Least squares (LS) and maximum likelihood (ML) are the two main methods for parameter estimation of two-dimensional (2-D) noncausal simultaneous autoregressive (SAR) models. ML is asymptotically consistent and unbiased but computationally unattractive. On the other hand, conventional LS is computationally efficient but does not produce accurate parameter estimates for noncausal models. Recently, in [17], a modified LS estimation method was proposed and shown to be unbiased. In this note we prove that, under certain assumptions, the method introduced in [17] is also consistent.