基于MODIS NDVI的青海高原植被覆盖时空变化特征分析

以2000-2014年MODIS NDVI数据为基础,综合利用MVC、SG滤波、Mann-Kendall检验等方法,对青海高原植被覆盖时空变化特征及其驱动因子进行了分析和研究。结果表明,受水资源、地形地貌类型等因素影响,研究区植被覆盖程度从东南向西北方向递减,植被生长发育周期区域差异性大,2000m以下的河湟谷地生长期最长,温度、降水量是其季节变化的重要驱动因子。15年间植被覆盖显著下降区域占11.3%,主要分布在柴达木盆地中部和青海高原东北部地区,32.1%的区域植被覆盖显著上升,分布在研究区中东部、青海湖、青南高原中部等地区,降雨量的增加和人类的改造活动是青海高原植被覆盖改善的重要影响因素。     

1982-2013年陕西不同植被类型NDVI变化特征分析

基于1982-2013年陕西NDVI数据和陕西植被类型图,在GIS等技术的支持下,运用一元线性回归趋势分析和聚类分析的方法,对这32年间陕西总的植被覆盖状况时空变化特征及陕西13种类型的植被覆盖状况时空变化特征进行综合分析。研究结果表明:陕西1982-2013年植被覆盖状况总体呈现改善的趋势,且在陕北黄土高原区改善趋势强于陕南秦巴山地区;13种类型的植被覆盖状况也均呈改善趋势,一年一熟粮作和耐寒经济作物和温带丛生禾草草原的植被覆盖改善程度最高,且也集中分布于陕北黄土高原区;13种植被类型NDVI的年变化特征可聚类为5组,同一群组的植被类型NDVI具有相似的年变化规律,同时在空间分布上也表现出较强的地域性。这为认识陕西不同类型植被覆盖状况的时空变化规律提供科学依据。     

近20年中国植被时空变化研究

利用1982-1999年的全球AVHRR/NDVI数据,通过年次最大植被指数随时间的变化斜率、各种土地覆盖类型上植被指数的变化、绿波和褐波推移变化、典型地带植被时空序列变化分析,从遥感角度反映出近20年中国的植被时空动态变化规律.总体上看,中国大多数地区的 NDVI 呈不同程度的增加趋势,表明中国陆地生态系统植被生长状况没有发生显著恶化.生长季节的延长和生长加速是中国 NDVI 增加的主要原因,而温度上升和夏季降水量的增加以及农业生产活动的加强可能是其主要的驱动因子.中国 NDVI 变化趋势显示了较大的空间异质性,东部沿海地区、珠江三角洲、长江三角洲、京津唐等环渤海地区 NDVI 呈下降趋势或变化不明显;农业生产区和西部部分地区增加显著.这种空间异质性是由于城市化过程、农业生产活动、区域气候特征以及植被对气候变化的区域响应等综合因素作用的结果.     

基于GIMMS NDVI数据的北方13省荒漠化趋势评价

北方13省处在干旱、半干旱和半湿润地区,植被对气候变化和人类活动最为敏感,一直是荒漠化研究的热点地区。基于GIMMS NDVI和降水数据,使用一元线性回归方法对北方13省1982年-2006年ΣNDVI和降水的年际变化趋势及其相关性进行了分析,并对ΣNDVI和降水的变化趋势差异做进一步分析。研究结果表明:从总体上来看,中国北方13省在25年间荒漠化趋势变缓,即植被覆盖度呈显著上升趋势,其中显著增加的像元数为35.3%,而显著降低的像元数仅占7.2%。从ΣNDVI与降水的斜率散点象限图来看,ΣNDVI和降水的差异主要在第二象限和第三象限,说明尽管降水在北方地区植被覆盖度变化中起到主要作用,但是降水并不能完全解释植被覆盖度的变化趋势,人类活动如植树造林等是植被覆盖度增加的重要驱动力。内蒙古自治区东北部和东北地区的三江平原呈现出荒漠化趋势,在大部分地区与降水的相关性不显著,表明在该地区降水的影响作用较弱,主要是人类活动等因素导致的。     

