土壤背景对冠层NDVI的影响分析

归一化差值植被指数NDVI是植被遥感中应用最为广泛的指数之一, 但它受土壤背景等因素的干扰比较强烈。结合实测的土壤数据以及公式推导、PROSAIL 模型模拟等方法分析了这种影响。首先, 假定与土壤线性混合且叶片呈水平分布的植被冠层, 根据土壤与植被分别在红光、近红外波段处的反射率值、植被覆盖度等参数, 利用公式推导了土壤背景对不同覆盖度下冠层NDVI的影响。其次, 利用PROSAIL冠层光谱模拟模型, 模拟分析了土壤背景对不同LAI下冠层NDVI的影响。分析的结果表明:LAI 越小, 土壤背景的影响越大; 暗土壤背景下的冠层NDVI值大于亮土壤背景下冠层的NDVI值; 并且,暗土壤条件下,NDVI值对土壤亮度的变化更敏感,而亮土壤下,NDVI值则对LAI或覆盖度的变化更敏感。最后利用实测的不同土壤背景下的冬小麦冠层光谱数据, 验证了公式推导和模型模拟的结果。     

北京地区植被盖度提取及其分布变化研究

基于2010年3个时期的TM遥感影像数据,应用像元二分模型进行北京地区的植被盖度反演。并根据野外实际测量数据研究植被盖度的季节变化情况。应用3个时相的TM数据,分别计算像元二分模型中的参数NDVIsoil和NDVIveg获得了北京地区不同时间的植被盖度信息。进一步应用实地监测的植被盖度数据进行精度验证。结果表明:反演的植被盖度与实地测量植被盖度具有较好的相关性,从散点图上看,数据点多集中在1∶1线附近,3个时期两者间的相关系数均大于0.8,并且2010年的3期植被盖度图像显示的季节变化与地表实际测量的植被盖度季节变化类似。     

基于遥感数据的流域土壤侵蚀强度快速估测方法

以北京延庆县境内的妫水河流域为例, 提出了一种基于遥感数据的土壤侵蚀强度快速估测方法。首先, 利用遥感数据和植被指数模型提取流域内土地利用类型信息和植被覆盖度信息; 其次, 利用数字高程模型数据生成坡度图; 然后, 结合土壤侵蚀强度分级指标, 将坡度图与土地类型图、植被覆盖度图空间叠加, 判断和计算侵蚀强度等级, 结果获得了流域土壤侵蚀强度等级图; 最后, 计算了流域的年平均侵蚀模数。结果表明, 妫水河流域的土壤侵蚀以微度和轻度为主, 所占面积比例为74.88% , 极度和剧烈侵蚀很少, 不到总面积的2%。整个流域的年侵蚀模数估计为1 74611/ km ²·a。     

土地复垦整理植被覆盖度的遥感评价

随着土地复垦工作的广泛开展,土地复垦整理效果评价日益重要。以湖南益阳中洲土地复垦区为例,选取多源多时相遥感影像数据,利用ERDAS IMAGINE软件实现植被覆盖度的计算分析,结果表明通过土地复垦后该项目区的植被覆盖度比复垦前还要高,与实际情况相符,充分说明利用遥感技术对土地复垦后的植被覆盖度进行评价是可行的。     

Vegetation dynamics from NDVI time series analysis using the wavelet transform

A multi-resolution analysis (MRA) based on the wavelet transform (WT) has been implemented to study NDVI time series. These series, which are non-stationary and present short-term, seasonal and long-term variations, can be decomposed using this MRA as a sum of series associated with different temporal scales. The main focus of the paper is to check the potential of this MRA to capture and describe both intra- and inter-annual changes in the data, i.e., to discuss the ability of the proposed procedure to monitor vegetation dynamics at regional scale. Our approach concentrates on what wavelet analysis can tell us about a NDVI time series. On the one hand, the intra-annual series, linked to the seasonality, has been used to estimate different key features related to the vegetation phenology, which depend on the vegetation cover type. On the other hand, the inter-annual series has been used to identify the trend, which is related to land-cover changes, and a Mann-Kendall test has been applied to confirm the significance of the observed trends. NDVI images from the MEDOKADS (Mediterranean Extended Daily One-km AVHRR Data Set) imagery series over Spain are processed according to a per-pixel strategy for this study. Results show that the wavelet analysis provides relevant information about vegetation dynamics at regional scale, such as the mean and minimum NDVI value, the amplitude of the phenological cycle, the timing of the maximum NDVI and the magnitude of the land-cover change. The latter, in combination with precipitation data, has been used to interpret the observed land-cover changes and identify those subtle changes associated to land degradation.     

