The responses of Moso bamboo (Phyllostachys heterocycla var. pubescens) forest aboveground biomass to Landsat TM spectral reflectance and NDVI

Bamboo is a special forest type in subtropical regions of china. Its huge biomass and carbon storage and its ecological function play an important role in global carbon sink. In this paper, Moso bamboo (Phyllostachys heterocycla var. pubescens) forest in Anji county, Zhejiang province, China was selected to examine the relationships between Landsat Thematic Mapper (TM) data, and aboveground biomass (AGB, Kg), This research indicates that (1) near infrared (TM4) and mid-infrared bands (TM5,TM7) are more important in explaining Moso bamboo AGB than the visible bands. In particular, TM band5 has higher path coefficient with AGB than any other TM bands, implying its important role in explaining Moso bamboo AGB; (2) the Normalized Difference Vegetation Index (NDVI) has weak correlation with Moso bamboo AGB, however, other vegetable indices such as Perpendicular Vegetation Index (PVI), Enhanced Vegetation Index(EVI), and Soil Adjust Vegetation Index (SAVI) which are related to soil adjustment parameters are significantly correlated with Moso bamboo AGB; (3) the new vegetation index developed in this paper is significantly correlated with Moso bamboo AGB (correlation coefficient is 0.48), and has higher correlation coefficient (R) than any other selected vegetation indices, implying that this new vegetation index can better explain Moso bamboo AGB than any other vegetation indices.     

大气校正对毛竹林生物量遥感估算的影响

基于Landsat TM影像对毛竹林生物量进行了估算,并利用6种大气校正方法(FLAASH、6S、DOS1～DOS4)分析了大气校正对毛竹林生物量遥感估算的影响.结果表明：6种大气校正模型均能有效地消除大气影响;不同大气校正模型校正后,归一化植被指数(NDVI)与毛竹林生物量之间的关系得到很好改善;对于同一种大气校正方法而言,NDVI、红外指数（II）和近红外指数（MI）与生物量之间关系的差异较大,说明在探讨植被指数的生物物理意义时必须进行大气校正;与其他5种模型相比,DOS3模型校正后的Landsat TM数据与毛竹林生物量之间具有最高的相关系数,但6种校正模型校正前后Landsat TM数据与毛竹林生物量之间的相关系数没有显著差异,说明采用单一时相遥感影像建立多元线性回归模型估算生物量时,可以不进行大气校正.     

毛竹扩张对杉木林土壤微生物残体碳积累的影响

亚热带毛竹扩张对杉木林土壤微生物残体碳积累的影响及机制尚不清楚。以毛竹向杉木林扩张带(包括杉木林、杉木-毛竹混交林和毛竹林)的凋落物(O层)和不同发生层土壤(A层、B层和BC层)为研究对象，通过分析凋落物和土壤样品中的氨基糖含量来表征微生物残体碳累积效应，并进一步评价微生物在土壤有机碳(SOC)形成过程中的作用。结果表明：毛竹扩张使杉木林凋落物数量和碳含量显著降低，但是凋落物中真菌残体碳(MRC-f)、细菌残体碳(MRC-b)和微生物残体碳(MRC)含量均显著增加；毛竹扩张显著提高了杉木林SOC、MRC-f、MRC-b和MRC含量，而且在毛竹扩张初期(杉木林演替为杉木-毛竹混交林)MRC-f、MRC-b和MRC在SOC中的比例也显著增加，说明毛竹扩张增强杉木林土壤MRC累积效应的同时，也提高了微生物对有机碳的贡献。而毛竹扩张后期MRC-f、MRC-b和MRC占SOC比例并没有显著变化，意味着毛竹扩张后期MRC和植物源残体碳对SOC含量的提升均有贡献，且两者贡献的相对比例保持不变。土壤MRC含量随着剖面深度的加深逐渐下降，而MRC占SOC比值却随着土壤深度的增加而逐渐升高，说明深层土壤中...     

