黄土高原泾河流域长时间序列的归一化植被指数动态变化及其驱动因素分析

泾河流域土地开发历史悠久, 是黄土高原水土流失的典型区域。研究气候变化和人类活动影响下泾河流域的植被覆盖变化及其原因, 对黄土高原的植被恢复、水土保持和景观管理等都具有重要意义。该研究应用GIMMS归一化植被指数NDVI、土地覆盖分类数据和气候数据, 采用趋势分析和相关分析方法, 研究了泾河流域1982-2005年植被覆盖变化趋势及其驱动因素。研究表明: 泾河流域24年间79.64%的区域NDVI无显著变化趋势, NDVI趋势显著增加的区域占16.33%, 主要集中在流域中部和南部, NDVI趋势显著减小的区域占4.03%, 主要集中在流域北部。流域所有气象站点的降水量均无显著变化趋势, 气温均呈显著升高趋势。分析发现气候变化不能很好地解释NDVI趋势的空间分异, 人为因素更为重要。从土地利用分析结果来看, NDVI不同趋势下各土地利用类型比例无明显变化, 但NDVI显著增加区以耕地为主, 显著减小区以草地为主, 由此推断NDVI的显著增加趋势主要由耕地NDVI增加引起, 显著减小趋势可能与林地减少和草地退化有关。通过分析不同分区的土地利用数据和社会经济资料, 着重探讨了造成植被覆盖显著变化趋势的人为因素。     

中国北方草原植被对气象因子的时滞响应

利用1982~1997年的气温、降水和1983~1997年生长季的NOAA/AVHRR的归一化植被指数(Normalized differential vegetation index, NDVI)遥感数据,分析了中国北方温带草原植被生长对气象因子的时滞响应。根据4个时间尺度(1~4个月)和4个时滞期(前0~3个月)将降水数据进行16种组合方式,计算了植被的NDVI与同期及前期(前1~6个月)降水之间的相关系数。同时,计算了植被的NDVI与同期和前一个月气温之间的相关系数。结果表明:1)中国北方温带草原植被的NDVI与同期降水和气温的显著相关。2)植被的NDVI对前一个月降水的时滞响应最强烈,植被的NDVI与当月降水和前两个月降水的累积量相关性最强。3)在生长季的起始阶段,去冬、今春的降水总量对草甸草原植被的生长有重要的作用。在生长季的中期和后期,当月和前一、二个月的降水对典型草原和荒漠草原的植被有显著影响。4)在草甸草原、典型草原区,生长季早期的气温均对植被生长的影响较为显著。在荒漠草原区,气温不仅在生长季初期与植被的NDVI呈现正相关,而且在生长季的中后期,气温与植被的NDVI呈现负相关性。     

青藏高原草地植被覆盖变化及其与气候因子的关系

为揭示气候变化对青藏高原草地生态系统的影响及其生态适应机制,利用1982~1999年间的NOAA/AVHRR NDVI数据和对应的气候资料,研究了近20年来青藏高原草地植被覆盖变化及其与气候因子的关系。结果表明,18年来研究区生长季NDVI显著增加(p=0.015),其增加率和增加量分别为0.41% a^-1和0.001 0 a^-1。生长季提前和生长季生长加速是青藏高原草地植被生长季NDVI增加的主要原因。春季为NDVI增加率和增加量最大的季节,其增加率和增加量分别为0.92% a^-1和0.001 4 a^-1;夏季NDVI的增加对生长季NDVI增加的贡献相对较小,其增加率和增加量分别为0.37% a^-1和0.001 0 a^-1。3种草地(高寒草甸、高寒草原、温性草原)春季NDVI均显著增加(p<0.01;p=0.001; p=0.002); 高寒草甸夏季NDVI显著增加(p=0.027),而高寒草原和温性草原夏季NDVI呈增加趋势,但都不显著(p=0.106; p=0.087);3种草地秋季NDVI则没有明显的变化趋势(p=0.585; p=0.461; p=0.143)。3种草地春季NDVI的增加是由春季温度上升所致。高寒草地(高寒草甸和高寒草原)夏季NDVI的增加是夏季温度和春季降水共同作用的结果。温性草原夏季NDVI变化与气候因子并没有表现出显著的相关关系。高寒草地植被生长对气候变化的响应存在滞后效应。     

