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。     

A new parameterization of canopy spectral response to incident solar radiation: case study with hyperspectral data from pine dominant forest

A small set of independent variables generally seems to suffice when attempting to describe the spectral response of a vegetation canopy to incident solar radiation. This set includes the soil reflectance, the single-scattering albedo, canopy transmittance, reflectance and interception, the portion of uncollided radiation in the total incident radiation, and portions of collided canopy transmittance and interception. All of these are measurable; they satisfy a simple system of equations and constitute a set that fully describes the law of energy conservation in vegetation canopies at any wavelength in the visible and near-infrared part of the solar spectrum. Further, the system of equations specifies the relationship between the optical properties at the leaf and the canopy scales. Thus, the information content of hyperspectral data can be fully exploited if these variables can be retrieved, for they can be more directly related to some of the physical properties of the canopy (e.g. leaf area index). This paper demonstrates this concept through retrievals of single-scattering albedo, canopy absorptance, portions of uncollided and collided canopy transmittance, and interception from hyperspectral data collected during a field campaign in Ruokolahti, Finland, June 14-21, 2000. The retrieved variables are then used to estimate canopy leaf area index, vegetation ground cover, and also the ratio of direct to total incident solar radiation at blue, green, red, and near-infrared spectral intervals.     

The Yearly Land Cover Dynamics (YLCD) method: An analysis of global vegetation from NDVI and LST parameters

NDVI (Normalized Difference Vegetation Index) has been widely used to monitor vegetation changes since the early eighties. On the other hand, little use has been made of land surface temperatures (LST), due to their sensitivity to the orbital drift which affects the NOAA (National Oceanic and Atmospheric Administration) platforms flying AVHRR sensor. This study presents a new method for monitoring vegetation by using NDVI and LST data, based on an orbital drift corrected dataset derived from data provided by the GIMMS (Global Inventory Modeling and Mapping Studies) group. This method, named Yearly Land Cover Dynamics (YLCD), characterizes NDVI and LST behavior on a yearly basis, through the retrieval of 3 parameters obtained by linear regression between NDVI and normalized LST data. These 3 parameters are the angle between regression line and abscissa axis, the extent of the data projected on the regression line, and the regression coefficient. Such parameters characterize respectively the vegetation type, the annual vegetation cycle length and the difference between real vegetation and ideal cases. Worldwide repartition of these three parameters is shown, and a map integrating these 3 parameters is presented. This map differentiates vegetation in function of climatic constraints, and shows that the presented method has good potential for vegetation monitoring, under the condition of a good filtering of the outliers in the data.     

Determinants of the interannual relationships between remote sensed photosynthetic activity and rainfall in tropical Africa

The response of photosynthetic activity to interannual rainfall variations in Africa South of the Sahara is examined using 20 years (1981-2000) of Normalised Difference Vegetation Index (NDVI) AVHRR data. Linear correlations and regressions were computed between annual NDVI and annual rainfall at a 0.5° latitude/longitude resolution, based on two gridded precipitation datasets (Climate Prediction Center Merged Analysis of Precipitation [CMAP] and Climatic Research Unit [CRU]). The spatial patterns were then examined to detect how they relate to the mean annual rainfall amounts, land-cover types as from the Global Land Cover 2000 data set, soil properties and soil types. Yearly means were computed starting from the beginning of the vegetative year (first month after the minimum of the NDVI mean regime), with a one-month lead for rainfall.One third of tropical Africa displays significant (95% c.l.) correlations between interannual NDVI variations and those of rainfall. At continental scale, soil types and soil properties are only minor factors in the overall distribution of the correlations. Mean annual rainfall amounts and land-cover types are much more discriminating. The largest correlations, mostly over 0.60, are distinctly found in semi-arid (200-600 mm annual rainfall) open grassland and cropland areas. The presence of one of these two determinants (semi-aridity, and favourable land-cover type, i.e. open grassland and cropland) in the absence of the other does not systematically result in a significant correlation between rainfall and NDVI. By contrast, NDVI variations are independent from those of rainfall in markedly arid environments and in most forest and woodland areas. This results from a low signal-to-noise ratio in the former, and the fact that precipitation is generally not a limiting factor in the latter.The marginal response of NDVI to a given increase/decrease in rainfall, as described by the slope of the regression, displays a similar pattern to that of the correlation, with maximum slopes in semi-arid regions, except that a weaker response is noted in more densely populated areas, suggesting an incidence of particular land-use and agricultural practises.One-year lag relationships between annual rainfall and NDVI in the next year were also considered. Ten percent of the grid-points show significant correlations, but the spatial patterns remain difficult to interpret.     

