Monitoring Urban Greenness Dynamics Using Multiple Endmember Spectral Mixture Analysis

Urban greenness is increasingly recognized as an essential constituent of the urban environment and can provide a range of services and enhance residents’ quality of life. Understanding the pattern of urban greenness and exploring its spatiotemporal dynamics would contribute valuable information for urban planning. In this paper, we investigated the pattern of urban greenness in Hangzhou, China, over the past two decades using time series Landsat-5 TM data obtained in 1990, 2002, and 2010. Multiple endmember spectral mixture analysis was used to derive vegetation cover fractions at the subpixel level. An RGB-vegetation fraction model, change intensity analysis and the concentric technique were integrated to reveal the detailed, spatial characteristics and the overall pattern of change in the vegetation cover fraction. Our results demonstrated the ability of multiple endmember spectral mixture analysis to accurately model the vegetation cover fraction in pixels despite the complex spectral confusion of different land cover types. The integration of multiple techniques revealed various changing patterns in urban greenness in this region. The overall vegetation cover has exhibited a drastic decrease over the past two decades, while no significant change occurred in the scenic spots that were studied. Meanwhile, a remarkable recovery of greenness was observed in the existing urban area. The increasing coverage of small green patches has played a vital role in the recovery of urban greenness. These changing patterns were more obvious during the period from 2002 to 2010 than from 1990 to 2002, and they revealed the combined effects of rapid urbanization and greening policies. This work demonstrates the usefulness of time series of vegetation cover fractions for conducting accurate and in-depth studies of the long-term trajectories of urban greenness to obtain meaningful information for sustainable urban development.     

Californian Salt-Marsh Vegetation: An Improved Model of Spatial Pattern

Although tidal wetland vegetation patterns are typically related to elevation, we hypothesized that the vertical range of a species may shift where the topography is more heterogeneous. We examined plant species occurrences in relation to elevation, proximity to the bay, and proximity to tidal creeks at a near-pristine wetland in San Quintín Bay, Baja California, Mexico. At the whole-wetland scale, most species occurred primarily within a 30-cm elevation band (the marsh plain). However, Spartina foliosa occurred only at the bayward margin, even though “suitable” elevations were present further inland. A similar pattern was found in San Diego Bay. At the microtopographic scale, three species on the marsh plain were strongly influenced by elevation, whereas four species responded to both elevation and proximity to tidal creeks. The latter species tended to “avoid” the lower 10 cm of the marsh plain except near a tidal creek. Species richness was thus greater (by 0.6 species at the lowest 10-cm class) at the tidal creek margin. Better drainage near creeks is the hypothesized cause. Our results help explain why species that are transplanted to constructed wetlands do not always grow at the full range of elevations they occupy in natural wetlands. We recommend that species be introduced to their modal elevation (determined from nearby reference marshes) and that salt-marsh construction designs include topographic heterogeneity (complex tidal creek networks). The analysis of broad-scale and fine-scale patterns of occurrence also suggests new habitat nomenclature. Elevation-based terms (“low,”“middle,” and “high” marsh) should be replaced by a system that considers elevation, landscape position, and conspicuous species. We suggest three habitat designations: (a) the high marsh—a 30- to 70-cm elevation range with Salicornia subterminalis; (b) the marsh plain—a 30-cm elevation range with heterogeneous topography and up to nine common species; and (c) cordgrass habitat—the bayward portion of the marsh plain and lower elevations, all occupied by Spartina foliosa. Although these habitats do not have discrete boundaries, separate terms are needed for wetland restoration plans and these designations will improve recognition that vegetation patterns respond to horizontal, as well as vertical, position.     

Equivariant Estimation for the Parameters of an Exponential Model Based on Censored Sampling

Lehmann (1983) provides a detailed discussion on equivariant estimation of the parameters of location, scale and location-scale models. Edwin Prabakaran and Chandrasekar (1994) developed simultaneous equivariant estimation approach and illustrated the method with examples. In this paper, we consider exponential models and obtain minimum risk equivariant estimators of the parameters based on Type II censored samples. The equivariant method of estimation is illustrated with biological and reliability applications.     

