不同数据源归一化植被指数在中国北方草原区的应用比较

中国北方草原区生产力在区域碳水循环、农牧业发展中举足轻重。归一化植被指数（Normalized Difference Vegetation Index,NDVI）广泛应用于生产力的计算,然而目前来源众多的NDVI数据反映中国北方草原植被时空动态的一致性仍未可知。本研究利用2000—2015年3个来源NDVI数据集（MODIS NDVI、GIMMS NDVI和SPOT NDVI）并以国际上公认的数据准确性较高的MODIS NDVI为基准对比分析了中国北方草原区NDVI时空动态的一致性,并选取适宜的NDVI产品揭示研究区NDVI长期的时空格局。结果表明：整个中国北方草原区以及部分草原类型（高寒草甸、高寒草原、高寒荒漠、温带荒漠草原）GIMMS NDVI和MODIS NDVI 2套数据集无论是数值范围,还是年际波动和变化趋势具有较高一致性（二者在高寒草甸、高寒草原、高寒荒漠、温带荒漠草原的相关系数分别为0.60、0.47、0.51、0.74）,而SPOT NDVI数值远高于其他2个数据集,尤其是在青藏高原草原区,SPOT NDVI数值每年较另外两套数据集约偏高0.15,表明该区域使用SPOT数据应慎重。部分温带草原类型（典型草原和草甸草原）GIMMS NDVI和SPOT NDVI数据集在年际波动以及变化趋势上具有较高的一致性（相关系数分别为0.85和0.60）,但温带草原区3种数据集NDVI数值范围整体相差不大,小于0.06。基于上述结果,本研究进一步采用时间序列最长且与MODIS NDVI一致性最好的GIMMS NDVI分析了研究区NDVI的时空动态,发现1982—2015年中国北方草原区NDVI整体呈增加趋势,25%的区域达显著水平（p<0.05）,主要集中在温带草原区;高寒草原区NDVI大部分区域变化不显著且有一定比例的区域NDVI呈显著下降趋势。本研究可以为模型数据集选择和预测中国北方草原区植被对未来气候变化的响应提供科学依据。     

新疆五彩湾矿区开发对荒漠植被的扰动分析

荒漠露天矿区植被受损评估及环境修复是近年研究的热点方向。为了研究新疆五彩湾地区矿产开发对矿区及周边荒漠植被的扰动影响,采用1990-2017年90景Landsat数据分析煤矿开发前后矿区及周边荒漠植被的时空变化特征,并定量分析矿区植被长势对气候变化、矿区扩张的响应。结果表明：① 2006-2013年矿区植被所受的扰动最大,在周边植被长势转好的情形下出现明显的退化,在1990-2006年和2014-2017年,扰动较小,矿区与周边植被长势变化一致;② 生长季的月度NDVI分析显示,矿区中心样区的植被经历了一个先退化后恢复的过程;③ 矿区开发对周边植被长势的扰动距离分别为“西-东”方向的-17~21 km和“南-北”方向的-13~23 km,其中2013年对植被的干扰距离最大;④ 冬春季降水是五彩湾矿区及周边植被长势转好的主要因素,虽然矿区一直处于扩张的状态,然而随着降水的增加和矿尘防护措施的加强,2014年来矿区植被长势转好,与周边植被变化趋于一致。本文的研究为干旱区露天煤矿及周边荒漠植被变化动态监测及矿区开采的扰动范围提供了准确的数据支持,便于矿区管理者合理制定相关环保法规及矿区管理办法,实施相关环境保护和污染控制等措施。     

大兴安岭NDVI时间序列的长程相关性特征分析

运用消除趋势波动分析方法和GIMMS数据集,研究大兴安岭1982-2006年NDVI长程相关性,揭示了大兴安岭NDVI动态的时间尺度特征,为气候-植被综合模型中时间尺度特性分析提供依据。主要结论有:(1)NDVI是一个复杂的动力系统,其动态过程受到多个因素和过程影响,NDVI可能存在多种不同的时空尺度。(2)一阶消除趋势波动分析可以避免忽略较小时间尺度特征,适合应用于15d分辨率的时间序列;大兴安岭NDVI在2-15个月内有较强的长程相关性;表明NDVI动态过程不是随机序列,是一个由内在自相似机制决定的长程相关过程;(3)随着时间的推移,NDVI动态时间特征发生变化,大兴安岭各生态地理区标度指数都存在"拐点",其出现时间在6.5-8.5个月之间,北段西侧与南段"拐点"出现时间比北段和中段早1-2个月。在较小时间尺度内,NDVI呈现出接近1/f噪声特点,在较大时间尺度上,NDVI具有长程幂律相关性,不同生态地理区NDVI持续性强度有差异。     

