In consideration of the effect of radiometric specification of a mapping camera on the matching accuracy of imaging, the quantification of main radiometric specifications are analyzed, and the mathematical model between them is developed to provide theoretical foundations for determining the specifications of the mapping camera. Firstly, Least Squares Image Matching Algorithm (LSIM) is deduced mathematically, and then the main factors impacting matching accuracy are presented, including the scene characteristics, Modulation Transfer Function (MTF) for an imaging system, Signal to Noise Ratio (SNR) and Radiometric Distortion (RD) metrics. Then, the image degradation owing to the above factors is modeled and simulated. Based on LSIM, the mathematical model between matching accuracy and radiometric specifications is developed using Genetic Algorithm and Back-propagation Neural Network (GABPNN). Finally, the model is verified using simulated images and on-orbit images. Experimental results indicate that the model precision is less than 0.01 pixels. It suggests that when the MTFN is set to be greater than 0.08, SNR greater than 45 and RD less than 4% based on the model, the error of matching accuracy can be less than 0.1 pixel.