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.     

Opposition to Solid Waste Incineration: Pre- Implementation Anxieties Surrounding a New Environmental Controversy*

Despite sociopolitical controversy surrounding the solid waste crisis, little sociological attention has focused on this crucial environmental issue. Drawing on research from the technological controversies, environmental concern, and solid waste literatures, this study examines the pre-implementation anxieties of a Louisiana community faced with a proposal to build an incinerator in its backyard. Utilizing survey data, a causal path model is developed in which the perceived advantages of the technology, general environmental concern, and support for recycling initiatives are identified as explanatory variables of incinerator opposition. Implications of these findings for the study of technical controversies and the larger solid waste crisis also are suggested.     

Ninth-Grade Students' Attitudes Toward Nontraditional Occupations

This study explored how students choose careers, their attitudes toward vocational education, and whether or not they would consider enrolling in a nontraditional vocational education program.     

Modelling map positional error to infer true feature location

The authors consider the issue of map positional error, or the difference between location as represented in a spatial database (i.e., a map) and the corresponding unobservable true location. They propose a fully model‐based approach that incorporates aspects of the map registration process commonly performed by users of geographic informations systems, including rubber‐sheeting. They explain how estimates of positional error can be obtained, hence estimates of true location. They show that with multiple maps of varying accuracy along with ground truthing data, suitable model averaging offers a strategy for using all of the maps to learn about true location.     

SUNK COSTS, PROFIT VARIABILITY, AND TURNOVER

Dynamic competitive models of industry evolution suggest that firm profit will be more volatile, and turnover lower, in industries with higher sunk costs. These implications are consistent with empirical observation. (JEL L00 )     

Joint Attention,Self‐Recognition,and Neurocognitive Function in Toddlers

Recent studies have attempted to understand the processes involved in joint attention because of its relevance to both atypical and normal development. Data from a recent study of young children with autism suggests that performance on a delay nonmatch to sample (DNMS) task associated with ventromedial prefrontal functions, but not an A‐not‐B/delayed response task associated with dorsolateral prefrontal cortex, was related to joint attention skills (Dawson et al., 2002). Recent research also suggests that joint attention is associated with dorsalmedial brain systems linked to self‐monitoring (Mundy, 2003). This study investigated the relations among joint attention, DNMS, and self‐recognition performance in a longitudinal study of 39 normally developing toddlers from 14 to 18 months. The results indicated that development on the DNMS and self‐recognition tasks, but not a means end task, predicted joint attention at 18 months. Further analysis showed that the model was only significant for initiating joint attention (IJA). The implications of these results for the neuro‐development of IJA are discussed.