Assessment of vegetation cover changes and the contributing factors in the Al-Ahsa Oasis using Normalized Difference Vegetation Index(NDVI)

The abandonment of date palm grove of the former Al-Ahsa Oasis in the eastern region of Saudi Arabia has resulted in the conversion of delicate agricultural area into urban area.The current state of the oasis is influenced by both expansion and degradation factors.Therefore,it is important to study the spatiotemporal variation of vegetation cover for the sustainable management of oasis resources.This study used Landsat satellite images in 1987,2002,and 2021 to monitor the spatiotemporal variation of vegetation cover in the Al-Ahsa Oasis,applied multi-temporal Normalized Difference Vegetation Index(NDVI)data spanning from 1987 to 2021 to assess environmental and spatiotemporal variations that have occurred in the Al-Ahsa Oasis,and investigated the factors influencing these variation.This study reveals that there is a significant improvement in the ecological environment of the oasis during 1987–2021,with increase of NDVI values being higher than 0.10.In 2021,the highest NDVI value is generally above 0.70,while the lowest value remains largely unchanged.However,there is a remarkable increase in NDVI values between 0.20 and 0.30.The area of low NDVI values(0.00–0.20)has remained almost stable,but the region with high NDVI values(above 0.70)expands during 1987–2021.Furthermore,this study finds that in 1987–2002,the increase of vegetation cover is most notable in the northern region of the study area,whereas from 2002 to 2021,the increase of vegetation cover is mainly concentrated in the northern and southern regions of the study area.From 1987 to 2021,NDVI values exhibit the most pronounced variation,with a significant increase in the“green”zone(characterized by NDVI values exceeding 0.40),indicating a substantial enhancement in the ecological environment of the oasis.The NDVI classification is validated through 50 ground validation points in the study area,demonstrating a mean accuracy of 92.00%in the detection of vegetation cover.In general,both the user’s and producer’s accuracies of NDVI classification are extremely high in 1987,2002,and 2021.Finally,this study suggests that environmental authorities should strengthen their overall forestry project arrangements to combat sand encroachment and enhance the ecological environment of the Al-Ahsa Oasis.

基于无人机多光谱NDVI值估测玉米产量

【目的】研究基于UAS-8无人机采集数据,运用归一化植被指数(Normalized Difference Vegetation Index)模型估测玉米产量,为大田无人机多光谱预测玉米产量提供理论依据。【方法】以新疆18份春播玉米为研究对象,获取开花期多光谱图像,经过辐射校正、大气校正、建立掩膜、提取NDVI图,计算植被覆盖率,得到区光谱反射率和归一化植被指数实际数值,将NDVI值与田间实测产量值进行模型拟合。【结果】幂函数Y=23411.46-10997.99/X(R^(2)=0.4886),二次函数为Y=39003.00-117963.03X+103130.25X 2(R^(2)=0.562),正反比函数(Inverse Proportional Function)为Y 2=2840.5 X/(1-X)(R^(2)=0.495),利用偏最小二乘回归(Partial Least Squares Regression),其线性函数Y=24458.22X-9620.55(R^(2)=0.521)。【结论】在数值0.5~0.8区间,NDVI与玉米产量具有较高的相关性,线性函数方程NDVI值可预测玉米的产量。

高寒气候区生长季NDVI与昼夜不对称增温的Copula分析

利用1982—2016年的青海地区归一化植被指数和气象数据,基于马尔科夫链蒙特卡罗的Copula函数方法,深入探索昼夜增温不对称性与植被活动之间的复杂关系,揭示了昼夜增温和NDVI之间的联合概率分布及其季节性差异。研究结果表明,昼夜增温与NDVI之间的关系在不同季节呈现显著差异。尤其在秋季,昼夜增温对NDVI的影响最为显著,其次是夏季和春季。通过Copula函数模型,发现昼夜增温与NDVI在特定温度区间内呈现正相关,表明适宜的温度条件下昼夜增温对植被生长具有促进作用。然而,当昼夜增温超过某一阈值时,其对NDVI的促进作用转变为抑制作用,从而限制了植被的生长。同时,还揭示了重现期与昼夜增温及NDVI之间的关系。在较低的重现期下,昼夜增温与NDVI的联合概率较高,表明在这些条件下,植被生长良好的情况出现的频率较高。反之,较高的重现期对应于昼夜增温与NDVI较低的联合概率,表明植被生长受到抑制。本研究通过Copula函数提供了一个全新的视角来理解昼夜增温与植被动态之间的相互作用,强调了气温变化对植被生长影响的复杂性。