1998—2011年甘肃河东地区NDVI时空变化

基于1998—2011年的SPOT VGT NDVI数据,运用最大化均值法、提取植被覆盖度法和一元线性回归趋势分析法,对甘肃河东地区连续14 a的植被覆盖时空变化特征进行动态研究。结果表明:河东地区植被南多北少。在时间上,整体植被呈缓慢上升趋势,增速为0.028·（10a）-1。其中,前4 a NDVI呈下降趋势,从1998年的0.392下降到 2001年0.314;后10 a NDVI呈波动上升趋势,从2002年的0.330上升到2011年的0.378。在空间上,陇南山区中北部、陇中高原南部植被呈增加趋势;而陇东高原东南部、甘南草原区则有所下降。     

诺敏河流域植被覆盖时空演变及其与径流的关系研究

基于GIMMS/NDVI数据对诺敏河流域1982-2006年间植被覆盖的时空演变特征进行了研究,并结合SCS模型模拟地表径流,在流域和像元尺度分析植被NDVI变化与径流的关系。研究表明:诺敏河流域植被NDVI值较高,但25a间整体呈下降趋势,NDVI减少的区域占总面积的82.5%,植被覆盖有所降低;NDVI空间差异明显,NDVI的高值区主要分布在中上游林区,而耕地分布较多的下游地区NDVI值相对较低。流域尺度上植被NDVI与径流不具有明显的相关性。但从像元尺度来看,植被NDVI和径流的正相关和负相关共存,流域不同空间位置的植被变化与径流的关系并不一致。     

1981—2015年中国西北牧区植被覆盖的时空变化北大核心CSCD

我国西北牧区绝大部分属于中温带干旱半干旱地区,其植被对环境变化极为敏感,也易受人类活动干扰。近年来,西北牧区植被发生了明显变化,影响了农牧业生产和生态建设。因此,亟需进一步掌握国家生态工程和种植业结构调整措施下西北牧区植被覆盖的动态变化特性,为农牧业生产和生态建设提供理论支持。利用1981—2015年8 km×8 km分辨率的GIMMS 3g NDVI产品,采用Theil-Sen Median趋势分析、Mann-Kendall检验与Hurst指数等方法,研究西北牧区植被覆盖的时空变化特性。结果表明：（1）1981—2015年,西北牧区植被覆盖发生了明显变化,改善面积占总面积的41.9%,其中,2006—2015年植被覆盖改善最明显,占比达到63.7%。（2）11种植被类型均呈恢复趋势,其中栽培植被改善面积占比超过80%,而草原和草丛改善超过60%。（3）35 a来,西北牧区植被覆盖呈正向可持续发展趋势,持续性恢复和稳定不变的面积占总面积的70%以上,其中,2006—2015年持续恢复和稳定不变的面积占总面积的63.8%。国家生态工程和种植业结构调整措施对西北牧区植被覆盖有明显影响,未来该区植被覆盖以持续性恢复为主。     

基于MODIS/NDVI的塔里木河流域植被覆盖变化驱动因素相对作用分析

塔里木河流域是我国生态较为脆弱的地区,过去几十年不合理的开发,导致植被覆盖遭到严重破坏。2001年以后,随着"塔里木河流域近期综合治理项目"等系列生态工程的实施,流域环境得到初步改善,植被覆盖日益好转。利用2001—2013年逐旬MODIS/NDVI数据和气象数据,通过分离气候变化对塔里木河流域植被覆盖的影响,对气候变化和人类活动对植被覆盖变化的相对作用进行定量分析。研究表明:(1)2001—2013年塔里木河流域植被覆盖总体呈增长趋势;植被覆盖呈改善趋势的区域占流域总面积的28.02%,呈退化趋势的区域占10.99%,其他区域则基本不变。(2)采用相关分析与残差法分析了气候变化和人类活动对植被覆盖变化的影响,结果表明植被覆盖变化与气候因子显著相关;人类活动对植被覆盖变化起积极作用的面积占流域总面积的61.8%,起消极作用的占38.2%。(3)通过对植被覆盖变化驱动因素进行相对作用分析,可以得出在植被改善区和植被退化区,人类活动的作用相对于气候因素更大,是植被覆盖变化的主要驱动因素。     

