In this paper, we investigate (and extend) Ripley’s circumference method to correct bias of density estimation of edges (or frontiers) of regions. The idea of the method was theoretical and diffcult to implement. We provide a simple technique based of properties of Gaussian kernels to effciently compute weights to correct border bias on frontiers of the region of interest, with an automatic selection of an optimal radius for the method. We illustrate the use of that technique to visualize hot spots of car accidents and campsite locations, as well as location of bike thefts. Kernel Density Estimation with Ripley’s Circumferential Correction

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