基于MODIS的广东省植被指数序列构建与应用

植被指数是衡量植被长势的重要指标,植被指数序列有助于准确地认知植被覆盖、土地利用和土壤水分的时空变化规律,以及进行干旱和植被生长监测.利用2004-2006年的MODIS数据,选择RVI、NDVI和EVI三种植被指数,采用最大值合成法进行广东省植被指数序列构建.按照不同植被覆盖对三种植被指数的年际变化规律进行分析,并通过NDVI进行植被覆盖度计算以及植被覆盖等级分类来分析植被的空间分布.结果表明,建立的植被指数序列能真实地反映植被生长规律,植被覆盖度和广东地区的植被实际分布状况一致.说明建立植被指数序列是动态监测广东省植被长势的及植被环境的变化的有效方法.     

Predictability of NDVI in semi-arid African regions

In semi-arid Africa, rainfall variability is an important issue for ecosystems and agricultural activities. However, due to its discrete nature in time and space, rainfall is difficult to measure, quantify, and predict. In the dry tropics, a good proxy for rainfall is vegetation activity since this parameter is well correlated with rainfall variations. In this study, over 20 years of Normalized Difference Vegetative Index (NDVI) data from the Advanced Very High Resolution Radiometers are used. The goal is to assess the skill of linear statistical models in estimating regional NDVI interannual variability based on ocean and atmospheric fields (but not rainfall) and then to hindcast it with a 1- to 2-month lead-time. Three semi-arid areas of ～150 000 km² located in Western, Southern, and Eastern Tropical Africa are considered for this purpose. The predictors are: the Niño3.4 sea surface temperature index, the main modes of National Center for Environmental Prediction (NCEP) surface temperature variability in a window centered over Africa, and regional-scale indices based on NCEP surface temperatures and atmospheric variables (relative humidity, geopotential heights, and winds). The regional indices, which are physically and statistically robust, are generally asynchronous with the NDVI predictand. The statistical models, based on linear multiple regressions, give significant results, and the correlation between observed and cross-validated NDVI is 0.67 in Southern Africa, 0.76 for the long rains and 0.83 for the short rains in Eastern Africa, and 0.88 in Western Africa. The results have implications for (1) better understanding the role of El Niño/Southern Oscillation in semi-arid Africa, and (2) highlight the importance of regional climate processes for vegetation growth at these scales, notably the role played by the Mediterranean Sea and its influence on the West African monsoon. The predictability of NDVI over these African regions is discussed.     

减化比值植被指数在城市热环境研究中的应用

以南京市ETM＋影像为数据源,经嵌套于ERDAS IMAGINE9.1中的ATCOR2大气校正后,提取了南京城区地表温度（land surface temperature,LST）、归一化植被指数（normalized difference vegetation index,NDVI）和减化比值植被指数（reduced simple ratio,RSR）,基于实测值和同时相AS-TER数据反演结果的双重验证,拟合了两种植被指数与地表温度的定量关系,并进行对比分析。结果表明,除水体外,植被覆盖度高的区域地表温度明显低于植被稀少或无植被区;地表温度与NDVI呈显著线性负相关,与RSR呈显著幂函数负相关,后者的相关性高于前者;当RSR小于3.2时,地表温度随植被覆盖增加而锐减,当RSR大于3.2时,植被覆盖继续增加,地表温度却趋于恒定,呈现植被降温效应＂饱和＂现象;对比比值植被指数（ratio vegetation index,RVI）应用结果发现,近红外和红光比值的线性拉伸是导致NDVI和RSR表征城市热环境效应存在差异的主因,还与短波红外对水分敏感和能真实反映植被冠层结构有关。中国6大城市热环境案例研究均表明,RSR能直接解释对于不同下垫面,增加相同的植被覆盖度其降温效果存在差异的现象,而不进行土地利用分类,NDVI则无法揭示此现象。     

