If an interpolating curve follows very closely to the data polygon, the length of the curve segment between two adjacent data points would be very close to the length of the chord of these two data points, and the length of the interpolating curve would also be very close to the total length of the data polygon. In the figure below, each curve segment of an interpolating polynomial is very close to the length of its supporting chord, and the length of the curve is close to the length of the data polygon. Therefore, if the domain is subdivided according to the distribution of the chord lengths, the parameters will be an approximation of the arc-length parameterization. This is the merit of the chord length or chordal method.-If an interpolating curve follows very closely to the data polygon, the length of the curve segment between two adjacent data points would be very close to the length of the chord of these two data points, and the the length of the interpolating curve would also be very close to the total length of the data polygon. In the figure below, each curve segment of an interpolating polynomial is very close to the length of its supporting chord, and the length of the curve is close to the length of the data polygon. Therefore, if the domain is subdivided according to the distribution of the chord lengths, the parameters will be an approximation of the arc-length parameterization. This is the merit of the chord length or chordal method.