青藏高原月NDVI时空动态变化及其对气候变化的 响应

青藏高原脆弱的高寒植被对外界干扰十分敏感,使其成为研究植被对气候变化响应的理想区域之一。青藏高原气候变化剧烈,在较短的合成时间研究气候变化对植被的影响十分必要。因此,本文利用GIMMS NDVI时间序列数据集,研究了1982-2012年青藏高原生长季月尺度植被生长的时空动态变化,探讨了其与气温、降水量和日照时数等气候因子的响应关系。结果表明：在区域尺度上,除8月外,其他各月份植被均呈增加趋势,显著增加多发生在4-7月和9月;大部分月份的NDVI增加速率随着时段的延长显著减小,表明NDVI增加趋势放缓;在像元尺度上,月NDVI显著变化的区域多呈增加趋势,但显著减少范围的扩张多快于显著增加。4月和7月植被生长主要是受气温和日照时数共同作用,6月和9月受气温的控制,而8月则主要受降水量的影响。长时间序列NDVI数据集的出现为采用嵌套时段研究植被生长变化趋势奠定了前提,而植被活动变化趋势的持续性则有助于形象表征植被活动变化过程、深入理解植被对气候变化的响应和预测植被未来生长变化趋势。由此推测,青藏高原月NDVI未来增加趋势总体上趋于缓和,但在像元尺度显著变化的区域趋于增加。     

京津冀地区NDVI变化及气候因子驱动分析

植被覆盖动态监测及与气候变化的响应,是陆地生态系统研究的重要内容。本文以2001-2013年间京津冀地区MOD13A 3月合成NDVI数据,结合生长季的降水和气温资料,运用偏相关和复相关分析、趋势分析方法,研究了该区域NDVI的变化特征和空间分布,以及其区域植被覆盖变化的气候驱动力。结果表明,该区域NDVI最大值在13a间缓慢增加,植被覆盖呈现改善趋势;NDVI和生长季降雨量及平均气温的平均偏相关系数分别为0.20和-0.14,表明在年际变化水平上,京津冀地区NDVI总体与降水量呈正相关,与平均气温呈负相关,且降水对NDVI的影响大于温度对NDVI的影响。对植被覆盖驱动分区得出,降水和气温驱动型占区域面积的5.68%;单独降水驱动型和气温驱动型分别占4.51%、0.18%;区域内植被覆盖变化主要受非气候因子驱动型为主,所占比例为89.63%,表明人类活动对植被变化的影响巨大。     

川西高原植被特征及其气候变化的相关分析

利用常规气象资料及NOAA-AVHRR的归一化植被指数（NDVI）资料和趋势系数、皮尔逊相关、Morlet小波分析等统计诊断方法,分析了1982年1月-2002年12月川西高原植被和气候因子（气温和降水）的变化特征及其相关关系和周期特征。结果表明：川西高原地区植被覆盖良好,大部分区域植被覆盖增加,局部退化（高原南部和东部）;气温总体呈增加趋势,降水量总体少变,局部有所减少;NDVI与气温和降水有一定相关性,其中与气温的相关性比与降水相关性大;NDVI周期约为5和10年左右,与降水和气温周期相同。川西高原地区植被及气候特征的分析为川西高原旅游和经济的发展规划提供依据,为研究川西高原的生态、气候资源提供参考。     