Assessing the Impact of Ozone Pollution on Summer NDVI\|based Vegetation Growth in North China

The severe summer ozone(O³) pollution in North China has attracted much attention.Combined summerO³ monitoring and NDVI data for 2015-2016,we firstly assessed the impact ofO³pollution on vegetation growth activities.Developed a simple linear simulation technique,then we detected and evaluatedO³’s impact on summer vegetation growth.The results show that summerO³pollution is closely related to vegetation growth in North China.In spatial-scale the stronger affected regions by O³,whereas associated with a highO³pollution intensity,and vice versa.In sum,summerO³ pollution affected on the vegetation growth activities in North China.In addition,in time\|scale,the impact of 2016 is very different from that of 2015.In 2016,a higher O³ pollution intensity than that of 2015,but a decrease in the impact with an approximately 2.75 %.In addition,O³pollution\|induced changes in vegetation growth activities during 2015-2016 were about 11.7 %.This study provides a method for remote sensing to monitor the effects ofO³pollution on terrestrial ecosystems.     

HJ-1A NDVI与MODIS NDVI时间序列提取植被物候特征对比研究

以HJ-1A和MODIS为数据源,通过动态阈值法提取物候特征参数,对HJ-1A NDVI和MODIS NDVI时间序列进行植被物候特征提取进行定性和定量比较,通过比较结果,提出HJ-1A NDVI数据在该应用中存在的问题,促进国产中空间高时间分辨率影像数据在植被物候信息提取研究中的应用,提高其在生态系统研究中的应用价值。结果表明:在SOS、EOS和LOS以及TOMS几个主要的物候时间点上,MODIS NDVI时间序列的标准差较小,所得物候数据更为集中,偏离度较小,所得物候数据较稳定;而HJ-1A NDVI时间序列所得物候数据的标准差较大,数据偏离程度较大,而在POS、BOS和AOS等表征植被生命周期中生长幅度数据上,其标准差较小,离散程度小。     

基于遥感的植被覆盖度估算方法述评

随着遥感技术的发展,作为描述植被覆盖及生长状况的度量参数--“植被覆盖度”在农业、环境、生态等领域应用越来越广泛。介绍了植被覆盖度的重要作用及研究意义,叙述了其遥感监测方法的研究现状及常用遥感数据源,主要从统计、物理、FCD等模型入手讨论植被覆盖度的遥感估算方法及其优缺点,并对今后研究方向及发展趋势进行了展望。
     

Analysis of NDVI and scaled difference vegetation index retrievals of vegetation fraction

The normalized difference vegetation index (NDVI) is the most widely used vegetation index for retrieval of vegetation canopy biophysical properties. Several studies have investigated the spatial scale dependencies of NDVI and the relationship between NDVI and fractional vegetation cover, but without any consensus on the two issues. The objectives of this paper are to analyze the spatial scale dependencies of NDVI and to analyze the relationship between NDVI and fractional vegetation cover at different resolutions based on linear spectral mixing models. Our results show strong spatial scale dependencies of NDVI over heterogeneous surfaces, indicating that NDVI values at different resolutions may not be comparable. The nonlinearity of NDVI over partially vegetated surfaces becomes prominent with darker soil backgrounds and with presence of shadow. Thus, the NDVI may not be suitable to infer vegetation fraction because of its nonlinearity and scale effects. We found that the scaled difference vegetation index (SDVI), a scale-invariant index based on linear spectral mixing of red and near-infrared reflectances, is a more suitable and robust approach for retrieval of vegetation fraction with remote sensing data, particularly over heterogeneous surfaces. The proposed method was validated with experimental field data, but further validation at the satellite level would be needed.     