基于FY3/MERSI数据的辽宁省植被指数重建及时空变化分析

为建立中国风云三系列气象卫星长时间序列归一化植被指数数据集,选用滤波和函数拟合方法,针对林地、湿地、水稻、玉米、大豆、城市和水体7类地物开展数据重建效果定量分析,确定最佳数据重建方法,并在辽宁省开展时空变化分析。结果表明：非对称高斯函数拟合法（Asymmetric Gaussians,AG）、Savitzky-Golay滤波法（SG）、双Logistic函数拟合法（Double Logistic,DL）和时间序列谐波分析法（Harmonic Analysis of Time Series,HANTS）四种方法均表现出相对较好的去噪能力。SG方法对噪声比较敏感,HANTS方法在低值区受噪声影响大。AG和DL方法平滑效果较好,DL方法的峰值更接近于原始峰值。在高植被覆盖区和季节性作物区,SG方法相关系数最高（>0.93）、均方根误差最低（< 0.1）;在城市和水体低植被指数区,HANTS方法相关系数最高,为0.87,但四种方法的均方根误差均在0.06左右,差别不大。综合考虑曲线和定量分析结果,选取SG方法进行辽宁省植被指数数据集数据重建。辽宁省植被指数数值高低的空间分布与下垫面植被类型相符合,东部山区林地植被指数最高,达到0.75以上。2009-2020年,辽宁省NDVI年均值存在波动,不同地物植被指数变化存在差别,水体和城市植被指数变化相对较小,旱田作物（玉米、大豆）的植被指数受干旱年的影响植被指数变化稍大。辽宁省主要粮食作物植被指数年内均呈单峰分布,与一年一熟型吻合,均在8月上旬达到最大值。     

A comparison of greenness measures in two semi-arid grasslands

A field experiment was conducted during 1988 in a semi-arid grassland along a portion of the U.S./Mexico border in which the utility of NDVI-transformed data for estimating green vegetation amount and cover was explored. Results showed that, although there was significant difference in green and total biomass between the U.S. and Mexico sites, we were unable to find any correlation between either these vegetation parameters and NDVI values calculated from reflectance measurements. Based on these results, it would appear that semi-arid perennial grasslands can pose problems for remote sensing analysis due to their erectophile structure, the likelihood of significant accumulation of senescent biomass, and dominance of soil background in sparsely vegetated areas. Therefore, if remotely-sensed data, and indices derived from them, are to be used in global change models, it is critical to establish if these indices are sufficiently sensitive to distinguish long-term change from the seasonal and spatial variability in vegetation biomass normally found within these perennial grassland communities.     

重庆岩溶地区气候变化对植被的影响

岩溶生态系统是一种脆弱的生态系统,植被类型与盖度成为岩溶环境中最重要、最敏感的自然要素。介绍了以重庆岩溶地区为对象,利用气象和NDVI数据,采用相关分析等方法探讨了植被对气候变化的响应。结果表明:(1)在多年平均水平上,气候对重庆岩溶植被生态系统起着比降水大的作用;在植被生长的年际变化方面,气温和降水对植被生长起着大致相反的趋势。(2)年际变化方面,气温和降水对植被生态系统的生长起着大致相反的作用。一般来说,气温与NDVI之间的关系为正相关。(3)植被指数的动态变化受气候波动的影响较大,近20 a来,总体呈增加的趋势。可为岩溶生态系统恢复和重建提供科学依据。     

基于神经网络算法的Sentinel-1和Sentinel-2遥感数据联合反演土壤湿度研究

以西班牙萨拉曼卡地区为研究区域,联合Sentinel-1后向散射系数和入射角信息、Sentinel-2光学数据提取的植被指数以及地面实测数据,构建了BP神经网络土壤湿度反演模型,并将该模型应用于试验区土壤湿度反演。结果表明:1)基于Sentinel-1卫星VV和VH极化雷达后向散射系数、雷达入射角和Sentinel-2植被指数数据构建的BP神经网络土壤湿度反演模型,能够实现对该地区土壤湿度高精度反演;2)在光学与微波数据联合反演植被覆盖区土壤湿度中,Sentinel-2的NDVI、NDWI1和NDWI2指数都可以用于削弱植被对土壤湿度反演的影响,但基于SWRI1波段的NDWI1能够获得更高精度的土壤湿度反演结果(RMSE为0.049 cm~3/cm~3,ubRMSE为0.048 cm~3/cm~3,Bias为0.008 cm~3/cm~3,r为0.681);3)相比于Sentinel-1 VH极化模式,Sentinel-1 VV极化模式在土壤湿度中表现出更大优势,说明Sentinel-1 VV极化模式更适用于土壤湿度反演。     

