Spectral‐ALS data fusion for different roughness parameterizations of forested floodplains

Natural river floodplains and adjacent wetlands grow typically a diverse and heterogeneous combination of herbs, shrubs and trees, which play an essential role in determining the total flow resistance. Hydrodynamic effects of trees in forested floodplains can provide the majority of flow resistance during flood events. Nevertheless, ground‐based techniques to acquire vegetation parameters are expensive and difficult to apply over long reaches. This paper presents a novel method of automated roughness parameterization of riparian woody vegetation by fusion of Quickbird multi‐spectral image with airborne laser scanning (ALS) data. The data fusion approach includes: individual tree detection and estimation of vegetation metrics from light detection and ranging (LiDAR) data, assessment of predictive models for the vegetation parameters and spatial mapping of the vegetation parameters for the forest plants in the riparian corridor. The proposed method focuses on estimation of plant density (d), crown diameters (D_C), tree height (h), stem diameter (D_S), crown base height (cbh) and leaf area index (LAI). The procedure is tested along a 14‐km reach of the Sieve River (Tuscany, Italy) characterized by high woody plant density. Due to the complex study area, the data fusion approach explains with variable reliability the local vegetation properties (R²(D_C) = 0.14, R²(h) = 0.84, R²(D_S) = 0.25, R²(cbh) = 0.66). The generated structural parameter maps represent spatially explicit data layers that can be used as inputs to hydrodynamic models used to analyse flow resistance effects in different submergence conditions of vegetation. A simple flow resistance model was applied over a test area comparing the results of the proposed method and a traditional ground‐based approach. The modelling results showed that the new method is able to provide accurate output data to describe the interaction between water levels and bio‐mechanical characteristics of vegetation. The proposed methodology provides a fast, repeatable and accurate way of obtaining floodplain roughness, which enables regular updating of vegetation characteristics. Copyright © 2010 John Wiley & Sons, Ltd.     

无动力处理方式在农村生活污水处理中的应用

论述了北方某镇采用无动力处理技术处理农村生活污水的方法,工艺流程为新型化粪池-人工湿地-氧化塘工艺。运行结果表明,工程出水中污染物日均浓度COD为35~55 mg/L、BOD5为10~20 mg/L、SS为5~18mg/L、氨氮为3~5 mg/L,均能达到《农田灌溉水质标准》(GB 5084-2005)中蔬菜a标准。处理后的出水用于周边农田灌溉,既治理了污染,又节约了资源,是绿色、低碳城镇建设的一个典范,非常适合北方乡镇新农村建设的生活污水处理和利用。     

Floodplain roughness parameterization using airborne laser scanning and spectral remote sensing

Floodplain roughness parameterization is one of the key elements of hydrodynamic modeling of river flow, which is directly linked to exceedance levels of the embankments of lowland fluvial areas. The present way of roughness mapping is based on manually delineated floodplain vegetation types, schematized as cylindrical elements of which the height (m) and the vertical density (the projected plant area in the direction of the flow per unit volume, m^− 1) have to be assigned using a lookup table. This paper presents a novel method of automated roughness parameterization. It delivers a spatially distributed roughness parameterization in an entire floodplain by fusion of CASI multispectral data with airborne laser scanning (ALS) data. The method consists of three stages: (1) pre-processing of the raw data, (2) image segmentation of the fused data set and classification into the dominant land cover classes (KHAT = 0.78), (3) determination of hydrodynamic roughness characteristics for each land cover class separately. In stage three, a lookup table provides numerical values that enable roughness calculation for the classes water, sand, paved area, meadows and built-up area. For forest and herbaceous vegetation, ALS data enable spatially detailed analysis of vegetation height and density. The hydrodynamic vegetation density of forest is mapped using a calibrated regression model. Herbaceous vegetation cover is further subdivided in single trees and non-woody vegetation. Single trees were delineated using a novel iterative cluster merging method, and their height is predicted (R² = 0.41, rse = 0.84 m). The vegetation density of single trees was determined in an identical way as for forest. Vegetation height and density of non-woody herbaceous vegetation were also determined using calibrated regression models. A 2D hydrodynamic model was applied with the results of this novel method, and compared with a traditional roughness parameterization approach. The modeling results showed that the new method is well able to provide accurate output data. The new method provides a faster, repeatable, and more accurate way of obtaining floodplain roughness, which enables regular updating of river flow models.     

