Yolanda Esteban

Quantifying changes in building footprint in the historic coastal town of Queenscliff

ABSTRACT The sea change phenomenon has attracted new residents to Australian coastal towns and brought with it expectations of residential housing formed in metropolitan settings. Consequently, the traditional ‘identifying’ neighbourhood character of these towns is changing. Much larger houses are now being built and site coverage has increased. To date, changes in character have been measured using data based on the subjective judgement of residents through surveys and interviews. More objective information would be beneficial in understanding change. This paper describes a methodology that has been developed to quantify the change in the building footprint in the historic coastal town of Queenscliff in Victoria. Using selected aerial photographs, the building footprint of the towns residential buildings has been estimated at four intervals from 1957 until 2006. This footprint has been compared to the block size at each interval so that changes in house-to-block ratio may be compared. Over 20% of the residential homes were assessed. Building footprint has risen from 30% to over 38% in the documented 50 years. The method developed here is a low-cost method of tracking footprint change over an extended period and informing local planners and residents of when and where the changes have occurred.

Adopting a computational approach to identifying and modelling future development initiatives within the urban context

Abstract In 2002 the State Government of Victoria, in partnership with the City of Greater Geelong and Deakin University, initiated an urban design framework to explore development opportunities of a series of redundant industrial sites adjacent to Geelong’s central activities area (CAA). One of the objectives of the framework was to explore a range of initiatives based on the expansion of the Deakin University Waterfront campus from 700 students to an expected cohort of 5000 students. Working with a set of predefined constructs for different types of city-based user groups, such as net floor space requirements and time/travel distances between facilities, the following paper presents a simple computational approach to assist in identifying, mapping, and spatially exploring different development scenarios.