青藏高原植被指数最新变化特征及其与气候因子的关系

利用GIMMS/NDVI(全球库存模拟和影像研究/归一化植被指数,Global Inventory Modeling and Mapping Studies,Normalized Difference Vegetation Index)和MODIS/NDVI遥感数据以及青藏高原6个气象代表站的站点数据,结合多种统计和计算方法,分析了青藏高原植被NDVI变化规律及其影响因子。结果表明:1982~2013年青藏高原多年平均植被NDVI的空间分布存在明显的区域差异,总体上呈从东南向西北递减的趋势,而且发现不同地区植被的时间变化规律也不尽相同。根据高原长势最好的6~9月植被NDVI进行经验正交分解,将青藏高原植被分为5个区,并进一步分析了不同分区内植被的变化规律,得出:青藏高原植被NDVI下降最明显的区域在二区的噶尔班公宽谷湖盆地地区和北羌塘高原地区,植被NDVI上升最明显的区域在四区的祁连山东部地区。为了探讨青藏高原不同分区内影响植被NDVI下降的因子,从青藏高原二区、四区、五区各选取NDVI处于下降趋势的两个代表站点。研究分析了各个站点植被NDVI与降水量、平均气温、平均最低气温、平均最高气温、日照百分率5个气象因子的关系,得出:在高原二区日照强度是其它分区的两倍左右,而降水量相对较少导致植被NDVI降低。高原四区由于降水量小、温度高、日照强,导致植被NDVI处于下降趋势;在青藏高原五区虽然降水充足,但日照较弱,限制了植被的正常成长导致NDVI处于下降趋势中;其结果为高原植被退化机制研究及高原植被对大气反馈等奠定了基础。     

气候变化对苏尼特草原NDVI的影响

利用苏尼特草原地区1982—2006年NOAA AVHRR的NDVI数字遥感影像,以及1998-2007年逐旬的SPOT VAG-NDVI数据集,结合研究区域内苏尼特左旗、苏尼特右旗、朱日和、二连浩特4个气象站点的同期降水、气温数据,对植被盖度与不同组合方式的降水及气温数据进行了相关分析,探讨了植被盖度与气象因子的关系。结果表明：苏尼特草原生长季平均盖度、逐月盖度与降水呈正相关关系,与气温呈负相关关系,其中降水对盖度的影响存在着时滞及累积效应。     

4～10月藏北地区地表植被参数的卫星遥感研究

利用MODIS可见光和近红外1~3波段的卫星资料推算得到“全球能量水循环之亚洲季风青藏高原实验”(GAME/Tibet)实验区4~10月季风前后的地表植被参数的变化情况,并将其与NOAA-14 AVHRR卫星资料分析得到的实验区的植被参数进行了比较。同时分析了不同算法在青藏高原的适用性。     

基于NDVI的西藏不同草地类型生物量回归建模分析

旨在建立西藏地区不同草地类型的NDVI遥感估测模型,利用多元线性回归建立了不同草地类型的鲜草生物量与SPOT/VEGETATION多年平均年最大归一化植被指数(NDVI)、年降水量和年积温等变量的回归估测模型。并分析了所有草地类型的平均鲜草生物量与平均年最大NDVI、平均年降水量等因子的相关关系。结果表明:年降水量是鲜草长势最重要的影响因子,基于NDVI的鲜草生物量多元线性回归模型能很好的拟合草地(R=0.964)、高寒草甸(R=0.959)、高寒荒漠草原(R=0.772)、温性草原(R=0.892)和高寒草原(R=0.797)等草地类型。      

Detecting Arctic Climate Change Using KÖppen Climate Classification

Ecological impacts of the recent warming trend in the Arctic are already noted as changes in tree line and a decrease in tundra area with the replacement of ground cover by shrubs in northern Alaska and several locations in northern Eurasia. The potential impact of vegetation changes to feedbacks on the atmospheric climate system is substantial because of the large land area impacted and the multi-year persistence of the vegetation cover. Satellite NDVI estimates beginning in 1981 and the Köppen climate classification, which relates surface types to monthly mean air temperatures from 1901 onward, track these changes on an Arctic-wide basis. Temperature fields from the NCEP/NCAR reanalysis and CRU analysis serve as proxy for vegetation cover over the century. A downward trend in the coverage of tundra group for the first 40 yr of the twentieth century was followed by two increases during 1940s and early 1960s, and then a rapid decrease in the last 20 yr. The decrease of tundra group in the 1920–40 period was localized, mostly over Scandinavia; whereas the decrease since 1990 is primarily pan-Arctic, but largest in NW Canada, and eastern and coastal Siberia. The decrease in inferred tundra coverage from 1980 to 2000 was 1.4 × 10⁶ km², or about a 20% reduction in tundra area based on the CRU analyses. This rate of decrease is confirmed by the NDVI data. These tundra group changes in the last 20 yr are accompanied by increase in the area of both the boreal and temperate groups. During the tundra group decrease in the first half of the century boreal group area also decreased while temperate group area increased. The calculated minimum coverage of tundra group from both the Köppen classification and NDVI indicates that the impact of warming on the spatial coverage of the tundra group in the 1990s is the strongest in the century, and will have multi-decadal consequences for the Arctic.     