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.     

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.     

基于SPOT4数据的黄土高原植被动态变化研究

以SPOT4/VEGETATION数据为基础,以NDVI变化率和年均NDVI值作为植被覆盖动态变化的指标,分析了1998~2005年黄土高原植被覆盖的时空动态变化特征。结果表明黄土高原地区植被动态变化显著增强,1998~2001年黄土高原的植被覆盖有所减少,幅度约为10.5%,2001年后,植被活动显著增强,植被覆盖面积呈增加趋势,2004年后稍有回落。植被生长季的延长和生长加速是该区域NDVI值增加的主要原因,黄土高原地区植被增加和减少的区域相互交错,这一特性是由农业生产活动、城市建设、政府决策及植被对气候变化的响应等综合因素作用的结果。     

Simple parameterizations of the radiation budget of uniform broadleaved and coniferous canopies

Simulations of the different components of the spectral radiation budget of structurally simple leaf and shoot canopies with varying canopy leaf area index (LAI) were performed. The aims were (1) to test a proposed parameterization of the budget using two spectrally invariant canopy structural parameters (p and p_t) governing canopy absorption and transmittance, respectively, and (2) to incorporate the effect of within-shoot scattering in the parameterization for shoot canopies. Results showed that canopy spectral absorption and scattering were well described by a single parameter, the canopy p value or ‘recollision probability’, which was closely related to LAI. The relationship between p and LAI was however different in leaf and shoot canopy: e.g., at the same LAI the recollision probability was larger in the shoot canopy. It was shown that the p value of the shoot canopy could be decomposed into the p value of an individual shoot (p_sh) and the p value of the leaf canopy with the same effective LAI (LAI_e). The canopy p value allows calculation of canopy absorption and scattering at any given wavelength from the leaf (or needle) scattering coefficient at the same wavelength. To calculate canopy reflectance, separation of the downward and upward scattered parts is needed in addition. The proposed parameter p_t worked rather well in the leaf canopy at moderate values of LAI, but not in the coniferous shoot canopy nor at high values of LAI. However, the simulated fraction of upward scattered radiation increased in a straightforward manner with LAI, and was not particularly sensitive to the leaf (or needle) scattering coefficient. Judged by this ‘smooth’ behavior, the existence of another kind of simple parameterization for this separation remains an interesting possibility.     

不同氮素水平油菜冠层反射光谱特征研究

2002～2003年油菜生长季节,在浙江大学实验农场设置了4个品种、3个供氮水平处理、3个重复的油菜田间小区试验,测定了不同发育时期的冠层光谱反射率及对应叶片、茎以及角果的鲜重和干重。结果表明：不同供氮水平的油菜冠层和叶片光谱差异明显,冠层光谱反射率随发育期推移,开花前在可见光范围逐渐降低、在近红外区域逐渐增大,开花后在可见光范围逐渐增大,在近红外区域逐渐降低。不同供氮水平的油菜冠层光谱差异明显,4个品种的油菜具有相似的变化规律,在近红外表现尤其明显,随着供氮水平的增加,光谱反射率明显升高;而在可见光波段处,随供氮水平提高,反射率反而降低。前期随发育期推移,NDVI和RVI都逐渐增大,在4月22日达到最大,其中N2和N3在4月14日受开花影响,NDVI和RVI有所降低。4月22日以后,由于后期叶片衰老变黄,NDVI和RVI都逐渐减小。     