锡林郭勒植被NDVI时空变化及其驱动力定量分析

定量评价归一化植被指数(NDVI)变化特征及其驱动机制, 对了解区域生态变化特征, 促进区域生态与社会经济的可持续发展具有重要作用。该文利用MODIS-NDVI数据, 采用趋势分析法探讨了锡林郭勒2000-2015年生长季植被NDVI时空格局; 然后, 将各驱动因子的空间影响面积与植被显著增加/减少区域进行空间叠加分析, 二者比例即为贡献率大小。结果表明: 研究区植被NDVI整体缓慢增加, 呈现“东北高西南低”的分布格局。NDVI显著增加面积大约是显著减少面积的2倍, 且在气候和人类活动的双重作用下, 植被NDVI表现出显著的空间异质性。在NDVI显著增加区域, 气候影响比例为47.79%, 且降水和气温影响比例相当; 禁牧及草畜平衡政策是最主要的人为影响因素, 占比69.55%。在NDVI显著减少区域, 气候因素占比52.55%, 且以降水影响为主; 人类活动占比24.73%。在NDVI显著增加区域, 人类活动的影响大于气候因素, 且二者耦合作用较突出。     

中国生态功能保护区归一化植被指数动态及气候因子驱动

为揭示生态功能保护区归一化植被指数(NDVI)与气候因子相关性, 为今后该区域植被动态监测提供有用的信息, 该研究基于2000-2015年MODIS NDVI数据和逐月格点降水与气温数据, 采用生态功能保护区和像元两种空间尺度, 应用线性倾向分析、偏相关分析、复相关分析等方法研究了46个生态功能保护区NDVI变化及其与气候因子的关系, 在此基础上基于相关系数显著性水平对生态功能保护区NDVI动态进行了气候因子驱动分区。主要结果: (1)生态功能保护区NDVI总体呈增加趋势, 其增率加权平均值为0.045·a^-1。像元分析表明, NDVI显著增加的区域主要分布在中部和东北部。(2)生态功能保护区NDVI与降水的偏相关系数在-0.30-0.72之间, 在32个分区呈正相关关系。NDVI与气温的偏相关性在-0.36-0.92之间, 在39个分区呈正相关关系。像元分析表明, 50.6%的像元NDVI与降水呈显著正偏相关关系, 主要分布在东北及西北地区。64.6%的像元NDVI与气温呈显著正偏相关关系, 主要分布在东北及青藏高原北缘地区。(3)气温-降水强驱动型是主要驱动类型, 占总面积的38.7%; 气温驱动型为次要驱动类型, 占27.3%; 非气候因子驱动型占17.6%。以上结果表明, 生态功能保护区NDVI与气温、降水气候因子改变具有显著相关性, 气候因子驱动的地区共占82.4%。研究气候变暖背景下生态功能保护区NDVI变化及其对气候因子的响应, 对于认识该区植被动态变化规律具有重要作用。     

泾河流域植被覆盖时空演变及其与降水的关系

在当前全球变化和人类活动剧烈影响下, 研究黄土高原植被覆盖的发展趋势及其与主要限制因子的关系, 对黄土高原退化生态系统的恢复和区域生态环境评价有着重要意义。我们利用GIMMS-NDVI数据和长期降雨数据, 对黄土高原中部泾河流域22 a的植被覆盖时空演变及其与降水的关系进行了研究。结果表明, 1)1982~2003年, 泾河流域植被覆盖整体呈微弱的增加趋势, 并在空间上表现出一定差异。植被覆盖增加的地区约69.62%, 其中显著增加的地区16.61%, 主要分布在泾河流域的中西部和下游小流域, 显著下降的地区约1.65%, 主要分布在泾河流域上游及周边地区; 2) NDVI与降水极显著相关。年NDVI随年降水服从对数分布, 生长季(4~11月)NDVI比降水滞后1个月; 3) 泾河流域降水利用效率不稳定变化, 土地退化状况未见有效改善, 并且泾河流域降水利用效率随降水量的增加而降低, 值得探索。     

