利用NOAA NDVI和MSAVI遥感监测中国北方不同纬度带植被生长季变化

将中国北方13个省按纬向划分为5个区域：32°～36°N（区域Ⅰ）、36°～40°N（区域Ⅱ）、40°～44°N（区域Ⅲ）、44°～48°N（区域Ⅳ）和48°～52°N（区域Ⅴ）,然后利用Savitzky-Golay滤波算法平滑了1982～1999年NOAA/AVHRR NDVI和MSAVI时间序列影像,基于经验正交函数（EOF）分析提取了不同区域植被NDVI和MSAVI主分量,估测了1982～1999年中国北方不同纬度带的植被生长季开始、结束和长度,最后对1982～1999年不同区域的生长季参数进行了线性拟合,分析了不同区域的植被生长季变化趋势.研究表明,不同纬度带的植被生长季开始日期均表现出不同程度的提前趋势,区域Ⅳ的植被生长季开始提前趋势最大;生长季结束日期呈现推迟的趋势,区域Ⅱ的植被活动结束日期的推迟趋势最大,而区域Ⅲ最小.整个生长季长度呈延长趋势,延长日期在10 d以上.     

阴山北麓农牧交错带植被变化及其对气候变化的响应

利用1982—2003年8kmNASA/GIMMS半月合成的植被指数(NDVI)数据和同期气候数据,分析了阴山北麓地区农牧交错带的NDVI年平均值、年累积值距平的动态变化以及NDVI年平均值与年平均温度和年降水的时间序列相关关系。结果表明:1982—2003年NDVI年平均值呈现逐渐增高趋势,1990年以后的NDVI年平均值明显高于以前;NDVI在空间变化上表现为牧业区<农牧区<农业区,说明农业区NDVI受气候的影响程度较牧业区和农牧区弱;研究区温度对植被指数的影响没有明显的规律性,但降水与植被指数呈正相关,降水的多寡决定了植被的生长状况。     

利用遥感信息研究西藏地区主要植被年内和年际变化规律

利用1982～2000年NOAA-AVHRR月合成NDVI遥感资料和相关气象台站数据对我国西藏地区的稀疏草地、浓密草地和Tebit森林等主要植被的变化进行了初探。利用月合成NDVI的多年平均值分析了植被指数年内季节性变化规律及其与气候因子的关系,利用多年月合成NDVI的标准差描述了NDVI年际间波动情况。结果表明,在西藏地区,浓密草地和Tebit森林的NDVI植被指数年内变化规律呈明显的季节性,而稀疏草地则不明显;在年际变化方面,浓密草地月合成NDVI值波动幅度最大,Tebit森林次之,稀疏草地最小,且波动幅度较大的月份集中在NDVI值较高的植被生长季节6～10月份。     

陕西省1982—2015 NDVI时空分布特征及其与气候因子相关性

基于1982—2015年8 km的GIMMS NDVI和气象资料,结合陕西省土地利用类型数据,利用斜率分析以及相关分析等方法,对陕西省近34 a来植被指数NDVI的时空分布特征、变化规律及其与气候因子之间的相关性进行了深入研究,得到如下主要结论:(1)1982—2015年陕西省年均NDVI呈现出明显南高北低的地理特征,年均NDVI分布的空间差异性与下垫面类型密切相关,年均NDVI呈轻度上升趋势,局部地区(如渭河流域)增长尤为明显。(2)NDVI年际变化具有阶段性明显特征,1982—1990间增长显著,1991—2000和2001—2015年两段时期增长较为缓慢;NDVI年内变化差异明显,夏季NDVI最高,冬季最低,春季上升趋势最为明显。月均NDVI变化曲线呈单峰型,6—8月NDVI最高。(3)研究区NDVI与同期降水之间的响应最为明显,而草地、农地相比于整体区域以及林地与滞后1月的气温敏感性高于同期。     

