Tree health mapping with multispectral remote sensing data at UC Davis, California

Tree health is a critical parameter for evaluating urban ecosystem health and sustainability. Traditionally, this parameter has been derived from field surveys. We used multispectral remote sensing data and GIS techniques to determine tree health at the University of California, Davis. The study area (363 ha) contained 8,962 trees of 215 species. Tree health conditions were mapped for each physiognomic type at two scales: pixel and whole tree. At the pixel scale, each tree pixel within the tree crown was classified as either healthy or unhealthy based on vegetation index values. At the whole tree scale, raster based statistical analysis was used to calculate tree health index which is the ratio of healthy pixels to entire tree pixels within the tree crown. The tree was classified as healthy if the index was greater than 70%. Accuracy was checked against a random sample of 1,186 trees. At the whole tree level, 86% of campus trees were classified as healthy with 88% mapping accuracy. At the pixel level, 86% of the campus tree cover was classified as healthy. This tree health evaluation approach allows managers to identify the location of unhealthy trees for further diagnosis and treatment. It can be used to track the spread of disease and monitor seasonal or annual changes in tree health. Also, it provides tree health information that is fundamental to modeling and analysis of the environmental, social, and economic services produced by urban forests.     

A modified false discovery rate multiple-comparisons procedure for discrete data, applied to human immunodeficiency virus genetics

Summary.  To help to design vaccines for acquired immune deficiency syndrome that protect broadly against many genetic variants of the human immunodeficiency virus, the mutation rates at 118 positions in HIV amino-acid sequences of subtype C versus those of subtype B were compared. The false discovery rate (FDR) multiple-comparisons procedure can be used to determine statistical significance. When the test statistics have discrete distributions, the FDR procedure can be made more powerful by a simple modification. The paper develops a modified FDR procedure for discrete data and applies it to the human immunodeficiency virus data. The new procedure detects 15 positions with significantly different mutation rates compared with 11 that are detected by the original FDR method. Simulations delineate conditions under which the modified FDR procedure confers large gains in power over the original technique. In general FDR adjustment methods can be improved for discrete data by incorporating the modification proposed.     

Book Reviews

Books reviewed:
R.J. Adler, R.E. Feldman & M.S. Taqqu, A Practical Guide to Heavy Tails: Statistical Techniques and Applications.
J.J. Foste, A Beginner's Guide to Data Analysis Using SPSS for Windows.
N. Limnios and G. Oprisan, Semi–Markov Processes and Reliability.     

Confidence Intervals for Current Status Data

Abstract.  The likelihood ratio statistic for testing pointwise hypotheses about the survival time distribution in the current status model can be inverted to yield confidence intervals (CIs). One advantage of this procedure is that CIs can be formed without estimating the unknown parameters that figure in the asymptotic distribution of the maximum likelihood estimator (MLE) of the distribution function. We discuss the likelihood ratio-based CIs for the distribution function and the quantile function and compare these intervals to several different intervals based on the MLE. The quantiles of the limiting distribution of the MLE are estimated using various methods including parametric fitting, kernel smoothing and subsampling techniques. Comparisons are carried out both for simulated data and on a data set involving time to immunization against rubella. The comparisons indicate that the likelihood ratio-based intervals are preferable from several perspectives.     

一个数据流查询系统的设计与实现

就目前大多数数据流查询处理过程中可能出现的一些问题，根据数据流处理的特点和要求，提出了新的查询处理结构，实现了数据共享及多流多查询环境下查询的处理．     

CCI与中国证券市场走势的实证分析

美英等国的消费者信心指数(CCI)对股市指数收益有很重要的影响力。为探讨CCI与中国证券市场走势的相关关系,通过两类模型对1999年10月~2004年8月间我国股市收益与CCI之间的关系进行了实证分析。结果表明:CCI对深沪五个指数的走势有显著的解释与预测效果,但对我国的B股市场似乎没有显著性。     

An evaluation of the childhood family structure measures from the sixth wave of the British Household Panel Survey

Summary.  The paper performs an evaluation of the data that were collected in the sixth wave of the British Household Panel Survey (BHPS) on childhood family structure. After comparing such data with a large number of studies by using external sources, we find that the BHPS data overestimate the proportion of people who report an experience of life in a non-intact family during childhood by about 10%. Although an explanation based on recall error that deteriorates with the age of the BHPS respondents is possible, the overestimation is likely to be accounted for by non-ignorable attrition that may affect most of the comparison studies based on longitudinal data. Conversely, comparisons with other independent measurements from the BHPS itself reveal that the wave 6 data underestimate the proportion of young people who have lived at least part of their childhood in a non-intact family by about 8%. The probability of disagreement between these two sets of measures is strongly associated with poor interview characteristics, which may affect the comparison measure more than the wave 6 measure. Despite such differences, there is therefore a substantial degree of similarity between the family structure information that was collected in the sixth wave of the BHPS and the host of highly diverse records against which it has been compared.     

Semiparametric linear transformation models for current status data

Current status data arise when the death of every subject in a study cannot be determined precisely, but is known only to have occurred before or after a random monitoring time. The authors discuss the analysis of such data under semiparametric linear transformation models for which they propose a general inference procedure based on estimating functions. They determine the properties of the estimates they propose for the regression parameters of the model and illustrate their technique using tumorigenicity data.     

城市蔓延与生产率:促进还是抑制? ——基于夜间灯光数据的分析

城市蔓延有利于提高城市生产率吗?文章首先从城市规模、城市人口密度两个方面阐释城市蔓延影响生产率的内在机理,基于长江经济带104个城市2002年~2013年夜间灯光数据,实证研究了城市蔓延的生产率效应,主要结论如下:1)城市蔓延对长江经济带生产率具有显著负向影响,意味着城市无序、低密度扩张阻碍了长江经济带生产率的提高.2)分区域研究发现,城市蔓延对东、中、西部地区城市生产率的影响为负,但对东部地区生产率影响最小,对中西部地区生产率产生较大影响.3)分产业研究发现,城市蔓延降低第二产业生产率的同时显著提升了第三产业生产率.4)考虑空间溢出效应的空间杜宾模型研究发现,城市蔓延影响生产率的直接效应与间接效应均显著为负,且间接效应远大于直接效应,意味着城市蔓延对长江经济带城市生产率的影响具有明显的空间溢出效应.     

重要数据跨境流动背景下风险路径的识别与分级

重要数据的跨境流动引发了数据安全、国家安全等风险挑战。风险路径的识别和分级是对重要数据跨境流动进行预警管理的重要内容。本文基于复杂网络中的二分网络模型,对重要数据的跨境流动进行研究。首先,通过重要数据跨境流动的二分网络和关联网络识别风险路径;其次,构建基于网络结构和接收节点属性的目标风险路径方法以计算其风险值;最后,对我国某重要行业跨境流动的数据开展实证分析,验证算法的有效性和精准度。本文旨在为重要数据跨境流动的预警管理提供量化方法,有效预防重要数据跨境流动带来的风险,提升我国数据治理能力。