植物物候及其变化是多个环境因子综合影响的结果,其中气候是最重要、最活跃的环境因子。主要从气候环境角度分析了植物物候与气候以及气候变化间的相互关系,概述了国内外有关植物物候及物候模拟等方面的研究进展。表明,温度是影响物候变化最重要的因子;同时,水分成为胁迫因子时对物候的影响也十分重要。近50a左右,世界范围内的植物物候呈现出了春季物候提前,秋季物候推迟或略有推迟的特征,从而导致了多数植物生长季节的延长,并成为全球物候变化的趋势。全球气候变暖改变了植物开始和结束生长的日期,其中冬季、春季气温的升高使植物的春季物候提前是植物生长季延长的主要原因。目前对物候学的研究方向主要集中在探讨物候与气候变化之间的关系,而模型模拟是定量研究气候变化与植物物候之间关系的重要方式,国内外已经开发出多种物候模型来分析气候驱动与物候响应之间的因果关系。另外遥感资料的应用也为物候模型研究提供了新的方向。物候机理研究、物候与气候关系以及物候模型研究将是研究的重点。

<p>根据现代气象观测资料及中国科学院物候观测网络26个观测站点的物候资料, 分析了近40年温度变化对我国木本植物物候变化的影响, 并建立了不同年代物候期与地理位置之间的关系模式, 分析了当前气候增暖背景下物候期地理分布模式对温度变化的响应. 结果表明: (1) 物候期的提前与推迟对温度的上升与下降的响应是非线性的. 20世纪80年代以后, 在同等升降温幅度情况下, 因降温而导致的物候期推迟幅度较因升温而导致的物候期提前幅度大; 因升温而导致的物候期提前日数的变化率随着升温幅度的增大而减小, 因降温而导致物候期推迟日数的变化率随着降温幅度的增大而加大. (2)物候期与地理位置的关系模式因气候变化而呈现不稳定特点. 随着20世纪80年代以后我国大部分地区的春季增温及秦岭以南广大地区的降温, 东北、华北及长江下游等地区的物候期提前, 西南东部、长江中游等地区的物候期推迟; 同时物候期随纬度变化的幅度减小.</p>

Abstract Changes in vegetative growing seasons are dominant indicators of the dynamic response of ecosystems to climate change. Therefore, knowledge of growing seasons over the past decades is essential to predict ecosystem changes. In this study, the long-term changes in the growing seasons of temperate vegetation over the Northern Hemisphere were examined by analyzing satellite-measured normalized difference vegetation index and reanalysis temperature during 1982–2008. Results showed that the length of the growing season (LOS) increased over the analysis period; however, the role of changes at the start of the growing season (SOS) and at the end of the growing season (EOS) differed depending on the time period. On a hemispheric scale, SOS advanced by 5.2 days in the early period (1982–1999) but advanced by only 0.2 days in the later period (2000–2008). EOS was delayed by 4.3 days in the early period, and it was further delayed by another 2.3 days in the later period. The difference between SOS and EOS in the later period was due to less warming during the preseason (January–April) before SOS compared with the magnitude of warming in the preseason (June–September) before EOS. At a regional scale, delayed EOS in later periods was shown. In North America, EOS was delayed by 8.1 days in the early period and delayed by another 1.3 days in the later period. In Europe, the delayed EOS by 8.2 days was more significant than the advanced SOS by 3.2 days in the later period. However, in East Asia, the overall increase in LOS during the early period was weakened in the later period. Admitting regional heterogeneity, changes in hemispheric features suggest that the longer-lasting vegetation growth in recent decades can be attributed to extended leaf senescence in autumn rather than earlier spring leaf-out.

Accurate measurements of regional to global scale vegetation dynamics (phenology) are required to improve models and understanding of inter-annual variability in terrestrial ecosystem carbon exchange and climate iosphere interactions. Since the mid-1980s, satellite data have been used to study these processes. In this paper, a new methodology to monitor global vegetation phenology from time series of satellite data is presented. The method uses series of piecewise logistic functions, which are fit to remotely sensed vegetation index (VI) data, to represent intra-annual vegetation dynamics. Using this approach, transition dates for vegetation activity within annual time series of VI data can be determined from satellite data. The method allows vegetation dynamics to be monitored at large scales in a fashion that it is ecologically meaningful and does not require pre-smoothing of data or the use of user-defined thresholds. Preliminary results based on an annual time series of Moderate Resolution Imaging Spectroradiometer (MODIS) data for the northeastern United States demonstrate that the method is able to monitor vegetation phenology with good success.

