Although a substantial body of literature has provided evidence supporting the positive effects of natural environments on well-being, little has been known about the specific spatial patterns of urban nature in promoting health-related quality of life (HRQOL) among children. This study assessed the association that the urban natural environment measured by landscape spatial patterns may have with obesity and HRQOL among Hispanic children. Ninety-two 4th and 5th grade students were recruited from Houston, Texas, and the Pediatric Quality of Life Inventory (PedsQL) was used to capture the children’s HRQOL. The quality of urban natural environments was assessed by quantifying the landscape spatial patterns, using landscape indices generated by Geographic Information Systems and remote sensing. From the bivariate analyses, children’s body mass index showed a significantly negative association with their HRQOL. After controlling for socio-demographic factors, the results revealed that larger and more tree areas were positively correlated with children’s HRQOL. In addition, those children living in areas with tree patches further apart from each other showed higher HRQOL. This research adds to the current multi-disciplinary area of research on environment-health relationships by investigating the roles of urban greeneries and linking their spatial structures with children’s HRQOL.

The aim of this study was to identify the major variables identified as important for considering the stabilization of slope revegetation based on hydroseeding applications and evaluate weights of each variable using the analytic hierarchy process (AHP) with both environmental experts and civil engineers. Twenty-five variables were selected by the experts’ survey from a total of 65 from the existing literature, with each variable considered as an important factor for slope stabilization in South Korea. The final results from the AHP method showed that variables associated with the driving force of water resources showed higher values in all expert groups such as rain intensity, seepage water and drainage condition. Other important variables were related to plant growth such as vegetation community, vegetation coverage and quality of soil ameliorant produced in an artificial factory such as tensile strength, permeability coefficient, soil texture and organic matter. The five highest-ranked variables that satisfied both environmental experts and civil engineers were rain intensity, seepage water, slope angle, drainage condition and ground layer. The findings of this research could be helpful for developing a more accurate rating system to evaluate the stability of slope revegetation.

Rapid urbanization has accelerated land use and land cover changes, and generated the urban heat island effect (UHI). Previous studies have reported positive effects of neighborhood landscapes on mitigating urban surface temperatures. However, the influence of neighborhood landscape spatial patterns on enhancing cooling effects has not yet been fully investigated. The main objective of this study was to assess the relationships between neighborhood landscape spatial patterns and land surface temperatures (LST) by using multi-regression models considering spatial autocorrelation issues. To measure the influence of neighborhood landscape spatial patterns on LST, this study analyzed neighborhood environments of 15,862 single-family houses in Austin, Texas, USA. Using aerial photos, geographic information systems (GIS), and remote sensing, FRAGSTATS was employed to calculate values of several landscape indices used to measure neighborhood landscape spatial patterns. After controlling for the spatial autocorrelation effect, results showed that larger and better-connected landscape spatial patterns were positively correlated with lower LST values in neighborhoods, while more fragmented and isolated neighborhood landscape patterns were negatively related to the reduction of LST.

Although recent studies have emphasized the benefits of Low Impact Development (LID), the influence of LID on impervious surface connectivity to downstream drainage has not yet been fully investigated by using quantitative measurements. Some previous studies have attempted to measure correlates between discharged stormwater volume and the directly connected impervious areas (DCIA), a fraction of the impervious area that is hydraulically connected to downstream drainage by a piped route. They found that DCIA could be a more accurate predictor of urban development impacts on stream ecosystems than is the total impervious area. This study measured the DCIA of urban watersheds in the Energy Corridor District, Houston, Texas, where rapid urbanization and increasing impervious surfaces have caused urban stream degradation during the past decades. This study primarily prioritized land use into four types based on the contribution of hypothetically implemented LID facilities to DCIA reduction for each land use. Stormwater infrastructure and impervious cover data were analyzed using Geographic Information Systems. Sutherland's equations taken from Sutherland, R.C. (1995) were utilized to compute DCIA at the parcel level. The results were 1) a greater value of current DCIA in commercial areas than in residential areas (single family houses 40%, multi-family houses 64%, big box retails 77%, scattered small-scale retails 71%); 2) a significant reduction of DCIA for all land uses after hypothetically implementing LID applications (reduction rates ranged from 6.4% to 52.2%); and 3) the greatest change of DCIA in big box retail areas with pervious pavement and vegetated swale installation. The results will contribute to determining which land use type is of higher priority in implementing source-control stormwater infrastructure and providing local governments with a better index to calculate drainage fees, which are currently imposed on property owners based on total impervious area.