Impact of climate and human activity on NDVI of various vegetation types in the Three-River Source Region, China

The Three-River Source Region(TRSR)in China holds a vital position and exhibits an irreplaceable strategic importance in ecological preservation at the national level.On the basis of an in-depth study of the vegetation evolution in the TRSR from 2000 to 2022,we conducted a detailed analysis of the feedback mechanism of vegetation growth to climate change and human activity for different vegetation types.During the growing season,the spatiotemporal variations of normalized difference vegetation index(NDVI)for different vegetation types in the TRSR were analyzed using the Moderate Resolution Imaging Spectroradiometer(MODIS)-NDVI data and meteorological data from 2000 to 2022.In addition,the response characteristics of vegetation to temperature,precipitation,and human activity were assessed using trend analysis,partial correlation analysis,and residual analysis.Results indicated that,after in-depth research,from 2000 to 2022,the TRSR's average NDVI during the growing season was 0.3482.The preliminary ranking of the average NDVI for different vegetation types was as follows:shrubland(0.5762)>forest(0.5443)>meadow(0.4219)>highland vegetation(0.2223)>steppe(0.2159).The NDVI during the growing season exhibited a fluctuating growth trend,with an average growth rate of 0.0018/10a(P<0.01).Notably,forests displayed a significant development trend throughout the growing season,possessing the fastest rate of change in NDVI(0.0028/10a).Moreover,the upward trends in NDVI for forests and steppes exhibited extensive spatial distributions,with significant increases accounting for 95.23%and 93.80%,respectively.The sensitivity to precipitation was significantly enhanced in other vegetation types other than highland vegetation.By contrast,steppes,meadows,and highland vegetation demonstrated relatively high vulnerability to temperature fluctuations.A further detailed analysis revealed that climate change had a significant positive impact on the TRSR from 2000 to 2022,particularly in its northwestern areas,accounting for 85.05%of the total area.Meanwhile,human activity played a notable positive role in the southwestern and southeastern areas of the TRSR,covering 62.65%of the total area.Therefore,climate change had a significantly higher impact on NDVI during the growing season in the TRSR than human activity.

Effect of seasonal snow on the start of growing season of typical vegetation in Northern Hemisphere

Under global warming, seasonal snow takes faster melting rate than before, which greatly changes the hydro-logical cycle. In this study, by targeting three typical seasonal snow-covered land types (i.e., open shrubland,evergreen needleleaf forest and mixed forest) in the Northern Hemisphere, the start of growing season (SGS) hasbeen found obviously advanced in the past years, greatly contributed by the faster melting rate of seasonal snow.It is manifested that significantly positive correlation has been found between SGS and May snow depth for openshrubs, March and April snow depth for evergreen needleleaf forests and March snow depth for mixed forests.However, such close association is not appeared in all the climate conditions of same vegetation. In the future,as the rate of melting snow becomes faster in the high emission of greenhouse gasses than the current situation,continuously advanced SGS will accelerate the change of vegetation distribution in the Northern Hemisphere.These findings offer insights into understanding the effect from seasonal snow on vegetation and promote thesustainable utilization of regional vegetation in the Northern Hemisphere.

Projections of the Advance in the Start of the Growing Season during the 21st Century Based on CMIP5 Simulations

It is well-known that global warming due to anthropogenic atmospheric greenhouse effects advanced the start of the vegetation growing season （SOS） across the globe during the 20th century. Projections of further changes in the SOS for the 21st century under certain emissions scenarios （Representative Concentration Pathways, RCPs） are useful for improving understanding of the consequences of global warming. In this study, we first evaluate a linear relationship between the SOS （defined using the normalized difference vegetation index） and the April temperature for most land areas of the Northern Hemisphere for 1982-2008. Based on this relationship and the ensemble projection of April temperature under RCPs from the latest state-of-the-art global coupled climate models, we show the possible changes in the SOS for most of the land areas of the Northern Hemisphere during the 21st century. By around 2040-59, the SOS will have advanced by -4.7 days under RCP2.6, -8.4 days under RCP4.5, and -10.1 days under RCPS.5, relative to 1985-2004. By 2080-99, it will have advanced by -4.3 days under RCP2.6, -11.3 days under RCP4.5, and -21.6 days under RCP8.5. The geographic pattern of SOS advance is considerably dependent on that of the temperature sensitivity of the SOS. The larger the temperature sensitivity, the larger the date-shift-rate of the SOS.