为了分析中国农牧交错带植被典型物候期(生长开始日期,生长结束日期和生长季长度)的变化趋势,利用2001-2010年SPOT-VGT NDVI(SPOT-VEGETATION normalized differential vegetation index)数据,基于Savitzky—Golay滤波和动态阈值法,提取了中国北方农牧交错带植被物候期,探讨研究区植被物候期的空间差异和时间变化。研究表明,农牧交错带植被的生长季一般从4月中旬到5月下旬开始,9月下旬至10月下旬结束;从西南部到东北部,植被物候表现出明显的空间差异;农田植被物候期与自然植被略有不同;对研究区10a物候期线性拟合,得出研究区大部分植被覆盖区域生长季开始日期呈现提前趋势,提前日期大约为1～10d左右;除部分地区外,2001-2010年农牧交错带植被生长季结束日期没有明显变化趋势;10a间研究区大部分草地生长季延长,也有一部分地区的生长季出现缩短趋势。研究提取结果与已有的相关研究结果较为一致,可为农牧交错带生态环境评价和保护提供一定的参考。

植被与气候的关系非常密切,植被物候可作为气候变化的指示器。东北地区位于我国最北部,是气候变化的敏感区域,研究该区植被物候对气候变化的响应对阐明陆地生态体统碳循环具有重要意义。利用GIMMS AVHRR遥感数据集得到了东北地区阔叶林、针叶林、草原和草甸4种植被25a(1982-2006年) 的物候时序变化,得出4种植被春季物候都表现出先提前后推迟的现象,秋季物候的变化则比较复杂,阔叶林和针叶林整体上呈现出秋季物候推迟的趋势,草原和草甸则表现为提前-推迟-提前的趋势。应用偏最小二乘(Partial Least Squares)回归分析了该区域植被物候与气候因子之间的关系,结果表明:春季温度与阔叶林、针叶林和草甸春季物候负相关,前一年冬季温度与草原春季物候正相关,降水与植被春季物候的关系有点复杂;4种植被秋季物候与夏季温度均呈正相关,除草原外,其余3种植被秋季物候均与夏季降水负相关。植被春季物候可能主要受温度影响,而秋季物候很可能主要受降水控制。

随着气候变化对农业系统的影响不断加剧，为保障粮食安全，须掌握变化中的自然与人文因素，而农业生态系统中变化最为明显直观的是农作物物候特征，如何提取大区域尺度上农作物物候期以及种植制度的时空格局特征，是评价区域粮食安全的重要因素。基于多时相遥感信息可以有效反映年内/年际农作物物候特征变化的原理，首先利用近10a来的SPOT/VGT\|NDVI时间序列数据，在进行数据序列平滑重构处理基础上，提取了华北地区农作物典型物候期的数量分布与空间格局特征；然后，基于上述物候期的分异特性建立了一年一熟和一年二熟等种植制度类型的遥感识别标志；最后，重点分析了上述种植制度的空间格局及其时间波动特征，并利用农业统计资料对提取结果进行了简单验证。分析结果表明，作物物候期特征的数量分布和空间分布在不同生长季均具有显著差异，直接体现了与外界环境条件（诸如区域温度、降水和光照等）的匹配程度以及作物类型自身的生长特征；从主要种植制度空间分布来看，华北地区南部地区农作物类型以夏收作物和二熟秋收作物为主，与之对应的农田种植制度以一年两熟为主；华北地区北部主要为一熟制区域，作物类型以一年一熟秋收作物为主，作物种植制度空间分布随着纬度递减呈现出简单到复杂的总体趋势；从近10a的种植情况来看，一年一熟作物种植面积最大，年际变化幅度亦较大，一年二熟的夏收作物种植比例次之，而年际变幅最小，二熟秋收作物比例最低，其年际变幅居中。研究中亦提出，在进一步加强多时相遥感技术监测大区域农业生态系统动态变化的同时，亦需深入探讨作物物候特征及种植制度变化的驱动因素及其对国家粮食安全的影响。

