Spatiotemporal pattern of urban forest leaf area index in response to rapid urbanization and urban greening

Rapid urbanization and urban greening have caused great changes to urban forests in China. Understanding spatiotemporal patterns of urban forest leaf area index(LAI) under rapid urbanization and urban greening is important for urban forest planning and management. We evaluated the potential for estimating urban forest LAI spatiotemporally by using Landsat TM imagery. We collected three scenes of Landsat TM(thematic mapper)images acquired in 1997, 2004 and 2010 and conducted a field survey to collect urban forest LAI. Finally, spatiotemporal maps of the urban forest LAI were created using a NDVI-based urban forest LAI predictive model.Our results show that normalized differential vegetation index(NDVI) could be used as a predictor for urban forest LAI similar to natural forests. Both rapid urbanization and urban greening contribute to the changing process of urban forest LAI. The urban forest has changed considerably from 1997 to 2010. Urban vegetated pixels decreased gradually from 1997 to 2010 due to intensive urbanization.Leaf area for the study area was 216.4, 145.2 and173.7 km~2 in the years 1997, 2004 and 2010, respectively.Urban forest LAI decreased sharply from 1997 to 2004 and increased slightly from 2004 to 2010 because of numerous greening policies. The urban forest LAI class distributions were skewed toward low values in 1997 and 2004. Moreover, the LAI presented a decreasing trend from suburban to downtown areas. We demonstrate the usefulness of TM remote-sensing in understanding spatiotemporal changing patterns of urban forest LAI under rapid urbanization and urban greening.     

Estimating vertical vegetation density through a SPOT5 imagery at multiple radiometric correction levels

There is growing concern about remote sensing of vertical vegetation density in rapidly expanding peri-urban interfaces.A widely used parameter for such density,i.e.,leaf area index (LAI),was measured in situ in Nanjing,China and then correlated with two vegetation indices (VI) derived from multiple radiometric correction levels of a SPOT5 imagery.The VIs were a normalized difference vegetation index (NDVI) and a ratio vegetation index (RVI),while the four radiometric correction levels were i) post atmospheric correction reflectance (PAC),ii) top of atmosphere reflectance (TOA),iii) satellite radiance (SR) and iv) digital number (DN).A total of 157 LAI-VI relationship models were established.The results showed that LAI is positively correlated with VI (r varies from 0.303 to 0.927,p < 0.001).The R 2 values of "pure" vegetation were generally higher than those of mixed vegetation.The average R 2 values of about 40 models based on DN data (0.688) were higher than that of the routinely used PAC (0.648).Independent variables of the optimal models for different vegetation quadrats included two vegetation indices at three radiometric correction levels,indicating the potential of vegetation indices at multiple radiometric correction levels in LAI inversion.The study demonstrates that taking heterogeneities of vegetation structures and uncertainties of radiometric corrections into account may help full mining of valuable information from remote sensing images,thus improving accuracies of LAI estimation.     

崂山林场森林冠层叶面积指数反演研究

本文以地处崂山林场东部林区作为研究区,运用逐步分析方法对6种植被指数和海拔、坡向、坡度等立地信息进行比较分析,筛选出3种植被指数NDVI、RVI、SAVI可敏感反映森林冠层LAI,建立分别以NDVI、DVI、SAVI为自变量的二次曲线模型、幂函数曲线模型、指数曲线模型以及包含这3种植被指数的多元线性模型,从决定系数(R2)和标准误差两个方面对基于不同植被指数LAI反演模型进行定量分析。结果表明,崂山林场LAI最佳的统计模型是多元线性模型,模型的R2是0.812,具有较好的估测效果。利用该模型反演了研究区的林分冠层LAI,并把崂山林场的林分冠层LAI分为5个等级,研究区的森林冠层LAI分布呈现西北部和东南部较低,而东北部和南部相对较高的特点。     

Asymmetric competition increases leaf inclination effect on light absorption in mixed canopies

? Context

The effects of leaf inclination on plant light capture, growth, and water balance of monospecific canopies are well documented, but we still lack information on such effects in the case of multispecific canopies.

