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.     

《中国植被志》的植被分类系统、植被类型划分及编排体系

植被志(vegegraphy)是基于植被调查资料, 全面记叙植被的群落外貌、种类组成、结构和功能、生境条件, 以及地理分布等特征, 并对同类植被进行归纳和总结的志书。“植被志”的英文译为“vegegraphy”, 是本文的新造词, 它是由“vegetation”的词头“vege-”和英文后缀“-graphy” (记叙之意)组成的合成词。《中国植被志》的研编是一项时间紧迫、内容复杂、工作量浩繁的重大科学工程。它的完成将极大提升中国植被科学和生态学的研究水平, 并为中国植被资源的合理利用、生物多样性保护及生态环境治理等提供不可或缺的基础资料。本文首先简述了植被的基本特征(主要包括外貌特征、种类组成、群落结构以及动态变化等)和国内外植被调查的进展情况, 简要回顾了中国植被分类系统的研究历史, 并对以往的分类系统进行了若干修订。在此基础上, 着重讨论并提出了《中国植被志》卷册编排体系和用于《中国植被志》研编的植被类型划分方案。在对植被分类系统的修订方面, 主要对高级分类单位及相对应的英文名称进行了讨论和修订。按照本文修订的分类系统, 中国植被的分类单位及其对应的英文名称分别是: 植被型组(Vegetation Formation Group)、植被型(Vegetation Formation)和植被亚型(Vegetation Subformation)、群系组(Alliance Group)、群系(Alliance)和亚群系(Suballiance)、群丛组(Association Group)以及群丛(Association)。在植被型组中, 划分为9类: 森林、灌丛、草本植被、荒漠、高山冻原与稀疏植被、沼泽与水生植被、农业植被、城市植被及无植被地段。关于《中国植被志》的卷册编排和“植被类型”划分, 首先按高级分类单位——植被型划分相应的“卷”; 在此框架下, 模糊“植被亚型”、“群系组”和“群系”的概念, 确定“植被类型” (Vegetation type), 并将其作为植被志各卷中的“册”。这样处理不仅保证了研编工作的可操作性, 也保持了同一卷册中特定植被类型的完整性。《中国植被志》编排体系中的“植被类型”的划分很重要, 它是指具有相同建群种及相同优势类群(如种、属)的植被组合, 但它不是严格意义上的植被分类单位。“植被类型”的划分遵循“优势类群及生活型的同一性, 生境条件的相对重要性, 植被特征及用途的差异性, 以及突出植被志的应用性”等原则。按该编排体系, 《中国植被志》将由48卷约110册组成。     

面向对象的优势树种类型信息提取技术

森林植被优势树种类型信息的提取是遥感影像分类中的难点.面向对象分类方法是用高空间分辨率遥感数据实现精确类型信息提取的新方法.本文以2013年Quickbird影像作为基础数据,选择福建省三明市将乐林场为研究区,采用面向对象多尺度分割方法提取耕地、灌草地、未成林造林地、马尾松、杉木和阔叶树等类型信息.分类特征融合植被的光谱、纹理和多种植被指数3类特征信息,建立类层次结构,对不同层次分别用隶属度函数和决策树分类规则,最终完成分类,并与只用纹理与光谱特征相结合的方法进行对比.结果表明:融合纹理、光谱、多种植被指数的面向对象的分类方法提取研究区优势树种类型信息的精度为91.3％,比只用纹理和光谱的方法精度提高了5.7％.     