【目的】NDVI时序数列能够模拟植物的生长过程，反映其生长状况。目前重建NDVI时序数列的方法有很多，由于模型和参数的不同导致结果存在不确定性以及偏差。本研究旨在对比3种模型（Whittaker平滑、HANTS和Savitzky-Golay滤波）在物候提取和复种指数提取中的应用，以探讨各模型的优缺点。【方法】采用16 d间隔的MODIS MOD13Q1 2000&mdash;2012年陕西地区影像，利用3种模型拟合重建NDVI时序数列。首先，将研究区划分为3个气候区，每区分别选择林地和耕地两个采样点，视觉比较各采样点3种模型拟合效果。其次，通过均方根误差、相关系数和信噪比对比各模型拟合精度，并探讨不同植被类型之间拟合精度的差异。然后，采用动态阈值法提取13年植被物候参数（生长开始日期SOS、生长结束日期EOS、生长周期LOS），对比模型提取不同植被类型物候参数均值和标准差的差异。最后，利用二次差分算法和提取规则获取陕西13年复种指数，对比3种模型提取和统计年鉴计算复种指数之间的差异。【结果】Savitzky-Golay滤波拟合精度较高，复种指数提取精度较高，但是提取物候参数方面存在较大误差；HANTS提取物候参数效果较好，但参数设置复杂以及精度较差；Whittaker平滑参数设置简单，能有效降低原始影像的信噪比，在精度和物候参数提取均表现良好；均方根误差和相关系数作为精度检验的标准，二者存在负相关，相关系数比均方根误差更灵敏。【结论】Whittaker平滑能够很好地平衡NDVI时序数列的保真度和粗糙度，在提取物候参数方面表现良好，在提取复种指数方面还有待进一步研究。

根据全国609个气象站1971-2000年的日气象观测资料,遵循地带性与非地带性相结合、发生同一性与区域气候特征相对一致性相结合、综合性和主导因素相结合、自下而上和自上而下相结合、空间分布连续性与取大去小等5个基本原则,在充分吸纳已有气候区划基本理论与区划方法的基础上,参照中国科学院《中国自然地理》编辑委员会制定的气候区划三级指标体系,对我国气候进行重新区划 结果将我国划分为12个温度带、24个干湿区、56个气候区。与先前区划方案相比发现：20世纪70年代以来,中国气候带、区的总体格局并未发生明显变化,但一些重要的气候分界线却出现了一定程度的移动。其中亚热带北界与暖温带北界均出现了北移,北方地区的半湿润与半干旱分界线也出现了不同程度的东移与南扩,同时中温带、暖温带、北亚热带和中亚热带的三级气候区也出现了一定程度的变动 这种变化可能主要是因为20世纪80年代以后我国大多数地区出现不同程度的增暖及北方一些区域出现干旱化而引起的 且与本区划所采用的资料站点和部分区划原则有一定更新有关。

<p>以藏北地区2007~2009年MODIS 16 d合成的NDVI时间序列为例,介绍了基于TIMESAT 2.3软件的3种主要拟合算法&mdash;&mdash;非对称高斯函数(AG)拟合、双Logistic曲线(D-L)拟合和Savitzky-Golay(S-G)滤波法的基本原理和实现流程；重点从拟合重建NDVI时间序列对原始NDVI值上包络线的拟合效果及保持原始高质量NDVI点值真实值的程度两个方面,分析比较3种算法的特点。结果表明：① 3种拟合算法均能不同程度提高整个区域的NDVI平均值,AG与D-L拟合法处理后的NDVI时间序列与原始NDVI曲线的整体特征较S\|G滤波方法更加吻合；② AG与D\|L拟合重建的NDVI时间曲线在生长季峰期高于上包络线,S-|G滤波法处理结果低于上包络线,3种方法中AG拟合结果与上包络线最为接近；③ 在保持原始高质量NDVI值真实性方面,AG与D\|L拟合法处理结果相似,除生长季曲线的峰期外,均优于Savitzky-Golay滤波法。该研究结论为基于NDVI时间序列进行陆地系统生态环境各方面研究中数据去噪预处理的方法选择提供参考。</p>

This letter describes the Harmonic ANalysis of Time Series (HANTS) algorithm. It performs two tasks: (i) screening and removal of cloud affected observations; and (ii) temporal interpolation of the remaining observations to reconstruct gapless images at a prescribed time. HANTS was applied to 36 AVHRR 10-days-maximum-NDVI composites covering most of Europe. The results show that cloud affected data are recognized successfully and replaced. Up to half the data points were rejected with no consequence for the successful reconstruction of seasonal NDVI profiles.

