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.     

Status of the Riparian Ecosystem in the Upper San Pedro River, Arizona: Application of an Assessment Model

A portion of Arizona’s San Pedro River is managed as a National Riparian Conservation Area but is potentially affected by ground-water withdrawals beyond the conservation area borders. We applied an assessment model to the Conservation Area as a basis for monitoring long-term changes in riparian ecosystem condition resulting from changes in river water availability, and collected multi-year data on a subset of the most sensitive bioindicators. The assessment model is based on nine vegetation bioindicators that are sensitive to changes in surface water or ground water. Site index scores allow for placement into one of three condition classes, each reflecting particular ranges for site hydrology and vegetation structure. We collected the bioindicator data at 26 sites distributed among 14 reaches that had similar stream flow hydrology (spatial flow intermittency) and geomorphology (channel sinuosity, flood-plain width). Overall, 39% of the riparian corridor fell within condition class 3 (the wettest condition), 55% in condition class 2, and 6% in the driest condition class. Condition class 3 reaches have high cover of herbaceous wetland plants (e.g., Juncus and Schoenoplectus spp.) along the perennial stream channel and dense, multi-aged Populus-Salix woodlands in the flood plain, sustained by shallow ground water in the stream alluvium. In condition class 2, intermittent stream flows result in low cover of streamside wetland herbs, but Populus-Salix remain abundant in the flood plain. Perennial wetland plants are absent from condition class 1, reflecting highly intermittent stream flows; the flood plain is vegetated by Tamarixa small tree that tolerates the deep and fluctuating ground water levels that typify this reach type. Abundance of herbaceous wetland plants and growth rate of Salix gooddingii varied between years with different stream flow rates, indicating utility of these measures for tracking short-term responses to hydrologic change. Repeat measurement of all bioindicators will indicate long-term trends in hydro-vegetational condition.     

基于改进的非线性GM(1,1)模型的职业病预测研究

为了更准确地预测职业病,在传统GM(1,1)模型的基础上,提出改进的非线性GM(1,1)模型,在传统的GM(1,1)模型中引入弱化算子,将紧邻均值与原始数据之间的线性假设改为非线性假设,提高曲线的拟合度。以2005—2014年的全国职业病例数为研究对象,进行数据拟合和预测分析,其中以2014年职业病例数作为验证数据,并利用后验差比值和小误差概率2个参数,检验该改进模型的预测精度。由应用实例的分析结果可知:在职业病发病趋势的预测方面,改进的非线性GM(1,1)模型的预测精度提高到一级,曲线拟合度较高,预测得到2015年的职业病例数为34 900例。     

不同自燃倾向性煤的指标气体产生规律实验研究

为研究不同自燃倾向性煤的自燃指标气体变化规律,提高对煤早期自燃预测预报的准确度,采用程序升温实验系统,得到内蒙古褐煤、神东长焰煤、河南气煤及枣庄焦煤4种不同变质程度煤的氧化时间随温度的变化关系,以及指标气体浓度在煤氧化过程中的变化规律。结果表明:自燃倾向性最高的褐煤应以CO和乙烯作为煤自燃早期预报的首选指标气体;易自燃的长焰煤应采用乙烯和烯烷比为主、以CO为辅的煤自燃判定指标;自燃倾向性较低的气煤应以乙烯和烯烷比作为煤自燃预报指标;CO是自燃倾向性最低的焦煤的最佳自燃预报指标气体。     

道路交通噪声预测声源简化研究

为了分析《环境影响评价技术导则声环境》(HJ 2.4—2009)中将道路声源简化为1条位于道路中心线处的线声源与按照车道数简化为多条线声源之间的误差,针对不同宽度的道路,推导了多条线声源与1条线声源在接收点噪声影响的误差计算公式,并基于Predictor-lima预测软件预测和现场噪声衰减规律实测进行了验证。研究结果表明,对于接收点到道路边缘的距离大于道路宽度的情况,可简化为1条线声源;对于接收点到道路边缘的距离小于道路宽度的情况,应按照车道数简化为多条线声源。     