Quantifying the Effects of Climate Change and Land Management on Vegetation Dynamics from 1982 to 1985 in the Source Region of Three-Rivers, China

Vegetation dynamics under a warming climate in the source region of the Three Rivers (SRTR) and its ecological impacts are a source of serious concern. In this study, we investigated the spatial and temporal variations of normalized difference vegetation index during the growing season (NDVIgr) and the start of the vegetation growing season (SOS) for six ecosystems. We examined the relationships between vegetation parameters, air temperature, precipitation and land management using residual trend method from 1982 to 2015. The NDVIgr increased at a rate of 0.0061/10a, and SOS advanced by 0.96 d/10a during the study period. The NDVIgr increased for the all six vegetation ecosystem from 1982 to 2015. The SOS showed advancing trend for the vegetation types for meadow (0.1236 d/a) and steppe (0.3480 d/a), but showing delaying trends for forest, shrub, barren land and alpine vegetation. The results of the correlation analysis indicate an increase in the air temperature in the SRTR is the main factor explaining increases in the NDVI and advancement of the SOS. In general, awarming-wetting climate and reasonable human activities had positive effects on vegetation growth, while the positive impact of human activities was weaker than that of climatic factors. This study provides a necessary basis for research on and the prediction of vegetation changes and their response to the climate warming of the SRTR in the Qinghai-Tibet Plateau (QTP).

Changing Spring Phenology Dates in the Three-Rivers Headwater Region of the Tibetan Plateau during 1960–2013

The variation of the vegetation growing season in the Three-Rivers Headwater Region of the Tibetan Plateau has recently become a controversial topic. One issue is that the estimated local trend in the start of the vegetation growing season(SOS)based on remote sensing data is easily affected by outliers because this data series is short. In this study, we determine that the spring minimum temperature is the most influential factor for SOS. The significant negative linear relationship between the two variables in the region is evaluated using Moderate Resolution Imaging Spectroradiometer–Normalized Difference Vegetation Index data for 2000–13. We then reconstruct the SOS time series based on the temperature data for 1960–2013.The regional mean SOS shows an advancing trend of 1.42 d(10 yr)during 1960–2013, with the SOS occurring on the 160th and 151st days in 1960 and 2013, respectively. The advancing trend enhances to 6.04 d(10 yr)during the past 14 years. The spatiotemporal variations of the reconstructed SOS data are similar to those deduced from remote sensing data during the past 14 years. The latter exhibit an even larger regional mean trend of SOS [7.98 d(10 yr)] during 2000–13. The Arctic Oscillation is found to have significantly influenced the changing SOS, especially for the eastern part of the region,during 2000–13.

Winter Wheat Drought Monitoring and Comprehensive Risk Assessment： Case Study of Xingtai Administrative District in North China

Drought monitoring is the base for drought coping and adaptation. Xingtai is located in North China＇s key winter wheat production areas where drought is severe and frequent. The rainfall during winter wheat growing season is just about 1/3 of total demand. Xingtai has typical mountainous, hilly and plain agricultural zones, compound rain-fed and irrigated farming patterns. The winter wheat irrigation has heavily depended on overdraw of groundwater in recent decades. In the study, the MODIS （Moderate-Resolution Imaging Spectroradiometer） images taken at the key winter wheat growing season （Mar. to May） in normal rainfall year （2006） were selected, extracted NDVI （Normalized Difference Vegetation Index） and LST （Land Surface Temperature） data, calculated TVDI （Temperature and Vegetation Drought Index）, classified and mapped winter wheat drought intensity. Further, based on TVDI, a CDRA （Comprehensive Drought Risk Assessment） model for winter wheat drought disaster risk assessment was constructed and zoning was made. Verified by winter wheat yield, the risk zoning by CDRA is consistent with actual crop failure space. This method can be used in drought risk management.