多尺度遥感综合监测我国北方典型草原区植被盖度

利用多尺度遥感影像综合进行全球和区域尺度的土地利用/覆盖变化(LUCC)研究是最近全球变化研究的重要方向之一。本文综合利用野外群落样方、数字相机、ETM+影像、NOAA/AVHRR影像,在遥感、GIS和GPS支持下,对我国北方典型草原区植被盖度进行了综合监测、模拟与分析。结果表明:(1) 利用经处理后的数字相机影像测量盖度的结果准确性较高,可以作为植被盖度测量的标准结果,反映真实的覆盖特征,并用以验证利用其它方法测量结果的精度。(2) 利用野外1 m2样方网格法目视估测的植被盖度结果变化较大,不稳定。本次实验中,与数字相机测量结果相比,样方估测的盖度普遍偏高,平均偏差为9.92%;但两者相关性较好(r2=0.89)。(3) 采用Gutman模型ETM+影像、NOAA/AVHRR影像反演植被盖度的结果与数字相机测量结果偏差分别为7.03%、7.83%,ETM+像元分解NOAA像元后得到的植被盖度与数字相机测量结果偏差5.68%。三者与数字相机测量结果的相关系数r2分别为0.78、0.61和0.76。(4)利用野外实测植被盖度数据直接与NOAA-NDVI影像建立统计模型估算植被盖度的精度较低(r2=0.65),而通过空间分辨率介于两者之间的ETM+影像进行转换后,该精度得到一定的提高(r2=0.80)。利用像元分解的方法提高了大尺度植被盖度监测的精度,是利用遥感数据进行尺     

基于高分一号 WFV 卫星影像的黄河口湿地草本植被生物量估算模型研究

基于高分一号 WFV 卫星数据,通过计算 NDVI、SRI、SAVI、MSAVI、GBNDVI 和 DVI 6种植被指数,结合黄河口湿地现场草本植被地上干生物量样本,进行一元线性、指数、对数和幂4种模型的回归分析,从中选出生物量最佳估算模型。结果表明：（1）指数模型是 NDVI 和 GBNDVI 的最佳生物量回归模型,幂模型是其它植被指数的最佳回归模型（P ＜0．001）;（2）6种植被指数干生物量最佳回归模型的决定系数（R2）都大于0．7,最大为0．77,由大到小排序为 MSAVI ＞SAVI ＞NDVI ＞DVI ＞SRI ＞GBNDVI;（3）各最佳回归模型的平均相对误差（MRE）都小于54％,最小为23．9％,由小到大排序为 NDVI ＜GBNDVI ＜SRI ＜DVI ＝SAVI ＜MSAVI。     

基于频谱图像灰度共生矩阵的无损测温方法

本文提出了一种基于哈达玛变换的频谱图像灰度共生矩阵(Hadamard-GLCM)的高强度聚焦超声治疗无损测温方法。利用高强度聚焦超声辐照新鲜离体猪肉组织,获取辐照前后的B超图像的减影图像,采用Hadamard变换对其进行处理,获取频谱图像,将频谱图像的灰度共生矩阵惯性矩作为反应温度变化的信息参数。实验表明:不仅单组数据的Hadamard-GLCM惯性矩(HGMI)和温度能很好的线性拟合,而且多组数据的Hadamard-GLCM惯性矩与温度也成近似的线性关系,而且斜率非常接近,拟合度更接近1,误差小,对温度的分辨能力高,容错能力强,与传统的测温方法相比有着明显的优势,能为HIFU治疗过程中的无损测温提供有效的实时依据。     

Estimation in an Island Model Using Simulation

Estimation for an island model where mutation maintains ak-allele neutral polymorphism at a single locus on each island is considered. The likelihood of an observed sample type configuration is obtained by applying a computational algorithm analogous to Griffiths and Tavaré (Theor. Popul. Biol.46(1994), 131–159). This allows the computation of sampling distributions in an island model and investigation of their properties. Given a sample type configuration, the maximum likelihood estimate of the migration parameter is obtained by simulating independently the likelihood at a grid of points and, also, using a surface simulation method. The latter method generates the whole likelihood trajectory in a single application of the simulation program. An estimate of variance of the estimate of the migration parameter is obtained using the likelihood trajectory. A comparison of the maximum likelihood estimates of the gene flow between subpopulations is made with those obtained by using Wright'sF_STstatistic.     

