Population estimation in inter-censual years has many important applications. In this research, high-resolution pan-sharpened IKONOS image, LiDAR data, and parcel data are used to estimate small-area population in the eastern part of the city of Denton, Texas. Residential buildings are extracted through object-based classification techniques supported by shape indices and spectral signatures. Three population indicators -building count, building volume and building area at block level are derived using spatial joining and zonal statistics in GIS. Linear regression and geographically weighted regression (GWR) models generated using the three variables and the census data are used to estimate population at the census block level. The maximum total estimation accuracy that can be attained by the models is 94.21%. Accuracy assessments suggest that the GWR models outperformed linear regression models due to their better handling of spatial heterogeneity. Models generated from building volume and area gave better results. The models have lower accuracy in both densely populated census blocks and sparsely populated census blocks, which could be partly attributed to the lower accuracy of the LiDAR data used.

The purpose of this study was to determine the effects of attendance at a senior center on the well being and quality of life of grandparents that were rearing grandchildren. Using convenience sampling, grandparents (N=130) who were rearing grandchildren were given a self administered demographic data survey along with an attendance at a senior center questionnaire, the Quality of Life Scale, the Well Being Scale by Liang, the UCLA Loneliness Scale, the Caregiver Burden Scale, and the Role Satisfaction Scale. An initial MANOVA (F 7, 69 = 2.72, p < .01) suggesting that senior center attendance affect the measures as a set was conducted and then a series of one way ANOVAs were carried out to test the hypothesis that attending a senior center has an effect on the dependent variables: well being, quality of life, role satisfaction, caregiver burden, loneliness, current health, and heath one year ago. Subsequently, a hierarchical regression analysis was conducted to find out whether frequency and quality of attendance of a senior center predicted quality of life, caregiver burden, well being, loneliness, and role satisfaction, controlling for the demographic data. The results of the MANOVA showed that the dependent variables: quality of life, caregiver burden, …