蒙古高原干旱时空特征及对植被物候的累积影响

蒙古高原是中国北方重要的生态安全屏障,为厘清蒙古高原干旱时空动态及对植被物候的影响,利用SPEIbase 2.9数据集和基于累积NDVI的Logistic曲线曲率极值法反演的植被物候数据集,分析1982—2022年蒙古高原干旱时空特征及干旱对植被返青期和枯黄期的累积影响。结果表明:(1)不同尺度SPEI均呈显著下降趋势,随着时间尺度的增加干旱化趋势加剧、干旱化面积明显增大,中部和西部地区干旱化尤为严重。(2)植被返青期提前和推迟的面积占比分别为50.03%和49.97%,枯黄期推迟和提前的面积占比分别为67.85%和32.15%;荒漠草原返青期和枯黄期主要表现为推迟趋势,针叶林和森林草原北部返青期显著提前、枯黄期呈推迟趋势。(3)蒙古高原(荒漠除外)79.62%的区域植被返青期与1~12个月尺度SPEI呈最大正相关,干旱尺度主要为中期尺度,尤其7~9个月尺度的干旱对植被返青期影响明显;54.15%的区域植被枯黄期与SPEI呈最大负相关,干旱尺度主要为1~3个月尺度。其结果对防御蒙古高原干旱及对植被物候和生产力的影响具有重要意义。

Start of vegetation growing season on the Tibetan Plateau inferred from multiple methods based on GIMMS and SPOT NDVI data

In this study, we have used four methods to investigate the start of the growing season （SGS） on the Tibetan Plateau （TP） from 1982 to 2012, using Normalized Difference Vegetation Index （NDVI） data obtained from Global Inventory Modeling and Mapping Studies （GIMSS, 1982-2006） and SPOT VEGETATION （SPOT-VGT, 1999-2012）. SGS values esti- mated using the four methods show similar spatial patterns along latitudinal or altitudinal gradients, but with significant variations in the SGS dates. The largest discrepancies are mainly found in the regions with the highest or the lowest vegetation coverage. Between 1982 and 1998, the SGS values derived from the four methods all display an advancing trend, however, according to the more recent SPOT VGT data （1999-2012）, there is no continu- ously advancing trend of SGS on the TP. Analysis of the correlation between the SGS values derived from GIMMS and SPOT between 1999 and 2006 demonstrates consistency in the tendency with regard both to the data sources and to the four analysis methods used. Com- pared with other methods, the greatest consistency between the in situ data and the SGS values retrieved is obtained with Method 3 （Threshold of NDVI ratio）. To avoid error, in a vast region with diverse vegetation types and physical environments, it is critical to know the seasonal change characteristics of the different vegetation types, particularly in areas with sparse grassland or evergreen forest.

2001-2020年黄土高原植被生长季干旱的时空分布

基于MODIS实际蒸散量(ET)和潜在蒸散量(PET)反演作物缺水指数(CWSI),研究黄土高原生长季干旱时空变化特征,并用CWSI和植被归一化指数(NDVI)进行偏相关分析以探究生长季内最干旱月份对NDVI的影响。结果表明:1)黄土高原生长季CWSI多年平均值为0.777,处于中度干旱状态,空间分布表现为东南部较轻,西北部较严重的特征,且高程在1200~1700 m区域内的干旱程度最高;2)2001-2020年多年生长季CWSI整体呈显著下降趋势,其中2001年干旱程度最高,2018年干旱程度最低;在整个生长季内,黄土高原在4月的干旱程度最高;8月的干旱程度最低。具体表现为:4-10月,干旱等级从重旱过渡到中旱和轻旱,又从轻旱演变成中旱;3)从植被类型角度分析,荒漠、草原的分布区域属于重旱;草甸、栽培植被、灌丛的分布区域属于中旱;针叶林、阔叶林的分布区域属于轻旱,且不同植被类型在植被生长季的CWSI均呈波动下降趋势。研究结果可为黄土高原地区的生态预警和旱灾预估提供科学依据。

