏.青藏高原春季植被变化特征及其对夏季气温的影响.地理科学[J].2008,28(2)：259-265.
[150]李敏敏,延军平.华北段农牧交错带气候变化特征及其响应.干旱区资源与环境[J].2013,27(5)：100-106.
[151]李明,吴正方,杜海波,宗盛伟,孟祥君,张莲芝.基于遥感方法的长白山地区植被物候期变化趋势研究.地理科学[J].2011,31(10)：1242-1248.
[152]李荣平,周广胜.1980-2005年中国东北木本植物物候特征及其对气温的响应.生态学杂志[J].2010,29(12)：2317-2326.
[153]李月臣,宫鹏,刘春霞,陈晋,于德永.北方13省1982-1999年植被变化及其与气候因子的关系.资源科学[J].2006,28(2)：109-117.
[154]梁爽,彭书时,林鑫,丛楠.1982-2010年全国草地生长时空变化.北京大学学报(自然科学版)[J].2013,49(2)：311-320.
[155]刘海文，周天军,朱玉祥,林一骅.东亚夏季风自20世纪90年代初开始恢复增强.科学通报[J].2012,57(9)：765-769.
[156]刘抗,李照荣,张宇.1971-2010年中国西北地区秋季降水变化特征.中国沙漠[J].2014,34(3¨-9.
[157]刘丽娟,庞勇,范文义,李增元,李明泽.基于时间序列MODISEVI数据的森林生长异常监测.林业科学[J].2012,48(2)：54-62.
[158]刘玲玲,刘良云,胡勇.1982-2006年欧亚大陆植被生长季开始时间遥感监测分析.地理科学进展[J].2012,31(11)：1433-1442.
[159]刘亚南,潘志华,李超,安萍莉,潘学标.近50年北方农牧交错带气候月季变化和空间分布规律.中国农业大学学报[J].2012,17(4)：96-102.
[160]马建勇,潘婕,许吟隆,姜江SRESAIB情景下东北地区未来干旱趋势预估.干旱区研究[J].2013,30(2)：329-335.
[161]毛睿,龚道溢,Chen D欧亚大陆春季植被状况与东亚夏季大气环流的显著联系.气象学报 [J].2008,66(4)：592-598.
[162]潘耀忠,李乐,张锦水,梁顺林,侯东.基于典型物候特征的MODIS-EVI时间序列数据农作物种植面积提取方法一小区域冬小麦实验研究.遥感学报[J].2011,15(3)：578-594.
[163]朴世龙,方精云.1982-1999年我国陆地植被活动对气候变化响应的季节差异.地理学报[J].2003,58(1)：119-125.
[164]邱海军,曹明明.基于SPOT VEGETATION数据的中国植被覆盖时空变化分析.资源科学[J].2011,33(2)：335-340.
[165]沈柏竹,廉毅,杨涵洧,张世轩.中国东北夏季温度年代际变化特征.地理科学[J].2012,32(6)：739-745.
[166]施雅风,沈永平,李栋梁,张国威,丁永建,胡汝骥,康尔泗.中国西北气候由暖干向暖湿转型的特征和趋势探讨.第四纪研究[J].2003,23(2)：152-164.
[167]孙华生,黄敬峰,彭代亮.利用MODIS数据识别水稻关键生长发育期.遥感学报[J].2009,13(6)：1122-1137.
[168]孙艳玲,郭鹏.1982-2006年华北植被覆盖变化及其与气候变化的关系.生态环境学报[J].2012,21(1)：7-12.
[169]王宏,李晓兵,李霞,莺歌,符娜.基于NOAANDVI和MSAVⅠ研究中国北方植被生长季变化.生态学报[J].2007,27(2)：504-515.
[170]王焕炯,戴君虎,葛全胜.1952～2007年中国白蜡树春季物候时空变化分析.中国科学：地球科学[J].2012,42(5)：701-710.
[171]王少鹏,王志恒,朴世龙,方精云.我国40年来增温时间存在显著的区域差异.科学通报[J].2010,55(16)：1538-1543.
[172]王晓爽,胡卓玮,赵文吉,刘洪岐.基于EVI植被指数的大尺度草地多源信息综合分类研究.草业科学[J].2011,28(1)：10.
[173]王宗明,国志兴,宋开山,罗玲,张柏,刘殿伟,黄妮,任春颖.中国东北地区植被NDVI对气候变化的响应.生态学杂志[J].2009,28(6)：1041-1048.
[174]吴文斌,杨鹏,唐华俊,周清波,张莉,唐鹏钦.过去20年中国耕地生长季起始期的时空变化.生态学报[J].2009,29(4)：1777-1786.