西南地区不同植被类型归一化植被指数与气候因子的相关分析

基于中国西南地区1982—2006年的归一化植被指数(NDVI)遥感数据集和气象数据,运用GIS技术对年均气温、年降水量和干旱指数进行插值,分析了西南地区不同植被类型(沼泽、灌丛、草丛、草原、草甸、针叶林、阔叶林、高山植被、栽培植被)NDVI的年际变化及其与气候因子的相关性.结果表明:研究期间,西南地区NDVI、年均气温、年降水量总体呈上升趋势,其中,年均气温的上升趋势达极显著水平,干旱指数则呈下降趋势;在9种植被类型中,沼泽和草丛NDVI呈下降趋势,且草丛的下降趋势达显著水平,其他7种植被类型的NDVI均呈上升趋势,且针叶林、草甸和高山植被的NDVI上升趋势达显著水平,灌丛NDVI呈极显著上升趋势.9种植被类型所在地区的年均气温均显著上升;年降水量的变化均不显著;沼泽、草丛和栽培植被所在地区的干旱指数呈上升趋势,草甸和高山植被所在地区的干旱指数显著下降,其他4种植被类型所在地区的干旱指数呈不明显的下降趋势.研究区灌丛和针叶林NDVI与年均气温呈显著正相关,灌丛和草甸NDVI与干旱指数呈显著负相关.在保持其他2个气候因子不变的情况下,针叶林、阔叶林、高山植被NDVI与年均气温的相关性最大,草丛NDVI与年降水...     

1983～1992年中国陆地NDVI变化的气候因子驱动分析

利用1983－1992年NOAA／AVHRR逐月的归一化植被指数（NDVI）资料和中国国家气象局全国160个基本标准气象站的月均温和降雨数据,探讨气温,降水对中国植NDVI动态变化驱动作用。首先计算了NDVI与气温,降水偏相关和复相关系数,研究了中国植被NDVI变化的气候因子驱动的区域分异规律,并据此,对中国植被NDVI变化的气候因子驱动进行了分区,共分出4个一级区,6个二级区和14个三级区,进一步表明了中国植被NDVI变化气候因子驱动的区域差异。     

基于ICEEMDAN方法的黄土高原植被覆盖变化及其对气候变化的响应

地理数据和遥感数据的长期序列中包含噪声和周期性波动信息。本研究基于ICEEMDAN方法对黄土高原1982—2015年归一化植被指数(NDVI)、降雨和温度进行逐像元分解,分解后得到的残差项减少了原始数据中的噪声和周期性波动,并利用残差项研究NDVI的变化趋势以及NDVI与气候因子之间的关系。结果表明: 1982—2015年,黄土高原NDVI以上升为主,残差项NDVI变化趋势的显著性(95.9%)大于原始NDVI变化趋势的显著性(72.3%),并且存在一定的空间差异性。温度和降雨的变化可以在很大程度上解释植被覆盖的变化。其中,温度与黄土高原NDVI之间呈极显著正相关的区域占83.7%,极显著负相关区域占13.9%;降雨与黄土高原NDVI之间呈极显著正相关的区域占54.4%,极显著负相关区域占37.2%。黄土高原植被对气候变化的响应存在明显的空间差异性,不同气候因子对不同植被覆盖类型的影响程度不同。总体上,黄土高原生长季不同植被与温度之间的相关性强于降水,温度是影响黄土高原植被覆盖变化的主要因素。     

太原南郊区越冬猛禽群落生态的初步观察

鸟类群落生态的研究,国外早在1957年已着手进行。我国自1980年以来亦先后见有报道,但对猛禽群落生态的研究甚少。我们于1982年～1984年的1～4月和9～12月,在太原市南郊区(东经112°28′～112°39′,北纬37°36′～37°51′),对越冬猛禽的群落结构特征、季节活动规律以及与环境条件的相互关系等进行了初步观察。现报道如下。工作区的自然概况详见刘焕金等(1982),本文不再赘述。一、工作方法沿汾河河漫滩(大马村～小店镇)5公里隔日观察候鸟季节迁徙。每次观察在春、秋季8～11时进行。依首次发现和最后遇见的时间确定其越冬居留期。根据本区牛…     

近20年藏北地区AVHRR NDVI与气候因子的关系

利用藏北那曲地区1981~2001年NOAA/AVHRR的旬合成NDVI资料和6个站的逐日气象资料,分析了(归一化指数NDVI)的年内和年际变化规律以及NDVI与8个气候要素的相关关系,主要结论:影响NDVI年变化最显著的气候因子是温度,其中水汽压与NDVI的相关程度明显大于降水量;日照时数与NDVI呈负相关;NDVI与日照时数的滞后时间约0~10d,与风速没有滞后现象,与潜在蒸散、温度、水汽压和降水约20~40d;影响NDVI年际变化最显著的气候因子是潜在蒸散量。     

