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The popularization of tracking devices, such as GPS, accelerometers and smartphones, have made it possible to detect, record, and analyze new patterns of human movement and behavior. However, employing GPS alone for indoor localization is not always possible due to the system's inability to determine location inside buildings or in places of signal occlusion. In this context, the application of local wireless networks for determining position is a promising alternative solution, although they still suffer from a number of limitations due to energy and IT-resources. Our research outlines the potential for employing indoor wireless network positioning and sensor-based systems to improve the collection of tracking data indoors. By applying various methods of GIScience we developed a methodology that can be applicable for diverse human indoor mobility analysis. To show the advantage of the proposed method, we present the result of an experiment that included mobility analysis of 37 participants. We tracked their movements on a university campus over the course of 41 days and demonstrated that their movement behavior can be successfully studied with our proposed method.

This paper presents and demonstrates a spatial framework for the application of strategic environmental assessment (SEA) in the context of change analysis for urban wetland environments. The proposed framework is focused on two key stages of the SEA process: scoping and environmental baseline assessment. These stages are arguably the most information-intense phases of SEA and have a significant effect on the quality of the SEA results. The study aims to meet the needs for proactive frameworks to assess and protect wetland habitat and services more efficiently, toward the goal of advancing more intelligent urban planning and development design. The proposed framework, adopting geographic information system and remote sensing tools and applications, supports the temporal evaluation of wetland change and sustainability assessment based on landscape indicator analysis. The framework was applied to a rapidly developing urban environment in the City of Saskatoon, Saskatchewan, Canada, analyzing wetland change and land-use pressures from 1985 to 2011. The SEA spatial scale was rescaled from administrative urban planning units to an ecologically meaningful area. Landscape change assessed was based on a suite of indicators that were subsequently rolled up into a single, multi-dimensional, and easy to understand and communicate index to examine the implications of land-use change for wetland sustainability. The results show that despite the recent extremely wet period in the Canadian prairie region, land-use change contributed to increasing threats to wetland sustainability.

This paper presents a scenario-based approach to strategic environmental assessment (SEA) for wetland trend analysis and land use and land cover (LUC) modeling in an urban environment. The application is focused on the Saskatoon urban environment, a rapidly growing urban municipality in Canada's prairie pothole region. Alternative future LUC was simulated using remote sensing data and city spatial planning documentation using a Markov Chain technique. Two alternatives were developed and compared for LUC change and threats to urban wetland sustainability: a zero alternative that simulated trends in urban development and wetland conservation under a business as usual scenario, in the absence of prescribed planning and zoning actions; and an alternative focused on implementation of current urban development plans, which simulated future LUC to account for prescribed wetland conservation strategies. Results show no improvement in future wetland conditions under the city's planned growth and wetland conservation scenario versus the business as usual scenario. Results also indicate that a blanket wetland conservation strategy for the city may not be sufficient to overcome the historic trend of urban wetland loss; and that spatially distributed conservation rates, based on individual wetland water catchment LUC peculiarities, may be more effective in terms of wetland conservation. The paper also demonstrates the OPEN ACCESSSustainability 2015, 7 812 challenges to applied SEA in a rapidly changing urban planning context, where data are often sparse and inconsistent across the urban region, and provides potential solutions through LUC classification and prediction tools to help overcome data limitations to support land use planning decisions for wetland conservation.