关中平原城市群气候变化和人类活动对植被NDVI变化的影响

[目的]研究关中平原城市群气候变化和人类活动对植被NDVI变化的影响。[方法]基于2001—2020年的植被NDVI和地表温度数据,运用趋势分析和残差分析等方法分析近20年关中平原城市群植被生长季植被NDVI变化趋势,以及气候变化和人类活动对生长季植被NDVI的驱动力分析及其贡献率。[结果]近20年来研究区生长季植被NDVI呈波动性增加趋势,其变化受气候变化和人类活动共同影响,且存在较大空间异质性,研究区中部生长季植被NDVI降低主要归因于人类活动的影响。气候变化和人类活动对生长季植被NDVI贡献率主要为正值,人类活动因素的贡献率更高,且研究区水系两侧多呈现气候变化抑制、人类活动促进的情况。[结论]关中平原城市群中人类活动对生长季植被NDVI的影响较大,建议在综合因素分析中多重视人类活动影响。

海河流域生长季植被覆盖度时空变化及驱动力分析

[目的]了解海河流域生长季植被覆盖度(FVC)的时空变化及其驱动力,以期为海河流域的生态保护、建设与可持续发展提供参考。[方法]基于MODIS NDVI遥感数据和同时期的18种影响因子,采用趋势分析法和M-K显著性检验分析了2001—2019年海河流域生长季植被覆盖度的时空变化特征;并利用地理探测器探讨了其空间分异特征与驱动力。[结果]2001—2019年海河流域生长季植被覆盖度总体呈显著上升趋势,线性倾向率为0.063/10 a,2011年之后增速减缓。空间分布差异明显,植被覆盖度总体较高,仅环渤海湾地带和一些城市区域植被覆盖率较低。改善区域的面积远大于退化面积,其中改善部分以极显著改善为主,占流域总面积的60.42%。海河流域生长季植被覆盖度的空间分布差异主要由林地比例和林草混合地比例所决定,解释力均在30%以上。对海河流域生长季植被覆盖度交互作用解释力最强的是林草混合地比例和农田比例。[结论]海河流域植被覆盖度总体显著上升,空间分布差异主要驱动力为林地比例和林草混合地比例。

腾格里沙漠南缘不同恢复阶段沙质草地植被的季节变化特征

植被的季节动态变化是陆地生态系统对气候变化最敏感且最直观的反映。在腾格里沙漠南缘,以紧邻的地带性植被荒漠草原为对照,选择流动沙地、半固定沙地、固定沙地作为沙质草地恢复序列,对比分析不同恢复阶段沙质草地植被盖度、物种多样性在生长季5-10月的动态变化特征,以确定开展沙质草地调查监测的恰当时间及数量指标,为沙质草地地面调查、遥感监测、恢复及利用提供依据。研究结果表明,腾格里沙漠南缘不同恢复阶段沙质草地的植被盖度和物种多样性明显不同,荒漠草原生长季的平均植被盖度与固定沙地接近,是流动沙地、半固定沙地的27.6和2.3倍;其Shannon多样性指数是流动沙地、半固定沙地和固定沙地的2.7、1.5和1.7倍。沙质草地的季节变化明显,植被盖度、物种丰富度、草本植物盖度均呈持续增加趋势,物种多样性均呈先降低后增加的趋势,9-10月是沙质草地调查的适宜时间。但是,不同恢复阶段沙质草地的季节变化程度及变化规律又明显不同,流动沙地植被盖度、草本植物盖度的季节变异系数最大,Gleason丰富度指数、多样性指数变异系数最小,荒漠草原植被盖度、草本植物盖度、多样性指数季节变异系数均低于流动沙丘,反映出恢复早期沙质草地的稳定性差。人工固沙植被建设促进了沙质草地的恢复演替,改变其季节变化特征,增强了其群落稳定性,但要继续推进固定沙质草地向地带性荒漠草原的恢复演替,仍需要加强封禁保护。