2000—2021年渭河流域NDVI变化及其影响因素

渭河流域是黄河中游重要的生态涵养地,同时也是黄土高原水土流失的典型区域,监测该地区植被生长变化趋势,并分析其与气候变化和人类活动的关系,对科学评估区域生态建设成效、黄土高原植被恢复和生态修复具有重要意义。基于2000—2021年归一化植被指数(NDVI)、气温、降水量、人口密度、土地利用数据,分析了渭河流域NDVI的时空变化特征,探究了气候变化和人类活动对NDVI变化趋势的影响。结果表明,2000—2021年,渭河流域植被生长季NDVI呈增加趋势,全区年平均增速为0.004。年际尺度上,NDVI与年平均降水量呈正相关关系,与年平均气温的相关性不显著;月尺度上,NDVI与4月和8月的气温、降水量均呈正相关关系,与7月气温呈弱的负相关关系。人口密度变化与NDVI变化趋势呈负相关,流域人口密度的减小有利于植被的恢复和改善。土地利用类型内部变化是植被NDVI变化的主要原因。NDVI显著减少区NDVI的减少趋势主要由关中平原耕地NDVI的减少引起,NDVI显著增加区NDVI的增加趋势主要由草地、林地以及黄土丘陵区、黄土残塬区耕地NDVI的增加引起。

基于MODIS-NDVI数据的延河流域植被覆盖时空变化及其对极端降水的响应

基于2010-2020年MODIS-NDVI数据,分析延河流域归一化植被指数(normalizeddifference vegetation index,NDVI)和极端降水指数,辅以利用Sen趋势分析、M-K趋势检验法、Pearson相关分析等方法,研究植被覆盖时空变化及其对极端降水的响应。结果表明:1)2010-2020年,延河流域NDVI呈显著增加趋势,植被覆盖状况逐年改善,其增加速率为0.073/(10 a)(P<0.001);2)空间上,延河流域NDVI呈现从东南到西北减小的布局;3)趋势上,NDVI呈上升和减小趋势的面积占比分别为98.02%和1.98%,整体呈上升趋势,植被覆盖显著改善;4)近11年极端降水指数总体趋势变化平缓,R20(number of very heavy precipitation days)、RX_(5day)(max5-day precipitation amount)、CDD(consecutive dry Days)和CWD(consecutive wet days)呈上升趋势,R_(95P)(very wet day precipitation)和SDII(simple daily intensity index)呈下降趋势;5)NDVI与极端降水指数的相关性整体上偏低,除SDII外,其余指数都与NDVI正相关,且NDVI与RX_(5day)相关性最强,与R20相关性最弱。

基于绿视率和NDVI的城市街道景观分析与优化研究

街道景观空间对市民健康和城市风貌具有重要影响。既往研究中常以归一化植被指数(NDVI)和绿视率(GVI)来分别代表二维和三维的绿色指标,但对二者的指标相关性研究甚少。采用基于深度学习的图像语义分割方法分析百度街景计算代表性街道的GVI,利用GF-1卫星数据计算NDVI,比较分析城市街道的GVI和NDVI指标特征及相关性。结果表明,1)中山市中心城区各代表街道GVI指标参差不齐,从8.06%到36.00%,其中石岐街道兴中道GVI最高;2)各街道观测点的NDVI均值随着缓冲区尺度的增加也随之呈现出不同变化,NDVI均值具有强烈的尺度敏感性;3)50 m GVI和DNVI均值的皮尔逊相关系数最高,达到0.832。在此基础上分析街道景观存在的不足并给出优化建议,为城市街景评估、空间优化、景观提升提供参考。