Although the Normalized Difference Vegetation Index (NDVI) time-series data, derived from NOAA/AVHRR, SPOT/VEGETATION, TERRA or AQUA/MODIS, has been successfully used in research regarding global environmental change, residual noise in the NDVI time-series data, even after applying strict pre-processing, impedes further analysis and risks generating erroneous results. Based on the assumptions that NDVI time-series follow annual cycles of growth and decline of vegetation, and that clouds or poor atmospheric conditions usually depress NDVI values, we have developed in the present study a simple but robust method based on the Savitzky olay filter to smooth out noise in NDVI time-series, specifically that caused primarily by cloud contamination and atmospheric variability. Our method was developed to make data approach the upper NDVI envelope and to reflect the changes in NDVI patterns via an iteration process. From the results obtained by applying the newly developed method to a 10-day MVC SPOT VGT-S product, we provide optimized parameters for the new method and compare this technique with the BISE algorithm and Fourier-based fitting method. Our results indicate that the new method is more effective in obtaining high-quality NDVI time-series.

基于遥感的植被长时序变化特征是植被生态学研究的核心领域, 也是全球变化研究的重点方向。AVHRR、SPOT VGT和MODIS是当前研究植被长时序趋势变化的主要数据源。海量数据不断积累的同时, 植被长时序趋势特征研究方法却缺乏对比评价和分析。当前常用的方法有代数运算法、傅里叶变换、主成分分析、小波变换法、回归分析法和相关系数分析法等。在对各种方法评述和分析的基础上, 重点讨论和对比了主流方法中的回归分析法和相关系数分析与新兴方法Sen＋Mann-Kendall法。结果表明, Sen＋Mann-Kendall能克服主流方法的不足, 不需要数据服从某一特定分布, 并且对数据的误差具有较强的抵抗能力。

Climate change has caused advances in spring phases of many plant species. Theoretically, however, strong warming in winter could slow the fulfillment of chilling requirements, which may delay spring phenology. This phenomenon should be particularly pronounced in regions that are experiencing rapid temperature increases and are characterized by highly temperature-responsive vegetation. To test this hypothesis, we used the Normalized Difference Vegetation Index ratio method to determine the beginning, end, and length of the growing season of meadow and steppe vegetation of the Tibetan Plateau in Western China between 1982 and 2006. We then correlated observed phenological dates with monthly temperatures for the entire period on record. For both vegetation types, spring phenology initially advanced, but started retreating in the mid-1990s in spite of continued warming. Together with an advancing end of the growing season for steppe vegetation, this led to a shortening of the growing period. Partial least-squares regression indicated that temperatures in both winter and spring had strong effects on spring phenology. Although warm springs led to an advance of the growing season, warm conditions in winter caused a delay of the spring phases. This delay appeared to be related to later fulfillment of chilling requirements. Because most plants from temperate and cold climates experience a period of dormancy in winter, it seems likely that similar effects occur in other environments. Continued warming may strengthen this effect and attenuate or even reverse the advancing trend in spring phenology that has dominated climate-change responses of plants thus far.

bProblem statement:/b Leaf phenology describes the seasonal cycle of leaf functioning and is essential for understanding the interactions between the biosphere, the climate and biogeochemical cycles. This study aimed to quantify changes in plant phenology of deciduous broadleaf forests between the years 1982-1999 and investigate the relationships between the onset dates of phenology and climatic factors. bApproach:/b We studied the climate changes effected on the growing season duration in vegetation of Iran, using the AVHRR/NDVI biweekly time-series data collected from 1982-1999 and concurrent mean temperature and precipitation data. The first estimated fastest changes of NDVI corresponded to the vegetation green-up and dormancy from the seasonal cycle of NDVI during 1982-1999. The onset dates of vegetation green-up and dormancy were determined based on the estimated rates and the NDVI seasonal cycles. bResults:/b The results showed that over the study period, the growing season duration has lengthened by 0.94 days yearsup-1/sup in study region. The green-up of vegetation has advanced in the spring by 0.63 days yearsup-1/sup and the dormancy delayed in autumn by 0.32 days yearsup-1/sup. The onset date of green-up for all vegetation types negatively correlated with mean preseason temperature for almost all the preseason periods significant, suggesting that the warmer winters probably benefit an earlier green-up the following spring. bConclusion:/b Based on NOAA/AVHRR NDVI biweekly time-series data and concurrent climate information, it was estimated that the growing season duration of Irans vegetation was significantly lengthened, primarily through an earlier green-up and a later dormancy during the period of 1982-1999.