《中国植被志》研编内容与规范

植被志是基于植被(或植物群落)调查资料, 全面记叙植被的外貌、物种组成、结构和功能, 以及地理分布和生境条件等特征, 并对同类植被进行归纳和总结的志书。《中国植被志》是第一部对中国植被进行全面记述的志书, 预计完成约48卷110册。在借鉴《中国植被》(1980)(简称“80方案”)植被分类基本原则的基础上,《中国植被志》将对中国植被分类系统的高级分类单位(植被型组、植被型和植被亚型)进行归纳和总结, 对中级和低级分类单位(群系组、群系、亚群系, 群丛组、群丛)进行详细描述。植被高级分类单位的描述具有概括性质, 是在中国植被分类系统中级和低级分类单位描述的基础上, 对其在全球和中国境内的地理分布、自然环境、群落外貌、植被类型及多样性、优势种或共优势种、生物多样性保育价值以及资源现状等进行概述, 并对“80方案”相关内容进行修订和拓展, 将提供对中国植被基本特征客观、准确的记述。在植被中级和低级分类单位中, 群系组描述的内容包括地理分布、自然环境、群落外貌、植被类型以及价值与保育等内容; 群系描述的主要内容包括地理分布、自然环境、生态特征、物种组成、群落结构、群丛组和群丛的分类与描述、优势种的生物学特性、生物量与生产力、植被动态与演替以及价值与保育等方面。作为植被志研编的核心内容, 群丛组和群丛的分类与描述主要基于植被调查资料, 采用数量分类方法, 根据群落结构和物种组成的差异划分出不同的植被类型, 并对其基本特征进行定量描述和归纳。其中, 群落的层片结构、特定植被分类单元的特征种或特征种组的筛选与甄别是植被类型划分的关键环节; 而群落外貌, 群落结构, 物种组成, 各类物种的生长习性、生境的偏适性等是群丛组和群丛描述与归纳的重点内容。该文提出了中国植被中级和低级分类单位的命名方案, 其特点在于植被类型的科学名称中同时体现了植被分类单元特征种或优势种的名称及其所属的高级植被分类单位(植被型组或植被型)的名称, 兼顾了植被名称的规范性与实用性。《中国植被志》的研编工作由文献整编、群落调查、数据分析与整理、文本撰写等环节组成。该文对植被样方的调查与收集, 文献收集与整编, 气候、土壤、地形等相关数据的来源及其整理方法, 植被分类方法, 植被命名, 植被分类单元描述的内容, 植被志章节编写大纲、体裁及撰写等多个规范进行了详细的阐述或示例。     

Airborne Laser Scanning as a Tool for Lowland Floodplain Vegetation Monitoring

Monitoring of three-dimensional floodplain vegetation structure is essential for ecological studies, as well as for hydrodynamic modelling of rivers. Height and density of submerged vegetation and density of emergent vegetation are the key characteristics from which roughness parameters in hydraulic models are derived. Airborne laser scanning is a technique with broad applications in vegetation structure mapping, which therefore may be a promising tool in monitoring floodplain vegetation for river management applications. This paper first provides an introduction to the laser scanning technique, and reviews previous studies on the extraction of vegetation height and density of forests, low vegetation and meadows or unvegetated areas. Reliable predictions using laser scan data have been reported for forest height (R²=0.64–0.98), parameters related to forest density, such as stem number, stem diameter, biomass, timber volume or basal area (R²=0.42–0.93), and herbaceous vegetation height (summer condition; R²=0.75–0.89). No empirical relations have been reported on density of herbaceous vegetation. Laser data of meadows and unvegetated areas show too much noise to predict vegetation structure correctly. In a case study for the lower Rhine river, the potential of laser scan mapping of vegetation structure was further explored for winter conditions. Three laser-derived metrics that are often reported in the literature have been applied to characterize local vertical distributions of laser reflections. The laser data clearly show the large structural differences both between and within vegetation units that currently are the basis of floodplain vegetation and roughness mapping. The results indicate that airborne laser scanning is a promising technique for extraction of 3D-structure of floodplain vegetation in winter, except for meadows and unvegetated areas.     

Albedo estimates for land surface models and support for a new paradigm based on foliage nitrogen concentration