1961-2020年黄河流域干燥度时空变化及其对植被NDVI的影响

基于黄河流域224个气象站点1961—2020年气象数据和2000—2020年MODIS的归一化植被指数(NDVI)数据,分析干燥度时空分布规律及其对NDVI的影响。结果表明:1961—2020年黄河流域年平均干燥度气候倾向率为-0.03·(10 a)^(-1),其多年平均值为2.56;从各站变化的区域分布看,黄河流域北部站点变化以下降为主(52.2%),中部以南站点以上升为主(41.5%)。在空间上,黄河流域干燥度总体呈西北高、东南低,表现为上游(3.74)>中游(1.99)>下游(1.74),上游地区包含干旱亚区、半干旱亚区和半湿润亚区,中游和下游地区大多为半湿润亚区。逐步回归分析显示,干燥度主要受降水量的影响,大部分地区年均干燥度减少是由太阳总辐射减少、降水量增加和气温降低造成的。2000—2020年黄河流域NDVI平均值为0.30,在空间上整体呈东南高、西北低,上游较小、下游最高;与干燥度呈极显著负相关(r=-0.52,P<0.01,n=224),特别是在上中游地区。

Drought trend analysis in a semi-arid area of Iraq based on Normalized Difference Vegetation Index, Normalized Difference Water Index and Standardized Precipitation Index

Drought was a severe recurring phenomenon in Iraq over the past two decades due to climate change despite the fact that Iraq has been one of the most water-rich countries in the Middle East in the past.The Iraqi Kurdistan Region(IKR)is located in the north of Iraq,which has also suffered from extreme drought.In this study,the drought severity status in Sulaimaniyah Province,one of four provinces of the IKR,was investigated for the years from 1998 to 2017.Thus,Landsat time series dataset,including 40 images,were downloaded and used in this study.The Normalized Difference Vegetation Index(NDVI)and the Normalized Difference Water Index(NDWI)were utilized as spectral-based drought indices and the Standardized Precipitation Index(SPI)was employed as a meteorological-based drought index,to assess the drought severity and analyse the changes of vegetative cover and water bodies.The study area experienced precipitation deficiency and severe drought in 1999,2000,2008,2009,and 2012.Study findings also revealed a drop in the vegetative cover by 33.3%in the year 2000.Furthermore,the most significant shrinkage in water bodies was observed in the Lake Darbandikhan(LDK),which lost 40.5%of its total surface area in 2009.The statistical analyses revealed that precipitation was significantly positively correlated with the SPI and the surface area of the LDK(correlation coefficients of 0.92 and 0.72,respectively).The relationship between SPI and NDVI-based vegetation cover was positive but not significant.Low precipitation did not always correspond to vegetative drought;the delay of the effect of precipitation on NDVI was one year.

Retrospective analysis of two northern California wild-land fires via Landsat five satellite imagery and Normalized Difference Vegetation Index (NDVI)

Wild-land fires are a dynamic and destructive force in natural ecosystems. In recent decades, fire disturbances have increased concerns and awareness over significant economic loss and landscape change. The focus of this research was to study two northern California wild-land fires: Butte Humboldt Complex and Butte Lightning Complex of 2008 and assessment of vegetation recovery after the fires via ground based measurements and utilization of Landsat 5 imagery and analysis software to assess landscape change. Multi-temporal and burn severity dynamics and assessment through satellite imagery were used to visually ascertain levels of landscape change, under two temporal scales. Visual interpretation indicated noticeable levels of landscape change and relevant insight into the magnitude and impact of both wild-land fires. Normalized Burn Ratio (NBR) and delta NBR (DNBR) data allowed for quantitative analysis of burn severity levels. DNBR results indicate low severity and low re-growth for Butte Humboldt Complex “burned center” subplots. In contrast, DNBR values for Butte Lightning Complex “burned center” subplots indicated low-moderate burn severity levels.

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.