毛竹种群向针阔林扩张的根系形态可塑性

为了弄清毛竹(Phyllostachys edulis)向针阔林扩张过程中根系的形态可塑性反应,在浙江天目山自然保护区毛竹向针阔林扩张的典型过渡地带,连续区域上设置毛竹纯林、针阔-毛竹混交林(以下简称过渡林)、针阔林3种样地。用根钻法采集样地毛竹根系、针阔树根系并比对其生物量密度、细根比根长、相邻同级侧根节点距等形态特征参数变化。结果表明:随着毛竹的扩张程度增加,林内根系生物量密度增加;且与针阔树竞争过程中毛竹将更多的根系放置于表层;同时在水平方向上随离样株距离的增加未出现明显变化,而针阔树根系则随离样木距离的增加而逐渐减少;毛竹根系比根长明显增加,平均增幅15%;一、二级侧根节点距则均有所下降,毛竹侧根数量增多。这些结果表明毛竹种群可通过根系生物量密度、细根比根长、相邻同级侧根节点距等形态可塑性方式实现向周边森林扩张。     

Spatial heterogeneity and carbon contribution of aboveground biomass of moso bamboo by using geostatistical theory

Moso bamboo extensively distributes in southeast and south Asia, and plays an important role in global carbon budget. However, its spatial distribution and heterogeneity are poorly understood. This research uses geostatistics theory to examine the spatial heterogeneity of aboveground biomass (AGB) of moso bamboo, and uses a point kriging interpolation method to estimate and map its spatial distribution. Results showed that (1) spatial heterogeneity and spatial pattern of moso bamboo’s AGB can be revealed by an exponential semivariance model. The analysis of the model structure indicating that the AGB spatial heterogeneity is mainly composed of spatial autocorrelation components, and spatial autocorrelation range is from 360 to 41,220 m; (2) kriging standard deviation map showing the level of the model errors indicates that the AGB spatial distribution by point kriging interpolation method is reliable; (3) the average AGB of moso bamboo in Anji County is 44.228 Mg hm⁻², and carbon density is 20.297 Mg C hm⁻². The total AGB of moso bamboo accounts for 16.97% of the total forest-stand biomass in Zhejiang province. The total carbon storage of moso bamboo in China is 68.3993 Tg C, accounting for 1.6286% of the total forest carbon storage. This implies the important contribution of moso bamboo in regional or national carbon budget.     

毛竹入侵对森林植物和土壤的影响研究进展

植物与土壤稳定性和动态变化反映了森林生态系统在复杂生境下的自我调控和适应能力。毛竹入侵森林生态系统造成的诸多影响已经成为新的研究热点。系统综述了毛竹入侵的机制,以及对植物生存能力、物种多样性、植被碳储量,土壤理化性质以及土壤微生物结构与功能影响的最新研究进展。针对目前研究存在的问题,提出了丰富毛竹入侵管控手段、着重不同类型毛竹—森林临界面演替长期监测、明确毛竹入侵阶段划分、加强毛竹入侵生态后效研究等研究展望。有助于理解森林与毛竹入侵之间的相互作用、森林对毛竹入侵的响应和适应对策,对了解毛竹入侵机制,预测植物和土壤在毛竹入侵后的变化特征具有一定的借鉴意义。     

酸雨对毛竹入侵阔叶林缓冲区根系形态及分布格局的影响

为明确亚热带毛竹与阔叶树根系对酸雨的适应策略,于2017-2018年在浙江省杭州临安天目山国家级自然保护区毛竹入侵阔叶林过渡区开展酸雨模拟试验,选取T1（pH=4.0）、T2（pH=2.5）、CK（pH=5.5）3个模拟酸雨梯度,分析不同强度酸雨作用下毛竹与阔叶树的根系变化。结果表明：T1对阔叶树根系形态指标具有显著的抑制作用（P<0.05）,导致阔叶树根系的总根长、总表面积、总体积及和细根比根长分别下降了39.9%,39.4%,42.3%和16.2%;T2对毛竹和阔叶树根系指标均有显著的抑制作用（P<0.05）,导致毛竹的根系总根长、总表面积、总体积及细根比根长分别下降了41.5%,42.9%,46.4%和15.1%,阔叶树根系分别下降了60.2%,63.3%,61.8%和20.5%。随着酸雨强度的增加,林内根系生物量密度减少,毛竹将更多的根系置于土壤表层。在水平方向上阔叶树根系则随离树距离的增加而逐渐减少,毛竹2-5 mm径级根系生物量在离竹20 cm,离树40 cm和20 cm之间差异显著（P<0.05）。pH、有机质、可溶有机碳、碱解氮、有效磷和速效钾对毛竹的根系可塑性具有显著的影响（P<0.05）。这些结果表明,毛竹在酸雨作用下利用根系形态可塑性实现种群竞争优势。     