“一带一路”国家和地区百年尺度干旱化特征分析

为了充分了解“一带一路”国家和地区百年的干旱变化规律和趋势,探索其干湿变化情况,本文利用标准化降水蒸散指数SPEI（Standardized Precipitation Evaporation Index）1901-2013年12个月和3个月尺度的0.5°×0.5°数据,结合线性趋势、PCA主成分分析、Mann-Kenndall非参数检验和小波分析等方法研究多时间尺度下干旱趋势和周期变化特征。结果表明,研究区百年尺度内（1901-2013）干旱指数和面积呈现波动上升趋势,但干旱化进程缓慢,60%以上地区呈现缓慢变湿趋势,SPEI指数发生显著上升地区面积百分比为25.38%,发生显著下降地区面积仅占12.02%。MK检验和PCA分析均显示15°~35°N的中低纬度地区干旱化程度最为严重,主要地区为北非及阿拉伯半岛、伊朗高原,常年呈现显著干旱状态,而俄罗斯、哈萨克斯坦、印度半岛以及中国和蒙古两国干湿变化季节性特征明显。基于Morlet小波分析的周期分析显示,年际和季节SPEI指数的周期特征既具有相似性,又存在一定的差异性,尺度越小干湿变化交替越明显,尺度越大虽有全局特征但所展示的周期不能通过显著性检验,最终得到可用显著周期年际SPEI变化显著尺度为2~4 a,干旱特征在此尺度的周期中时间变化显著。     

中国西北地区植被NDVI的时空变化及其影响因子分析

利用GIMMS/NDVI数据分析了中国西北地区1982-2006年植被NDVI时空变化特征及其影响因子。近25年来,中国西北地区年均植被NDVI增速为0.5%/10a,并存在明显的空间差异。天山、阿尔泰山、祁连山、青海的中东部等地区植被NDVI显著增加;青海南部地区、陕西和宁夏交界地区、甘肃部分地区,以及新疆部分地区的植被NDVI下降。从不同植被类型看:林地、草地和耕地的年均NDVI都在提高。研究表明:中国西北地区植被NDVI变化是各种自然和人为因素综合作用的结果。植被NDVI与气温、降水的年际变化整体上都呈弱的正相关。但与其年内变化则都呈显著的线性关系,当月均温量超过20℃时,植被NDVI呈下降趋势;当月降水量在0¹00mm期间,植被NDVI随降水线性增长,当月降水量超过100mm之后,不再有明显的增长趋势。农业生产水平提高和植被生态建设等人类活动对西北地区植被NDVI增加有重要影响。     

2000-2013年三江源植被NDVI变化趋势及影响因素分析

基于2000-2013年三江源MODIS NDVI数据,本文系统地分析了三江源植被生长季累计NDVI的时空变化特征,并结合三江源生态保护与建设工程实施的相关统计数据,探讨了人类活动对三江源植被变化的影响,最后通过气候因子与生长季累计NDVI的相关性分析,揭示了影响三江源不同地区植被变化的主要气候限制因素。结果表明,2000-2013年三江源植被NDVI整体上呈增加趋势,NDVI明显增加的区域面积比例达17.84%,主要分布于研究区的西部和北部;明显减少的区域仅占0.78%,多零星分布于研究区中部;NDVI变化稳定或没有显著变化趋势的区域面积比例为59.64%,主要位于研究区东部和南部。三江源生态保护与建设工程的实施虽然促进了植被恢复,但对区域植被整体变化的影响有限,研究时段内区域植被整体好转主要受气候因素控制。西部长江源区的植被生长主要受气温影响,东北部黄河源区主要受降水制约,南部澜沧江源区降水和气温的限制性均不明显。     

北方农牧交错区干旱特征变化及其对植被总初级生产力的影响

北方农牧交错区地处半湿润/半干旱生态脆弱过渡带,干旱是影响该区植被生产力的关键因素之一。探究干旱对植被总初级生产力的影响,对深刻理解气候变化下生态系统生产力变化响应特征及优化区域碳水循环具有重要意义。为了更好地了解水分限制区不同干旱特征对GPP影响,本研究以北方农牧交错区为例,基于长时间序列的标准化降水蒸散发指数(SPEI3,1900—2020年)和植被总初级生产力(GPP,1982—2018年)等数据,首先采用小波分析明确SPEI3与GPP强相关周期,在此基础上利用游程理论识别干旱特征,进而分析了北方农牧交错区干旱特征与GPP的变化趋势,最后厘定了不同干旱特征对GPP的影响。结果表明:(1) 1982—2018年北方农牧交错区SPEI3与GPP在半年周期和年周期存在显著相关关系,滞后效应随时间变化而变化;年际分析能够减弱滞后效应对SPEI3与GPP相关性的影响;(2) 1900—2020年北方农牧交错区干旱历时、干旱烈度和烈度峰值均呈现显著增加趋势,干旱烈度随着干旱历时和烈度峰值的增加而加剧,干旱特征高值区往往具有更强的增加趋势;(3) 1982—2018年北方农牧交错区GPP总体呈...     