青藏高原冬、春植被归一化指数变化特征及其与高原夏季降水的联系

青藏高原气候独特,影响高原夏季降水的原因是十分复杂的和多方面的。文中利用1982—2001年的卫星遥感植被归一化指数(NDVI)资料和青藏高原55个实测台站降水资料,应用经验正交分解(EOF)、奇异值分解(SVD)等方法分析了青藏高原冬、春植被变化特征及其与高原夏季降水的联系,得到以下几点初步认识:青藏高原冬、春季植被分布基本呈现东南地区植被覆盖较好,逐渐向西北地区减少的特征。其中高原东南部地区和高原南侧边界地区NDVI值最大,而西北地区和北侧边界地区NDVI较小。EOF分析表明,20年来冬、春季高原植被的变化趋势是总体呈阶段性增加,其中尤以高原北部、西北部(昆仑山、阿尔金山和祁连山沿线)和南部的雅鲁藏布江流域植被增加明显。由SVD方法得到的高原前期NDVI与后期降水的相关性是较稳定的。青藏高原多数区域冬、春植被与夏季降水存在较好的正相关,且这种滞后相关存在明显的区域差异。高原南部和北部区域的NDVI在冬春两季都与夏季降水有明显的正相关,即冬春季植被对夏季降水的影响较显著。而冬季高原中东部玉树地区附近区域的NDVI与夏季降水也存在较明显的负相关,即冬季中东部区域的植被变化对夏季降水的影响也较显著。由此可见,高原前期NDVI的变化特征,可以作为高原降水长期预报综合考虑的一个重要参考因子。     

青藏高原感热指数的建立及与华南降水的联系

利用1982-2012年青藏高原中东部70个气象站的月平均地面感热资料、华南地区92个气象站的月平均降水资料、NCEP/NCAR月平均再分析资料和SEOF（season reliant EOF）方法选取了4个高原代表站,建立了青藏高原地面感热强度距平指数（I_SH）,并讨论了春季I_SH与华南盛夏（7月和8月）降水的关系。结果表明:I_SH可以较好地表征青藏高原中东部地面感热的年际变化特征,且具有更好的持续性。春季I_SH与华南盛夏降水具有显著的负相关关系,当春季I_SH偏大时,后期对流层中上层高度场异常偏高,且高度场异常偏高的响应随时间从低层向高层传递,使夏季副热带高压偏强、偏西,南亚高压异常偏强,华南地区盛夏降水偏少;反之亦然。此外,去除Ni?o3.4区海温对华南盛夏降水影响后,两者的负相关关系变得更为显著。     

气候变化背景下黄河流域植被变化及其成因北大核心CSCD

研究黄河流域植被的时空变化及其影响因素,对生态文明建设政策的制定具有重要意义。基于2001~2020年MODIS(Moderate Resolution Imaging Spectroradiometer)植被指数(Normalized Different Vegetation Index,NDVI)数据集及同期气象数据,运用均值法、一元线性回归、偏相关性分析和回归残差法等方法研究了近20年黄河流域植被时空变化及驱动因素。结果表明:黄河流域NDVI整体呈上升趋势并具有较大的空间异质性,其中黄河中游NDVI增长幅度最大,为0.0496(10 a)^(-1)。生长季受降水和沿黄灌区耕作的影响,西部地区、东南部区域和宁夏平原、河套平原植被指数明显较高;从整个流域来看,降水和温度变化对NDVI的贡献分别为32.6%和15.9%,其中降水对NDVI变化的贡献主要体现在黄河上游(50.7%),而温度的贡献则在黄河下游表现最突出(32.3%);20年来,人类活动和气候变化分别对黄河流域植被变化贡献了78%和22%,其中人类活动贡献率超过80%的区域主要集中在黄土高原中部区域;整个黄河流域NDVI与干旱程度有显著的正相关性,尤其在陇中黄土高原和河东沙区等区域。黄河上游NDVI与改进的帕默尔干旱指数scPDSI的相关性最高,而下游相对较低。     

用MODIS植被指数研究福州城区空间扩展变化

城区空间的扩展变化对人居环境产生的影响越来越受到人们的关注。利用2001-2005年美国EOS卫星的MODIS遥感资料，以福州市为示范区，逐年计算能反映城区植被覆盖变化的比值植被指数、差值植被指数、归一化植被指数和植被覆盖度，在地理信息系统（GIS）和全球定位系统（GPS）的辅助下，对福州市各种植被指数的年际动态变化过程进行了研究，并在此基础上对福州市的城区空间扩展变化情况进行遥感动态监测，同时结合社会经济统计数据加以分析。结果表明：福州市从2001年到2005年，城区空间扩展约29km^2，每年平均扩展约7．3km^2，与实际情况一致。利用MODIS资料能准确地监测城区空间扩展变化面积的大小。     