2000—2021年青藏高原生长季植被敏感性的时空变异

为揭示青藏高原陆地生态系统对气候变化敏感性的时空变异性,基于植被敏感性指数(Vegetation Sensitivity Index,VSI),使用2000—2021年青藏高原6—8月生长季MODIS EVI和ERA5再分析资料的温度、降水和太阳辐射数据,首先探究了22年里青藏高原陆地生态系统敏感性的空间变异性及其主要气候驱动因素,其次探究了青藏高原VSI在P_(1)(2000—2006年)、P_(2)(2007—2013年)和P_(3)(2014—2021年)时期内VSI的时间变异性,研究表明:(1)2000—2021年青藏高原生长季VSI的空间异质性较强,其中东南部灌木和森林的VSI较高,而西北部高山荒漠、高山草原和高山草甸的VSI较低;(2)22年里温度、降水和太阳辐射分别主导着青藏高原55.89%、19.24%和24.87%地区的VSI变化,其中温度主导着东南部灌木和森林的VSI,降水主导着东北大部分地区高山草甸的VSI,而太阳辐射主导着西南大部分地区高山草原的VSI。时间变异性结果表明:(3)P_(1)—P_(3)时期内青藏高原18.39%像元内的VSI持续增加而10.09%像元内的VSI持续减少。高山荒漠、高山草原和高山草甸的VSI在P_(1)—P_(2)时期基本不变而在P_(2)—P_(3)时期呈现上升态势,与之相比,灌木和森林的VSI呈先增长后下降的态势;(4)3个时期内主导青藏高原VSI变化的气候变量具有较强的时空异质性,其中温度为主导因子的像元数量在P_(1)—P_(2)时期基本一致而在P_(3)时期明显减少,其占比分别为P_(1)(58.15%),P_(2)(61.34%)和P_(3)(49.47%),降水为主导因子的像元数量在P_(1)(18.57%)和P_(2)(18.47%)时期内基本不变但在P_(3)(26.64%)时期内明显增加,与温度和降水相比,以辐射为主导因子的像元数在3个时期内基本不变。总体而言,青藏高原高山草原和高山草甸生态系统对气候变化的响应呈增加态势,在青藏高原气候多变的背景下,草地生态系统可能存在退化的风险。研究旨在为全球气候变化背景下青藏高原生态系统敏感性的动态评估提供参考。

2000—2020年河湟谷地农业干旱研究

选取植被健康指数(Vegetation health index,VHI)为农业干旱程度衡量指标,利用Mann-Kendall(M-K)检验法和小波分析法对河湟谷地2000—2020年农作物生长季(3—11月)干旱程度进行逐年和逐季节研究(以3—5月为春季、6—8月为夏季、9—11月为秋季)。结果表明:(1)河湟谷地农业干旱区主要集中在大通河中游地区、湟水河干流区和黄河谷地。(2)河湟谷地农业干旱面积呈现明显的地域分异特点,由北到南农业干旱面积逐渐增大。(3)河湟谷地农业干旱面积在年际尺度上有在周期性波动中不断减小的趋势,2007—2008年是河湟谷地农业干旱面积发生突变的时间点,此后河湟谷地农业干旱面积开始急剧减少;春季是河湟谷地受农业干旱影响最严重的季节。研究结果对掌握河湟谷地农业干旱空间分布及变化趋势、促进青海省农业健康发展具有重要意义。

蒙古高原250 m分辨率植被生长季NDVI年际时空变化数据集(2001-2021年)

