A gender analysis of quality of life in Saskatoon, Saskatchewan

While many community initiatives have attempted to assess the nature and determinants of their citizens’ quality of life (QOL), these initiatives have produced little about whether the key determinants of life quality differ by gender. Using both quantitative and qualitative data from a recent QOL research project in Saskatoon, Saskatchewan, Canada, this study explores whether factors that predict poor QOL are similar for women and men. The study also examines whether the nature of these gender differences varies across low, medium and high socio-economic status locales. Results showed that men and women were very similar in: (1) their QOL ratings, (2) reports of deterioration in neighborhood QOL, and (3) rating particular aspects of their neighborhood. Few gender differences were also found when analyzing data referring to place characteristics and social cohesion. Multivariate analysis revealed further similarities: (1) being divorced/widowed was a significant predictor of poor QOL, and (2) a negative view of community security issues was associated with deterioration in perceived neighborhood quality of life. For women, however, other variables were important predictors of QOL: being middle aged, being single, and having a poor opinion of the overall quality of their neighborhood. Qualitative analysis revealed that while men and women shared concern about general areas such as safety and neighborhood supports, their perceptions of the details around these issues differed. The multi-method results suggest that urban policy actions should include a gendered discussion of common QOL issues.     

一种基于可预报性的暴雨预报评分新方法Ⅱ:暴雨检验评分模型及评估试验

针对当前暴雨预报检验采用二分类事件检验方法存在较严重的“空报”“漏报”双重惩罚,没有考虑暴雨时空分布不均和预报评分可比性不够等问题,在分析预报员对暴雨预报评分期望值基础上,设计了一种基于可预报性的暴雨预报检验评分新方法和计算模型,分析了理想评分,并对2015-2016年4-10月中国中央气象台5 km×5 km定量降水格点预报和降水落区等级暴雨预报进行评分试验,获得了以下结果和结论:（1）预报员对暴雨预报评分期望值呈现梯级下降特征,与传统的TS评分存在显著差异;（2）设计了一种基于可预报性的暴雨预报检验新方法,通过引入e指数函数构建暴雨预报评分基函数,进而构建暴雨评分模型,该模型可以较好地拟合预报员对暴雨预报评分的期望值,同时改善了评分在不同量级阈值处的断崖式突变情况;（3）提出了预报与观测的邻域匹配方法,即一个预报点与所定义邻域中的一组观测相匹配,并利用距离加权最大值法确定暴雨评分值权重系数,预报与观测距离越近,距离权重系数越大,评分值权重越大,提高了评分的合理性,避免了距离较远的匹配站点得高分不利于鼓励预报员提高预报精度的问题;（4）对中国中央气象台逐日5 km×5 km水平分辨率的定量降水格点预报产品和中央气象台定量降水落区等级预报产品进行了评分试验,暴雨预报准确率全国平均值大于60分。基于可预报性的暴雨预报检验新评分与传统暴雨预报TS评分逐日演变特征相似,但可以较好地解析TS为0的预报评分,解析后的新评分与预报员和公众的心理预期更为接近。      

Five decades of neighborhood classifications and their transitions: A comparison of four US cities, 1970–2010

This paper examines 50-year spatio-temporal trajectories of neighborhoods (Census Tracts) for four cities discerned by their population growth trends and spatial patterns of growth: Buffalo, New York; Charlotte, North Carolina; Chicago, Illinois; and Portland, Oregon. Using five decades of Census data from 1970 to 2010, a clustering procedure is used to establish five classes of neighborhoods: Suburban, Stability, Blue Collar, Struggling, and New Starts. The transitions and sequences of neighborhoods through these groups are compared, revealing marked differences in the dynamics of neighborhoods according by city. Findings show that while Struggling neighborhoods, characterized largely by high poverty and unemployment levels, were very unlikely to transition out of this group over the course of 50 years in the cities of Buffalo, Charlotte, and Chicago, nearly half Portland's struggling neighborhoods transitioned to a neighborhood of higher socioeconomic status during that time period. The types of neighborhoods that exhibited signs of gentrification also varied according to city. The variability of neighborhood trajectories was greatest for the rapidly growing cities of Charlotte and Portland while neighborhoods in Buffalo and Chicago tended to follow a more predicable downgrading process.     

Breaking the chain: Understanding the association between foreclosure intensity and neighborhood satisfaction

Extensive research has been conducted on the factors that cause foreclosure and the resulting neighborhood contagion effects. When residents see concentrated foreclosed homes in their neighborhood, their perceptions of their neighborhood are often negatively affected. Despite the potential psychological effects of foreclosures on residents, no research has looked at foreclosure intensity and impacts on other residents' satisfaction in the neighborhood.We used the 2004 Homeowner Satisfaction Survey and foreclosed property data from 2001 to 2004 in Franklin County, Ohio to explore the effect of foreclosure intensity on resident satisfaction. We used a structural equation model to capture the chain reaction of concentrated neighborhood disadvantage on foreclosure intensity and residents' neighborhood satisfaction. We found that the impacts of foreclosures are not limited to lenders and owners of mortgaged homes but extended to other residents living in the neighborhood. In this regard, we recommend housing recession recovery efforts must incorporate programs to alleviate neighbors' psychological distress.     