基于TM遥感影像的陕北黄土区结构化植被因子指数提取

根据结构化植被因子指数的概念,以TM影像为信息源,探讨了利用遥感技术提取陕北黄土区结构化植被因子指数（C_s）的途径与方法.结果表明：在陕北黄土区,C_s能更好地描述植被群落的水土保持效益,其与绿度植被指数（归一化植被指数NDVI、修正土壤调整植被指数MSAVI）和黄度植被指（归一化差异衰败指数NDSVI、归一化耕作指数NDTI）等单一的遥感植被指数虽然均存在良好的相关关系,但用绿度与黄度植被指数相结合可综合反映植被的水土保持功能,能较好地克服单一指数在描述植被控制水土流失中的不足;MSAVI、NDTI分别是基于遥感影像提取C_s较为理想的绿度和黄度植被指数;根据群落结构化植被因子指数与遥感植被指数的关系推算区域尺度上的结构化植被因子指数是可行的,但由于不同地区植物物候期的差异,要使该方法在其他地区适用,仍需开展相应的率定和验证工作.     

亚热带地区马尾松林碳储量的遥感估算——以长汀河田盆地为例

全球气候的变化已使得人类日益关注森林生态系统的碳储量变化.以福建省长汀县河田盆地为例,开展马尾松林碳储量估算模型的研究.通过2010年的野外样地调查获得了马尾松林的实测数据,并将其与同年的ALOS遥感影像对应样地的植被光谱信息进行比较.通过研究5种遥感植被指数与马尾松林碳储量之间的相关关系,从中选取了基于归一化植被指数(NDVI)的研究区最佳马尾松林碳储量反演模型.精度分析表明,该模型平均相对误差为-1.95％,均方根误差为3.01 t/hm2,因此可以有效地用于反演研究区的马尾松林碳储量.利用该模型反演出河田盆地2010年马尾松林的总碳储量为114.58×104 t,碳密度为34.92 t./hm2.     

桃江县毛竹林生态系统碳储量及其空间分布

采用标准地调查和生物量实测方法,研究了湖南省桃江县毛竹林生态系统生物量、碳含量、碳储量及空间分布格局。结果表明,不同年龄毛竹林生态系统总生物量分别为:28.147、30.889 t/hm~2和57.763 t/hm~2,其中竹林层生物量为20.254、25.036、55.685 t/hm~2,各器官生物量均以竹竿最高,占器官生物量的63.0%以上。不同年龄毛竹各器官碳平均含量为0.466—0.483 g C/g;灌木层碳含量为0.474—0.489 g C/g;草本层为0.472—0.490 g C/g;死地被物层为0.213—0.276 g C/g;土壤层有机碳含量为14.790—34.503 g C/g。各年龄毛竹林生态系统总碳储量分别为131.273、139.089 t/hm~2和167.817 t/hm~2,其中植被层碳储量为13.627—28.419 t/hm~2,占系统总碳储量的9.935%—16.935%;死地被物为0.307—0.420 t/hm~2,占0.234%—0.265%;土壤层为117.339—138.978 t/hm~2,占82.815%—89.799%。毛竹林生态系统碳储量分布格局为:土壤层植被层死地被物层。研究结果可为深入研究毛竹林的碳平衡提供基础数据。     

Wide Dynamic Range Vegetation Index for remote quantification of biophysical characteristics of vegetation

