Quantifying landscape pattern and its change are essential for the monitoring and assessment of environmental consequences of urban area. This paper aims to analyze spatiotemporal patterns of urban landscape changes in Kathmandu Valley, Nepal by combining remote sensing, GIS and landscape metrics. Multi-temporal satellite images from high resolution (CORONA, SPIN and IKONOS) to moderate resolution (LANDSAT: MSS, TM) were processed to identify the temporal changes in landscape patterns. A hybrid approach with a series of steps was developed for mapping the land uses in the valley. Four land use maps were prepared from the images for the year 1967, 1978, 1991 and 2000. A set of landscape metrics was used to evaluate temporal dynamics of land uses from the maps at class and landscape levels. The results suggested that the urban/builtup area in the valley increased from 3 % in

Debate regarding suburban sprawl in urban studies is contentious. It is fair to say that the phenomenon is not fully understood to satisfaction in the academic, policy, or planning communities and there are a host of reasons why this may be the case. Characterization of sprawl in the literature is often narrative and subjective. Measurement is piecemeal and largely data-driven. Existing studies yield contrary results for the same cities in many cases. The partial appreciation for the intricacies of sprawl is problematic. In practice, city planning agencies and citizen advocacy groups are scrambling to suggest and develop “smart growth ” strategies to curb sprawl, without a strong empirical basis for measuring the phenomenon. Yet, sprawl is extremely popular with consumers. In this paper, we develop an innovative approach to diagnosing sprawl, looking across the full range of its characteristic attributes in a comprehensive fashion that is robust to some well-known challenges. This proves to be very useful in sweeping the parameter space of the phenomenon, enabling the visualization and valuation of sprawl surfaces across attributes, allowing us to check the pulse of a developing city. We apply the work to Austin, TX, a controversial exemplar of American sprawl, with the surprising result that sprawl and “smart growth ” are found to co-exist and co-evolve. This raises questions about relationships between the two, with consequences for planning and public policy.

The agent-based modelling (ABM) paradigm provides a mechanism for understanding the effects of interactions of individuals and through such interactions emergent structures develop, both in the social and physical environment of cities. This paper explores how through the use of ABM, and its linkage with complexity theory, allows one to create agent-based models for the studying cities from the bottom-up. Specifically the paper focuses on segregation and land-use change. Furthermore, it will highlight the growing interest between geographical information systems (GIS) and ABM. This linkage is allowing modellers to create spatially explicit agent-based models, thus relating agents to actual geographical places. This approach allows one to explore the link between socio-economic geography of the city and its built physical form, and can support decision-making regarding interventions within the social and physical environment. 1

Abstract: There is a growing interest in relating agent-based models to realworld locations by combining them with geographical information systems (GIS) which can be seen with the proliferation of geosimulation models in recent years. This coincides with the proliferation of digital data both in the two and three dimensions allowing one to construct detailed and extensive feature rich and highly visual 3D city models. This paper explores some of these developments in relation to our own initial work on building 3D geospatial agent-based models of urban systems and the technologies that allow for such models to be created. Furthermore, we highlight some techniques for the creation of 3D agent-based models and stress that such models are not a substitute to good models. 1 1