1982-2012年中亚植被变化及其对气候变化的响应

归一化植被指数(NDVI)能够反映植被生长状况, 被广泛应用于区域乃至全球的植被变化研究中。该文利用1982-2012年GIMMS-NDVI数据, 通过基于像元的线性趋势分析、偏相关分析, 基于场域的经验正交分解(EOF)、奇异值分解(SVD), 综合时间和空间两个维度上的信息, 研究了近31年来中亚植被的变化及其变化中的区域差异, 分析了植被对气候变化的响应关系。线性趋势分析发现, 34%的中亚植被NDVI显著增长(p < 0.05), 山区植被NDVI的增长速率可达到每年0.004。偏相关分析表明, 63%的中亚植被受到降水的显著影响(p < 0.05, 仅4%为负相关), 而32%的植被受到气温的显著影响(p < 0.05, 仅9%为正相关)。EOF分析发现, 中亚植被NDVI的变化表现出较大的空间差异: 山区及东北部的植被NDVI变化主要分为3个阶段, 即先增长(1982-1994年)、后波动(1994-2002年)、然后继续增长(2002-2012年); 而西北部平原区的植被NDVI变化主要表现为两个阶段, 即先增长(1982-1994年)而后减少(1994-2012年)。SVD分析表明: 1982-2012年间中亚植被受到降水和气温的共同影响, 植被NDVI的空间变化特征与降水的空间变化特征较为一致, 但西北部和山区的植被NDVI对气温的响应存在差异。     

中国西南部地区植被对极端气候事件的响应

在全球气候变化背景下, 极端气候事件频发。中国西南部地区植被对于气候变化及极端气候事件的响应较为敏感。为探究西南部地区植被对极端气候事件的响应程度, 该文采用Pettitt检验、趋势分析法对数据进行分析, 并对数据进行去趋势处理, 分析去趋势前后极端气候指数与归一化植被指数(NDVI)的相关关系。结果表明: (1) 1982-2015年西南部地区植被NDVI呈现显著上升的趋势, NDVI在1994年发生突变, 突变前上升不显著, 突变后呈现显著上升的趋势; (2)去趋势前, 1982-2015年间, 极端降水指数与NDVI显著相关的仅有1日最大降水量, 其与NDVI显著正相关; 除气温日较差外, 其他极端温度指数均与NDVI显著相关。1994-2015年间, 1日最大降水量与NDVI显著正相关, 降水日数与NDVI显著负相关; 在极端温度指数中, 日最低气温最大值、暖昼日数、夏季日数、生长季长度和气温日较差与NDVI显著正相关, 冷昼日数、冰冻日数、冷夜日数和霜冻日数与NDVI显著负相关。1982-2015年间NDVI对年平均气温的响应最强, 而在1994-2015年间NDVI对夏季日数和气温日较差的响应强于对年平均气温的响应。(3)去趋势后, 极端降水指数与NDVI的相关性在两个时段都不显著; 而日最高气温最大值、暖昼日数、夏季日数和气温日较差在这两个时段与NDVI显著正相关, 但其与NDVI的相关系数都在1994-2015年间更高。气温日较差在两个时段与NDVI的相关系数都最高。只在1982-2015年冷昼日数与NDVI显著负相关。     

基于MODIS的泾河流域植被动态年际变化

以中分辨率成像光谱仪数据(Moderate resolution imaging spectroradiometer, MODIS)为基础计算泾河流域归一化差异植被指数(Normalized difference vegetation index, NDVI)在2001~2004年的时间序列值,分别采用相关系数r值和成对t检验的t值定量描述年内NDVI曲线在年际间的协同性和差异性。以农田、森林、灌丛和草地4种土地利用类型NDVI曲线在年际间变化显著的面积百分比为参数,在2001~2004年间分为1、2和3年间隔共6个时间组,比较分析4种土地利用类型的NDVI曲线在6个时间组内的协同性和差异性,进而探讨泾河流域植被年际变化及其与土地利用之间的关系。结果表明:4种土地利用类型NDVI波动对外界环境的响应在不同的时间间隔里表现一致,在2001~2003年和2001~2004年间变化比较明显;在各个时间组内比较发现有较大面积的农田和草地NDVI协同性较差,尤其在2001~2002年间,这可能与退耕还林还草政策的实施有关;4年来泾河流域内4种土地利用类型的NDVI值有增加趋势,植被状况趋于良好;NDVI年际间差异最明显的是草地,其次是农田和灌丛,森林的NDVI比较稳定。     

