Automated dual tip scanning near field optical microscope for investigation of nanophotonic systems The main goal of this dissertation was to realize a fully automated and robust dual tip scanning near field optical microscope (SNOM) and demonstrate its capabilities to characterize nanophotonic systems. The dual tip SNOM accesses optical information not simply attained with other super resolution microscopy techniques. This work thoroughly explained the implementation of a collision prevention scheme and the realization of the fully automated dual tip SNOM in which the detection tip automatically scans the entire area surrounding the excitation tip without collision. After successfully implementing the automated dual tip SNOM the setup was utilized to measure the near field of different photonic materials. First the dual tip SNOM was used to explore the polarization characteristic of the emission from the bent fiber aperture tip through exciting surface plasmon polaritons (SPPs) on an air gold interface. Another unique application of the dual tip SNOM is to excite the edge or corner of a photonic system locally. The automated detection tip was used to map a complex near field pattern due to the excited SPPs and reflected SPPs from the edges of the truncated triangular gold platelet. The most distinguished capability of the automated dual tip SNOM shown in this thesis is spectral and spatial dependent near field measurements of a nanodisk metasurface as a nanostructured sample. In spectral dependent near field measurements the excitation tip illuminated the silicon metasurface at different wavelengths. In spatial dependence near field measurements the fixed excitation wavelength was used to measure the position dependent near field intensities when the metasurface was displaced relative to the excitation tip. It was demonstrated that the integrated measured near field intensities by the detection tip could be related to the metasurfaces partial local density of optical states at the excitation tips position.