A unified framework is proposed for analysis and synthesis of two-dimensional spatial sound field in reverberant environments. In the sound field analysis (SFA) phase, an unbaffled 24-element circular microphone array is utilized to encode the sound field based on the plane-wave decomposition. Depending on the sparsity of the sound sources, the SFA stage can be implemented in two manners. For sparse-source scenarios, a one-stage algorithm based on compressive sensing algorithm is utilized. Alternatively, a two-stage algorithm can be used, where the minimum power distortionless response beamformer is used to localize the sources and Tikhonov regularization algorithm is used to extract the source amplitudes. In the sound field synthesis (SFS), a 32-element rectangular loudspeaker array is employed to decode the target sound field using pressure matching technique. To establish the room response model, as required in the pressure matching step of the SFS phase, an SFA technique for nonsparse-source scenarios is utilized. Choice of regularization parameters is vital to the reproduced sound field. In the SFS phase, three SFS approaches are compared in terms of localization performance and voice reproduction quality. Experimental results obtained in a reverberant room are presented and reveal that an accurate room response model is vital to immersive rendering of the reproduced sound field.