This paper explores the characteristics of splicing of linear rules of two-dimensional cellular automata (2D CA) with m states and n neighborhoods. The study of splicing in 2D CA is worth examining since it enhances the average distance between linear rules and improves their distribution across the linear rule space. We present an algorithm for splicing two 2D CA linear rules and investigate several properties of the splicing operation. We also examine the algebraic properties of the proposed splicing operation on two-dimensional cellular automaton rules, which help characterize the underlying properties of splicing. These properties are motivated by the connection between splicing and DNA recombination and provide a foundation for its use in biologically motivated computational models. The distribution and proximity of linear rules within the rule space are analyzed using Hamming distance and Manhattan distance.