基于植被指数的典型草原区生物量模型——以内蒙古锡林浩特市为例

利用遥感估测地上生物量是国内外生态学与地理学的研究热点。但基于植被指数的生物量回归模型结果差异较大,究竟哪种植被指数与哪种模型更适合典型草原的生物量反演,是现代草地遥感急需解决的问题之一。该文基于TM影像数据的不同植被指数(VI)差异性,分别选取了RVI(比值植被指数)、NDVI(归一化差异植被指数)、SAVI(土壤调节植被指数)、MASVI(修改型土壤调整植被指数)和RSR(简化比率植被指数)5种植被指数,与同期的内蒙古典型草原区地面实测地上生物量做相关分析,分别建立了5种植被指数与地上生物量的线性及3种非线性(对数、二次多项式、三次多项式)回归模型。研究结果表明:对于中国北方典型草原区而言,地上生物量与5种植被指数(RVI、NDVI、SAVI、MSAVI和RSR)均呈现出显著相关,但地上生物量与后4种植被指数是正相关,与RVI为负相关;利用5种植被指数(RVI、NDVI、SAVI、MSAVI和RSR)监测草地植被生物量的复相关系数均大于0.6,充分说明利用植被指数检测典型草原生物量是一种简单可行的方法;NDVI建立的生物量回归模型,其复相关系数大于其它4类植被指数(RVI、SAVI、MSAVI和RSR),说明NDVI-生物量模型优于植被指数RVI、SAVI、MSAVI和RSR 模型,其模拟地表生物量的效果好;对于TM影像来说,植被生物量的线性模型与3种非线性模型(三次多项式生物量模型、二次多项式生物量模型、对数模型)都表现出较好的模拟效果,都通过了0.01的显著性检验,而且该研究的结果显示出三次多项式生物量回归模型最优,其次是二次多项式生物量模型,再次是线性模型,相对较差的是对数模型。通过NDVI-生物量三次多项式回归模型模拟锡林浩特草原的生物量,可以看出整个研究区的地上生物量基本上是东高西低、东南高西北低的趋势,这与研究区的地形、气候及土地利用等多种因素有关。     

Correlation analysis of Normalized Different Vegetation Index (NDVI)difference series and climate variables in the Xilingole steppe,China from 1983 to 1999

There is a crucial need in the study of global change to understand how terrestrial ecosystems respond to the climate system.It has been demonstrated by many researches that Normalized Different Vegetation Index (NDVI)time series from remotely sensed data,which provide effective information of vegetation conditions on a large scale with highly temporal resolution,have a good relation with meteorological factors.However,few of these studies have taken the cumulative property of NDVI time series into account.In this study,NDVI difference series were proposed to replace the original NDVI time series with NDVI difference series to reappraise the relationship between NDVI and meteorological factors.As a proxy of the vegetation growing process,NDVI difference represents net primary productivity of vegetation at a certain time interval under an environment controlled by certain climatic conditions and other factors.This data replacement is helpful to eliminate the cumulative effect that exist in original NDVI time series,and thus is more appropriate to understand how climate system affects vegetation growth in a short time scale.By using the correlation analysis method,we studied the relationship between NOAA/AVHRR ten-day NDVI difference series and corresponding meteorological data from 1983 to 1999 from 11 meteorological stations located in the Xilingole steppe in Inner Mongolia.The results show that:(1)meteorological factors are found to be more significantly correlation with NDVI difference at the biomass-rising phase than that at the falling phase;(2)the relationship between NDVI difference and climate variables varies with vegetation types and vegetation communities.In a typical steppe dominated by Leymus chinensis,temperature has higher correlation with NDVI difference than precipitation does,and in a typical steppe dominated by Stipa krylovii,the correlation between temperature and NDVI difference is lower than that between precipitation and NDVI difference.In a typical steppe dominated by Stipa grandis,there is no significant difference between the two correlations.Precipitation is the key factor influencing vegetation growth in a desert steppe,and temperature has poor correlation with NDVI difference;(3)the response of NDVI difference to precipitation is fast and almost simultaneous both in a typical steppe and desert steppe,however,mean temperature exhibits a time-lag effect especially in the desert steppe and some typical steppe dominated by Stipa krylovii;(4)the relationship between NDVI difference and temperature is becoming stronger with global warming.     