The Normalized Difference Vegetation Index (NDVI) is widely used for monitoring, analyzing, and mapping temporal and spatial distributions of physiological and biophysical characteristics of vegetation. It is well documented that the NDVI approaches saturation asymptotically under conditions of moderate-to-high aboveground biomass. While reflectance in the red region (rho(red)) exhibits a nearly flat response once the leaf area index (LAI) exceeds 2, the near infrared (NIR) reflectance (PNIR) continue to respond significantly to changes in moderate-to-high vegetation density (LAI from 2 to 6) in crops. However, this higher sensitivity of the rho(NIR) has little effect on NDVI values once the rho(NIR) exceeds 30%. In this paper a simple modification of the NDVI was proposed. The Wide Dynamic Range Vegetation Index, WDRVI = (a * rho(NIR-rho(red))/(a * rho(NIR) + rho(red)), where the weighting coefficient a has a value of 0.1-0.2, increases correlation with vegetation fraction by linearizing the relationship for typical wheat, soybean, and maize canopies. The sensitivity of the WDRVI to moderate-to-high LAI (between 2 and 6) was at least three times greater than that of the NDVI. By enhancing the dynamic range while using the same bands as the NDVI, the WDRVI enables a more robust characterization of crop physiological and phenological characteristics. Although this index needs further evaluation, the linear relationship with vegetation fraction and much higher sensitivity to change in LAI will be especially valuable for precision agriculture and monitoring vegetation status under conditions of moderate-to-high density. It is anticipated that the new index will complement the NDVI and other vegetation indices that are based on the red and NIR spectral bands.     

森林生物量遥感降尺度研究

森林生物量是评价全球碳氧平衡、气候变化的重要指标。目前已有基于星载激光雷达数据的全球森林生物量产品,但空间分辨率较低,不能很好地满足小区域森林调查和动态监测的需要。针对这一现状,以美国马里兰州两个森林分布状况不同的区域为研究区,基于CMS(Carbon Monitoring System)30 m分辨率和GEOCARBON 1 km分辨率森林地上生物量产品以及TM等数据源,通过升尺度模拟低分辨率生物量数据和直接使用低分辨率产品两种方式,分别尝试建立了多光谱地表参数和低分辨率森林地上生物量之间的统计关系,以此作为降尺度模型实现了森林地上生物量空间分辨率从1 km到30 m的转换,并对降尺度结果进行精度评价和误差分析。结果表明:模拟数据降尺度后的30 m分辨率森林地上生物量空间分布和CMS森林地上生物量分布状况大致相同,RMSE=59.2—65.5 Mg/hm~2,相关系数约为0.7;其降尺度结果优于GEOCARBON产品直接降尺度结果RMSE=75.3—79.9 Mg/hm~2;相较于线性模型,非线性模型能更好地呈现森林地上生物量和地表参数间的关系;总体上,降尺度生物量呈现高值区低估,低值区高估的现象。     

Spectral response of the seagrass Zostera noltii with different sediment backgrounds

The efficiency of vegetation indices (VIs) to estimate the above-ground biomass of the seagrass species Zostera noltii Hornem. from remote sensing was tested experimentally on different substrata, since terrestrial vegetation studies have shown that VIs can be adversely influenced by the spectral properties of soils and background surfaces. Leaves placed on medium sand, fine sand and autoclaved fine sand were incrementally removed, and the spectral reflectance was measured in the 400–900 nm wavelength range. Several VIs were evaluated: ratios using visible and near infrared wavelengths, narrow-band indices, indices based on derivative analysis and continuum removal. Background spectral reflectance was clearly visible in the leaf reflectance spectra, showing marked brightness and spectral contrast variations for the same amount of vegetation. Paradoxically, indices used to minimize soil effects, such as the Soil-Adjusted Vegetation Index (SAVI) and the Modified second Soil-Adjusted Vegetation Index (MSAVI₂) showed a high sensitivity to background effects. Similar results were found for the widely used Normalized Difference Vegetation Index (NDVI) and for Pigment Specific Simple Ratios (PSSRs). In fact, background effects were most reduced for VIs integrating a blue band correction, namely the modified specific ratio (mSR₍₇₀₅₎), the modified Normalized Difference (mND₍₇₀₅₎), and two modified NDVIs proposed in this study. However, these indices showed a faster saturation for high seagrass biomass. The background effects were also substantially reduced using Modified Gaussian Model indices at 620 and 675 nm. The blue band corrected VIs should now be tested for air-borne or satellite remote sensing applications, but some require sensors with a hyperspectral resolution. Nevertheless, this type of index can be applied to analyse broad band multispectral satellite images with a blue band.     