Vegetation albedo is a critical component of the Earth's climate system, yet efforts to evaluate and improve albedo parameterizations in climate models have lagged relative to other aspects of model development. Here, we calculated growing season albedos for deciduous and evergreen forests, crops, and grasslands based on over 40 site‐years of data from the AmeriFlux network and compared them with estimates presently used in the land surface formulations of a variety of climate models. Generally, the albedo estimates used in land surface models agreed well with this data compilation. However, a variety of models using fixed seasonal estimates of albedo overestimated the growing season albedo of northerly evergreen trees. In contrast, climate models that rely on a common two‐stream albedo submodel provided accurate predictions of boreal needle‐leaf evergreen albedo but overestimated grassland albedos. Inverse analysis showed that parameters of the two‐stream model were highly correlated. Consistent with recent observations based on remotely sensed albedo, the AmeriFlux dataset demonstrated a tight linear relationship between canopy albedo and foliage nitrogen concentration (for forest vegetation: albedo=0.01+0.071%N, r²=0.91; forests, grassland, and maize: albedo=0.02+0.067%N, r²=0.80). However, this relationship saturated at the higher nitrogen concentrations displayed by soybean foliage. We developed similar relationships between a foliar parameter used in the two‐stream albedo model and foliage nitrogen concentration. These nitrogen‐based relationships can serve as the basis for a new approach to land surface albedo modeling that simplifies albedo estimation while providing a link to other important ecosystem processes.     

Model for the potential natural vegetation mapping of Friuli Venezia-Giulia (NE Italy) and its application for a biogeographic classification of the region

ABSTRACT

The aim of this paper is to present a joint vegetation data base and GIS application to produce a model to map the potential natural vegetation (PNV) of the Friuli-Venezia Giulia region (NE Italy) and to show how the map can be used to draw a biogeographic classification of the region. All the natural arboreal coenoses growing below the timber line, as well as the dwarf shrubs and prairies developing above this limit, were considered. Some cross sections, extracted from the potential vegetation map, were tested against transects of real vegetation distribution.     

The value of indicator species for landscape characterization

Given that different types of landscape are affected by different environmental factors, is it possible to identify plant species indicative of these landscape types? An analysis of indicator species was made using 140 vegetation samples distributed over five landscape types. A total of 30 indicator species were identified, displaying varying indicator value. The variation disclosed the existence of a gradient between landscape types in terms of the prevailing ecological conditions. The analysis of the results also led to a reflection on the hierarchical level of which species are indicative (landscape vs. ecosystem). Further 20 samples were taken to check the validity of the indicator species. The identification of the indicator species present in these samples enabled each sample to be assigned to one of the landscape types; that assignment was subsequently checked against the actual landscape from which samples were taken. Seventy-five percent of the 20 validation samples were correctly assigned; the misassignment of the remaining 25% was due largely to the heterogeneous nature of the landscapes. On the basis of these results, we concluded that it is possible to characterize landscapes on the basis of indicative plant species, although characterization becomes more incomplete as the internally heterogeneous nature of the landscape increases.     

A dynamic global vegetation model for use with climate models: concepts and description of simulated vegetation dynamics

Changes in vegetation structure and biogeography due to climate change feedback to alter climate by changing fluxes of energy, moisture, and momentum between land and atmosphere. While the current class of land process models used with climate models parameterizes these fluxes in detail, these models prescribe surface vegetation and leaf area from data sets. In this paper, we describe an approach in which ecological concepts from a global vegetation dynamics model are added to the land component of a climate model to grow plants interactively. The vegetation dynamics model is the Lund–Potsdam–Jena (LPJ) dynamic global vegetation model. The land model is the National Center for Atmospheric Research (NCAR) Land Surface Model (LSM). Vegetation is defined in terms of plant functional types. Each plant functional type is represented by an individual plant with the average biomass, crown area, height, and stem diameter (trees only) of its population, by the number of individuals in the population, and by the fractional cover in the grid cell. Three time‐scales (minutes, days, and years) govern the processes. Energy fluxes, the hydrologic cycle, and carbon assimilation, core processes in LSM, occur at a 20 min time step. Instantaneous net assimilated carbon is accumulated annually to update vegetation once a year. This is carried out with the addition of establishment, resource competition, growth, mortality, and fire parameterizations from LPJ. The leaf area index is updated daily based on prevailing environmental conditions, but the maximum value depends on the annual vegetation dynamics. The coupling approach is successful. The model simulates global biogeography, net primary production, and dynamics of tundra, boreal forest, northern hardwood forest, tropical rainforest, and savanna ecosystems, which are consistent with observations. This suggests that the model can be used with a climate model to study biogeophysical feedbacks in the climate system related to vegetation dynamics.     

