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Image-based versatile LU information: A multidimensional classification scheme to support local planning in Indonesia

Land-cover (LC) and Land-use (LU) are recognised as important factors in environmental assessment and planning. However, different applications normally require different LC/LU information contents. Various planning tasks might face difficulties when two or more LC/LU maps with different classification schemes share the same area of interest. Consequently, redundant works on LC/LU surveys of the area are carried out in order to make sure that the collected LC/LU maps to be used contain relevant information. In order to overcome such problem, a versatile LU information system (VLUIS) is developed. The VLUIS is mainly developed based on remotely sensed imagery. Its versatility is characterised by the following aspects: (a) multilevel categorisation with respect to particular range of spatial resolution; (b)multiple attributes of LC and LU contained in a classification scheme, represented by five LU dimensions, i.e. spectral, spatial, temporal, ecological, and socio-economic function; (c)layer stack data storing model for those dimensions enabling flexible attribute retrieval through a spatial query for relevant applications. In this paper, examples of extraction methods using remotely sensed imagery, i.e. Landsat TM/ETM (30 m) and Quickbird (2.4 m) are given, particularly for the first dimension of the VLUIS. Semarang area in Central Java, Indonesia, was chosen due to its relatively complex LU phenomena within a narrow strip of image coverage. The use of the VLUIS is put in the context of refinement of the KDLD (Key Dataset for Local Development), which has been developed by various local governments in Indonesia. As compared to Landsat TM/ETM+-based image processing, the use of high-spatial resolution imagery such as Quickbird multispectral requires more complex spatial analysis in order to derive versatile LU dataset.