基于MODIS/NDVI的陕北地区植被动态监测与评价

陕北地区从1999年退耕还林试点工程实施以来,区域植被发生很大变化,退耕前后植被动态变化监测成为退耕还林工程评价任务之一,而当前植被恢复监测评价的难点在于如何确定哪些是由于退耕而引起的植被变化。针对此问题,选取适合陕北地区植被变化监测的MODIS/NDVI数据,利用均值变化及趋势分析方法,从不同土地利用/覆被类型和不同坡度植被指数动态变化两方面分析退耕还林对植被动态变化的影响。结论如下:(1)陕北地区平均NDVI从2000-2008年呈现较明显的增长趋势,坡耕地和草地NDVI增长速度相对较快;(2)趋势分析结果显示,陕北绝大部分地区植被恢复良好,植被指数呈明显改善的面积占整个地区面积的64.96%,中度改善占18.58%,其中又以坡耕地、草地植被明显改善面积分别占陕北地区明显改善面积的45.43%和17.10%,坡耕地对陕北地区植被明显改善面积贡献最大;(3)7 15°、15 25°及25 35°坡度植被明显改善面积分别占总改善面积的39.91%、25.81%、2.28%,其中7 25°坡度植被明显改善面积占总面积的65.72%;(4)基于陕北地区近年气候呈暖干化发展趋势,同期降雨并未呈现显著变化,说明非气候因子中退耕还林等人为因素是引起NDVI增长的主要因素,退耕还林对于陕北地区植被恢复有明显促进作用。     

1982-2012年中亚地区植被时空变化特征及其与气候变化的相关分析

干旱区植被生态系统对气候变化极为敏感，并且干旱区的植被变化研究对全球碳循环具有重要意义。然而近几十年来，中亚干旱区植被对气候变化的响应机制尚不甚明朗。利用归一化植被指数NDVI数据集和MERRA（Modern-Era Retrospective Analysis for Research and Applications）气象数据，采用经验正交函数（EOF，Empirical Orthogonal Function）和最小二乘法等方法系统分析了31a（1982-2012年）来中亚地区NDVI在不同时间尺度的时空变化特征。进一步分析和研究NDVI与气温和降水的相关性，结果表明：1982-2012年，中亚地区年NDVI总体呈现缓慢增长趋势，而1994年以后年NDVI呈现明显下降趋势，尤其在哈萨克斯坦北部草原地区下降趋势尤为突出。这可能是由于过去30年间，中亚地区降水累计量的持续减少造成的。NDVI的季节变化表明春季NDVI增长最为明显，冬季则显著下降。与平原区相比，中亚山区的NDVI值增长幅度最大，并且山区年NDVI与季节NDVI呈现显著增加趋势（P < 0.05）。中亚地区年NDVI与年降水量正相关，而年NDVI与气温变化存在弱负相关。年NDVI和气温的正相关中心在中亚南部地区，负相关中心则出现在哈萨克斯坦的西部和北部地区；NDVI和降水的相关性中心刚好与气温相反。此外，在近30年间的每年6月至9月，中亚地区NDVI与气温存在近一个月的时间延迟现象。本研究为中亚干旱区生态系统变化和中亚地区碳循环的估算提供科学依据。     

1982-2009年东北多年冻土区植被净初级生产力动态及其对全球变化的响应

东北多年冻土区作为高纬度寒区之一,对全球变化较敏感.本文基于AVHRR和MODIS两种遥感数据源的归一化植被指数,应用CASA模型对1982-2009年东北多年冻土区植被净初级生产力(NPP)进行模拟.结果表明:1982-2009年,东北多年冻土区年均气温、年太阳辐射总量和年日照时数显著上升,年降水量显著下降,CO2浓度及其年增长率显著增大;植被年NPP呈显著的先增加后降低趋势,变化分异节点在1998年.研究期间,东北多年冻土区植被年均NPP总量为623 g C·m-2,植被年NPP空间分布差异明显.降水是该区生长季植被生长的主要影响因子,植被NPP对气候变化响应的空间异质性明显.土地利用变化通过改变土地覆被状况使植被NPP发生变化,影响了植被NPP的时空分布特征,植被NPP与CO2浓度呈显著正相关.多年冻土退化对植被NPP的影响随着各区域环境的不同而有所差异.多年冻土区植被NPP与年均地温呈显著正相关,与年最大冻土深度呈负相关.     