? Aims

We investigated the effects of leaf inclination on the absorption of photosynthetically active radiation (PAR) of a mixed forest.

? Methods

We ran a 3D mechanistic radiation transfer model for a Mediterranean forest where Pinus halepensis makes the upper strata while Quercus ilex occupies the lower strata. As factors, we included (1) the distributions of leaf inclinations that ranged from vertical to horizontal (including the actual inclinations), (2) the fraction of diffuse light, sun position, and leaf area index (LAI), and (3) the Pinus/Quercus LAI ratio.

? Results

Simulated PAR absorption was more than twice as sensitive to leaf inclination in oaks than in pines because oaks depended on PAR transmitted below the pine layer. The extent of the effect depended on season, fraction of diffuse light, LAI, and vegetation spatial structure. None of the observed inclinations maximized PAR absorption, suggesting a trade-off with water economy.

? Conclusion

Erroneous assumptions about leaf inclination lead to larger errors when modelling heterogeneous, mixed canopies. This also highlights potential caveats when using models that do not account for the spatial structure of canopies.     

Characterization of radiation regimes in nonrandom forest canopies: theory,measurements, and a simplified modeling approach

We used field measurements and Monte Carlo simulations of canopy gap-size distribution and gap fraction to examine how beam radiation interacts with clumped boreal forest canopies of aspen (Populus tremuloides Michx.), black spruce (Picea mariana (Mill.) B.S.P.) and jack pine (Pinus banksiana Lamb.). We demonstrate that the Beer-Lambert law can be modified to accommodate transmission of radiation through a clumped forest canopy as a function of path length or sun zenith angle. Multiband Vegetation Imager (MVI) measurements and Monte Carlo simulations showed that values of the zenith element clumping index (Omega(e)(0)) are typically between 0.4 and 0.5 in jack pine and black spruce and 0.65 in aspen. Estimates of LAI obtained from MVI measurements of the canopy gap fraction and adjusted for canopy clumping and branch architecture yielded LAI values of 3.0 in jack pine, 3.3 in aspen, and about 6.0 in black spruce. These LAI estimates were within 10-25% of direct measurements made at the same sites. Data obtained with the MVI, along with numerical simulations, demonstrated that assumptions of random foliage distributions in boreal forests are invalid and could yield erroneous values of LAI measured by indirect techniques and false characterizations of atmosphere-biosphere interactions. Monte Carlo simulations were used to develop a general equation for beam radiation penetration as a function of zenith angle in clumped canopies. The essential measurements included stem spacing, crown diameter, crown depth, and within-crown gap fraction.     

不同密度杉木林内辐射与叶面积垂直分布对生长的影响

本文通过对八年生杉木人工林内太阳辐射与叶面积垂直分布的观测与研究，用计算机绘图与计算，得出以下结果：杉木叶面积的垂直分布和叶面积指数与密度有关，冠形因密度增加由圆锥形变为圆柱形，叶面积指数是先上升后下降。杉木林内辐射的消减随密度的增加而加剧，在冠层深3／4处趋于平缓，当郁闭度低于0．85时，林冠下辐射有回升，用累加叶面积指数分层计算林冠消光系数，可减少因叶片分布不均匀而产生的误差，用累计值计算辐射，可简化观测与计算，用辐射吸收率、叶面积指数，杉木个体生物量及年均生物增长量4个指标对杉木林生长作综合评价，八年生杉木林生长的较适宜工是2m×1m。     

基于多元回归模型的叶面积指数遥感反演

采用2011年8月获取的黄丰桥林场SPOT5数据为信息源,并同步开展现地样地调查,依据典型抽样,以不同的海拔、坡度、坡向进行选样,利用手持GPS和LAI-2000植物冠层分析仪,分别对选取的60块样地进行定位和叶面积指数测量。结合遥感数据和实地调查数据,对地理因子和遥感因子变量进行主成分分析,采用逐步回归法筛选出2个主成分建立多元回归方程,对该研究区域的植被叶面积指数进行模拟,精度达到84.17%。结果表明:RVI,NDVI,MSAVI,MCAVI和DVI与LAI之间存在较好的相关性。     