Spatio-temporal Analysis of Vegetation Phenology with Multiple Methods over the Tibetan Plateau based on MODIS NDVI Data

In the context of global climate change,vegetation phenology analysis based on remote sensing has become an critical method for studying the characteristics of physical and physiological changes of vegetation.This paper uses the MODIS NDVI time\|series data of 96 meteorological stations over the Tibetan Plateau during 2000\|2014 to explore the development trend of vegetation phenological and geographical environment factors of each meteorological station,typical vegetation coverage and the whole plateau region.Firstly,using three cubic spline function method (Spline),double logistic function method(D\|L)and singular spectrum analysis (SSA),NDVI time\|series data is reconstructed,then using the derivative method (Der)and threshold method (Trs),the key parameters of phenological information is extracted,after that differences and application conditions between the six methods are analyzed and compared.Secondly,using M\|K test trend analysis method,the phenological development trend of each site and area were calculated,the relationship between phenological development trend and altitude,precipitation,temperature is studied.Finally,by the Growing season length(GSL)obtained by temperature threshold method,LOS is compared and verified.in grassland and forest land cover types,SSA,Spline,D\|L combined with threshold method to get the Start of Season(SOS),end of season(EOS),Length of season (SOS)respectively is a good combination strategy.(2)The spatial differences of various phenological parameters extracted by different methods are large,and the trend is relatively consistent at small scales.Southeast humid and semi\|humid shrub steppe region and northwestern desert steppe in the Tibetan Plateau,SOS and EOS delayed,but LOS prolonged;southwestern humid region,SOS and EOS delayed,LOS shortened;widely distributed grassland,the phenological parameters did not show significant tendency.(3)Temperature is related to the development trend of phenological parameters.With temperature increasing,the phenomena of SOS advance,EOS lag are presented.Because of the complexity of the plateau landform and climate,there was no significant relationship between phenological development trend for most of the site with the altitude and precipitation,only a few sites have strong correlation,the correlation between GSL and LOS also showed similar characteristics.For remote sensing based phonological analyses,our study identify there is no method existing here that is a adaptive across all the Tibetan Plateau.in addition,at point scale the phenological parameters do not represent a significant earlier or later trend.     

面向对象的黑河下游河岸林植被覆盖信息分类!

地表植被覆盖是描述区域生态系统的基础数据,也是全球及区域陆面过程、生态与水文众多模型中所需的重要地表参数。对于黑河下游额济纳绿洲,以Landsat 30m分辨率为主的遥感影像难以真实提取下游绿洲河岸林植被覆盖信息,而高分辨率影像目标地物轮廓清晰、空间细节信息丰富,有利于干旱背景下景观破碎、异质性强的植被覆盖信息分类。基于黑河下游额济纳绿洲QuickBird影像,通过面向对象的分类方法提取耕地、胡杨、柽柳、草地和裸地等主要植被覆盖类型,分类总体精度和Kappa系数分别为84.71%和0.7986。结果表明:利用面向对象分类方法对高分辨率影像进行植被覆盖信息分类,分类结果较好,能够满足精度要求。     

基于面向对象多端元混解模型的植被覆盖度反演及其时空分布研究北大核心CSCD

近年来湿地的植被退化一直是全球关注的问题,对湿地植被覆盖度进行反演并研究其时空分布特征显得尤为重要。而为了解决植被反演中存在的混合像元问题,提出了基于面向对象的多端元光谱混合分析方法。以扎龙湿地保护区为研究对象,中高分辨率Landsat影像为数据源,从时间尺度和植被覆盖度等级变化层面,研究湿地植被时空变化特征。面向对象多端元混解模型,有效地减少了计算量和混合像元的端元变化,且反演值与检验值相关性较高,均方根误差较小,优于传统多端元混解模型方法,提高了植被覆盖度反演精度。扎龙湿地多年植被覆盖度整体呈现退化趋势,2001～2017年的平均变化速率高于1985～2000年,对于提高全球气候变化情景下植被转移预测精度具有重要理论意义。     