气候变化和人类活动对华北地区植被NDVI的影响研究

归一化植被指数(Normalized Differential Vegetation Index,NDVI)是反映植被生长状态的重要指标,是反映陆地生态环境状况的“指示器”。华北地区地处我国的政治和文化中心,土地覆盖类型复杂多样,是我国重要的粮食生产地,同时受到气候暖干化及加剧的人类活动影响,华北地区的植被生态变得十分脆弱。本研究基于卫星资料NOAACDRAVHRR NDVI和气象数据资料,采用趋势分析、偏相关分析和残差趋势分析等方法,探究了1982-2019年华北地区NDVI的时空变异特征及其对气候变化和人类活动的响应。研究结果表明:(1)1982-2019年华北地区春季、夏季、秋季和生长季的植被NDVI呈显著上升趋势,空间异质性强,其中夏季和生长季的增长速率最快为0.024(10a)^(-1),显著增加的区域面积占比分别为57.35%和58.10%。(2)华北地区春季、夏季和生长季NDVI与降水呈显著正相关关系,秋季NDVI主要受气温的影响,夏季NDVI同时受到气温、降水和相对湿度的积极影响。(3)气候变化和人类活动对华北地区植被的生长影响具有区域差异性,在植被改善区,气候变化的相对作用为45.64%,人类活动的相对作用为54.36%;在植被退化区,气候变化的相对作用为32.66%,人类活动的相对作用为67.34%。(4)不同土地利用类型中,华北地区森林和农田的植被生长较快,其植被改善主要受人类活动的影响,人类活动的相对作用分别为66.07%和60.82%,草地植被的退化也主要受人类活动的影响,相对作用为69.48%,人类活动对华北地区植被的重要影响主要源于我国近几十年来三北防护林等人类重大生态工程的建设以及城市扩张、人口激增的影响,该研究成果也对华北地区生态屏障的建设以及生态环境保护提供了重要理论支撑。

贵州省2020年植被NDVI变化及其驱动因素分析

探究2020年贵州省逐月植被动态变化及其影响因素,为区域生态环境恢复与治理提供科学依据。基于2020年逐月归一化植被指数(NDVI)数据,辅以同期气象数据、相关分析及滞后性分析等方法,深入解析贵州省植被时空变化特征及其对气候变化响应机制。研究表明:2020年贵州省植被覆盖度良好,且非喀斯特地区高于喀斯特地区,其中喀斯特区域中等覆盖度及以上面积占全省面积的46.78%;贵州省的NDVI与同期降雨量、气温均呈现良好的相关性,而植被生长对气温变化敏感性高于降水变化;2020年贵州省植被变化受气候变化影响较大,植被生长对降水存在滞后效应,滞后时间为1个月。

1988—2018年粤北植被NDVI时空分布特征分析

植被是陆地生态系统的核心组成部分,而归一化植被指数(Normalized Difference Vegetation Index,NDVI)是反映地表植被覆盖和生长状况的重要参数。以粤北为研究区,结合1988—2018年长时间序列NOAA/AVHRR产品数据和高程数据,采用变化率分析法和空间分析法,分析31年间粤北NDVI变化特征及其与地形因子的关联性。结果表明,1988—2018年,粤北NDVI年均值整体呈现出北高南低、西高东低的分布特征,NDVI年均值介于0.20~0.87。其中,连山壮族瑶族自治县NDVI年均值最高,达到0.82,而清远市清城区NDVI年均值最低,仅为0.68。2018年,NDVI年均值达到最高,为0.84;1988年,NDVI年均值达到最低,为0.74。随着高程的增加,粤北NDVI年均值呈现出上升趋势,NDVI分布特征受到人类活动、地形和气候的综合影响。研究结果可为粤北山地城市生态屏障区建设提供重要理论支持。

基于NDVI和EVI不同植被指数表征的粤港澳大湾区植被空间格局驱动因子影响力比较分析

为研究归一化植被指数(normalized difference vegetation index,NDVI)和增强植被指数(enhanced vegetation index,EVI)的表征差异是否会造成有关植被研究的结果差异,分别在采用2005—2020年MODISNDVI、MODIS-EVI 2种不同遥感植被指数表征粤港澳大湾区植被空间特征的基础上,以同时期17个自然因子和人为因子作为驱动因子,通过地理探测器模型方法,计算各驱动因子对基于NDVI和EVI的植被空间特征的影响力。结果显示,虽然粤港澳大湾区南亚热带-热带植被在NDVI和EVI的表征下,其结果存在差异,但在不同植被指数下,通过地理探测器模型方法计算各驱动因子影响力量化及排序结果基本一致,未受不同植被指数表征差异的影响。在驱动因子中,土地利用类型、高程均是最主要驱动因子,对植被空间分布影响力均超过50%。因子之间均表现出双因子增强作用。土地利用类型协同人口分布因子对NDVI表征下的植被空间分布影响力最强;高程协同人口分布因子对EVI表征下的植被空间分布影响力最强。研究结果表明,虽然NDVI、EVI在表征植被覆盖特征方面存在差异,但是基于不同植被指数计算的驱动因子定量分析结果趋于一致。

