Seismic interferometry is a technique by which the Green’s function (or impulse response) between two receivers can be acquired from the crosscorrelations of wavefield responses at these receivers. Recent developments of this method has led researchers to exploit active as well as passive seismic wavefields to retrieve surface wave Green’s functions by crosscorrelation. The primary objective of these applications has been to gain near surface resolution from the high frequency content of the active data while gaining greater depth resolution from the low frequency content of the passive data. In these applications however, a Green’s function is retrieved for each data type and therefore a matching filter or a form of joint inversion is required to benefit from the additional bandwidth of both data types. Interferometry by multidimensional deconvolution (MDD) is a relatively new method of Green’s function retrieval that provides several advantages over interferometry by crosscorrelation. This thesis proposes a new method of merging active and passive data during the process of MDD. A primary advantage of this method over the alternatives is that the source signatures are disregarded and only a single Green’s function with the combined characteristics of both the active and passive data is retrieved. Using numerical modelling it is demonstrated that a broadband Green’s function response can be retrieved from combined active and passive data without the need to compensate for the differences in source signatures or variations in amplitude. Merging active and passive data prior to deconvolution may in fact improve the retrieved response due to the additional illumination provided by the supplementary data. In addition to expanding the bandwidth of the retrieved response, this method is shown to be capable of using data from one source type to spatially infill gaps in illumination in another source type when the bandwidth of the two are comparable.