1982-2009年东北多年冻土区植被净初级生产力动态及其对全球变化的响应

东北多年冻土区作为高纬度寒区之一,对全球变化较敏感.本文基于AVHRR和MODIS两种遥感数据源的归一化植被指数,应用CASA模型对1982-2009年东北多年冻土区植被净初级生产力（NPP）进行模拟.结果表明： 1982-2009年,东北多年冻土区年均气温、年太阳辐射总量和年日照时数显著上升,年降水量显著下降,CO₂浓度及其年增长率显著增大;植被年NPP呈显著的先增加后降低趋势,变化分异节点在1998年.研究期间,东北多年冻土区植被年均NPP总量为623 g C·m^-2,植被年NPP空间分布差异明显.降水是该区生长季植被生长的主要影响因子,植被NPP对气候变化响应的空间异质性明显.土地利用变化通过改变土地覆被状况使植被NPP发生变化,影响了植被NPP的时空分布特征.植被NPP与CO₂浓度呈显著正相关.多年冻土退化对植被NPP的影响随着各区域环境的不同而有所差异.多年冻土区植被NPP与年均地温呈显著正相关,与年最大冻土深度呈负相关.     

Higher northern latitude normalized difference vegetation index and growing season trends from 1982 to 1999

Normalized difference vegetation index data from the polar-orbiting National Oceanic and Atmospheric Administration meteorological satellites from 1982 to 1999 show significant variations in photosynthetic activity and growing season length at latitudes above 35°N. Two distinct periods of increasing plant growth are apparent: 1982–1991 and 1992–1999, separated by a reduction from 1991 to 1992 associated with global cooling resulting from the volcanic eruption of Mt. Pinatubo in June 1991. The average May to September normalized difference vegetation index from 45°N to 75°N increased by 9% from 1982 to 1991, decreased by 5% from 1991 to 1992, and increased by 8% from 1992 to 1999. Variations in the normalized difference vegetation index were associated with variations in the start of the growing season of –5.6, +3.9, and –1.7 days respectively, for the three time periods. Our results support surface temperature increases within the same period at higher northern latitudes where temperature limits plant growth. Received: 25 October 2000 / Revised: 20 August 2001 / Accepted: 22 August 2001     

雅鲁藏布江流域NDVI变化与风沙化土地演变的耦合关系

运用1982-2010年的两种NDVI数据集（Pathfinder AVHRR和SPOT VEGETATION）,以及1975、1990、2000和2008年4期遥感数据,通过GIS技术、人工目视解译和灰色关联分析方法,研究了雅鲁藏布江流域NDVI变化和风沙化土地演变的耦合关系,结合1957-2007年降水和气温逐日气象资料,探讨了气候变化对其耦合关系的影响。结果表明：（1）流域内1982-2010年NDVI的年际变化总体上呈波动式增长的趋势。NDVI空间分布呈现由下游向中上游逐渐降低的趋势,以米林宽谷最大、马泉河宽谷最小。（2）2008年流域内共有风沙化土地273 697.54hm²,呈现由江源区马泉河宽谷向中下游递减的趋势。1975-2008年流域内风沙化土地呈缓慢增长趋势,以1990-1999年增长率最高,2000-2008年的增长率最小。（3）对于NDVI年变化和植被生长季（7-9月份）的变化,马泉河宽谷受平均气温的影响最大,日喀则宽谷和山南宽谷受年降水量的影响最大;米林宽谷NDVI的年变化受风沙化土地扩展的影响最大,植被生长季变化受年降水量的影响最大。（4）不同宽谷段NDVI与风沙化土地年变化的关联度自下游向中上游呈总体减小的趋势。流域尺度NDVI植被生长季变化主要受平均气温和年降水量的影响,非植被生长季（10月-翌年6月）变化主要受风沙化土地扩展的影响。     