锡林郭勒草原1983～1999年NDVI逐旬变化量与气象因子的相关分析

 陆地生态系统对气候变化的响应关系一直是全球变化研究的热点。大量研究表明表征植被生长状况的遥感植被指数——NDVI与温度、降水的相关性非常高。但这些研究都忽略了NDVI 数据本身的累积性,而这一点对研究较短时间尺度上植被生长与气候因子间的关系尤为重要。因此,本文提出应以NDVI的变化量序列取代一般研究中使用的NDVI时间序列数据。基于该论点,该文采用1983～1999年NOAA/AVHRR的NDVI逐旬变化量数据序列对锡林郭勒盟草原的草原植被生长与气象因子的相互关系进行了研究。研究结果表明：1）NDVI变化量与气象因子之间的相关性最高的时间段为植被生长过程中NDVI增长阶段部分,这一时期草原植被的生长对气候反映最为敏感,在衰败阶段,其相关性比较弱;2）在典型草原,温度和降水与NDVI变化量的相关性随其主要植被类型的不同而不同,在以羊草（Leymus chinensis ）为主的典型草原,温度比降水的影响作用高;而在以克氏针茅（Stipa krylovii）为主的典型草原,降水的影响高于温度;在大针茅（Stipa grandis）为主的草原,两者与NDVI变化量的相关性相差不大。而在荒漠草原,降水是最主要的影响因子,同期的温度作用并不显著; 3）无论是典型草原还是荒漠草原,该地区草原植被的生长对同期的降水反应最为敏感,而非前期。而在荒漠草原以及以旱生性较强的克氏针茅为主的典型草原,温度对NDVI变化量会有较明显的时滞效应;4）在温度升高、降水基本不变的情况下,典型草原和荒漠草原 N DVI变化量对温度的响应能力都有所提高,降水的响应能力则变化不大。     

Correlation analysis of Normalized Different Vegetation Index (NDVI) difference series and climate variables in the Xilingole steppe, China from 1983 to 1999

There is a crucial need in the study of global change to understand how terrestrial ecosystems respond to the climate system. It has been demonstrated by many researches that Normalized Different Vegetation Index (NDVI) time series from remotely sensed data, which provide effective information of vegetation conditions on a large scale with highly temporal resolution, have a good relation with meteorological factors. However, few of these studies have taken the cumulative property of NDVI time series into account. In this study, NDVI difference series were proposed to replace the original NDVI time series with NDVI difference series to reappraise the relationship between NDVI and meteorological factors. As a proxy of the vegetation growing process, NDVI difference represents net primary productivity of vegetation at a certain time interval under an environment controlled by certain climatic conditions and other factors. This data replacement is helpful to eliminate the cumulative effect that exist in original NDVI time series, and thus is more appropriate to understand how climate system affects vegetation growth in a short time scale. By using the correlation analysis method, we studied the relationship between NOAA/AVHRR ten-day NDVI difference series and corresponding meteorological data from 1983 to 1999 from 11 meteorological stations located in the Xilingole steppe in Inner Mongolia. The results show that: (1) meteorological factors are found to be more significantly correlation with NDVI difference at the biomass-rising phase than that at the falling phase; (2) the relationship between NDVI difference and climate variables varies with vegetation types and vegetation communities. In a typical steppe dominated by Leymus chinensis, temperature has higher correlation with NDVI difference than precipitation does, and in a typical steppe dominated by Stipa krylovii, the correlation between temperature and NDVI difference is lower than that between precipitation and NDVI difference. In a typical steppe dominated by Stipa grandis, there is no significant difference between the two correlations. Precipitation is the key factor influencing vegetation growth in a desert steppe, and temperature has poor correlation with NDVI difference; (3) the response of NDVI difference to precipitation is fast and almost simultaneous both in a typical steppe and desert steppe, however, mean temperature exhibits a time-lag effect especially in the desert steppe and some typical steppe dominated by Stipa krylovii; (4) the relationship between NDVI difference and temperature is becoming stronger with global warming. __________ Translated from Acta Phytoecologica Sinica, 2005, 29(5): 753–765 [译自: 植物生态学报]     