Detecting Global Vegetation Changes Using Mann-Kendal(MK) Trend Test for 1982–2015 Time Period

Vegetation is the main component of the terrestrial ecosystem and plays a key role in global climate change. Remotely sensed vegetation indices are widely used to detect vegetation trends at large scales. To understand the trends of vegetation cover, this research examined the spatial-temporal trends of global vegetation by employing the normalized difference vegetation index(NDVI) from the Advanced Very High Resolution Radiometer(AVHRR) Global Inventory Modeling and Mapping Studies(GIMMS) time series(1982–2015). Ten samples were selected to test the temporal trend of NDVI, and the results show that in arid and semi-arid regions, NDVI showed a deceasing trend, while it showed a growing trend in other regions. Mann-Kendal(MK) trend test results indicate that 83.37% of NDVI pixels exhibited positive trends and that only 16.63% showed negative trends(P 0.05) during the period from 1982 to 2015. The increasing NDVI trends primarily occurred in tree-covered regions because of forest growth and re-growth and also because of vegetation succession after a forest disturbance. The increasing trend of the NDVI in cropland regions was primarily because of the increasing cropland area and the improvement in planting techniques. This research describes the spatial vegetation trends at a global scale over the past 30+ years, especially for different land cover types.     

Comparison of the spatio-temporal dynamics of vegetation between the Changbai Mountains of eastern Eurasia and the Appalachian Mountains of eastern North America

The Changbai Mountains and the Appalachian Mountains have similar spatial contexts. The elevation, latitude, and moisture gradients of both mountain ranges offer regional insight for investigating the vegetation dynamics in eastern Eurasia and eastern North America. We determined and compared the spatial patterns and temporal trends in the normalized difference vegetation index (NDVI) in the Changbai Mountains and the Appalachian Mountains using time series data from the Global Inventory Modeling and Mapping Studies 3rd generation dataset from 1982 to 2013. The spatial pattern of NDVI in the Changbai Mountains exhibited fragmentation, whereas NDVI in the Appalachian Mountains decreased from south to north. The vegetation dynamics in the Changbai Mountains had an insignificant trend at the regional scale, whereas the dynamics in the Appalachian Mountains had a significant increasing trend. NDVI increased in 55% of the area of the Changbai Mountains and in 95% of the area of the Appalachian Mountains. The peak NDVI occurred one month later in the Changbai Mountains than in the Appalachian Mountains. The results revealed a significant increase in NDVI in autumn in both mountain ranges. The climatic trend in the Changbai Mountains included warming and decreased precipitation, and whereas that in the Appalachian Mountains included significant warming and increased precipitation. Positive and negative correlations existed between NDVI and temperature and precipitation, respectively, in both mountain ranges. Particularly, the spring temperature and NDVI exhibited a significant positive correlation in both mountain ranges. The results of this study suggest that human actives caused the differences in the spatial patterns of NDVI and that various characteristics of climate change and intensity of human actives dominated the differences in the NDVI trends between the Changbai Mountains and the Appalachian Mountains. Additionally, the vegetation dynamics of both mountain ranges were not identical to those in previous broader-scale studies.     

