Pathological alterations of the microcirculatory system can be identified by measuring the temporal and spectral properties of laser Doppler flowmetry (LDF) signals acquired on the skin, and their changes following physiological stimulation. A wide range of stimulation protocols and measurement locations is observed in literature. Researchers often use non-invasive stimulation techniques, such as post-occlusive hyperaemia, cold tests, and local heating. As concerns the stimulation/recording sites, the forearm, fingers, and toes are typically selected to conduct microcirculation studies. However, recent clinical investigations showed that different anatomical sites present dissimilar blood flow patterns. Therefore, studies involving the comparison of LDF data, obtained from various anatomical locations, and thus subjected to the intrinsic heterogeneity of the microcirculation, may be methodologically inaccurate. At the moment, no consensus has been reached upon the optimal measurement location, the stimulation pattern, and the physiological parameters of interest. The aim of this study is to quantitatively characterize the heterogeneity of the peripheral perfusion at different anatomical locations: the index finger, the forearm, and the hallux. The skin microvascular system exhibits a complex vasodilatory response in the temporal domain, upon local heating. This physiological reactive hyperaemia comprises two effects: a fast transient response, correlated to neural activation, named axon reflex, followed by a slower hyperaemic plateau, mediated by the release of nitric oxide. In this work, we compare the vasodilatory reaction to heating at the different sites, based on a parametric representation of the perfusion signal. Moreover, skin blood flow is characterized by several components fluctuating at different time scales. Time-frequency decomposition of LDF signals allows to quantitatively evaluate the relative contribution of known physiological mechanisms to the regulation of the peripheral circulation. For this reason, we analyze the wavelet transform coefficients of LDF signals at baseline, to assess potential spatial heterogeneities of the perfusion power spectra among the aforementioned anatomical locations.