Illumination Normalization of Face Image Based on Illuminant Direction Estimation and Improved Retinex

Illumination normalization of face image for face recognition and facial expression recognition is one of the most frequent and difficult problems in image processing. In order to obtain a face image with normal illumination, our method firstly divides the input face image into sixteen local regions and calculates the edge level percentage in each of them. Secondly, three local regions, which meet the requirements of lower complexity and larger average gray value, are selected to calculate the final illuminant direction according to the error function between the measured intensity and the calculated intensity, and the constraint function for an infinite light source model. After knowing the final illuminant direction of the input face image, the Retinex algorithm is improved from two aspects: (1) we optimize the surround function; (2) we intercept the values in both ends of histogram of face image, determine the range of gray levels, and stretch the range of gray levels into the dynamic range of display device. Finally, we achieve illumination normalization and get the final face image. Unlike previous illumination normalization approaches, the method proposed in this paper does not require any training step or any knowledge of 3D face and reflective surface model. The experimental results using extended Yale face database B and CMU-PIE show that our method achieves better normalization effect comparing with the existing techniques.     

Improved Glomerular Filtration Rate Estimation by an Artificial Neural Network

Background

Accurate evaluation of glomerular filtration rates (GFRs) is of critical importance in clinical practice. A previous study showed that models based on artificial neural networks (ANNs) could achieve a better performance than traditional equations. However, large-sample cross-sectional surveys have not resolved questions about ANN performance.

Methods

A total of 1,180 patients that had chronic kidney disease (CKD) were enrolled in the development data set, the internal validation data set and the external validation data set. Additional 222 patients that were admitted to two independent institutions were externally validated. Several ANNs were constructed and finally a Back Propagation network optimized by a genetic algorithm (GABP network) was chosen as a superior model, which included six input variables; i.e., serum creatinine, serum urea nitrogen, age, height, weight and gender, and estimated GFR as the one output variable. Performance was then compared with the Cockcroft-Gault equation, the MDRD equations and the CKD-EPI equation.

Results

In the external validation data set, Bland-Altman analysis demonstrated that the precision of the six-variable GABP network was the highest among all of the estimation models; i.e., 46.7 ml/min/1.73 m² vs. a range from 71.3 to 101.7 ml/min/1.73 m², allowing improvement in accuracy (15% accuracy, 49.0%; 30% accuracy, 75.1%; 50% accuracy, 90.5% [P<0.001 for all]) and CKD stage classification (misclassification rate of CKD stage, 32.4% vs. a range from 47.3% to 53.3% [P<0.001 for all]). Furthermore, in the additional external validation data set, precision and accuracy were improved by the six-variable GABP network.

Conclusions

A new ANN model (the six-variable GABP network) for CKD patients was developed that could provide a simple, more accurate and reliable means for the estimation of GFR and stage of CKD than traditional equations. Further validations are needed to assess the ability of the ANN model in diverse populations.     

基于NDVI的米仓山植被覆盖变化趋势分析

基于1998年4月至2009年12月的SPOT-VEGETATION逐旬NDVI数据,采用MVC(最大值合成法)获得月NDVI值,用均值法计算各季及年均NDVI值;对5种植被类型的年均NDVIy和生长季NDVIg进行一元线性回归,辅助以趋势线分析定量描述研究区植被覆盖动态变化,并采用R/S分析(重标极差法)动态预测米仓山植被覆盖未来变化趋势。结果表明:研究区12年间NDVI整体呈上升趋势,相对于前期(1999~2001年)、中期(2003~2005年)和后期(2007~2009年)的NDVI增加显著;年最大NDVI≥0.70的区域占总面积的98.95%,年均NDVI≥0.70的区域占93.69%,且植被覆盖增加的面积远大于减少的面积;划分的5种植被类型中,阔叶林类NDVI值最高,人工植被类NDVI值最低;R/S法计算结果显示,Hurst指数(H)为0.876 8,表现为很强的持续性,预示未来一定时限内米仓山植被覆盖将有稳定的增加趋势。     

Addition of Nitrogen Increases Variability of Vegetation Cover in an Arid System with Unpredictable Rainfall

Ecosystems - Addition of nitrogen (N) to rangeland that has been degraded through overgrazing or drought can hasten vegetation recovery. Additional N may influence temporal stability of vegetation...     

