GORS 2(16) Study and Evaluation Geometric Correction of Cartosat Images for Various Terrain Types Using Different Mathematical Models

Abstract

Abstract: The main Advantage of satellite images is that they allow dealing with reality effectively and save a lot of time, effort, and cost compared to the traditional methods used. However, before using satellite images in optimal ways, all spatial distortions present in these images must be removed through the process of ortho-ratification. This research aims to evaluate and study the process of geometric correction of Indian (Cartosat) satellite images of 2.5 meters spatial resolution using several mathematical models (polynomial of different degrees - the projective model) in addition to the (Rational Function Model) RFM the original model for these images to determine the most appropriate alternative mathematical model for these images in the case that the data of the original model is lost. In parallel with the use of the aforementioned mathematical models, the process of geometric correction for several areas with different terrain (plain areas - rugged areas) is studied and the accuracy of this process regarding different types of terrain is evaluated. The results showed that the original model RFM gives the highest spatial accuracy of up to 2 meters, and the Projective model comes with an accuracy of up to 6 meters, so this model can be used instead of RFM when its data is lost but only for projects that do not require high spatial accuracy. Geometric correction was also done for Cartosat images covering different terrain areas, represented by plain areas and mountainous areas, the resulting accuracy values ​​were 2 m, and 6 m respectively. The reason for the low spatial accuracy in mountainous areas is due to the increase in the negative effect of elevation values, which is represented by the weak accuracy of monitoring locations GCPs on the raw images.