不同端元模型下湿地植被覆盖度的提取方法——以北京市野鸭湖湿地自然保护区为例

植被覆盖度作为反映湿地植物生长状况的重要生态学参数,在评估和检测湿地生态环境方面起着关键的作用.以华北内陆典型的淡水湿地——北京市野鸭湖湿地自然保护区为研究对象,中等分辨率的Landsat TM影像为数据源,基于线性光谱混合模型(LSMM)对研究区的植被覆盖度进行了估算.针对湿地植被类型丰富、土地利用类型多样化的特点,利用归一化植被指数(NDVI)在反映植物生长状况、覆盖程度以及区分地表覆盖类型方面的优势,通过对原始Landsat TM影像增加NDVI数据维对影像进行维度扩展,克服了传统研究中通常从Landsat TM影像上提取3-4种端元的局限,经最小噪声分离变换(MNF变换)、纯像元指数(PPI)计算以及人机交互端元选取等一系列运算,构建以陆生植物、水生植物、高反射率地物、低反射率地物、裸露土壤为组分的五端元模型来反映研究区的地物组成;同时,以原始Landsat TM影像为基础,构建植物、高反射率地物、低反射率地物、裸露土壤为组分的四端元模型.针对两种端元模型,采用全约束下的LSMM算法进行混合像元分解以获取研究区的植被覆盖度,其次辅以研究区的纯水体信息对其进行优化.精度检验采用相同时期的高分辨率WorldView-2多光谱影像来进行.研究表明:虽然四端元模型与五端元模型对植被覆盖度的估算结果在空间上具有基本一致的分布趋势,但是前者的估算结果在数值上要普遍低于后者,在研究区的水体及其附近,四端元模型难以体现水生植物的植被覆盖信息;另外,五端元模型的估算结果与检验数据的相关系数R达到0.9023,均方根误差(RMSE)为0.0939,明显优于四端元模型的R=0.8671和RMSE=0.1711.这反映了通过对影像进行维度扩展的方法来改进端元提取的数量是可行的,而由此构建的五端元模型可以更充分的反映研究区地物之间的光谱差异,从而获得更好的估算精度.     

经营措施对毛竹林土壤不同组分有机碳、氮及化学结构的影响

以次生常绿阔叶林为对照,选择立地条件相近的无经营、粗放经营和集约经营3种类型毛竹林为研究对象,应用密度-粒径联合分组以及化学、生物分析和傅里叶变换红外光谱(FTIR)方法,探讨经营措施对毛竹林土壤不同组分有机碳、氮含量,分配比例及结构特征的影响。结果表明: 与对照相比,无经营和粗放经营毛竹林显著提高了土壤总有机碳(TOC)、全氮(TN)、游离态颗粒有机碳、氮、可溶性有机碳(DOC)、氮(DON)和矿物结合态有机碳、氮的含量。无经营毛竹林虽然显著增大了游离态颗粒有机碳、氮的分配比例,但其与黏土矿物结合的有机碳依然是土壤有机碳的最大贮存库(67.6%)。集约经营导致竹林土壤有机碳、全氮的贮量及各组分有机碳、氮含量下降,但明显增大了DOC/TOC、微生物生物量氮与全氮比值以及微生物生物量碳和土壤有机碳的比值(微生物商)。经营措施对土壤有机碳的化学结构也具有显著影响。与对照相比,无经营和粗放经营毛竹林土壤有机碳中酚醇-OH、脂肪族-CH、芳香族C=C和羰基C=O吸收峰相对强度增强,土壤疏水性显著增加。土壤有机碳的脂肪碳、芳香碳和疏水性与土壤碳氮总量呈显著正相关,与微生物商呈显著负相关。在人为干扰减少的情况下,毛竹林凋落物、根系等有机质残体输入量的增多引起土壤难分解化合物的相对积累,使有机碳化学稳定性明显增强。同时,土壤黏土矿物质对土壤有机碳起到了很好的保护作用,通过矿物-有机碳复合使土壤碳储存稳定性更高,进而有利于土壤碳的长期保存。     