Development of an Improved Selective Agar Medium for Isolation of Yersinia pestis

Existing media designed for selective isolation of clinically important members of the genus Yersinia were found to be unsatisfactory for the growth and isolation of Yersinia pestis. We report the development of a new selective agar medium (termed BIN) that supports the growth of Y. pestis. The development of the formulation of this medium was based on a fluorescence screening system designed for monitoring bacterial growth on semisolid media, using a green fluorescent protein-expressing strain. High-throughput combinatorial experiments can be conducted for the quantitative evaluation of the effect of different medium components on growth. Generation of fluorescence plots in this system, using microplates, allowed the quantitative evaluation of the growth rate of Y. pestis EV76 cultures in different agar compositions. The final BIN formulation is based on brain heart infusion agar, to which the selective agents irgasan, cholate salts, crystal violet, and nystatin were introduced. It was found that BIN agar is more efficient in supporting colony formation and recovery of Y. pestis than are the conventional semisolid media MacConkey agar and Yersinia-selective agar (cefsulodin-irgasan-novobiocin agar). The advantage of BIN over other media has been also demonstrated in recovering virulent Y. pestis from the mixed bacterial populations found in decaying carcasses of infected mice. The BIN medium is suggested as a selective medium for isolation and recovery of Y. pestis from various backgrounds.     

Soil TPH Concentration Estimation Using Vegetation Indices in an Oil Polluted Area of Eastern China

Assessing oil pollution using traditional field-based methods over large areas is difficult and expensive. Remote sensing technologies with good spatial and temporal coverage might provide an alternative for monitoring oil pollution by recording the spectral signals of plants growing in polluted soils. Total petroleum hydrocarbon concentrations of soils and the hyperspectral canopy reflectance were measured in wetlands dominated by reeds (Phragmites australis) around oil wells that have been producing oil for approximately 10 years in the Yellow River Delta, eastern China to evaluate the potential of vegetation indices and red edge parameters to estimate soil oil pollution. The detrimental effect of oil pollution on reed communities was confirmed by the evidence that the aboveground biomass decreased from 1076.5 g m⁻² to 5.3 g m⁻² with increasing total petroleum hydrocarbon concentrations ranging from 9.45 mg kg⁻¹ to 652 mg kg⁻¹. The modified chlorophyll absorption ratio index (MCARI) best estimated soil TPH concentration among 20 vegetation indices. The linear model involving MCARI had the highest coefficient of determination (R ² = 0.73) and accuracy of prediction (RMSE = 104.2 mg kg⁻¹). For other vegetation indices and red edge parameters, the R² and RMSE values ranged from 0.64 to 0.71 and from 120.2 mg kg⁻¹ to 106.8 mg kg⁻¹ respectively. The traditional broadband normalized difference vegetation index (NDVI), one of the broadband multispectral vegetation indices (BMVIs), produced a prediction (R ² = 0.70 and RMSE = 110.1 mg kg⁻¹) similar to that of MCARI. These results corroborated the potential of remote sensing for assessing soil oil pollution in large areas. Traditional BMVIs are still of great value in monitoring soil oil pollution when hyperspectral data are unavailable.     

基于谱域光学相干层析系统中光谱涨落的指纹获取

指纹因其特异性和稳定性等特点而被称为"证据之首",在案件侦破中起着极其重要的作用。多种物理学、化学和光学技术都可以用于获取现场遗留的指纹,然而这些方法存在一些缺点,如会对指纹造成破坏、潜在的毒副作用、在现场留有痕迹等。利用谱域光学相干层析(spectral domain optical coherence tomography,简记为SD-OCT)技术进行指纹探测具有非接触、对指纹无损伤和高灵敏度的优势,利用OCT系统的相位敏感性我们可以在低对比条件下再现遗留在物体表面的指纹,但处理结果受指纹所在表面高低起伏影响,使得指纹信息对比度降低,难以被分离和提取。本文提出了一种基于干涉光谱涨落的指纹获取方法,只需对OCT系统得到的干涉光谱的涨落进行处理分析,即可得到遗留在物体表面的指纹图案,不需进行相位和表面轮廓高度的求取,算法简单、处理速度快,处理结果不受样品表面高低起伏的影响。实验结果表明,在起伏表面上,使用该方法也能较好地显现遗留在物体表面的指纹图案。     