<p>利用MODIS归一化植被指数(NDVI)对2001-2013年毛乌素沙地植被物候的时空变化进行了研究,并分析了物候与海拔、气候的关系。结果显示:(1)毛乌素沙地植被生长开始期(SOG)集中在第90～156天,生长结束期(EOG)在第245～323天,生长季长度(LOG)118～200 d;从东到西,SOG逐渐推迟,LOG逐渐缩短;随着海拔的升高,SOG显著推迟,EOG提前,LOG显著缩短。(2)2001-2013年,毛乌素沙地植被SOG明显提前,变化幅度为9 d/10a(<em>R</em>=-0.46,<em>p</em>=0.06),EOG和LOG分别呈提前和延长趋势,但变化都不显著。(3)研究区植被物候与温度的相关性不明显,但较多受降水量的影响,SOG与春季降水量的相关系数为-0.58(<em>p</em>=0.02);EOG与秋季降水量的相关系数为0.42(<em>p</em>=0.07);LOG与秋季降水量的相关系数为0.48(<em>p</em>=0.05)。</p>

基本地貌类型划分是陕西省地理国(省)情监测试点需要解决的重点问题之一。以数字高程模型为基础数据,根据地貌划分基本原理,将陕西省划分为6个典型地貌区。探讨省域地貌区域划分的方法和指标,确定符合陕西省地方特点的地貌类型系统,并介绍根据省域地貌特点选取划分指标的方法。以此为依据完成陕西省基本地貌区域的定量划分,并从划分成果的位置关系、统计数据和形态成因等方面讨论划分方法和成果的合理性。

植被物候是陆地生态系统对全球气候变化响应的最佳指示器,研究其时空变化对深入理解陆面水热过程、碳循环过程及预测陆地生态系统的时空变化具有重要意义。本文采用2001-2010年MODIS MOD09A1产品,通过引入MOD09A1的时间控制层DOY(Day of Year)提高EVI的时间精度;采用最大变化速率法和阈值法相结合提取秦岭森林物候期。结果表明,随着水热条件变化,由低海拔至高海拔,东南向西北,生长季始期(Start of Growth Season,SOG)逐渐推迟,集中在第81~120 d(即从3月下旬-4月末);生长季末期(End of Growth Season,EOG)逐渐提前,集中在第270~311 d(10月初-11月上旬);生长季长度(Length of Growth Season,LOG)逐渐缩短,集中在150~230 d。秦岭森林物候期与海拔关系密切,海拔每升高100 m,SOG推迟2 d,EOG提前1.9 d,LOG缩短3.9 d。2001-2010年,森林SOG提前、EOG延后和LOG延长主要分布于秦岭中高海拔区;SOG延后、EOG提前和LOG缩短主要分布在海拔1000 m以下部分区域。高海拔区物候的年际变化要比低海拔区复杂,2000 m以上区域SOG提前、EOG提前、LOG缩短。上述研究结果量化了不同海拔梯度森林的物候差异,揭示了近10年秦岭森林物候的时空格局,可为秦岭地区生态环境评价和保护提供科学依据。

A double logistic function has been used to describe global inventory mapping and monitoring studies (GIMMS) normalized difference vegetation index (NDVI) yearly evolution for the 1981 to 2003 period, in order to estimate land surface phenology parameter. A principal component analysis on the resulting time series indicates that the first components explain 36, 53 and 37% of the variance for the start, end and length of growing season, respectively, and shows generally good spatial homogeneity. Mann endall trend tests have been carried out, and trends were estimated by linear regression. Maps of these trends show a global advance in spring dates of 0.38 days per year, a global delay in autumn dates of 0.45 days per year and a global increase of 0.8 days per year in the growing seasons validated by comparison with previous works. Correlations between retrieved phenological parameters and climate indices generally showed a good spatial coherence.

基于植物物候的遥感监测对于研究植被对气候变化的响应具有重要的科学价值。本文在阐述植物物候遥感监测原理及其通用技术流程的基础上,分别从植被类型及其所处的地理条件、遥感数据源及其预处理、植物物候遥感识别方法和植物物候遥感监测结果评价4个方面分析了影响植物物候遥感监测精度的因素,并针对当前研究中存在的不足,探讨了提高植物物候遥感监测精度的可行性途径,即建立高分辨率的近地面遥感定点观测及数据共享网络,发展普适性更强的卫星遥感时序数据去噪及植被指数曲线重建方法,寻求稳定性更高的植物物候期遥感识别方法,探索综合运用地面观测、遥感监测与模型模拟实现物候观测空间尺度拓展的可能性。