Modelling the development of Asian cities using Airphotos and Remote Sensing data
ir C.A. de Bruijn
ITC - Urban Survey Division, Netherlands
Abstract
Urban models are used to simulate the development of cities in order to anticipate the needs for land, infrastructure and facilities. Modelling is an important planning tool but depends on the availability of accurate and detailed datasets on socio-economic aspects and interactions. Not in all countries such data are readily collected from air photos or remote sensing images, particularly urban landuse at various points in time.
A GIS enables analysis of the development process as an interaction between landuse changes, infrastructure and distribution of major activity nodes. In this way it is possible to establish and quantify relationships that model the spatial development rather well. Case studies on the development of Hyderabad in India and Bangkok in Thailand will be described to illustrate the potential of landuse based urban modelling.
Using existing knowledge from GIS systems and model - derived probabilities will make it possible to create time series of comparable urban development data based on routine remote sensing processing.
1 Introduction
As a contribution to rational procedures in the planning process models are important. Models quantify assumptions how an urban area develops and grows, not in isolation but in an integrated way: the assumptions mutually influence each other which may reinforce or reduce certain expected effects.
The arrival of PC's at planners' desks increase the accessibility of models as a planning tool. FOOT ( 1984) discussing some practical examples of modelling states that since computers are now readily available urban models can easily be developed and can provide good useful information to assist the decision maker.
Performance and spatial resolution of the model depend on quality and accuracy of the basic data. In many developing countries small area statistics may not be available or they could be highly unreliable and incomplete. Administrative data will not ( yet/) be accessible for modeling exercises and they may be also far from comprehensive.
Development of a class of models that is based on observable physical changes that can be interpreted from airphotos and/or satellites could be a way out of the data problem.