[175]武永峰,李茂松,刘布春,白文波,蒋卫国.基于NOAA NDVI的中国植被绿度始期变化.地理科学进展[J].2008,27(6)：32-40.
[176]袭祝香,杨雪艳,刘实,纪玲玲.东北地区夏季干旱风险评估与区划.地理科学[J].2013,33(6)：735-740.
[177]信忠保,许炯心,郑伟.气候变化和人类活动对黄土高原植被覆盖变化的影响.中国科学(D辑)[J]-007,37(11)：1504-1514.
[178]徐岩岩,张佳华,Limin Y.基于MODIS-EVI数据和Symlet11小波识别东北地区水稻主要物候期.生态学报[J].2012,32(7)：2091-2098.
[179]闫峰,王艳姣,吴波.近50年河北省干旱时空分布特征.地理研究[J].2010,29(3)：423-430.
[180]闫慧敏,肖向明,黄河清.黄淮海多熟种植农业区作物历遥感检测与时空特征.生态学报[J].2010,30(9)：2416-2423.
[181]闫娜,李登科,杜继稳,延军平.基于MODIS产品LST/NDVI/EVI的陕西旱情监测.自然灾害学报[J].2010,19(4)：178-182.
[182]颜梅春,张先聪，胡莎,王元超.基于MODIS数据的京津唐地区干旱监测研究.地理与地理信息科学[J].2012,28(2)：94-103.
[183]杨金虎,江志红,裴永成.欧亚大陆春季植被对同年中国西北夏季大气环流和气候的影响研究.冰川冻土[J].2011,33(5)：1014-1021.
[184]殷贺,李正国,王仰麟,蔡福.基于时间序列植被特征的内蒙古荒漠化评价.地理学报[J].2011,66(5)：653-661.
[185]于信芳,庄大方.基于MODIS NDVI数据的东北森林物候期监测.资源科学[J].2006,28(4)：111-117.
[186]张戈丽,陶健,董金玮,徐兴良.1960年-2010年内蒙古东部地区生长季变化分析.资源科学[J].2011a,33(12)：2323-2332.
[187]张戈丽,徐兴良,周才平,张宏斌,欧阳华.近30年来呼伦贝尔地区草地植被变化对气候变化的响应.地理学报[J].2011b,66(1)：47-58.
[188]张金龙,刘学锋,于长文.河北省干旱分布特征和变化规律分析.干旱区研究[J].2012,29(1)：41-46.
[189]张井勇,董文杰,叶笃正,符淙斌.中国植被覆盖对夏季气候影响的新证据.科学通报[J].2003,48(1)：91-95.
[190]张明伟,周清波,陈仲新,周勇,刘佳,蔡崇法.基于物候模型的作物种植面积变化监测方法.农业工程学报[J].2006,22(10)：139-144.
[191]张生军,王涛,王天明,卢爱刚,葛剑平.新疆不同植被NDVI的变化及其与气候因子的关系.草业科学[J].2009,26(5)：26-31.
[192]张钛仁,柴秀梅,李自珍.中国北方植被覆盖度特征及其与沙尘暴关系.高原气象[J].2010,29(1)：137-145.
[193]张伟,闫敏华,陈泮勤.松嫩平原近50年来生长季降水资源特征分析.干旱区资源与环境[J].2007,21(10)：73-78.
[194]张学珍,戴君虎,葛全胜.1982-2006年中国东部春季植被变化的区域差异.地理学报[J].2012,67(1)：53-61.
[195]张学珍,郑景云,何凡能,戴君虎.1982-2006年中国东部秋季植被覆盖变化过程的区域差异.自然资源学报[J].2013,28(1)：28-37.
[196]张延伟,魏文寿,姜逢清,刘明哲,王雯雯,白磊,韩茜,洪雯,陆恒,李雪梅.近50年新疆气温和降水量变化及其与NAO指数的交叉小波谱分析.高原气象[J].2012,31(4)：974-982.
[197]赵霞,谭琨,方精云.1982-2006年新疆植被活动的年际变化及其季节差异.干旱区研究[J].2011,28(1)：10-16.
[198]郑景云,葛全胜,郝志新.气候增暖对我国近40年植物物候变化的影响.科学通报[J].2002,47(20)：1582-1587.
[199]周峰,许有鹏,吕慧华.基于MODIS-EVI数据的长江三角洲地区植被变化的特征.长江流域资源与环境[J].2012,21(11)：1363-1369.
[200]朱大威,金之庆.气候及其变率变化对东北地区粮食生产的影响.作物学报[J].2008,34(9)：1588-1597.
[201]宗海锋,陈烈庭,张庆云ENSO与中国夏季降水年际变化关系的不稳定性特征.大气科学[J].2010,34(1)：184-192