近30 a青海省植被变化及其气候驱动因子分析

基于1982—2013年GIMMS NDVI 3g数据集及青海省50个国家气象观测站同期气象资料,利用趋势分析、相关分析方法,对青海省植被覆盖时空变化特征及其驱动因子进行分析。结果表明:(1)受气候及地形地貌影响,青海省植被覆盖空间差异明显,总体呈现从东南向西北递减趋势。(2)近30 a,青海省气温、降水呈上升趋势,气候由冷干向暖湿化转变。植被覆盖呈现整体升高,局部退化趋势。植被的年代际变化显示,青海省植被覆盖在近30 a呈现增加—减小—再增加的趋势。(3)青海省生长季(4—9月)植被受气温和降水共同影响,除个别站点外,全省NDVI与气温和降水均呈显著正相关关系,与降水相比,NDVI与气温的相关性更强,气温是影响青海省植被变化的主要气候因子。     

基于SPOT/NDVI华北地区植被变化动态监测与评价

利用1998-2011年SPOT NDVI数据反映华北地区植被覆盖变化情况,结合该地区土地覆盖数据以及1982-2011年84个气象站点的气温和降水数据,分别从时间和空间两个方面对其进行植被动态监测与评价,并简要分析其变化原因。结果表明:1)从时间上来看,华北地区NDVI在1998-2011年总体呈增长趋势,表明该地区植被覆盖情况整体上得到改善,其中,森林和农田NDVI增长最快;2)从空间上来看,华北地区地表植被覆盖得到改善的区域比退化区域面积要大,其中,森林和农田的恢复效果最为明显,而灌丛、草地、沙漠退化面积均超过改善面积,表明华北地区水土流失和荒漠化现象依然严峻;3)在华北地区气候长期趋于暖干化的背景下,华北植被变化与降水变化关系比与气温变化关系密切,表明植被覆盖变化受降水影响较大,此外,人类活动也是引起植被覆盖变化的重要驱动因子。     

Quantitative distinction of the relative actions of climate change and human activities on vegetation evolution in the Yellow River Basin of China during 1981-2019

Under the combined influence of climate change and human activities, vegetation ecosystem has undergone profound changes. It can be seen that there are obvious differences in the evolution patterns and driving mechanisms of vegetation ecosystem in different historical periods. Therefore, it is urgent to identify and reveal the dominant factors and their contribution rates in the vegetation change cycle. Based on the data of climate elements (sunshine hours, precipitation and temperature), human activities (population intensity and GDP intensity) and other natural factors (altitude, slope and aspect), this study explored the spatial and temporal evolution patterns of vegetation NDVI in the Yellow River Basin of China from 1989 to 2019 through a residual method, a trend analysis, and a gravity center model, and quantitatively distinguished the relative actions of climate change and human activities on vegetation evolution based on Geodetector model. The results showed that the spatial distribution of vegetation NDVI in the Yellow River Basin showed a decreasing trend from southeast to northwest. During 1981-2019, the temporal variation of vegetation NDVI showed an overall increasing trend. The gravity centers of average vegetation NDVI during the study period was distributed in Zhenyuan County, Gansu Province, and the center moved northeastwards from 1981 to 2019. During 1981-2000 and 2001-2019, the proportion of vegetation restoration areas promoted by the combined action of climate change and human activities was the largest. During the study period (1981-2019), the dominant factors influencing vegetation NDVI shifted from natural factors to human activities. These results could provide decision support for the protection and restoration of vegetation ecosystem in the Yellow River Basin.     

Monitoring the impact of climate change andhuman activities on grassland vegetation dynamics in the northeastern Qinghai-Tibet Plateauof China during 2000-2015