蒙古高原对我国北方生态安全有着重要的影响,植被对气候变化和生态环境有着重要的指示作用,植被的时空变化格局与趋势是评估区域生态状况的重要指标。本研究基于MOD13Q1 NDVI数据,利用R语言调用Google Earth Engine服务进行月度最大值合成,之后使用R语言terra包完成生长季年度均值合成、变异系数计算、Theil-Sen median趋势分析和Mann-Kendall显著性检验以及Hurst指数计算,形成了2001-2021年蒙古高原250m分辨率植被生长季NDVI年际时空变化数据集,包含蒙古高原地区生长季NDVI时空变化格局和趋势特征信息。通过在国家地球系统科学数据中心共享数据,为科学认识蒙古高原区域植被覆盖时空变化规律提供数据支撑。

高原夏菜复合气象灾害综合评判与分析

河西走廊东部高原夏菜生长过程受多种气象灾害影响,为了解其成灾特征,基于层次分析法(AHP)给不同灾害、不同致灾程度赋予权重,通过建立评价模型,对2010—2021年复合灾害强度进行评判与分析。结果表明:复合灾害频次高、影响大、极端性强,沿川区、沿沙区高温热害最典型,加上持续干旱,复合灾害影响将会进一步加剧。从复合灾害强度看,沿沙区与沿川区偏大,春茬中沿沙区复合灾害强度变化显著,倾向率为0.029·a^(-1),已严重威胁到产业发展。通过冷凉山区蒜苗试验,评价结果得到进一步验证。针对复合灾害影响评价及分布特点,高原夏菜生产还需因时因地制宜。

Variations of Vegetation Phenology Extracted from Remote Sensing Data over the Tibetan Plateau Hinterland during 2000–2014

How vegetation phenology responds to climate change is a key to the understanding of the mechanisms driving historic and future changes in regional terrestrial ecosystem productivity. Based on the 250-m and 8-day moderate resolution imaging spectroradiometer(MODIS) normalized difference vegetation index(NDVI) data for 2000-2014 in the Three-River Source Region(TRSR) of Qinghai Province, China, i.e., the hinterland of the Tibetan Plateau, we extracted relevant vegetation phenological information(e.g., start, end, and length of growing season) and analyzed the changes in the TRSR vegetation in response to climate change. The results reveal that, under the increasingly warm and humid climate, the start of vegetation growing season(SOS) advanced 1.03 day yr-1 while the end of vegetation growing season(EOS) exhibited no significant changes, which led to extended growing season length. It is found that the SOS was greatly affected by the preceding winter precipitation, with progressively enhanced precipitation facilitating an earlier SOS. Moreover, as the variations of SOS and its trend depended strongly on topography, we estimated the elevation break-points for SOS. The lower the elevations were, the earlier the SOS started. In the areas below 3095-m elevation, the SOS delay changed rapidly with increasing elevation;whereas above that, the SOS changes were relatively minor. The SOS trend had three elevation break-points at 2660, 3880, and 5240 m.

Spatial variations in responses of vegetation autumn phenology to climate change on the tibetan Plateau

Aims Information about changes in the start and end of the vegetation growing season(SOS and EOS)is crucial for assessing ecosystem responses to climate change because of the high sensitivity of both to climate and their extensive influence on ecological processes in temperate and cold regions.climatic warming substantially advanced SOS on the tibetan Plateau from 1982 to 2011.However,it is unclear why EOS showed little delay despite increasing tem-perature over this period.Methods We used multiple methods to determine EOS from the satellite-observed normalized-difference vegetation index and investigated the relationships between EOS and its potential drivers on the tibetan Plateau over 1982-2011.Important findings We found a slight but non-significant delay in regionally averaged EOS of 0.7 day decade−1(P=0.18)and a widespread but weak delaying trend across the Plateau over this period.the inter-annual variations in regionally averaged EOS were driven mainly by pre-season temperature(partial R=0.62,P<0.01),and precipitation and insolation showed weak impact on EOS(P>0.10).Pre-season warming delayed EOS mainly in the eastern half and north-western area of the plateau.In the south-west,EOS was significantly and positively related to SOS,suggesting potentially indirect effects of winter weather conditions on the following autumn’s phenology through regulation of spring phenology.EOS was more strongly related with pre-season temperature in colder and wetter areas,reflecting vegetation adaptation to local climate.Interestingly,pre-season temperature had weaker delaying effects on EOS for vegeta-tion with a shorter growing season,for which SOS had a stronger control on inter-annual variations in EOS than for vegetation with a longer growing season.this indicates that shorter-season tibetan Plateau vegetation may have lower plasticity in adjusting the length of its growing season,whenever it begins,and that climate change is more likely to shift the growing season than extend it for that vegetation.

