The proliferation of impervious surfaces results in a series of environmental issues, such as the decrease of vegetated areas and the aggravation of the urban heat island effects. The mapping of impervious surface and its spatial distributions is of significance for the ecological study of urban environment. Currently, the integration of optical and synthetic aperture radar (SAR) data has shown advantages in accurately characterizing impervious surface. However, the fusion mainly occurs at the pixel and feature levels which are subject to influences of data noises and feature selections, respectively. In this paper, an innovative and effective method was developed to extract urban impervious surface by synergistically utilizing optical and SAR images at the decision level. The objective of this paper was to obtain an accurate urban impervious surface map based on the random forest classifier and the evidence theory and to provide a detailed uncertainty analysis accompanying the fused impervious surface maps. In this study, both the GaoFen (GF-1) and Sentinel-1A imagery were first used as independent data sources for mapping urban impervious surfaces. Then additional spectral features and texture features were extracted and integrated with the original GF-1 and Sentinel-1A images in generating impervious surfaces. Finally, based on the Dempster-Shafer (D-S) theory, impervious surfaces were produced by fusing the previously estimated impervious surfaces from different datasets at the decision level. Results showed that impervious surfaces estimated from the combined use of original images and features yielded a higher accuracy than those from the original optical or SAR data. Further validations suggested that optical data was better than SAR data in separating impervious surfaces from non-impervious surfaces. The fused impervious surfaces at the decision level had a higher overall accuracy than those produced independently by optical or SAR data. It was also highlighted that the fusion of GF-1 and Sentinel-1A images reduced the amount of confusions among the low reflectance of impervious surface and water, as well as for low reflectance of bare land. An overall accuracy of 95.33% was achieved for extracting urban impervious surfaces by fused datasets. The spatial distributions of uncertainties provided by the evidence theory displayed a confidence level of at least 75% for the impervious surfaces derived from the fused datasets.

Significant research has been conducted on how environmental attributes influence people’s decisions to walk. In much of this research, however, environmental attributes are averaged for neighborhoods or census geographies for sampled populations. Moreover, the effect of an agent’s walking choices on other actors is not adequately represented by either objective or perceived measures in the literature. Macro-level patterns of walkability arise from interactions across actors and urban environments. The agent-based approach allows for modeling individual uses of the environment by treating the populations as objects that can interact with the environment and other people. This study builds on previous research on pedestrian movement and geographic information system (GIS) measures of the built environment using the agent-based approach to explore the dynamics of the built environment and people’s decision-making processes concerning walking. The results show that models that take individual perspective into account and include social interaction can better capture characteristics of the built and social environment that influence people’s walking choices. This method lays out a new framework for assessing macro-level patterns of walkability across a city using micro-level data.

Policies focusing on enforcing property code violations and the improvement of vacant properties are argued to be more efficacious than demolition policies to fight urban blight. This study applies parcel level data to a multi-year hybrid modeling structure. A fine-grained analysis is conducted on the dynamic patterns of abandonment and demolition for a unique period of four years before and after the City of Buffalo’s stepped-up demolition efforts. Results showed that proximity to vacant and abandoned properties, sustained over the years, had the greatest impact on the possibility of a property being abandoned. The second greatest positive impact on property abandonment was small lot front size. Results also showed that neighborhood vacancy density had the greatest negative impact on surrounding housing sales prices over the years. There was no significant impact of demolition on housing sales prices. These findings suggested that the City should aim to have more incentive programs that are tailored to control the number of vacant properties, rather than focusing primarily on demolition-oriented programs.

Most GIS-related planning practices and education are currently limited to two-dimensional mapping and analysis although 3D GIS is a powerful tool to study the complex urban environment in its full spatial extent. This paper reviews current GIS and 3D visualization uses and development in planning practice and education. Current literature provides little information in 3D GIS education. This paper offers suggestions for 3D GIS course setting and educational methods aiming to set up a framework to supplement current two-dimensional GIS education in planning using 3D modelling programs.

Despite the documented importance of the neighbourhood environment on youth physical activity, little empirical research exists regarding the geographical boundaries of neighbourhoods within which youth are physically active around their homes. Studies and public policies often arbitrarily assume the extent of these boundaries, which vary from study to study. This paper combines GPS data, diaries and accelerometry to delineate empirically the local area and distance within which youth play in Erie County, New York. The study found that youth tend to be physically active within a quarter-mile radius around their homes and to focus on one section of the often assumed circled neighbourhood.