Integrating remote sensing and local ecological knowledge to monitor rangeland dynamics

Rangelands are among the most extensive anthropogenic landscapes on earth, supporting nearly 500 million people. Disagreements over the extent and severity of rangeland degradation affect pastoralist livelihoods, especially when impacts of drought and over-grazing are confounded. While vegetation indices (such as NDVI, or Normalized Difference Vegetation Index) derived from remotely sensed imagery are often used to monitor rangelands, their strategic integration with local ecological knowledge (LEK) is under-appreciated. Here, we explore these complementary approaches in Kyrgyzstan’s pasture-rich province of Naryn, where disagreements regarding pasture degradation could greatly benefit from additional information. We examine a time series of MODIS satellite imagery (2000–2015) to characterize browning trends in vegetation as well as to distinguish between climate- and grazing-induced trends. We also compare and contrast measured trends with LEK perceptions of pasture degradation. To do so, we first examine statistical trends in NDVI as well as in NDVI residuals after de-trending with meteorological data. Second, we use participatory mapping to identify areas local pasture managers believe are overgrazed, a particularly useful approach in lieu of reliable historical stocking rates for livestock in this region. Lastly, we compare the strengths and weaknesses of LEK and remote sensing for landscape monitoring.Browning trends were widespread as declining trends in NDVI (and NDVI residuals) covered 24% (and 9%) of the landscape, respectively. Local managers’ perceptions of pasture degradation better reflected trends seen in NDVI than in climate-controlled NDVI residuals, suggesting patterns in the latter are less apparent to managers. Our approach demonstrated great potential for the integration of two inexpensive and effective methods of rangeland monitoring well-suited to the country’s needs. Despite limitations due to terrain, our approach was most successful within the semi-arid steppe where pasture degradation is believed to be most severe. In many parts of the world, sources of long-term spatially extensive data are rare or even non-existent. Thus, paired LEK and remote sensing can contribute to comprehensive and informative assessments of land degradation, especially where contentious management issues intersect with sparse data availability. LEK is a valuable source of complementary information to remote sensing and should be integrated more routinely and formally into landscape monitoring. To aid this endeavor, we synthesize advice for linking LEK and remote sensing across diverse landscape situations.     

典型草原退化群落不同恢复演替阶段羊草种群空间格局的比较

羊草(Leymus chinensis)为典型草原群落的主要建群种之一, 在群落中扮演着重要角色。应用摄影定位法测定处于不同恢复演替阶段的羊草种群空间格局, 通过点格局、种群空斑、种群领地及种群领地密度等方法分析发现, 羊草种群在恢复演替过程中经历了种群增长和种群衰退的过程。在此过程中, 羊草种群数量出现最高点, 此点之前, 种群拓殖大于自疏, 种群整体增长; 此点之后, 种间竞争及种内竞争致使种群衰退, 而种间竞争占主导地位, 种内竞争相对较弱。羊草种群的增衰导致种群空斑发生变化, 从而引起种群格局类型发生相应的变化, 表现为在恢复21 a的群落中, 羊草种群在10 m×10 m的取样范围内表现出两种格局分布类型: 在0~4.85 m之间呈现聚集分布, 当尺度大于4.85 m时, 则表现为随机分布; 在恢复8 a的群落中, 羊草种群在10 m×10 m的取样范围内出现3种格局分布类型: 在0~3.01 m之间呈聚集分布, 在3.01~3.37 m之间为随机分布, 当尺度大于3.37 m时则表现为均匀分布; 在严重退化群落中, 羊草种群在整个10 m×10 m测定尺度上呈现聚集分布。由此可见, 羊草种群格局在恢复演替过程中是变化的, 这种变化主要由群落剩余资源驱动下的种群拓殖及种内种间竞争所致。     

