With the increasing demand for multidimensional data processing, Clifford Algebra (CA) has attracted more and more attention in the field of geographical information system. Clifford algebra unifies and generalizes real number, complex, quaternion, and vector algebra, converts complicated relations and operations into intuitive matrix algebra independent of coordinate systems. CA provides the solution for solving multidimensional information processing with a high correlation among the dimension and avoids the loss of the information. Traditional methods of Computer Vision (CV) and Artificial Intelligence (AI) after combing with the CA provide robust results in multidimensional processing and give additional feature analysis facility to remote sensing images. In this paper, we provide a detailed survey of CA in different fields of AI and CV with applications and current developments in geospatial research. We also discuss Clifford Fourier Transformation (CFT) and Quaternions (sub-algebra of CA) because of their necessity in remote sense image processing. We focused on how CA is helping AI and solving the classification problems and improving those methods using geometric algebra processing. Finally, we discuss the issues, challenges, and future perspectives of CA with possible research directions.