基于NOAA NDVI和MSAVI研究中国北方植被生长季变化

利用1982～1999年的NOAA／AVHRRNDVI和MSAVI指数监测了中国北方植被生长季变化规律，主要内容包括：（1）不同植被类型的生长季变化监测。提取植被的1982～1999年NDVI和MSAVI时间序列，利用阈值法和滑动平均法逐年估测植被类型的生长季的开始、结束日期及长度。对估测的生长季开始、结束时间和长度进行一次线性拟合，得到了18a中植被生长季的开始、结束日期和长度的线性变化趋势；（2）不同区域的植被生长季变化监测。将中国北方13省、区按纬向划分为32～36°N，36～40°N，40～44°N，44～48°N，48-52°N等5个区域。基于最大变化斜率法估测了不同年份的生长季开始、结束和长度；（3）研究区域植被生长季的空间变化监测。利用曲线拟合出1982～1999年像元对应的空间位置的植被平均生长季变化，然后讨论了多年平均的植被生长季的空间分异规律，并利用一次线性拟合分析了这18a的植被生长季的变化趋势。结果表明：部分植被类型生长季的开始日期提前，结束日期推迟，而生长季长度延长，提前或推迟的天数不一，如典型草原、荒漠草原、寒温带山地落叶针叶林。而一些植被类型的生长季并没有表现出这样的趋势，而是开始日期延迟或结束日期推迟，如温带落叶阔叶林。不同纬度带的植被生长季变化监测表明，大部分纬度带植被生长季开始日期都表现出不同程度的提前趋势，生长季结束日期表现出推迟的趋势，整个生长季长度表现出延长的趋势。中国北方植被生长季空间变化研究表明，青海、甘肃、陕南地区的植被生长季开始较早。新疆天山、东北北部、青海、甘肃的部分地区植被生长季结束较早。东北、青海、新疆的大部分地区的植被生长季有明显的延长趋势，整个研究区内有一部分地区的植被生长季长度表现出缩短的趋势。

基于NOAA NDVI的植被生长季模拟方法研究

在近几年里,大尺度的植被生长季监测已经成为全球气候变化研究中的一个重要科学问题。NOAA/NDVI数据为研究植被生长季时空变化规律提供了重要手段。文章综述并分析比较了基于NDVI估测植被生长季开始、结束、长度等特征参数的方法:NDVI阈值、时间序列分析、物候期的频率分布型与NDVI相结合、主分量分析、利用曲线进行拟合等方法。受不同因素影响,各方法有不同的应用局限性,因此,在以前研究的基础上,利用较常用的四种方法:阈值法、滑动平均法、最大变化斜率、曲线拟合模型模拟了锡林浩特1991～1999年的草原生长季,最后利用野外实测的草原返青期验证了监测结果。结果表明:与地面观测数据相结合,基于阈值可得到较好的草原返青期;基于曲线拟合模型能适用于大尺度上的植被生长季变化监测,但存在问题是拟合曲线很难接近于实际曲线,因此,需要进一步研究的内容是选择合适的曲线估测模型,监测不同植被类型生长季的年际变化规律。