基于因子分析法优选河流水体中氮浓度预测方法的研究

定量的河流水体中氮浓度预测方法有很多种,如何优选出预测精度较高的方法一直是学术界多年来致力于研究的重点。本研究采用因子分析法对预测方法的精度评价指标进行分析,并建立了预测方法精度的评价模型,对回归分析法、神经网络法、灰色系统法和增长率统计法4种水体氮浓度预测方法进行综合评估,优选出精度较高的河流水体氮浓度预测模型——BP神经网络预测模型。结果表明,此评估模型对类似研究具有一定的参考价值,能为选择出合适的河流水体氮浓度预测方法提供依据。     

湖北“两圈”区域发展可持续性评价与预测

利用可持续发展指数（SDI）对湖北“两圈”各市州发展现状进行了评价,而后利用9年的人均生物资源生态承载量年平均增长率、人口年平均增长率和足迹承载量比值年平均增长率及2006年相关数据对未来44年进行了预测。结果表明,截至2006年底,湖北省有一半以上国土面积的生物资源开采超过当地土地负荷,人均生物资源生态承载量持续下降,资源日益紧张,呈不可持续发展;武汉城市圈2006年生物资源生态足迹超出生物资源生态承载量的32%;鄂西生态文化旅游圈（简称：鄂西生态圈）除襄樊、荆州、荆门因人口多,生物资源生态足迹较大等原因导致SDI值较高外,其他市州的SDI值均较低;神农架的SDI最小;武汉城市圈人均生物资源生态承载量呈负增长,人口控制较好,足迹承载量比值增长较快;鄂西生态圈人均生物资源生态承载量呈负增长,增长速率大于武汉城市圈和湖北省,人口控制较差,足迹承载量比值增长较慢;按照现有发展模式,无论是武汉城市圈还是鄂西生态圈,无论其当前发展是可持续性还是不可持续的,未来他们都将进入不可持续的发展状态。因此,对“两圈”进行规划时要根据各自发展现状制定长期、科学的发展规划.     

基于元素毒性赋值的模糊数学环境质量评价

利用模糊数学方法,根据元素毒性的大小进行权重赋值,对成都经济区近地表大气尘进行地球化学环境质量评价。结果显示：不同城市中,成都、乐山、眉山的大气环境质量较好,处于一级清洁级别;眉山、雅安的大气环境质量处于二级安全级别;德阳的大气环境质量已经处于三级警戒级。不同地区中,绵阳和眉山的大气环境质量较好,处于一级清洁级别;德阳和雅安处于二级安全级别,成都和乐山处于三级警戒级.     

事故状态下污染物排放对水环境影响的预测研究

对辽河油田欢喜岭采油厂在事故状态下污染物排放对大凌河水域环境的影响进行预测研究。计算了洪水淹没、油罐冒顶泄漏、油井井喷泄漏、联合站泄漏、管道泄漏、暴雨径流带走落地油等16种情景下对该河流水质的影响情况,并建立数学模型,进行情景模拟。研究结果表明,事故状态下对大凌河水质影响的次序由大到小依次为:洪水淹没、油罐冒顶泄漏、油井井喷泄漏、联合站泄漏、管道泄漏、暴雨径流。     

集中排烟公路隧道入口段火灾下诱导风速研究

为研究集中排烟模式下公路隧道入口段发生火灾时的合理诱导风速,以某公路隧道为背景,运用火灾动力学模拟软件FDS对隧道人口段火灾时不同坡度、不同诱导风速的16组火灾工况进行模拟研究,通过对各工况下隧道内的温度场分布及烟气控制效果模拟结果的分析,得到了各工况下的合理诱导风速,研究结果可为公路隧道集中排烟系统关键设计参数提供参考.