基于植被降水利用效率和NDVI的黄河上游地区生态退化研究

提出了一种植被降水利用效率和NDVI变化趋势分析相结合识别生态退化、生态恢复区域的方法。利用黄河上游地区1982—2006年的AVHRR NDVI数据及同期16个气象站的降水量数据为基础数据源,计算每个像元的降水利用效率及其变化趋势,结合NDVI变化辨识生态退化和生态恢复的区域范围。结果表明,研究区域80%处于生态恢复阶段,恢复现象较为明显的区域主要位于东南部;生态退化显著的区域主要集中在玛多县县城,扎陵湖、鄂陵湖附近和龙羊峡库区周边。该结果与黄河上游地区草地退化的现状基本吻合,表明该方法可靠性较强,可以作为评估区域生态退化或生态恢复的方法。植被降水利用效率与NDVI变化趋势相结合的方法可以避免仅使用降水利用效率可能产生的误判。研究可为黄河上游地区开展生态恢复工程,合理规划和调整生态建设布局提供科学依据。     

Satellite observed widespread decline in Mongolian grasslands largely due to overgrazing

The Mongolian Steppe is one of the largest remaining grassland ecosystems. Recent studies have reported widespread decline of vegetation across the steppe and about 70% of this ecosystem is now considered degraded. Among the scientific community there has been an active debate about whether the observed degradation is related to climate, or over‐grazing, or both. Here, we employ a new atmospheric correction and cloud screening algorithm (MAIAC) to investigate trends in satellite observed vegetation phenology. We relate these trends to changes in climate and domestic animal populations. A series of harmonic functions is fitted to Moderate Resolution Imaging Spectroradiometer (MODIS) observed phenological curves to quantify seasonal and inter‐annual changes in vegetation. Our results show a widespread decline (of about 12% on average) in MODIS observed normalized difference vegetation index (NDVI) across the country but particularly in the transition zone between grassland and the Gobi desert, where recent decline was as much as 40% below the 2002 mean NDVI. While we found considerable regional differences in the causes of landscape degradation, about 80% of the decline in NDVI could be attributed to increase in livestock. Changes in precipitation were able to explain about 30% of degradation across the country as a whole but up to 50% in areas with denser vegetation cover (P < 0.05). Temperature changes, while significant, played only a minor role (r² = 0.10, P < 0.05). Our results suggest that the cumulative effect of overgrazing is a primary contributor to the degradation of the Mongolian steppe and is at least partially responsible for desertification reported in previous studies.     

中国典型植被类型NDVI动态变化与气温、降水变化的敏感性分析

利用 198 3～ 1992年覆盖全国范围的、多时相的、NOAA/AVHRR的 NDVI数字影像 ,结合我国 16 0个基本标准气象站逐月的气温、降水资料 ,对 10年来中国主要植被类型的遥感特征参数 NDVI的动态变化与同期气温、降水变化的关系进行了分析。结果显示 :就全国而言 ,从北到南 ,NDVI的变化与气候条件变化的相关系数逐渐降低 ;从东南到西北 ,NDVI的变化与气候条件变化的相关系数逐渐增加。     

中国典型植被类型NDVI动态变化与气温、降水变化的敏感性分析

 利用1983～1992年覆盖全国范围的、多时相的、NOAA／AVHRR的NDVI数字影像,结合我国160个基本标准气象站逐月的气温、降水资料,对10年来中国主要植被类型的遥感特征参数NDVI的动态变化与同期气温、降水变化的关系进行了分析。结果显示：就全国而言,从北到南,NDVI的变化与气候条件变化的相关系数逐渐降低;从东南到西北,NDVI的变化与气候条件变化的相关系数逐渐增加。     

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...