The Holocene at Lac de Creno, Corsica, France: a key site for the whole island

Two Holocene lake sequences from Lac de Creno, Corsica were analysed on the basis of 119 pollen spectra and with the support of 13 ¹⁴C-calibrated dates. The lower part of one of these sequences, corresponding to the late- glacial period, has been published previously. The first third of the Post-glacial is characterized by very particular forest dynamics, namely the absence of a role for deciduous Quercus and Corylus , the presence of mesophilous vegetation types dominated by Taxus , and the major forest role of Erica arborea at lower and mean altitude. At about 7440 cal BP, the occurrence of a major anthropogenic action brought about significant changes in the vegetation, notably an increase of deciduous Quercus and the expansion of Quercus ilex . Later, three major human-induced events are identified: the first, at about 2290 cal BP, is the cause of a short local expansion of Abies ; the second, at about 1150 cal BP, is the degradation of deciduous forests to the benefit of Fagus ; the third, at about 310 cal BP, corresponds to the disappearance of Fagus and its replacement by Pinus . Pollen data indicate that Q. ilex , Abies and Fagus are not indigenous in Corsica but spread there during the Postglacial ; this probably took place at about 6980 cal BP for Q. ilex .     

An assessment of the aquatic and wetland vegetation of the Upper Mississippi River

Illinois, Iowa, Minnesota, Missouri, and Wisconsin have strong botanical traditions that have resulted in a macrophyte literature which documents the identity, taxonomy, floristics, and ecology of aquatic macrophytes and wetland vegetation of the Upper Mississippi River and its floodplain. These findings are reviewed with respect to floristics, vegetation dynamics (patterns, history, production and management), and environmental changes that impact vegetation. Aspects requiring future study are noted to direct subsequent investigations.     

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.     

叶冠尺度野鸭湖湿地植物群落含水量的高光谱估算模型

利用高光谱遥感技术定量估测野鸭湖湿地植被含水量,对于监测和诊断野鸭湖湿地植被的生理状况及生长趋势具有重要意义,也能够为高光谱遥感影像在野鸭湖湿地植被含水量诊断中的实际应用提供理论依据和技术支持.采用Field Spec 3野外高光谱辐射仪,获取了野鸭湖典型湿地植被冠层和叶片的光谱,并测定了对应的含水量.以上述实测数据为基础,首先以芦苇为例初步探明了不同含水量水平下典型湿地植被冠层和叶片光谱反射率的响应模式,然后采用相关性及单变量线性与非线性拟合分析技术,从冠层和叶片两种层次,对不同尺度下的含水量与“三边”参数及高光谱植被指数进行了分析拟合,并采用交叉检验中的3K-CV方法对估算模型进行了测试和检验,确立了不同尺度下野鸭湖湿地植被含水量的定量监测模型.结果表明:(1)随着含水量水平的增加,芦苇冠层与叶片光谱在可见光波段(350-760 nm)和红外波段(760-2500 nm)的反射率均呈逐渐降低趋势.(2)不同尺度含水量与选取的光谱特征参数整体上相关性较强,与“三边”参数基本上都呈极显著相关,相关系数最大达到0.906;与高光谱指数全部呈极显著相关,相关系数最小为0.455,最大达到0.919,并通过选取不同尺度上相关性最佳的光谱特征参数,分别基于“三边”参数和高光谱植被指数构建了不同尺度下的含水量估算模型.其中,冠层尺度下,黄边面积(SDy)与SRWI( Simple Ratio Water Index)的估算效果最好,估算模型分别为y=-9.462x2 -2.671x+0.608和y=0.219e1.010x;叶片尺度下,红边面积(SDr)与WI( Water Index)的估算效果最好,估算模型分别为y=0.562x+0.376和y=2.028x2 -0.476x-1.009.通过3K-CV的交叉验证,不同尺度下的含水量估算模型均取得了较为理想的预测精度,预测精度的最小值为94.92％,最大值为97.06％,表明估测模型具有较高的可靠性与普适性.(3)高光谱植被指数与含水量拟合方程的拟合度相对高于“三边”参数与之建立方程的拟合度,说明多波段组合的光谱特征参数更适合含水量的判别.     