利用植被覆盖度-地表温度特征空间提取厦门市土壤湿度信息

土壤湿度是水文学、气象学以及农业科学研究领域的一个重要参数。利用1989年和1996年两个时相Landsat TM遥感卫星影像来获取厦门的植被覆盖度和地表温度,并由此构建了植被覆盖度和地表温度组成的特征空间,最后利用该特征空间反演了土壤湿度,并分析湿度在两个时相中的变化情况。结果显示,在所研究的时间段内,厦门西南老城区的湿度得到增加。但是在东北部城市建成区扩展的地区,土壤湿度则明显降低。     

弯道对植被群河道水流结构影响的试验研究北大核心CSCD

为了解弯道对含植被群河道水流结构的影响,本文在180°U型弯道水槽中进行试验,采用圆形竹筷模拟低密度植被群,圆柱体模拟高密度植被群,运用声学多普勒流速仪测量三维流速,不同密度植被群放置于水槽相同位置,对比分析弯道的影响。试验结果发现,植被群上游调整长度及其稳定尾流区长度受弯道影响发生了明显调整,植被群密度的影响仅作用于植被群尾流结构,包括其中垂向湍动能的差异。植被群后出现植被群直径尺度的涡,使纵向湍动能分布出现波峰,峰值大小受弯道影响;植被群在弯道中所处位置越后,峰值越小。湍流谱分析中验证了此现象,并发现弯道作用使得植被群后小尺度涡增多,从而使得植被群后较小湍动能峰值的大小不随植被群放置位置改变。     

基于高光谱激光雷达的滞尘叶片光谱特征分析

城市绿植为城市生态系统提供自净功能, 起到净化空气以及滞尘降尘等多种环境保护作用, 而滞尘等因素也 会对绿植产生影响。为了研究滞尘对城市绿植叶片光谱特征的影响, 采集了四种常绿绿植 (八角金盘、石楠、香樟和 玉兰) 叶片样本, 使用高光谱激光雷达系统获取高光谱点云数据, 分析了滞尘对叶片光谱特征的影响。分析结果表明: 对于不同种类叶片, 滞尘对可见光波段反射率均有较大影响; 对于同种类叶片, 滞尘对近红外波段的反射率差异影响 较大, 可见光波段的反射率差异为 1.21%∼3.41%, 近红外为 1.76%∼8.49%; 线性四点内插法计算和光谱导数分析表明 滞尘对四种叶片的红边位置无显著影响; 四种叶片的叶面水含量指数 (LWI) 对滞尘的响应程度最小 (均小于 3.7%), 而 比值植被指数 (RVI) 对滞尘的响应程度最大 (除香樟外, 均大于 20.0%), 红边指数 (SDr)、简单比值指数 (SR) 和叶面叶 绿素指数 (LCI) 的响应程度稳定性较差。进一步建立了滞尘植被指数和响应程度的线性相关性拟合模型并进行了检 验, 其中以 LCI 为自变量建立的模型为最稳定拟合模型, 可表示为 y = −1.527x + 0.6597, 决定系数约为 0.88。     

Effects of woody elements on simulated canopy reflectance: Implications for forest chlorophyll content retrieval