1981~2020年昆仑山-阿尔金山草地NDVI时空变化及其对气温、降水的响应

基于NOAA-AVHRR NDVI数据,采用最大值合成法、回归分析法与相关分析法,探讨了1981~2020年昆仑山-阿尔金山草地归一化植被指数(NDVI)时空变化及其对气温、降水的响应。结果显示:1981~2020年,昆仑山-阿尔金山草地NDVI具有时序波动,在1989~1994年、1995~2000年与2006~2020年草地NDVI表现为显著增加。草地NDVI自西向东逐渐递减,多年均值为0.227(±0.037),相较于1981年(0.213),2020年(0.257)增加了0.044;过去40年,占昆仑山-阿尔金山草地总面积15.00%的草地NDVI呈显著增加,13.00%为显著减少。1981~2020年,昆仑山-阿尔金山气候变化以“暖湿化”(面积占比为48.02%)为主,草地NDVI与气温表现为正相关,与降水呈负相关,与气温、降水呈显著正相关的草地面积占比分别为18.00%、2.00%,呈显著负相关的面积占比分别为2.00%、11.00%。高寒草原类、温性荒漠类呈“暖湿化”的面积占比分别为18.06%、11.04%,相应的草地NDVI呈显著增加的面积占比分别为14.18%、16.82%;温性荒漠类对气温、降水呈显著正响应的面积占比分别为3.28%、0.60%;高寒草原类与气温呈显著正相关的面积占比为6.77%,与降水呈显著负相关的面积占比为4.94%。昆仑山北坡气温上升与适度的降水增加有利于草地植被生长,但降水的过度增加可能导致滑坡、泥石流,破坏草地生境,影响草地植被生长。

Interannual Variability of the Normalized Difference Vegetation Index on the Tibetan Plateau and Its Relationship with Climate Change

The Qinghai-Xizang Plateau, or Tibetan Plateau, is a sensitive region for climate change, where the manifestation of global warming is particularly noticeable. The wide climate variability in this region significantly affects the local land ecosystem and could consequently lead to notable vegetation changes. In this paper, the interannual variations of the plateau vegetation are investigated using a 21-year normalized difference vegetation index （NDVI） dataset to quantify the consequences of climate warming for the regional ecosystem and its interactions. The results show that vegetation coverage is best in the eastern and southern plateau regions and deteriorates toward the west and north. On the whole, vegetation activity demonstrates a gradual enhancement in an oscillatory manner during 1982-2002. The temporal variation also exhibits striking regional differences： an increasing trend is most apparent in the west, south, north and southeast, whereas a decreasing trend is present along the southern plateau boundary and in the central-east region. Covariance analysis between the NDVI and surface temperature/precipitation suggests that vegetation change is closely related to climate change. However, the controlling physical processes vary geographically. In the west and east, vegetation variability is found to be driven predominantly by temperature, with the impact of precipitation being of secondary importance. In the central plateau, however, temperature and precipitation factors are equally important in modulating the interannual vegetation variability.

基于Copula函数的北京市气候变化及人类活动对NDVI影响的识别

在气候变化和人类活动的双重影响下,城市植被受到严重影响,识别气候变化和人类活动对植被的影响,对城市的生态建设具有重要意义。本文依据《北京市城市总体规划》,运用Copula函数的方法考虑气候变化和人类活动对植被的影响进行分析。结果表明:北京市的植被在各个季节都呈现出较好的增长趋势,且在生态涵养区的增长趋势更加明显。NDVI-P的最优Copula函数主要为Frank Copula和Clayton Copula,而NDVI-T的最优Copula函数主要是Frank Copula函数。根据Copula函数的依赖结构分析表明,气候变化主要是通过影响植被的生长期和促进植被的光合作用来影响植被的生长;人类活动对植被的影响主要是通过建设活动与政策来影响植被的分布。

西鄂尔多斯地区植被NDVI时空变化及其对气温和降水的响应

西鄂尔多斯地区现存许多珍稀动植物,是生物多样性保护的重点区域,该地区地处北方生态环境脆弱带,对环境变化敏感。为了解该地区植被覆盖的变化及影响因素,基于MODIS NDVI数据及同期气象数据,采用趋势线分析、重心迁移模型和偏相关分析方法,对西鄂尔多斯地区2000—2020年生长季(4—10月)植被覆盖度变化趋势及其影响因素进行研究。结果表明,西鄂尔多斯80.28%的区域植被NDVI(normalized difference vegetation index)在2000—2020年间显著增加(P<0.05),且重心迁移结果显示东南区域增长更加明显。偏相关分析表明降水是影响该地区植被覆盖变化的主要气候因素,尤其表现在研究区西南半部的乌海市与鄂托克旗。

