Abstract
An observation network will never be enough for creating good information about monthly rainfall. An interpolation method is always needed. For operational purposes, inverse distance weighting (IDW) method is used. In East Java, 197 observation points are involved, then IDW's parameters used are neighbor=12 and power=2. The consequences of this framework are investigated in this study. By reversing IDW's formula, two kinds of raster analyses are developed, distance to neighbor used (DNU) and coefficient from point (CFP). DNU shows how far points are used for doing interpolation in some area by kilometer (km) meanwhile CFP describes an area impacted by a point and value sent to another cell from an observation point. Data used in this study are longitude and latitude of 197 observation points. The scripts are written in R Language. Analysis based on local governmental region shows that Sumenep has very far DNU. In average, the first point used located more than 25 km, and its twelfth is 112 km (average other regions DNU1=7 km and DNU12=35 km). It means there should be a unique interpolation mechanism for Sumenep. CFP confirms that some points give impact in unnatural ways (impacted area=5741 km2). We propose DNU and CFP as alternative quality control parameters for investigating consequences in interpolating rainfall.
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