中国西北地区植被时空演变特征及其对气候变化的响应

利用GIMMS/NDVI数据分析了1982~2006年我国西北地区植被覆盖时空变化特征及其对气温和降水变化的响应。结果表明：近25 a来,中国西北地区年均植被NDVI增速为0.5%/10a,7月、8月和10月份增加趋势最显著。天山、阿尔泰山、祁连山、青海的中东部等地区植被覆盖显著增加;青海的格尔木至玉树一线、陕西的南部地区、新疆的塔里木盆地、吐鲁番、塔河、托里等地区植被退化。植被覆盖与气温、降水的年际关系都呈弱的正相关。但年内关系则都呈显著的线性关系,植被覆盖随月均温升高而增加,当月均温超过20℃时,植被NDVI呈下降趋势;月降水量在0~100 mm之间,植被NDVI随降水呈线性增长,当月降水量超过100 mm之后,不再有明显的增长趋势。     

一种基于多光谱遥感影像的喀斯特地区裸岩率的计算方法初探

石漠化是我国西南地区广泛分布的一种生态—地质灾害。石漠化地区的提取和等级的划分是石漠化研究的首要前提。裸岩率作为石漠化等级划分的一个重要指标,对其科学快速的运算,是石漠化等级划分和石漠化地区提取的基础。提出了一种基于多光谱遥感影像的裸岩率的计算方法,并选取贵州省普定县后寨河流域1987年的TM影像进行了实验。首先,对影像进行预处理获得影像对象,再通过波段运算提取后寨河流域的归一化植被指数NDVI和裸土指数BI,分别用来计算植被覆盖度和土壤裸露率,最后通过图层算术运算获得实验区的裸岩率。结果表明这种裸岩率的提取方法具有可行性。     

Quantifying intra-annual persistent behaviour in SPOT-VEGETATION NDVI data for Mediterranean ecosystems of southern Italy

Multi-temporal series of satellite SPOT-VEGETATION Normalized Difference of Vegetation Index (NDVI) data from 1998 to 2003 were exploited for studying persistence in Mediterranean ecosystems of southern Italy. We used Multiple Segmenting Method (MSM), which is well suited to analyze scaling behaviour in short time series, and the Detrended Fluctuation Analysis (DFA), which permits the detection of persistent properties in nonstationary signal fluctuations. Our findings point out to the characterization of Mediterranean ecosystems as governed by persistent mechanisms.     

Verification of the analysis method for extracting the spatial continuity of the vegetation distribution on a regional scale

Vegetation plays a key role in not only improving urban environments, but also conserving ecosystems. The spatial continuity of vegetation distributions can be expected to make green corridors for landscape management, wind paths against heat island phenomena. In this paper, we develop a spatial analysis method of vegetation distributions using remotely sensed data on a regional scale. The method consists of a spatial autocorrelation analysis, an overlay analysis, and a hydrological analysis with the Normalized Difference Vegetation Index (NDVI) adopted as the proxy of vegetation abundance. Application of the method leads to the extraction of the lines between the core areas and sparse areas of vegetation. The purpose of this study is to verify our method through applying a vegetation map digitized from aerial photographs. The map contained three vegetation types of land cover: grasslands, agricultural fields, and tree-covered areas. We use remotely sensed data collected at four different time periods at the regional scale, along with information on the seasonal fluctuations of the vegetation. As a result, the exclusion of seasonal land-cover changes, as in the reaping of agricultural fields, in the process of applying the proposed method produces an effect. The analysis reveals steady areas unaffected by the seasonal fluctuation of vegetation along the lines extracted by applying the proposed method.     