江苏省海滩植被演替的研究

江苏省海滩植被可分为滨海盐土植被、盐沼植被及海滩沙生植被三个基本类型。本文论述了这些植被类型的演替规律。滨海盐土植被与盐沼植被的演替,外因于土壤盐分含量递减与有机质含量的递增;海滩沙生植被的演替,外因于土壤沙颗粒大小及其相应的土壤含水量的变化,所以海滩植被演替为外因动态演替。     

Flowering phenology in the vegetation of Shervaroys,South India

Flowering phenology of 475 herbaceous and 348 arborescent taxa that form the vegetation of Shervaroys (Eastern Ghats: South India) was studied in relation to growth form, altitude and vegetation type. It was found that the majority of the herbaceous taxa flowered following rains while the arborescent taxa bloomed predominantly during the dry period irrespective of altitude and vegetation type.     

中国喀斯特植被分类系统

我国喀斯特地貌分布广泛,是全球喀斯特集中分布区面积最大且岩溶发育最强烈的典型区域。喀斯特植被物种组成独特,生物多样性丰富,群落结构复杂,植被类型极其丰富。该文对已发表的喀斯特植被类型和近期的调查资料进行系统整理,依据《中国植被志》的分类原则,在群系尺度上编制了中国喀斯特植被分类系统,包括3个植被型组、13个植被型和554个群系。探讨了喀斯特植被的分类系统与原有分类系统的衔接,并依据相关资料,对喀斯特生境专性群系进行了识别和判定,以期为喀斯特区域的石漠化治理、植被修复提供科学参考。     

Reconstructing pre-impact vegetation cover in modified landscapes using environmental modelling, historical surveys and remnant vegetation data: a case study in the Fleurieu Peninsula, South Australia

Aim To investigate the application of environmental modelling to reconstructive mapping of pre‐impact vegetation using historical survey records and remnant vegetation data. Location The higher elevation regions of the Fleurieu Peninsula region in South Australia were selected as a case study. The Fleurieu Peninsula is an area typical of many agricultural regions in temperate Australia that have undergone massive environmental transformation since European settlement. Around 9% of the present land cover is remnant vegetation and historical survey records from the ad 1880s exist. It is a region with strong gradients in climate and topography. Methods Records of pre‐impact vegetation distribution made in surveyors’ field notebooks were transcribed into a geographical information system and the spatial and classificatory accuracy of these records was assessed. Maps of remnant vegetation distribution were obtained. Analysis was undertaken to quantify the environmental domains of historical survey record and remnant vegetation data to selected meso‐scaled climatic parameters and topo‐scaled terrain‐related indices at a 20 m resolution. An exploratory analytical procedure was used to quantify the probability of occurrence of vegetation types in environmental domains. Probability models spatially extended to geographical space produce maps of the probability of occurrence of vegetation types. Individual probability maps were combined to produce a pre‐impact vegetation map of the region. Results Surveyors’ field notebook records provide reliable information that is accurately locatable to levels of resolution such that the vegetation data can be spatially correlated with environmental variables generated on 20 m resolution environmental data sets. Historical survey records of vegetation were weakly correlated with the topo‐scaled environmental variables but were correlated with meso‐scaled climate. Remnant vegetation records similarly not only correlated to climate but also displayed stronger relationships with the topo‐scaled environmental variables, particularly slope. Main conclusions A major conclusion of this study is that multiple sources of evidence are required to reconstruct past vegetation patterns in heavily transformed region. Neither the remnant vegetation data nor historical survey records provided adequate data sets on their own to reconstruct the pre‐impact vegetation of the Fleurieu Peninsula. Multiple sources of evidence provide the only means of assessing the environmental and historical representativeness of data sets. The spatial distribution of historical survey records was more environmentally representative than remnant vegetation data, which reflect biases due to land clearance. Historical survey records were also shown to be classificatory and spatially accurate, thus are suitable for quantitative spatial analyses. Analysis of different spatial vegetation data sets in an environmental modelling framework provided a rigorous means of assessing and comparing respective data sets as well as mapping their predicted distributions based on quantitative correlations. The method could be usefully applied to other regions where predictions of pre‐impact vegetation cover are required.