Point Sampling Digital Imagery with ‘Samplepoint’

Measuring percent occurrence of objects from digital images can save time and expense relative to conventional field measurements. However, the accuracy of image analysis had, until now, not reached the level of the best conventional field measurements. Additionally, most image-analysis software programs require advanced user training to successfully analyze images. Here we present a new software program, ‘SamplePoint,’ that provides the user a single-pixel sample point and the ability to view and identify the pixel context. We found SamplePoint to allow accuracy comparable with the most accurate field-methods for ground-cover measurements. Expert use of the program requires minimal training and its ease of use allows rapid measurements from image data. We recommend SamplePoint for calibrating the threshold-detection level of image-analysis software or for making direct measurements of percent occurrence from digital images.     

乌鲁木齐市采暖季空气质量变化趋势分析

为了定量评价乌鲁木齐市采暖季空气污染近五年的治理成效,给环境治理决策提供科学依据,运用回归分析方法,对乌鲁木齐市采暖季空气质量的浓度、级别和变化规律进行回归分析。分析结果表明,PM10、SO2、NO2三项污染物的浓度都有所下降,空气质量级别的污染天数呈现明显的月变化规律。乌鲁木齐市采暖季空气的重污染状况有所遏制,但SO2污染凸现,在下一步的治理工作中,加强尘污染治理的同时要加大对SO2的治理力度。     

Water Quality during Development and Apportionment of Pollution from Rivers in Tapeng Lagoon, Taiwan

This work investigated water samples collected from Tapeng Lagoon, Taiwan. Factor analysis was conducted to explain the characteristics and the variation in the quality of water during the disassembly of oyster frames and fishery boxes. The result shows that the most important latent factors in Tapeng Lagoon are the ocean factor, primary productivity factor, and the fishery pollution factor. Canonical discriminant analysis is applied to identify the source of pollution in neighboring rivers outside Tapeng Lagoon. The two constructed discriminant functions (CDFs) showed markedly contribution to all discriminant variables, and that total nitrogen, algae, dissolved oxygen and total phosphate, combined in the nutrient effect factor. The recognition capacities in these two CDFs were 95.6%, 4.4%, respectively. The water quality in the Kaoping river most strongly determined that in the Tapeng Lagoon the best is. And disassembling the oyster frames and fishery boxes improves the water quality markedly. However, environmental topographic conditions indicate that strengthening stream pollution prevention and to constructing another entrance to the ocean are the best approaches for improving the quality of water in Tapeng Lagoon, especially by reducing eutrophication. These approaches and results yield useful information concerning habitat recovery and water resource management.     

Temperature Effect on Migration of Zn and Cd Through Natural Clay

To investigate the effect of temperature on effective diffusion coefficients and retardation factors for Zn and Cd, combined diffusion and sequential extraction analyses were conducted at 15 ^˚C and 55 ^˚C. The effective diffusion coefficients of the metals increased up to ten times according to the increased temperature. On the other hand, the effect of temperature on the retardation factor depended on the retention mechanisms of the metals. The distribution coefficient for Zn, which was mainly partitioned in the carbonate phase, increased up to two times with the increase in temperature. On the other hand, the distribution coefficient for Cd, which was mainly partitioned in the exchangeable phase, was hardly affected by the temperature change. Results of combined diffusion and sequential extraction analysis showed that the effect of temperature on the heavy metals’ (Zn and Cd) migration through the compacted natural clay was influenced by the combined effects of the diffusion coefficient and the retardation factor. Additionally, we could also observe the change in retention mechanism for the metals with the change in pore water concentration.     

Characterization and Identification of the Sources of Chromium, Zinc, Lead, Cadmium, Nickel, Manganese and Iron in Pm10 Particulates at the Two Sites of Kolkata, India

Monitoring of ambient PM₁₀ (particulate matter which passes through a size selective impactor inlet with a 50% efficiency cut-off at 10 μm aerodynamic diameter) has been done at residential (Kasba) and industrial (Cossipore) sites of an urban region of Kolkata during November 2003 to November 2004. These sites were selected depending on the dominant anthropogenic activities. Metal constituents of atmospheric PM₁₀ deposited on glass fibre filter paper were estimated using Inductively Coupled Plasma Atomic Emission Spectrometer (ICP-AES). Chromium (Cr), zinc (Zn), lead (Pb), cadmium (Cd), nickel (Ni), manganese (Mn) and iron (Fe) are the seven toxic trace metals quantified from the measured PM₁₀ concentrations. The 24 h average concentrations of Cr, Zn, Pb, Cd, Ni, Mn and Fe from ninety PM₁₀ particulate samples of Kolkata were found to be 6.9, 506.1, 79.1, 3.3, 7.4, 2.4 and 103.6 ng/m³, respectively. The 24 h average PM₁₀ concentration exceeded national ambient air quality standard (NAAQS) as specified by central pollution control board, India at both residential (Kasba) and industrial (Cossipore) areas with mean concentration of 140.1 and 196.6 μg/m³, respectively. A simultaneous meteorology study was performed to assess the influence of air masses by wind speed, wind direction, rainfall, relative humidity and temperature. The measured toxic trace metals generally showed inverse relationship with wind speed, relative humidity and temperature. Factor analysis, a receptor modeling technique has been used for identification of the possible sources contributing to the PM₁₀. Varimax rotated factor analysis identified four possible sources of measured trace metals comprising solid waste dumping, vehicular traffic with the influence of road dust, road dust and soil dust at residential site (Kasba), while vehicular traffic with the influence of soil dust, road dust, galvanizing and electroplating industry, and tanning industry at industrial site (Cossipore).     