高光谱遥感森林叶面积指数估测方法研究

叶面积指数(LAI)是反映植物叶片数量、冠层结构变化、植物群落生命活力及其环境效应的重要参数,其定义为植株所有叶片单面面积总和与植株所占的土地面积的比值。文中总结国内外利用高光谱遥感数据估测森林叶面积指数的研究进展,并对众多的估测方法进行比较,最后分析了高光谱遥感森林叶面积指数估测研究的发展趋势。       

Leaf area dynamics of a boreal black spruce fire chronosequence

Specific leaf area (SLA) and leaf area index (LAI) were estimated using site-specific allometric equations for a boreal black spruce (Picea mariana (Mill.) BSP) fire chronosequence in northern Manitoba, Canada. Stands ranged from 3 to 131 years in age and had soils that were categorized as well or poorly drained. The goals of the study were to: (i) measure SLA for the dominant tree and understory species of boreal black spruce-dominated stands, and examine the effect of various biophysical conditions on SLA; and (ii) examine leaf area dynamics of both understory and overstory for well- and poorly drained stands in the chronosequence. Overall, average SLA values for black spruce (n = 215), jack pine (Pinus banksiana Lamb., n = 72) and trembling aspen (Populus tremuloides Michx., n = 27) were 5.82 +/- 1.91, 5.76 +/- 1.91 and 17.42 +/- 2.21 m2 x kg-1, respectively. Foliage age, stand age, vertical position in the canopy and soil drainage had significant effects on SLA. Black spruce dominated overstory LAI in the older stands. Well-drained stands had significantly higher overstory LAI (P < 0.001), but lower understory LAI (P = 0.022), than poorly drained stands. Overstory LAI was negligible in the recent (3-12 years old) burn sites and highest in the 70-year-old burn site (6.8 and 3.0 in the well- and poorly drained stands, respectively), declining significantly (by 30-50%) from this peak in the oldest stands. Understory leaf area represented a significant portion (> 40%) of total leaf area in all stands except the oldest.     

Light spectral composition in a tropical forest: measurements and model

I present a simple model that simulates vertical variations in the light spectrum within a forest canopy. The model considers only the vertical, downward transmission of light. The light in each canopy level was assumed to consist of non-intercepted radiation and radiation intercepted within the level and transmitted. The spectrum of non-intercepted light in each canopy level is the same as that of incident light above the canopy (input parameter), whereas the spectrum of transmitted light depends on leaf area index (LAI) and the mean transmission spectrum of leaves. The model was tested in a forest and provided adequate predictions of measured values. Stronger deviations were produced in the near infrared (NIR) waveband in lower canopy levels. Multiple regression between LAI, as the dependent variable, and spectral characteristics (Blue, Green, Red and NIR intensities) had an r(2) of 0.926. As a complement to other methods, I suggest light spectrum analysis as a non-destructive technique for estimating LAI in forest canopies.     

Estimation of LAI in the forested watershed using ASTER data based on Price’s model in summer and winter

Leaf area index (LAI) is an important parameter to identify the water balance in forested watershed as a biological factor influencing directly on the evapotranspiration in the forest area. The purpose of this study was to estimate the LAI in a small forested watershed in summer and winter by applying the Terra/Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data to the LAI estimation method. In this study, the estimation was based on the absorption and scattering processes of the solar radiation in the vegetation canopy and the spectral reflectance characteristics of soil vegetation. First, we estimated LAI based on Price’s model by application of ASTER data on the forested watershed located in the Tenzan Mountains of Saga, Japan. To validate the results of LAI estimation, secondly, we compared them to the measured LAI obtained by a plant canopy analyzer (LAI-2000) on the observation area inside the target region. This study showed that the LAI estimation method was a feasible and accurate method as indicated by the high relationship (r = 0.97) between LAI derived from ASTER data and LAI measured by LAI-2000. This paper is the first report on LAI estimation using Terra/ASTER data based on Price’s model and field investigation. This LAI estimation method is a reliable and applicable method.     