Spatial-temporal changes of vegetation cover in Guizhou Province,Southern China

Guizhou Province is an important karst area in the world and a fragile ecological area in China. Ecological risk assessment is very necessary to be conducted in this region. This study investigates different characteristics of the spatial-temporal changes of vegetation cover in Guizhou Province of Southern China using the data set of SPOT VEGETATION(1999–2015) at spatial resolution of 1-km and temporal resolution of 10-day. The coefficient of variation, the Theil-Sen median trend analysis, and the Mann-Kendall test are used to investigate the spatial-temporal change of vegetation cover and its future trend. Results show that: 1) the spatial distribution pattern of vegetation cover in Guizhou Plateau is high in the east whereas low in the west. The average annual normalized difference vegetation index(NDVI) from west to east is higher than that from south to north. 2) Average annual NDVI improved obviously in the past 17 years. The growth rate of average annual NDVI is 0.028/10 yr, which is slower than that of vegetation in the country(0.048/10 yr) from 1998 to 2007. Average annual NDVI in karst area is lower than that in non-karst area. However, the growing rate of average annual NDVI in karst area(0.030/10 yr) is faster than that in non-karst area(0.023/10 yr), indicating that vegetation coverage increases more rapidly in karst area. 3) Vegetation coverage in the study area is stable overall, but fluctuates in the local scales. 4) Vegetation coverage presents a continuous increasing trend. The Hurst exponent of NDVI in different vegetation types has an obvious threshold in various elevations. 5) The proportion of vegetation cover with sustainable increase is higher than that of vegetation cover with sustainable decrease. The improvement in vegetation cover may expand to most parts of the study area.     

1982-2006年加纳植被覆盖时空变化及其气候影响

非洲陆地生态系统是气候变化的高敏感区,研究该区域植被覆盖变化及其控制因素,对深刻认识气候变化的影响具有重要意义。本文利用1982-2006年植被指数（NDVI）数据,研究位于非洲西部热带地区的加纳共和国植被覆盖的时空变化特征,结合同期的气温和降水量数据,分析其植被活动对气候变化的响应特征。研究结果表明,加纳86.4%的植被覆盖区NDVI在25 a间都呈现不同程度的增加趋势。20世纪80年代初和21世纪初这2个时期,NDVI值大于0.4的面积百分比呈增加趋势;NDVI值大于0.5的面积百分比从26%增加到38.2%;NDVI值在0.4-0.5之间的面积百分比从47.5%增加到51.9%。NDVI受降水量控制的区域占总区域面积的57.2%,而受气温控制的面积占总区域面积的42.8%。总的来看,加纳植被覆盖对降水量变化的敏感程度强于气温变化。     

2001-2010年蒙古国MODIS-NDVI时空变化监测分析

利用2001 - 2010年的空间分辨率为1km的MODIS-NDVI数据,以蒙古国为研究区域,利用最大值合成法、均值法与差值法、一元线性回归等方法,分析了不同季节下植被覆盖的年内变化、年际变化与波动趋势、空间变化特征.结果表明:M(ODIS- NDVI对植被的生长变化具有较高的敏感度,可有效应用于植被生态的评估和监测...     

Spatio-temporal distribution of vegetation index and its influencing factors——a case study of the Jiaozhou Bay,China

The coastal zone is an area characterized by intense interaction between land and sea, high sensitivity to regional environmental changes, and concentrated human activities. Little research has investigated vegetation cover changes in coastal zones resulting from climate change and land-use change, with a lack of knowledge about the driving mechanism. Normalized diff erence vegetation index(NDVI) can be used as an indicator for change of the coastal environment. In this study, we analyzed the interannual changes and spatial distribution of NDVI in the coastal zone around Jiaozhou Bay in Qingdao, a coastal city undergoing rapid urbanization in northeast China. The underlying causes of NDVI variations were discussed in the context of climate change and land-use change. Results showed that the spatio-temporal distribution of NDVI displayed high spatial variability in the study area and showed a typical trend of gradually increasing from coastal to inland regions. The significant increase area of NDVI was mainly found in newly added construction land, extending along the coastline towards the inland. Land vegetation cover demonstrated a certain response relationship to sea-land climate change and land-based activities. The impact of land-based human activities was slightly greater than that of sea-land climate change for land vegetation cover. The results indicate that promoting ecological policies can build an ecological security framework of vegetation suitable for the resource characteristics of coastal cities. The framework will buf fer the negative ef fects of sea-land climate change and land-based human activities on vegetation cover and thereby achieve the balance of regional development and ecological benefits in the coastal zone.