Climate change and human activities can influence vegetation net primary productivity (NPP), a key component of natural ecosystems. The Qinghai-Tibet Plateau of China, in spite of its significant natural and cultural values, is one of the most susceptible regions to climate change and human disturbancesin the world. To assess the impact of climate change and human activities on vegetation dynamics in the grassland ecosystems ofthe northeastern Qinghai-Tibet Plateau, we applied a time-series trend analysis to normalized difference vegetation index (NDVI) datasets from 2000 to 2015 and compared these spatiotemporal variations with trends in climatic variables over the same time period. The constrained ordination approach (redundancy analysis) was used to determine which climatic variables or human-related factors mostly in?uenced the variation of NDVI. Furthermore, in order to determine whether current conservation measures and programs are effectivein ecological protection and reconstruction, we divided the northeastern Qinghai-Tibet Plateau into two parts: the Three-River Headwater conservation area (TRH zone) in the south and the non-conservation area (NTRH zone) in the north. The results indicatedan overall (73.32%)increasing trend of vegetation NPP in grasslands throughout the study area. During the period 2000-2015, NDVI in the TRH and NTRH zones increased at the rates of 0.0015/aand 0.0020/a, respectively.Specifically, precipitation accounted for 9.2% of the total variation in NDVI, while temperature accounted for 13.4%. In addition, variation in vegetation NPP of grasslands responded not only to long- and short-term changes in climate, as conceptualized in non-equilibrium theory, but also to the impact of human activities and their associated perturbations. The redundancy analysis successfully separated the relative contributions of climate change and human activities, of whichvillage populationand agricultural gross domestic product were the two most important contributors to the NDVI changes, explaining 17.8% and 17.1% of the total variationof NDVI (with the total contribution >30.0%), respectively. The total contributionpercentages of climate change and human activitiesto the NDVI variation were27.5% and 34.9%, respectively, inthe northeastern Qinghai-Tibet Plateau. Finally, our study shows that the grassland restoration in the study area was enhanced by protection measures and programs in the TRH zone, which explained 7.6% of the total variation in NDVI.     

Spatiotemporal variation in snow cover and its effects on grassland phenology on the Mongolian Plateau

Snow cover is an important water source for vegetation growth in arid and semi-arid areas,and grassland phenology provides valuable information on the response of terrestrial ecosystems to climate change.The Mongolian Plateau features both abundant snow cover resources and typical grassland ecosystems.In recent years,with the intensification of global climate change,the snow cover on the Mongolian Plateau has changed correspondingly,with resulting effects on vegetation growth.In this study,using MOD10A1 snow cover data and MOD13A1 Normalized Difference Vegetation Index(NDVI)data combined with remote sensing(RS)and geographic information system(GIS)techniques,we analyzed the spatiotemporal changes in snow cover and grassland phenology on the Mongolian Plateau from 2001 to 2018.The correlation analysis and grey relation analysis were used to determine the influence of snow cover parameters(snow cover fraction(SCF),snow cover duration(SCD),snow cover onset date(SCOD),and snow cover end date(SCED))on different types of grassland vegetation.The results showed wide snow cover areas,an early start time,a late end time,and a long duration of snow cover over the northern Mongolian Plateau.Additionally,a late start,an early end,and a short duration were observed for grassland phenology,but the southern area showed the opposite trend.The SCF decreased at an annual rate of 0.33%.The SCD was shortened at an annual rate of 0.57 d.The SCOD and SCED in more than half of the study area advanced at annual rates of 5.33 and 5.74 DOY(day of year),respectively.For grassland phenology,the start of the growing season(SOS)advanced at an annual rate of 0.03 DOY,the end of the growing season(EOS)was delayed at an annual rate of 0.14 DOY,and the length of the growing season(LOS)was prolonged at an annual rate of 0.17 d.The SCF,SCD,and SCED in the snow season were significantly positively correlated with the SOS and negatively correlated with the EOS and LOS.The SCOD was significantly negatively correlated with the SOS and positively correlated with the EOS and LOS.The SCD and SCF can directly affect the SOS of grassland vegetation,while the EOS and LOS were obviously influenced by the SCOD and SCED.This study provides a scientific basis for exploring the response trends of alpine vegetation to global climate change.     