基于MODIS NDVI的中国东部植被覆盖时空变化特征

基于2001~2010年逐月MODIS NDVI产品,采用Mann-Kendall检验和Hurst指数,研究中国东部及5个子区(东北区、黄淮海区、长江中下游区、江南区和华南区)植被覆盖的时空动态特征。结果表明:10 a期间中国东部植被覆盖以不显著改善和不显著退化特征为主,前者稍占优势,4个季节中秋季改善状况最显著;未来态势主要表现为不显著改善且未来将持续改善和不显著退化且未来将持续退化两种特征。植被覆盖为不显著退化且将持续退化的区域主要分布在大型城市或城市群周围;5个子区中,除江南区年内主要表现为不显著退化且将持续退化特征外,其余4区均主要表现为不显著改善且未来将持续改善特征。     

Character of Vegetation Coverage Change along Coastal Areas of Maritime Silk Road

The character and trends of vegetation coverage change along coastal areas of Maritime Silk Road during 2000~2016 has been studied based on MOD13C2 data using MVC method,Change Vector Analysis(CVA),linear regression,Hurst index and Spatial Analysis techniques,therefore generating the change map of vegetation coverage．The results showed that the vegetation coverage significantly increased from 2000 to 2016,and about one\|third of the area changed.The vegetation improvement area accounted for 28.31% of the whole study area and the degradation area was 5.33%,and there was evident self\|similarity and long\|range dependence of vegetation coverage change.The significant vegetation improvement areas were concentrated in South Asia and Western Asia.In addition to part of the concentrated distribution in Africa,the vegetation degradation area scattered along the coastline.Analysis showed that the vegetation coverage was affected by the intensity of human activities along the coast and overall economic development in the region,such as China and Southeast Asia,whose economy is at a stage of development,although the overall vegetation coverage showed improvement and basically unchanged trend,about half of the ports in the region showed the trend of vegetation degradation.However,the economy of Europe are flourishing,the vegetation coverage around the port is mostly improved.     

The impact of soil reflectance on the quantification of the green vegetation fraction from NDVI

The green vegetation fraction (Fg) is an important climate and hydrologic model parameter. A common method to calculate Fg is to create a simple linear mixing model between two NDVI endmembers: bare soil NDVI (NDVI_o) and full vegetation NDVI (NDVI_∞). Usually it is assumed that NDVI_o is close to zero (NDVI_o ∼ 0.05) and is generally chosen from the lowest observed NDVI values. However, the mean soil NDVI computed from 2906 samples is much larger (NDVI = 0.2) and is highly variable (standard deviation = 0.1). We show that the underestimation of NDVI_o yields overestimations of Fg. The largest errors occur in grassland and shrubland areas. Using parameters for NDVI_o and NDVI_∞ derived from global scenes yields overestimations of Fg that are larger than 0.2 for the majority of U.S. land cover types when pixel NDVI values are 0.2 < NDVI_pixel < 0.4. When using conterminous U.S. scenes to derive NDVI_o and NDVI_∞, the overestimation is less (0.10-0.17 for 0.2 < NDVI_pixel < 0.4). As a result, parts of the conterminous U.S. are affected at different times of the year depending on the local seasonal NDVI cycle. We propose using global databases of NDVI_o along with information on historical NDVI_pixel values to compute a statistically most-likely estimate of Fg. Using in situ measurements made at the Sevilleta LTER, we show that this approach yields better estimates of Fg than using global invariant NDVI_o values estimated from whole scenes. At the two studied sites, the Fg estimate was adjusted by 52% at the grassland and 86% at the shrubland. More significant advances will require information on spatial distribution of soil reflectance.     