联合GF-6和Sentinel-2红边波段的森林地上生物量反演

光谱反射率能反映地物差异,是森林地上生物量（Aboveground Biomass,AGB）遥感反演的理论基础。红边波段处于近红外与红光波段交界处快速变化的区域,能对植被冠层结构和叶绿素含量的微小变化做出快速反应,对植被生长状况较敏感。研究以GF-6和Sentinel-2多光谱影像作为数据源,结合野外调查AGB数据,构建落叶松和樟子松AGB线性和非线性估测模型,通过比较模型精度选择最优模型进行森林AGB反演和空间分布制图。结果表明：GF-6和Sentinel-2影像红边波段反射率与落叶松、樟子松AGB均呈显著相关（P<0.05）,红边波段对AGB估测较敏感。多变量估测模型整体估测效果优于单变量模型,所有模型中多元线性回归模型取得了最优的决定系数（落叶松R²=0.66,樟子松R²=0.65）和最低的均方根误差（落叶松RMSE=31.45 t/hm²,樟子松RMSE=54.77 t/hm²）。相比单个数据源,联合GF-6和Sentinel-2影像构建的多元线性回归模型估测效果得到了显著提升,模型RMSE对于落叶松和樟子松AGB估测分别最大降低了22.9%和11.2%。增加红边波段进行AGB估测能显著提高模型估测精度,三组数据源分别加入红边波段信息后进行建模,模型RMSE得到了显著降低。GF-6拥有800 km观测幅宽和高效的重访周期,可以快速地提供大尺度时间序列数据,在森林地上生物量反演和动态监测方面有着很大潜力。     

Comparative Study of Carbon Storage in Different Forest Stands in Subtropical China

Selection and development of tree species with high fixing CO₂ capacity is an increasing problem worldwide. A comparative study on carbon fixation ability of three forest stands was conducted at Linlong Mountain, Li’nan County, Zhejiang Province, China. The results showed that total carbon storage in the ecosystems of Moso bamboo, Chinese fir, and Masson pine stands were 104.83, 95.66, and 96.49 t C/ha, respectively. The spatial distribution of carbon storage in the three ecosystems decreased in the order: soil > tree story > the vegetation under the forests. Carbon storage in the soils under Moso bamboo, Chinese fir, and Masson pine stands accounted for 65.3, 61.4, and 55.6% of the total CSs, respectively. The Moso bamboo forest ecosystem fixed 1.69 and 1.63 times as much C (9.64 t C/ha/year) as the Chinese fir and Masson pine forest ecosystems, respectively.     

Forest responses to simulated elevated CO2 under alternate hypotheses of size‐ and age‐dependent mortality

