A heatmap can represent the density of incident location and can find the high crime intensity area directly. 

        To create a heat map, point data is analyzed in order to create an interpolated surface showing the density of occurrence. Each raster cell is assigned a density value and the entire layer is visualized using a gradient.                The end visualization which affects how the data is interpreted by the viewer is a subjective one.  The two maps below show the same heat map analysis but with different number of class and cell ranges to set up the gradient.

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        Hot spot analysis uses statistical analysis in order to define areas of high occurrence versus areas of low occurrence.  Since hot spots areas are statistically significant, the end visualization is less subjective. Heat maps show that crime happens just in a certain area,  but hot spot analysis can have a high reliability that crime happens in a certain area, which can have a better allocation of cameras. High confident hot spots means that incident did happen frequently in this area.