小麦生长期土壤养分与根系活力变化及其相关性研究

研究了小麦生长期内土壤氮、钾与小麦根系活力变化及其相关性。结果表明,土壤速效氮、速效钾和非交换性钾含量随小麦生育进程呈现有规律的变化;小麦根系活力呈现先增加,孕穗期峰值出现后迅速下降,成熟时根系活力下降到最低值的变化规律,不同施肥处理小麦整个生育期内根系活力大小顺序为:MNPK、NPK>NK>N、NP>CK、M。土壤速效氮、速效钾、非交换性钾含量与小麦根系活力呈显著或极显著正相关,说明土壤N、K养分有效性的高低是影响小麦根系活力的重要因素。     

用植被指数监测干旱并估计冬麦产量

探讨用AVHRR/LAC资料导出的多时相标准化差异植被指数(NOVI)监测干旱和估计冬麦产量的可能性。对甘肃省1991一1992年的干旱和造成小麦严重减产的原因进行了分析。结果表明，植被指数的相对变率分布与相应时期的20cm土壤相对湿度和降水量的偏差场基本相似，但线性相关系数不高。如果取冬麦生育期的累积植被指数和累积降水量的相对变率则其间的相关系数将提高。冬麦整个生育期全县平均累积NDVI和相应县的冬麦平均每亩产量之间的线性相关已达较高的准确度。     

砂姜黑土长期定位施肥对小麦生长及土壤养分含量的影响

砂姜黑土10年定位试验结果表明:施肥是砂姜黑土小麦增产的关键,N肥增产贡献率为69.4%,P肥增产贡献率为23.3%,K肥为7.3%。P、K肥的肥效随时间的推移逐渐提高。凡施肥处理土壤有机质含量都有所提高,施P处理土壤速效P含量提高幅度较大,每年每公顷施135kg K2O尚不能满足一年两季作物的高产需求,应适当提高K肥用量。     

Depicting the Asymmetries of Vegetation Phenology over Northeast China Using Remote Sensing NDVI Dataset

Vegetation phenology is an important ecological indicator for global climate change.Plant greenup phenology in the spring time has been well studied,whereas autumn phenology and its asymmetry with spring phenology still remain unclear.Here,the GIMMS NDVI3g dataset for Northeast China was applied to extract the key phenological parameters during plant growth process,then three phenological asymmetry indices were defined according to the difference between greenup rate and senescence rate(AsyR),growth length in spring and autumn(AsyL),mean vegetation greenness index in spring and autumn(AsyV).First,plant growing curve was fitted with double logistic function and the phenological parameters was calculated.Second,the spatiotemporal pattern of asymmetry indices was explored.The results indicate that the three phenological asymmetry indices show a significant interannual variability and a time cycle of around ten years.The direction of amplitude for AsyV and AsyL was opposite with that of AsyR.Three indices could depict the phenological asymmetries from various perspectives and have a degree of uncertainty.The landscape pattern for AsyV and Asy R is similar.AsyV and AsyR show a capability of distinguishing cropland and natural vegetation cover.AsyL reflects a complex spatial distribution.Phenological asymmetries reveal that coniferous forest and broad-leaved forest present a dominant control of senescence vegetation activities.These natural vegetation commonly show a growth feature of rapid growth in spring and slow decrease in autumn.Cropland exhibits a slowly growing rate in spring and a rapid decrease in autumn.Phenological asymmetry is not significant in grassland area.Phenological asymmetry could enhance our knowledge on ecosystem carbon sink.In a practical way,phenological asymmetry could serve as a useful tools in vegetation type classification,agricultural investigation and plant ecosystem management.     

模拟降雨条件下秸秆编织地表覆盖物对土壤侵蚀和小麦产量的影响

通过自制土壤冲蚀槽,并进行人工模拟降雨试验,研究了稻秆编织地表覆盖物对坡地土壤侵蚀和小麦产量的影响。结果表明:在坡度为27°,每次降雨强度为0.5~0.8mm/m in,小麦整个生育期降雨量为672mm条件下,与无覆盖等高种植和顺坡种植相比,应用秸秆编织地表覆盖物分别减少地表径流量28.36%~44.49%和25.26%~36.74%;分别减少土壤侵蚀55.66%~85.44%和12.13%~47.43%;增加小麦产量36.08%和27.95%。