An important bio-indicator of actual plant health status, the foliar content of chlorophyll a and b (Cab), can be estimated using imaging spectroscopy. For forest canopies, however, the relationship between the spectral response and leaf chemistry is confounded by factors such as background (e.g. understory), canopy structure, and the presence of non-photosynthetic vegetation (NPV, e.g. woody elements)—particularly the appreciable amounts of standing and fallen dead wood found in older forests. We present a sensitivity analysis for the estimation of chlorophyll content in woody coniferous canopies using radiative transfer modeling, and use the modeled top-of-canopy reflectance data to analyze the contribution of woody elements, leaf area index (LAI), and crown cover (CC) to the retrieval of foliar Cab content. The radiative transfer model used comprises two linked submodels: one at leaf level (PROSPECT) and one at canopy level (FLIGHT). This generated bidirectional reflectance data according to the band settings of the Compact High Resolution Imaging Spectrometer (CHRIS) from which chlorophyll indices were calculated. Most of the chlorophyll indices outperformed single wavelengths in predicting Cab content at canopy level, with best results obtained by the Maccioni index ([R₇₈₀ − R₇₁₀] / [R₇₈₀ − R₆₈₀]). We demonstrate the performance of this index with respect to structural information on three distinct coniferous forest types (young, early mature and old-growth stands). The modeling results suggest that the spectral variation due to variation in canopy chlorophyll content is best captured for stands with medium dense canopies. However, the strength of the up-scaled Cab signal weakens with increasing crown NPV scattering elements, especially when crown cover exceeds 30%. LAI exerts the least perturbations. We conclude that the spectral influence of woody elements is an important variable that should be considered in radiative transfer approaches when retrieving foliar pigment estimates in heterogeneous stands, particularly if the stands are partly defoliated or long-lived.     

Spatial and temporal variability of macrophyte cover and productivity in the eastern Amazon floodplain: A remote sensing approach

Herbaceous aquatic macrophytes cover extensive areas on the floodplains of the Amazon basin and are an important habitat and input of organic carbon. These communities have large intra- and inter-annual variability, and characterization of this variability is necessary to quantify the role of macrophytes in the ecology and biogeochemistry of the floodplain. A novel approach for mapping the temporal evolution of aquatic vegetation in the Amazon floodplain, which could be adapted to other spatially and temporally changing environments, is presented. Macrophyte cover varied seasonally and inter-annually, ranging between 104 and 198 km² for the floodplain examined (total area, 984 km²). The observed evolution of plant distribution indicated a spatial and temporal partition of macrophyte communities into short-lived and annual groups. A simulation of macrophyte net primary production (NPP) based on the mapping results indicated that at least 3% of NPP could be attributed to the short-lived communities. The present results suggest that significant changes in the macrophyte's contribution to carbon cycling in the Amazon floodplain could occur as a result of the predicted increase in frequency of drought years for the Amazon system due to climate change.     

基于Landsat-TM影像的鄱阳湖典型湿地动态变化研究

利用分层分类法,通过对鄱阳湖典型湿地(蚌湖与赣江中支口三角洲)长序列秋季Landsat-TM影像进行解译分析,探讨了1991年~2008年间鄱阳湖典型湿地动态变化特征。结果表明分层分类方法能够有效地应用于Landsat-TM遥感影像的解译;从1991年到2008年蚌湖和赣江中支口三角洲湿地的植被面积分别增加18.56km2和6.01km2,其中赣江主支三角洲洲滩植被分布呈向湖体扩展态势。植被分布受水情影响比较大,蚌湖湿地的苔草面积与同时期水面积呈负相关性,而赣江主支三角洲湿地植被类型结构变化受水位影响也比较明显,苔草面积变化与秋季湖口水位表现为负相关,芦苇分布面积变化则与湖口水位变化趋势较为一致。     

基于ETM＋的北京西部山区乔木群落结构研究

利用遥感技术结合地面调查的方法对2008年春季北京西部山区乔木群落的多样性进行了研究。提取归一化植被指数（NDVI）,并计算NDVI随时间的变化率（△NDVI）;利用地面调查数据计算研究区的健康指数、Mar-galef丰富度指数、Shannon-Wiener多样性指数和Simpson多样性指数,并分析△NDVI、健康指数和多样性指数之间的关系。结果表明：（1）健康指数和多样性指数之间存在正相关关系,群落多样性指数越高,群落的整体健康状况越好。（2）△NDVI与健康指数之间呈正相关关系,健康指数越高的群落,单位时间内NDVI的增加值越大,植被群落的生长变化越明显。（3）△NDVI的高低可以代表区域植被的健康程度,反映区域植物群落的丰富度、多样性。△NDVI的值越高,植被群落的健康程度越好,植被群落的丰富度、多样性指数越高。本文的研究较好的将遥感技术和地面调查相结合,对△NDVI与群落植被健康程度、多样性指数进行了研究和验证,为以后研究植被群落多样性提供了一定的借鉴。