<![CDATA[Spatial planning and regional development, which are interrelated, require Gross Regional Domestic Product (GRDP) data that is spatially representative. The GRDP officially released by the government assumes that its value is distributed homogeneously across an administrative area, making it less representative. Therefore, a method is needed to provide spatial economic data that reflects the heterogeneity of economic activities within a region, allowing for sharper analysis and more targeted planning recommendations. Geographically Weighted Regression (GWR) downscaling can be applied due to the diverse geographical characteristics of a region. GWR downscaling is sensitive in representing regional heterogeneity with smaller spatial units. In this study, GRDP downscaling was carried out to an estimated grid with a resolution of 500 m x 500 m. Several weighting technique approaches are available to produce the best GRDP estimated grid values. To test this, the study compares weighting techniques using different types of kernel functions combined with bandwidth types. The results of the study indicate that the Gaussian-Fixed weighting technique produces the best GRDP estimated grid values compared to other techniques.]]>
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