The greening and browning of Alaska based on 1982–2003 satellite data

Aim To examine the trends of 1982–2003 satellite‐derived normalized difference vegetation index (NDVI) values at several spatial scales within tundra and boreal forest areas of Alaska. Location Arctic and subarctic Alaska. Methods Annual maximum NDVI data from the twice monthly Global Inventory Modelling and Mapping Studies (GIMMS) NDVI 1982–2003 data set with 64‐km² pixels were extracted from a spatial hierarchy including three large regions: ecoregion polygons within regions, ecozone polygons within boreal ecoregions and 100‐km climate station buffers. The 1982–2003 trends of mean annual maximum NDVI values within each area, and within individual pixels, were computed using simple linear regression. The relationship between NDVI and temperature and precipitation was investigated within climate station buffers. Results At the largest spatial scale of polar, boreal and maritime regions, the strongest trend was a negative trend in NDVI within the boreal region. At a finer scale of ecoregion polygons, there was a strong positive NDVI trend in cold arctic tundra areas, and a strong negative trend in interior boreal forest areas. Within boreal ecozone polygons, the weakest negative trends were from areas with a maritime climate or colder mountainous ecozones, while the strongest negative trends were from warmer basin ecozones. The trends from climate station buffers were similar to ecoregion trends, with no significant trends from Bering tundra buffers, significant increasing trends among arctic tundra buffers and significant decreasing trends among interior boreal forest buffers. The interannual variability of NDVI among the arctic tundra buffers was related to the previous summer warmth index. The spatial pattern of increasing tundra NDVI at the pixel level was related to the west‐to‐east spatial pattern in changing climate across arctic Alaska. There was no significant relationship between interannual NDVI and precipitation or temperature among the boreal forest buffers. The decreasing NDVI trend in interior boreal forests may be due to several factors including increased insect/disease infestations, reduced photosynthesis and a change in root/leaf carbon allocation in response to warmer and drier growing season climate. Main conclusions There was a contrast in trends of 1982–2003 annual maximum NDVI, with cold arctic tundra significantly increasing in NDVI and relatively warm and dry interior boreal forest areas consistently decreasing in NDVI. The annual maximum NDVI from arctic tundra areas was strongly related to a summer warmth index, while there were no significant relationships in boreal areas between annual maximum NDVI and precipitation or temperature. Annual maximum NDVI was not related to spring NDVI in either arctic tundra or boreal buffers.     

Consistent response of vegetation dynamics to recent climate change in tropical mountain regions

Global climate change has emerged as a major driver of ecosystem change. Here, we present evidence for globally consistent responses in vegetation dynamics to recent climate change in the world's mountain ecosystems located in the pan‐tropical belt (30°N–30°S). We analyzed decadal‐scale trends and seasonal cycles of vegetation greenness using monthly time series of satellite greenness (Normalized Difference Vegetation Index) and climate data for the period 1982–2006 for 47 mountain protected areas in five biodiversity hotspots. The time series of annual maximum NDVI for each of five continental regions shows mild greening trends followed by reversal to stronger browning trends around the mid‐1990s. During the same period we found increasing trends in temperature but only marginal change in precipitation. The amplitude of the annual greenness cycle increased with time, and was strongly associated with the observed increase in temperature amplitude. We applied dynamic models with time‐dependent regression parameters to study the time evolution of NDVI–climate relationships. We found that the relationship between vegetation greenness and temperature weakened over time or was negative. Such loss of positive temperature sensitivity has been documented in other regions as a response to temperature‐induced moisture stress. We also used dynamic models to extract the trends in vegetation greenness that remain after accounting for the effects of temperature and precipitation. We found residual browning and greening trends in all regions, which indicate that factors other than temperature and precipitation also influence vegetation dynamics. Browning rates became progressively weaker with increase in elevation as indicated by quantile regression models. Tropical mountain vegetation is considered sensitive to climatic changes, so these consistent vegetation responses across widespread regions indicate persistent global‐scale effects of climate warming and associated moisture stresses.     

Variability of the start of the growing season in Fennoscandia, 1982–2002

Fennoscandia is characterized by a large degree of climatic diversity. Vegetation phenology may respond differently to climate change according to the climatic gradients within the region. To map the annual and spatial variability of the start of the growing season (SOS) in Fennoscandia, the twice-monthly GIMMS-NDVI satellite dataset was used. The data set has an 8 × 8 km² spatial resolution and covers the period from 1982 to 2002. The mapping was done by applying pixel-specific threshold values to the NDVI data. These threshold values were determined form surface phenology data on birch (Betula sp.). Then, we produced NDVI based maps of SOS for each of the 21 years. Finally, the time differences between the SOS and the last day of snow cover, as well as dates of passing different temperatures, were analyzed for 21 meteorological stations. The analyses showed that 1985 was the most extreme year in terms of late SOS. In terms of early SOS, the year 1990 was by far the most extreme. Locally, the SOS has an average range of 1 month between the earliest and latest recorded SOS, with a trend towards a bigger range in the oceanic parts. The results indicate that a 1°C increase in spring temperatures in general corresponds to an advancement of 5–6 days in SOS. However, there is a clear trend according to the degree of oceanity, with a 1°C increase in the most oceanic parts corresponding roughly to 7–9 days earlier SOS, compared to less than 5 days earlier in the continental parts.