The influence of vegetation variation on Northeast Asian dust activity

In this study, we investigate the influence of vegetation variations on dust activity (dust load, dust transport in the troposphere, and dust weather frequency) over Northeast Asia during springtime. By using the Integrated Wind Erosion Modeling System, two model experiments are run over four-month periods, from February 1 to May 31, for each year from 1982 to 2006; one experiment uses the observed atmospheric conditions and vegetation (OBS), and the other uses the specified atmospheric conditions in 2006 and the observed vegetation (CTRL). Comparison of the two model experiments reveals that there are sensitive regions in southeastern Mongolia and central northern China, in which vegetation has a large potential to influence dust activity due to both the high dust emission rate and large variations in vegetation coverage. Over these sensitive regions, vegetation effectively lessens dust loads on interannual and interdecadal timescales; dust load is decreased by 2864 μg m^?2 for an increment of 0.1 in the normalized difference vegetation index (NDVI). Vegetation increase in the sensitive areas also reduces two major branches of dust transports in the low troposphere; one stretches from eastern Mongolia to regions northeastward, and the other flows across the south of northeastern China to Korea. In addition to dust loads and transports, vegetation increase in the sensitive areas evidently decreases dust storm frequency and blowing dust frequency, but it exerts a weak influence on the floating dust frequency. In the sensitive regions, as NDVI increases by 0.1, dust storms, blowing dust, and floating dust decrease by 4.0 days/spring, 1.5 days/spring, and 0.2 days/spring, respectively. In summary, vegetation variations in southeastern Mongolia and central northern China have considerable impact on northeast Asian dust during springtime.     

西藏那曲县NDVI变化及与气象因子、畜牧量相关分析

利用NASA提供的16天合成MODIS数据,以归一化植被指数(NDVI)作为植被覆盖特征指标,研究了2001~2008年那曲县NDVI变化特征,分析了温度、降水等气象因子与NDVI关系。结果显示:近年来那曲县最大NDVI、年均NDVI呈减小趋势;NDVI月变化与温度、降水显著正相关;年平均NDVI、植被生长季平均NDVI与气象因子相关性不明显;畜牧总量与植被生长季NDVI显著负相关。      

A comparison of the vegetation response to rainfall in the Sahel and East Africa,using normalized difference vegetation index from NOAA AVHRR

This article presents the results of a study of the relationship between rainfall and Normalized Difference Vegetation Index (NDVI) in East Africa and the Sahel. Monthly data for the years 1982 to 1985 have been analyzed. We have evaluated NDVI-rainfall relationships by vegetation type, using the major formations described by White (1983). In the article, a comparison of the differential response of vegetation growth to rainfall in the two study regions is emphasized. The most important conclusions of our research are as follows:

1. The spatial patterns of annually-integrated NDVI closely reflect mean annual rainfall.
2. There is a good relationship between rainfall variations and NDVI on seasonal and interannual time scales for areas where mean annual rainfall ranges from approximately 200 to 1200 mm.
3. In most cases, NDVI is best correlated with the rainfall total for the concurrent plus two antecedent months; the correlation is better in the Sahel than in East Africa.
4. The ratios of NDVI to rainfall are considerably higher in East Africa than in the Sahel.
5. Mean annually-integrated NDVI is linearly related to mean annual rainfall in the Sahel. In East Africa the relationship is approximately log-linear; above some threshold value of rainfall, NDVI values level off and vary minimally with rainfall.

Two possible explanations of this last conclusion are suggested: above this threshold, rainfall is no longer the limiting factor in vegetation growth and/or NDVI is not a good indicator of vegetation growth. The latter is a likely possibility since NDVI directly reflects photosynthetic activity and becomes a poor indicator of biomass (i.e., growth) as high canopy densities are reached. The NDVI-rainfall relationship for East Africa is markedly similar to the relationship between NDVI and Leaf Area Index demonstrated by Sellers (1985) and Asrar et al. (1984).     

基于遥感和GIS的中国植被指数变化的驱动因子分析及模型研究

在样带和典型区研究的基础上,采用相关分析和偏相关分析方法,对影响植被指数变化的因子（水、热和地表植被覆盖类型）进行了分析。结果表明：中国植被指数的时空变化极其复杂,虽受水、热和地表植被覆盖类型三个主导因子的影响和控制,但因时和因地而异,三者对植被指数影响和控制的主导地位也因时因地而不同;基于空间上的概念模型Indv=F(x,y,z)只能定性地描述以上三个主导因子时空变化同植被指数的相互关系。