INTEGRATING REMOTELY SENSED DATA IN LAND USE ASSESSMENT MODEL

The usefulness of GIS and spatial analysis is increasingly realized by researchers, analysts, planners and policy makers as GIS has proven to be an added value to conventional analysis of quantitative and qualitative method. While GIS and spatial analysis techniques are widely used, there is still a wide opportunity for improvement particularly in integrating and manipulating the data bases within and beyond a specific model. In an area or region facing rapid development it demand for close monitoring as its land use often change dynamically and unpredictably. This often requires for current and reliable data to model and simulate the change of land use and make predictions about future use. Remotely sensed data offers reliability and up-to-date data.

The research proposed an integrated land use assessment model (ILA) to monitor development particularly in the region undergoing rapid development. For the purpose of this study, the Klang Valley region occupying an area of 2,830 square kilometres and also the fastest growing region in Malaysia, is selected as the study area. The model was developed and implemented through the incorporation of data bases within a multi-criteria decision making processes. The decision making process was based on selected criteria from the database, weighted and then applied to generate development scenarios based on specified objectives. ILA is an extension of the stand alone sector-based approach conducted under the ‘Application of GIS for Klang Valley Region (AGISwlk)’ project. In essence, the model developed incorporate two types of assessment namely Land Resources assessment and Land Capacity assessment which is designed to provide sufficient flexibility to the users in terms of evaluating development planning within diverse situations. A user interface functions was also created and designed to ease access to data bases and execute the ILA model. Since the model requires trend data, temporal remotely sensed data are used to generate past and current land use data. These data were used to estimate the intensity of change and evaluate pattern of land use in the study area. While high resolution remotely sensed data are used to update data to ensure its currentness and reliability. The implementation of ILA basically attempted to adopt an integrated approach in achieving and maintain equilibrium between the demand and supply of land use for existing and future development.

Remotely sensed data has proven to be useful for continuous evaluation and analysis of development in relation to land use or land cover change analysis. The study undertaken clearly shows that temporal remotely sensed data can be used effectively to evaluate trends of land use change as well as assess urban sprawl to better understand the pattern of urban growth. Integrating information derived from remotely sensed data in land use assessment model would enable the assessment on land supply, availability and allocation of land for future development as well as analyzing the implications of projected development activities to be more significant and useful to the decision makers.