Elevated atmospheric carbon dioxide (eCO₂) is predicted to increase growth rates of forest trees. The extent to which increased growth translates to changes in biomass is dependent on the turnover time of the carbon, and thus tree mortality rates. Size‐ or age‐dependent mortality combined with increased growth rates could result in either decreased carbon turnover from a speeding up of tree life cycles, or increased biomass from trees reaching larger sizes, respectively. However, most vegetation models currently lack any representation of size‐ or age‐dependent mortality and the effect of eCO₂ on changes in biomass and carbon turnover times is thus a major source of uncertainty in predictions of future vegetation dynamics. Using a reduced‐complexity form of the vegetation demographic model the Functionally Assembled Terrestrial Ecosystem Simulator to simulate an idealised tropical forest, we find increases in biomass despite reductions in carbon turnover time in both size‐ and age‐dependent mortality scenarios in response to a hypothetical eCO₂‐driven 25% increase in woody net primary productivity (wNPP). Carbon turnover times decreased by 9.6% in size‐dependent mortality scenarios due to a speeding up of tree life cycles, but also by 2.0% when mortality was age‐dependent, as larger crowns led to increased light competition. Increases in aboveground biomass (AGB) were much larger when mortality was age‐dependent (24.3%) compared with size‐dependent (13.4%) as trees reached larger sizes before death. In simulations with a constant background mortality rate, carbon turnover time decreased by 2.1% and AGB increased by 24.0%, however, absolute values of AGB and carbon turnover were higher than in either size‐ or age‐dependent mortality scenario. The extent to which AGB increases and carbon turnover decreases will thus depend on the mechanisms of large tree mortality: if increased size itself results in elevated mortality rates, then this could reduce by about half the increase in AGB relative to the increase in wNPP.     

Investigating phenological changes using MODIS vegetation indices in deciduous broadleaf forest over continental U.S. during 2000–2008

Vegetation phenology describing the seasonal cycle of plants is currently one of the main concerns in the study of climate change and carbon balance estimation in ecosystems. Remote sensing techniques which can capture canopy reflectance allow vegetation photosynthetic capacity to be assessed. In this study, the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and Leaf Area Index (LAI) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) measurements were used to identify onset date of greenness in deciduous broadleaf forest (DBF) over the continental United States from year 2000 to 2008. Onset dates determined by these three indices were compared with North American First Leaf Lilac Phenology Data over the same time period. NDVI has a best agreement with the field data among the three vegetation indices. Spatial analysis was performed on the onset dates predicted with NDVI. Four major conclusions were drawn from this study are: 1) onset dates are not only dependent on latitude but also associated with ecoregions and altitudes; 2) onset of greenness moves northward gradually and the average change of onset dates along latitude is about 3 days per degree. Interannual variability of onset dates is greater at higher latitudes (> 43 °N) than at lower latitudes (≤ 43 °N); 3) at the same latitude, DBF in mountain area tends to green up latter and coastal forest tends to green up earlier than other ecoregions; and 4) the impact of altitude is more obvious when the range of elevation achieves more than 1000 m. These conclusions provide insight for assessing vegetation indices in determining onset date of greenness at regional scale, and can be exploited to analyze the impacts of climate change on terrestrial ecosystem.     

基于HJ1B和ALOS/PALSAR数据的森林地上生物量遥感估算

森林地上生物量的精确估算能够减小碳储量估算的不确定性。为了探寻一种有效地提高森林生物量估算精度的方法,探讨了基于遥感物理模型和经验统计模型估算山地森林地上生物量的方法。首先,基于Li-Strahler几何光学模型和多元前向模式(MFM)进行模型模拟,结合查找表算法(LUT)从多光谱图像HJ1B估算贺兰山研究区的森林地上生物量。其次,采用统计方法建立了2种回归模型:(1)多光谱图像HJ1B进行混合像元分解(SMA),并与雷达图像ALOS/PALSAR进行图像融合建立生物量回归模型;(2)雷达图像ALOS/PALSAR后向散射系数和实测生物量建立了生物量回归模型。用实测数据对3种算法估算结果进行精度验证。研究结果表明:采用几何光学模型和MFM算法估算的森林地上生物量精度最好(决定系数R2=0.61,均方根误差RMSE=8.33 t/hm2,P0.001),其估算地上生物量与实测值一致性较好,估算生物量精度略优于SMA估算的精度(R2=0.60,RMSE=9.417 t/hm2);ALOS/PALSAR多元回归估算的精度最差(R2=0.39,RMSE=14.89 t/hm2)。由此可见,采用几何光学模型和混合像元分解SMA适合估算森林地上生物量,利用这2种方法进行森林地上生物量遥感监测研究具有一定的应用潜力。