基于4种高分辨率模式的辽宁省雷达回波预报邻域检验结果对比

选取2017—2018年6—9月辽宁省不同降水性质,具有2种不同特征的20次天气过程个例,应用模糊检验邻域法中的分数技巧评分(Fraction Skill Score, FSS),评估华东模式、华北模式、GRAPES＿3km模式和睿图东北模式对辽宁省中小尺度系统的预报能力。结果表明：区域性降水过程和局地性降水过程雷达回波强度越小,邻域半径越大,高分辨率模式预报技巧越高。当雷达回波大于30 dBz时,各高分辨率模式对局地性降水的雷达回波预报FSS评分均较高。当邻域半径为3 km时,区域性降水过程中,华北模式预报技巧在各级别雷达回波预报中均高于其他模式,最大FSS差值为0.031。局地性降水过程中,华东模式预报效果较好,最大FSS评分为0.127,表明华东模式预报中小尺度对流系统能力更强。局地性降水过程,睿图东北模式在08—23时预报时次中,“中间”时次的预报效果优于“两头”时次的预报,两个时次最大FSS差值为0.121。     

矢量数据辅助的高分辨率遥感影像道路自动提取

高分辨率遥感影像上细节信息繁杂、干扰物普遍存在,对其进行自动化道路识别与提取的相关研究仍处在探索阶段。在道路提取过程中引入矢量数据辅助,可解决初始信息获取的困难,得到可靠性较强的训练样本。为此,提出一种矢量数据辅助下的道路提取方法,能够筛选出矢量数据中包含的有效信息,引导实现对高分辨率遥感影像的道路自动提取。利用Mean-shift滤波对图像进行预处理后,首先从矢量数据获取候选种子点,并通过提炼同质区域的形状特征剔除错误候选点;然后,自动获取负样本点以进行朴素贝叶斯分类,并采用邻域质心投票算法从分类影像提取道路中心线;最后,结合像素跟踪与方向判断矢量化道路中心线,并提出一种基于矢量几何分析的断线连接与毛刺剔除方法,对提取结果进行信息修复与规整、优化。实验结果显示,该算法的提取质量达到80%以上,且具备较强的稳健性,能够适应具有不同道路辐射和分布特征的高分辨率遥感影像。     

基于PCA/NDVI的森林覆盖遥感信息提取方法研究

摘要： 以大兴安岭为试验区，提出将主成分分析（PCA）得到的第1分量、归一化植被指数（NDVI）和Landsat TM 1~TM 7某一波段进行合成，增强森林覆盖区和背景区信息的反差，并利用最大似然法对影像进行监督分类，分类精度超过92%。通过对不同云雾量和森林覆盖的2个时相影像试验表明，本方法提高了遥感影像森林覆盖信息提取的自动化程度和精度。     

Selection of LiDAR geometric features with adaptive neighborhood size for urban land cover classification

LiDAR has been an effective technology for acquiring urban land cover data in recent decades. Previous studies indicate that geometric features have a strong impact on land cover classification. Here, we analyzed an urban LiDAR dataset to explore the optimal feature subset from 25 geometric features incorporating 25 scales under 6 definitions for urban land cover classification. We performed a feature selection strategy to remove irrelevant or redundant features based on the correlation coefficient between features and classification accuracy of each features. The neighborhood scales were divided into small (0.5–1.5 m), medium (1.5–6 m) and large (>6 m) scale. Combining features with lower correlation coefficient and better classification performance would improve classification accuracy. The feature depicting homogeneity or heterogeneity of points would be calculated at a small scale, and the features to smooth points at a medium scale and the features of height different at large scale. As to the neighborhood definition, cuboid and cylinder were recommended. This study can guide the selection of optimal geometric features with adaptive neighborhood scale for urban land cover classification.     

The relationship between transit rich neighborhoods and transit ridership: Evidence from the decentralization of poverty

The concept of transit-rich neighborhoods (TRNs) has become a focus of more interest as it relates to rapidly growing and congested communities, and it has received national attention because of its contribution to smart growth in the United States. Although most investment in transit services has been concentrated in denser central cities, where most transit users, including those of low income, reside, the trend toward the decentralization of poverty has become evident in many metropolitan areas and underscored the need to improve suburban transit services. Many studies pertaining to transit ridership have focused on the physical characteristics of stations, their catchment areas, and equity issues for low-income riders, particularly in central cities, without accounting for the evolving socioeconomic characteristics of the neighborhoods being served. To address this issue, this paper categorizes TRNs based on changing socioeconomic and spatial characteristics and uses multiple regression to examine the relationship between types of TRNs and transit ridership in the Atlanta metropolitan area, focusing on the decentralization of poverty. The results show that suburban TRNs became more diverse in terms of income and race between 2000 and 2009, which suggests that investment in commuter rail transit is an important contribution to social and economic equality at the regional level. Furthermore, poverty rates in suburban areas, compared to those in their downtown and inner-city counterpart TRNs, positively influence the percentage of transit ridership. The increased use of suburban transit services suggests the potential presence of increased latent demand, which is further supported by the decentralization of poverty.     

Remaking white residential segregation: metropolitan diversity and neighborhood change in the United States

From 1990 to 2010, white tracts fell from 82% to 70% of all metropolitan tracts. This loss was concentrated among the most segregated white tracts – those with low diversity. White tracts that were moderately diverse actually doubled in number between 1990 and 2010 although this increase was insufficient to cancel the loss of low diversity white tracts. We model the effects of metropolitan characteristics on white-tract change by metropolitan area. Greater metropolitan-scale diversity increases the probability that low-diversity white tracts transition to moderate-diversity white. Moderately diverse white tracts, however, become more stable with increased diversity. A large metropolitan percentage of blacks or the foreign born reverses this stabilizing effect, increasing the probability that moderately diverse white tracts transition to non-white tracts. Overall, the results suggest a reconfiguration rather than a dissolving of white dominated neighborhood space in response to increased metropolitan area diversity.