Spatiotemporal Changes in NDVI and Its Driving Factors in the Kherlen River Basin

Vegetation is an important factor linking the atmosphere,water,soil,and biological functions,and it plays a specific role in the climate change response and sustainable development of regional economies.However,little information is available on vegetation vulnerability and its driving mechanism.Therefore,studying temporal and spatial change characteristics of vegetation and their corresponding mechanisms is important for assessing ecosystem stability and formulating ecological policies in the Kherlen River Basin.We used Moderate-resolution Imaging Spectroradiometer(MODIS)normalized difference vegetation index(NDVI)remote sensing images from 2000 to 2020 to analyse temporal changes in NDVI with the autoregressive moving average model(ARMA)and the breaks for additive season trend(BFAST)in the basin and to assess natural,anthropogenic and topographic factors with the Geodetector model.The results show that:1)the long NDVI time series remained stable in the Kherlen River Basin from 2000 to 2020,with a certain significant mutation period from 2013 to 2017;2)the coefficient of variation(CV)in the analysis of the spatial NDVI was generally constant,mainly at the level of 0.01–0.07,and the spatial NDVI change was minimally impacted by external interference;and 3)temperature and precipitation are the key factors affecting the NDVI in the basin,and changes in local hydrothermal conditions directly affect the local NDVI.The results of this study could provide a scientific basis for the effective protection of the ecological environment and will aid in understanding the influence of vegetation change mechanisms and the corresponding factors.

青藏高原典型草地NDVI时空演变的季节差异及其气候驱动

基于全球库存建模和制图研究(GIMMS)第三代归一化植被指数(NDVI3g)产品和气象数据,利用一元线性回归模型、偏相关分析和显著性T检验,分析了1982—2015年青藏高原高寒草甸和高寒草原春、夏、秋季NDVI时空演变的差异特征及其与气候因子的关系。研究表明:(1)高寒草甸春、夏、秋季NDVI整体均无明显变化趋势,高寒草原春季和夏季NDVI均显著增加,变化速率均为0.0002/a(P<0.05),而秋季NDVI变化趋势不明显。(2)空间上,高寒草甸春季NDVI显著增加面积占比31.95%,集中分布在祁连山区和三江源区,夏季NDVI显著增加的面积占比32.12%,主要分布在祁连山区、三江源地区和一江两河流域;秋季NDVI显著增加的比例为24.59%,集中分布于祁连山区和一江两河流域。高寒草原春、夏、秋季NDVI显著增加的区域均集中分布于西藏自治区北部和柴达木盆地南缘地区,分别占比44.20%、43.09%和37.99%。(3)高寒草甸春季和秋季NDVI均与气温显著正相关,偏相关系数达0.41(P<0.05)和0.23(P<0.05),夏季NDVI与气温、降水量和太阳辐射均呈显著相关性,偏相关系数分别为0.35(P<0.01)、0.56(P<0.01)和-0.57(P<0.01);高寒草原春季NDVI与气温和降水量均呈显著正相关,且与降水量偏相关系数较高,为0.31(P<0.05),夏季NDVI与气温、降水量和太阳辐射均呈显著相关性,与降水量偏相关系数最高,为0.46(P<0.01),秋季NDVI与太阳辐射显著正相关。(4)空间上高寒草甸春季和秋季NDVI与气温呈正相关的像元分别占比76.50%和67.86%,集中于祁连山区和三江源区,夏季NDVI与降水量呈正相关的像元占比58.42%,与太阳辐射呈负相关的像元占比53.69%,均集中分布于祁连山区、三江源区和一江两河流域。高寒草原春季和夏季NDVI与降水量呈正相关的像元分别占比63.02%和67.62%,集中分布在西藏自治区西部和柴达木盆地南缘。研究可为保护青藏高原草地资源、管理高寒生态系统植被碳库以及推动青藏高原长效生态增汇提供科学依据。