古尔班通古特沙漠植被覆盖变化及其对沙尘天气的影响

利用1981～2003年逐月NOAA/AVHRR NDVI时间序列数据,分析了古尔班通古特沙漠荒漠植被覆盖的动态变化及其对沙漠南缘绿洲沙尘天气的影响。结果表明:近23年来古尔班通古特沙漠覆盖面积总体上呈现增加趋势,植被覆盖程度较高的区域分布在沙漠中部和西部,同时,这里也是23年来植被覆盖程度显著增加的区域;春、夏季植被覆盖与沙尘天气日数之间均呈现负相关关系,其中,夏季植被覆盖程度与沙尘天气日数之间的负相关最为显著。这说明在古尔班通古特沙漠植被覆盖程度与其南缘绿洲沙尘日数间存在负耦合关系,植被覆盖是影响沙尘天气发生及其强度的因子之一。     

Vegetation dynamics and its response to climate change in Central Asia

The plant ecosystems are particularly sensitive to climate change in arid and semi-arid regions. However, the responses of vegetation dynamics to climate change in Central Asia are still unclear. In this study, we used the normalized difference vegetation index(NDVI) data to analyze the spatial-temporal changes of vegetation and the correlation of vegetation and climatic variables over the period of 1982–2012 in Central Asia by using the empirical orthogonal function and least square methods. The results showed that the annual NDVI in Central Asia experienced a weak increasing trend overall during the study period. Specifically, the annual NDVI showed a significant increasing trend between1982 and 1994, and exhibited a decreasing trend since 1994. The regions where the annual NDVI decreased were mainly distributed in western Central Asia, which may be caused by the decreased precipitation. The NDVI exhibited a larger increasing trend in spring than in the other three seasons. In mountainous areas, the NDVI had a significant increasing trend at the annual and seasonal scales; further, the largest increasing trend of NDVI mainly appeared in the middle mountain belt(1,700–2,650 m asl). The annual NDVI was positively correlated with annual precipitation in Central Asia, and there was a weak negative correlation between annual NDVI and temperature. Moreover, a one-month time lag was found in the response of NDVI to temperature from June to September in Central Asia during 1982–2012.     

黄土高原水蚀风蚀交错带植被覆盖度动态变化

以GIMMS（global inventory modeling and mapping studies）归一化植被指数（normalized difference vegetation index,NDVI）为数据源,采用像元二分模型,提取1982-2006年黄土高原水蚀风蚀交错带不同时段（1982-1989年、1990-1999年、2000-2006年）的植被覆盖度,并运用转移矩阵模型,定量分析水蚀风蚀交错带植被覆盖变化情况。结果显示：研究区植被覆盖度整体呈增加趋势,时段间先增加后减少;从植被空间分布来看,中低植被覆盖度所占比重最大,其次为低植被覆盖和中植被覆盖类型,高植被覆盖度类型所占比例最小。总体来说,从时段1（1982-1989年）到时段3（2000-2006年）研究区植被是良性发展的,虽然局部环境有一定恶化,但整体环境仍呈改善趋势。分析发现,低覆盖度植被类型重心向西南方向移动,而中高覆盖度类型和高覆盖度类型重心向东移动,反映了黄土高原西南地区宁夏、甘肃中部受降雨减少和城市化等因素的影响,在近25 a植被受到了一定破坏,而中东部吴旗、志丹、安塞、延安等地及毛乌素沙地东胜附近近年来进行的退耕还林等一系列生态建设,产生了较好的效益。     

榆林地区植被指数动态变化及其对气候和人类活动的响应

榆林地区是中国典型生态脆弱区,植被生态系统对气候变化和人类活动影响较为敏感。以榆林地区2000—2015年MODIS NDVI为基础,结合气温、降水数据,利用线性趋势法、相关系数、偏相关系数及缓冲区方法,分析了区域NDVI(归一化差异植被指数)动态变化及其对气候和人类活动的响应,结果表明:(1)榆林地区总体上NDVI较小,植被覆盖水平较低。2000—2015年NDVI以每年0.009 6的线性速率递增,空间上主要表现出线性增加趋势,占总面积的97.06%,减少趋势面积较小且主要与人类活动有关,分布在区域西南部山区、城镇附近及中、东部的河流谷地。(2)相关分析表明,榆林地区NDVI与气温以负相关为主,而与降水以正相关为主,反映出干旱、半干旱地区水分是植物生长的主导因子。(3)NDVI变化过程反映出人类活动范围中,市级行政中心缓冲区人类活动强度高于县级行政中心缓冲区。市级行政中心缓冲区范围可划分为5 km以内受人类活动剧烈影响区域、5~9km受人类活动影响递减区域和9 km以外未受人类活动影响区域。