帽儿山地区叶面积指数遥感反演

以黑龙江省尚志市帽儿山林场(东北林业大学试验林场)为研究区,利用现代卫星遥感技术,结合实地调查采样数据和GPS测量技术,建立了从Landsat TM影像数据提取的植被指数(Vegetation Index,VI)与地面实测的叶面积指数(Leaf Area Index,LAI)的统计回归模型。然后再从众多统计模型中按照各自的相关系数(R)和确定系数(R2),选出反演LAI的最佳模型。     

Calibration and assessment of seasonal changes in leaf area index of a tropical dry forest in different stages of succession

A simple measure of the amount of foliage present in a forest is leaf area index (LAI; the amount of foliage per unit ground surface area), which can be determined by optical estimation (gap fraction method) with an instrument such as the Li-Cor LAI-2000 Plant Canopy Analyzer. However, optical instruments such as the LAI-2000 cannot directly differentiate between foliage and woody components of the canopy. Studies investigating LAI and its calibration (extracting foliar LAI from optical estimates) in tropical forests are rare. We calibrated optical estimates of LAI from the LAI-2000 with leaf litter data for a tropical dry forest. We also developed a robust method for determining LAI from leaf litter data in a tropical dry forest environment. We found that, depending on the successional stage of the canopy and the season, the LAI-2000 may underestimate LAI by 17% to over 40%. In the dry season, the instrument overestimated LAI by the contribution of the woody area index. Examination of the seasonal variation in LAI for three successional stages in a tropical dry forest indicated differences in timing of leaf fall according to successional stage and functional group (i.e., lianas and trees). We conclude that when calculating LAI from optical estimates, it is necessary to account for the differences between values obtained from optical and semi-direct techniques. In addition, to calculate LAI from litter collected in traps, specific leaf area must be calculated for each species rather than from a mean value for multiple species.     

植被遥感研究的新思路——走出传统光谱理论应用的误区

对遥感中沿用几十年的植被光谱理论提出质疑,阐述了传统植被遥感中存在的误区,提出新的观点及研究思路。第一次提出干旱植被指数(LDVI)和综合植被指数(IVI)的概念,探讨了干旱地区草原植被的信息提取及定量分析方法。     

深圳市立交绿地植物多样性及其叶面积指数研究

对深圳市部分立交绿地植物群落的物种丰富度指数、多样性指数、均匀度指数、群落林冠孔隙度和群落叶面积指数进行了比较分析。结果表明,深圳市立交绿地的植物物种丰富,但分布不均匀,多样性不够高;平均叶面积指数为3.05,属中等水平,但不同的立交绿地由于物种组成及结构的不同,其叶面积指数值有差异;平均林冠孔隙度为14.47,在保护较好的立交绿地具有较丰富的非林冠层乔木种类的幼苗。     

Estimating and mapping forest biomass in northeast China using joint forest resources inventory and remote sensing data

Being able to accurately estimate and map forest biomass at large scales is important for a better understanding of the terrestrial carbon cycle and for improving the effectiveness of forest management. In this study, forest plot sample data, forest resources inventory(FRI) data, and SPOT Vegetation(SPOT-VGT) normalized difference vegetation index(NDVI) data were used to estimate total forest biomass and spatial distribution of forest biomass in northeast China(with 1 km resolution). Total forest biomass at both county and provincial scales was estimated using FRI data of 11 different forest types obtained by sampling 1156 forest plots, and newly-created volume to biomass conversion models. The biomass density at the county scale and SPOT-VGT NDVI data were used to estimate the spatial distribution of forest biomass. The results suggest that the total forest biomass was 2.4 Pg(1 Pg = 10~(15) g), with an average of 77.2 Mg ha~(-1), during the study period. Forests having greater biomass density were located in the middle mountain ranges in the study area. Human activities affected forest biomass at different elevations, slopes and aspects. The results suggest that the volume to biomass conversion models that could be developed using more plot samples and more detailed forest type classifications would be better suited for the study area and would provide more accurate biomass estimates. Use of both FRI and remote sensing data allowed the down-scaling of regional forest biomass statistics to forest cover pixels to produce a relatively fineresolution biomass map.     