天津地区集装箱内部低温环境条件研究

以天津地区冬季采用集装箱储存货物为背景,在天津对集装箱内部温度和大气温度等数据进行测试,对数据进行回归分析后,建立集装箱内部温度模型,预测出该地区集装箱内部最恶劣的低温极值范围,为危险货物集装箱安全储运提供理论依据,并提出了相应的对策及建议。     

基于GIS的北京市妫水河流域水土流失的初步分析

基于ArcGIS空间分析平台和ERDAS空间建模平台,利用水土流失综合指数法,分别以坡度、植被覆盖度和土地利用类型为主要背景因子,分析了北京市妫水河流域水土流失的空间背景特征.结果表明,妫水河流域水土流失的空间背景特征是缓坡、低植被覆盖度和疏林灌草地,而这些特征正是妫水河流域山前洪冲积扇地区的主要特点,缓坡、低植被覆盖度(不考虑城市建成区)和疏林灌草地也主要集中在流域内山前洪冲积扇地区.并提出防治妫水河流域水土流失的有效措施.      

一株反硝化菌的分离鉴定和系统发育分析

从反硝化反应器中分离到一株异养型兼氧反硝化细菌,命名为菌株JIN1,分离菌株为革兰氏染色阴性杆状。茵落颜色为乳白色。该菌株能以硝酸钠为唯一氮源进行反硝化作用并产生亚硝酸。部分长度的16SrDNA序列分析表明,分离菌株JIN1与Aquaspirillum菌具有99%相似,与Microvirgulaaerodenitrificans菌具有99%相似。其生化性状与Aquaspirillum菌不相符。系统发育学分析表明菌株JIN1与Microvirgulaaerodenitrificans菌关系最近。故确认菌株JIN1属Microvirgulaaerodenitrificans菌。     

运用QSPR预测有机磷农药的色谱保留值

通过计算43种有机磷农药的各种结构参数,运用多元线性回归分析方法比较了适用于有机磷农药色谱保留值的定量关系表达式,建立了有机磷农药结构参数对色谱保留值的QSPR模型.模型分析表明:磷酸酯与硫逐磷酸酯两类有机磷农药的模型非交叉验证相关系数R2分别为0.991和0.998,标准误差SE分别为0.0539和0.2874,交叉验证相关系数Q2分别为0.976和0.990,标准偏差Scv分别为0.086和0.610.在已知磷酸酯与硫逐磷酸酯两类有机磷农药结构参数的情况下,此模型可有助于有机磷农药的色谱分析.     

Synergistic Techniques for Better Understanding and Classifying the Environmental Structure of Landscapes

The desire to capture natural regions in the landscape has been a goal of geographic and environmental classification and ecological land classification (ELC) for decades. Since the increased adoption of data-centric, multivariate, computational methods, the search for natural regions has become the search for the best classification that optimally trades off classification complexity for class homogeneity. In this study, three techniques are investigated for their ability to find the best classification of the physical environments of the Mt. Lofty Ranges in South Australia: AutoClass-C (a Bayesian classifier), a Kohonen Self-Organising Map neural network, and a k-means classifier with homogeneity analysis. AutoClass-C is specifically designed to find the classification that optimally trades off classification complexity for class homogeneity. However, AutoClass analysis was not found to be assumption-free because it was very sensitive to the user-specified level of relative error of input data. The AutoClass results suggest that there may be no way of finding the best classification without making critical assumptions as to the level of class heterogeneity acceptable in the classification when using continuous environmental data. Therefore, rather than relying on adjusting abstract parameters to arrive at a classification of suitable complexity, it is better to quantify and visualize the data structure and the relationship between classification complexity and class homogeneity. Individually and when integrated, the Self-Organizing Map and k-means classification with homogeneity analysis techniques also used in this study facilitate this and provide information upon which the decision of the scale of classification can be made. It is argued that instead of searching for the elusive classification of natural regions in the landscape, it is much better to understand and visualize the environmental structure of the landscape and to use this knowledge to select the best ELC at the required scale of analysis.