基于改进型组织特异纹理滤波器的乳腺肿瘤超声图像处理

基于乳腺超声图像的多参数纹理分类实验,改进了Gjenna Sfippel等的自适应纹理滤波器,通过引入模糊函数、增加重叠区域和迭代次数的措施,在减少图像噪声的同时,增强肿瘤与周围正常组织的视觉差别。量化比较乳腺超声图像经该滤波算法和几种常用滤波算法处理前后的的统计特征参量和肿瘤边缘检测的精确率,验证了该算法的有效性和优越性。     

基于MODIS数据黄海绿潮覆盖面积精细化提取

针对MODIS数据绿潮提取存在大量混合像元导致绿潮覆盖面积偏大这一问题,基于3 m分辨率的机载SAR高分影像,结合归一化植被指数(NDVI),对MODIS研究区中大于NDVI阈值的像元进行混合像元分解得到绿潮的"覆盖面积";获取的准同步3 m机载SAR提取的绿潮面积为"真实值",然后建立二者之间的关系模型,并选取不同的样本区域对该模型进行了验证。实验结果表明:NDVI等传统算法所提取的绿潮覆盖面积约为"真实值"的2.68倍;基于混合像元分解的方法所提取的绿潮面积较"真实值"偏小,约为"真值"的0.56倍;与传统的NDVI等多波段比值法相比,该精细化模型方法提取的绿潮覆盖面积更接近于"真实值",与"真实值"误差仅为6.7%。     

A Synthesis of Climate and Vegetation Cover Effects on Biogeochemical Cycling in Shrub-Dominated Drylands

Semi-arid and arid ecosystems dominated by shrubs (“dry shrublands”) are an important component of the global C cycle, but impacts of climate change and elevated atmospheric CO₂ on biogeochemical cycling in these ecosystems have not been synthetically assessed. This study synthesizes data from manipulative studies and from studies contrasting ecosystem processes in different vegetation microsites (that is, shrub or herbaceous canopy versus intercanopy microsites), to assess how changes in climate and atmospheric CO₂ affect biogeochemical cycles by altering plant and microbial physiology and ecosystem structure. Further, we explore how ecosystem structure impacts on biogeochemical cycles differ across a climate gradient. We found that: (1) our ability to project ecological responses to changes in climate and atmospheric CO₂ is limited by a dearth of manipulative studies, and by a lack of measurements in those studies that can explain biogeochemical changes, (2) changes in ecosystem structure will impact biogeochemical cycling, with decreasing pools and fluxes of C and N if vegetation canopy microsites were to decline, and (3) differences in biogeochemical cycling between microsites are predictable with a simple aridity index (MAP/MAT), where the relative difference in pools and fluxes of C and N between vegetation canopy and intercanopy microsites is positively correlated with aridity. We conclude that if climate change alters ecosystem structure, it will strongly impact biogeochemical cycles, with increasing aridity leading to greater heterogeneity in biogeochemical cycling among microsites. Additional long-term manipulative experiments situated across dry shrublands are required to better predict climate change impacts on biogeochemical cycling in deserts.     

Estimation of Coupling Strength in Regenerated Lamprey Spinal Cords Based on a Stochastic Phase Model

We present a simple stochastic model of two coupled phase oscillators and a method of fitting the model to experimental spike-train data or to sequences of burst times. We apply the method to data from lesioned isolated lamprey spinal cords. The remaining tracts at the lesion site are either regenerated medial tracts, regenerated lateral tracts, control medial tracts, or control lateral tracts. We show that regenerated tracts on average provide significantly weaker coupling than control tracts. We compare our model-dependent estimate of coupling strength to a measure of coordination based on the size of deflections in the spike-train cross-correlation histogram (CCH). Using simulated data, we show that our estimates are able to detect changes in coupling strength that do not change the size of deflections in the CCH. Our estimates are also more resistant to changes in the level of dynamic noise and to changes in relative oscillator frequency than is the CCH. In simulations with high levels of dynamic noise and in one experimental preparation, we are able detect significant coupling strength although there are no significant deflections in the CCH.     

Estimation of Variance Components Based on a Diallel Model Involving Maternal and Maternal Interaction Effects

For a diallel model (TOPHAM, 1966) estimators of variance components are obtained by adopting the general approach outlined by SEELY (1969, 1970, 1971), SEELY and ZYSKIND (1971) and YUAN (1977) in the case of unbalanced data.