辽宁抚顺近10年来市域热场与植被变化分析

利用1999年和2010年的TM卫星遥感影像,定量反演了抚顺市域的热场和植被指数,并对其变化进行了分析。结果表明,11 a全市的平均热场温度升高了1.53 ℃,城市热岛主要集中在抚顺市的城市建成区以及苏子河河谷和黑大线沿线地带,但强热岛和极强热岛的空间分布范围2010年较1999年压缩幅度空前。从植被盖度总体情况来看,高覆盖度植被覆盖面积均在60%以上,而全市低覆盖度等级以下的植被面积比例很小,其面积比例都在1.5％以下。从植被盖度的变化看,高覆盖度和较高覆盖度的植被面积比例分别下降了3.22％和2.31％;而中覆盖度的植被面积比例增加了4.94％,其变化最大的区域在抚顺市区,该区域变化的比率是全市变化的3~5倍。从热场与植被的变化原因来看,首先是受植物生长季节气候的暖干化变化趋势的影响,其次还与土地利用类型中耕地和草地的减少以及建设用地的快速增加有关,此外,抚顺市生态建设工作对其也有一定程度的影响。     

利用MERIS和AATSR资料估算黄土高原塬区植被含水量时空变化

通过利用2005年黄土高原塬区夏季地表过程野外观测试验期间收集的地面观测的植被含水量、中分辨率影像光谱仪(Medium Resolution Imaging Spectrometer,MERIS)和高级沿轨迹扫描辐射计(Advanced Along-Track Scanning Radiometer,AATSR)卫星遥感资料,分别对归一化差值植被指数(Normalized Different Vegetation Index)和归一化差值水分指数(NormalizedDifferent Water Index)与植被含水量(Vegetation water content)变化关系进行了分析比较,得到了两种不同的植被指数在作物生长背景影响下的异同。并分别利用MERIS的观测资料计算了NDVI,利用AATSR观测资料计算了NDWI,通过分析得出:随着作物的生长或生物量的增加,归一化差值植被指数变化趋于饱和,而归一化差值水分指数仍然继续增加。进一步通过同步地面野外观测植被含水量与卫星遥感观测资料的对比,建立了归一化差值植被指数、归一化差值水分指数和实际野外测量植被含水量的关系,并且得到由两种植被指数反演植被含水量的方法和地面观测之间的误差分别为1.030 64 kg·m-2和0.940 45 kg·m-2。最后通过分析后总结出,利用归一化差值水分指数来反演黄土高原塬区夏季玉米冠层的含水量优于利用归一化差值植被指数。     

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Landsat影像和不规则梯形方法遥感反演延安城市森林表层土壤水分

反演模型对土壤水分评估结果有重要影响,基于此,以黄土沟壑区城市森林表层土壤为研究对象,以3期Landsat影像和实地土壤水分传感器测定数据为数据源,分别通过像元在二维空间（LST-NDVI与STR-NDVI,LST为地表温度,NDVI为归一化植被指数,STR为短波红外转换反射系数）中的散点图及其拟合的干燥边界与湿润边界,获取TOTRAM（热学—光学不规则梯形模型）和OPTRAM（光学不规则梯形模型）的参数,然后在像素水平上（30 m×30 m）反演出延安城市森林表层土壤水分（W）,验证两模型的精度,并比较两模型估算结果的差异及线性边界与非线性边界对反演结果的影响。结果发现：①除OPTRAM 模型在Landsat 7和Landsat 8上干湿边界呈现非线性外,像素在LST-NDVI空间和STR—NDVI空间中的干湿边界均呈线性,且包络成不规则梯形形状;②与实地测定数据相比,TOTRAM与OPTRAM两模型的平均误差（ME）分别为0.009和0.0455,表明两模型估算结果均偏高,但OPTRAM模型的均方根误差（RMSE）较TOTRAM模型更接近0。OPTRAM模型估算的W值均匀地分布在1∶1参考线两侧,且位于参考线上的点数多于TOTRAM模型,表明OPTRAM准确度高于TOTRAM模型,且非线性边界的反演精度高于线性边界;③与TOTRAM模型相比,OPTRAM模型估算出的W空间分异规律与土地利用/覆被类型具有较高的相关性,且OPTRAM模型对植被覆盖度极低的区域敏感。因此,在后续研究中,应在OPTRAM模型中探讨干湿边界复杂性与模型准确性改善之间的关系,同时考虑周围环境、降雨量、森林干扰和NDVI饱和等因素对两模型估算准确性的影响。