EOS/MODIS遥感监测在甘肃迭部重大森林火灾中的应用

森林生态系统是陆地自然生态系统中最大的生态系统,它在整个自然界的动态平衡中具有重要的作用.森林火灾是生态环境的一种重大自然灾害,全世界每年发生森林火灾几十万次.特别是20世纪80年代以来,全球气候持续变暖,林火有上升的趋势(舒立福等,1997).     

Modelling biomass and leaf area index in a sub-arctic Scandinavian mountain area

Estimates of biomass and leaf area index (LAI) are important variables in ecological and climate models. However, very little is known about the biomass and LAI of the vegetation in the Scandinavian mountain area. In this study, extensive field data consisting of diameter at breast height for 13?000 trees and height for 550 trees were collected. Furthermore, biomass and leaf area (LA) measurements for 46 mountain birch trees [Betula pubescens ssp. czerepanovii (Orlowa) Hämet-Ahti] and biomass and LA measurements for shrubs (e.g. Salix spp., Betula nana) at 36 sample plots were carried out. Multiplicative linear models for trees were fitted to tree biomass and LA measurements using basal area at breast height, height, crown diameter and diameter at stump height as explanatory variables. Additive linear models were fitted to shrub biomass and LAI measurements using coverage of shrubs, topographic variables and soil type as explanatory variables. The functions were then used to predict the biomass and LAI for trees and shrubs for the entire test area, which covers an area of 84 km² and is located at latitude 68° N. The mean total biomass estimates were 27?493 kg ha^?1 for the forest and 7650 kg ha^?1 for snow-protected heath and meadow vegetation. The LAIs were 2.06 and 0.52, respectively. For monitoring biomass and LAI in the Scandinavian mountain area, the functions could also be applied to data from traditional field-based inventories and the estimates might further be improved by combining the estimates from the test area with auxiliary information such as remote sensing images.     

Spatiotemporal analyses of urban vegetation structural attributes using multitemporal Landsat TM data and field measurements

Key message

We conducted spatiotemporal analyses of urban vegetation structural attributes using multitemporal Landsat TM data and field measurements. We showed that multitemporal TM data has the potential of rapidly estimating urban vegetation structural attributes including LAI, CC , and BA at an urban landscape level.

Context

Urban vegetation structural properties/attributes are closely linked to their ecological functions and thus directly affect urban ecosystem process such as energy, water, and gas exchange. Understanding spatiotemporal dynamics of urban vegetation structures is important for sustaining urban ecosystem service and improving the urban environment.

Aims

The purposes of this study were to evaluate the potential of estimating urban vegetation structural attributes from multitemporal Landsat TM imagery and to analyze spatiotemporal changes of the urban structural attributes.

Methods

We first collected three scenes of TM images acquired in 1997, 2004, and 2010 and conducted a field survey to collect urban vegetation structural data (including crown closure (CC), tree height (H), leaf area index (LAI), basal area (BA), stem density (SD), diameter at breast height (DBH), etc.). We then calculated and normalized NDVI maps from the multitemporal TM images. Finally, spatiotemporal urban vegetation structural maps were created using NDVI-based urban vegetation structure predictive models.

Results

The results show that NDVI can be used as a predictor for some selected urban vegetation structural attributes (i.e., CC, LAI, and BA), but not for the other attributes (i.e., H, SD, and DBH) that are well predicted by NDVI in natural vegetation. The results also indicate that urban vegetation structural attributes (i.e., CC, LAI, and BA) in the study area decreased sharply from 1997 to 2004 but increased slightly from 2004 to 2010. The CC, LAI, and BA class distributions were all skewed toward low values in 1997 and 2004. Moreover, LAI, CC, and BA of urban vegetation all present a decreasing trend from suburban areas to urban central areas.

Conclusion

The experimental results demonstrate that Landsat TM imagery could provide a fast and cost-effective method to obtain a spatiotemporal 30-m resolution urban vegetation structural dataset (including CC, LAI, and BA).

     

唐山市植被分布及其变化分析

在全球变化和城市化日益发展的背景下,区域植被受到剧烈影响,但植被又具有多种生态服务功能,这使其成为生态学的研究热点。植被指数是指卫星探测数据的线性或非线性组合,是反映植被的存在、数量、质量、状态及时空分布特点的指数。目