Remote Sensing Effects and Invariants in Land Surface Studies

Remote sensing is a technique to acquire information from a distance. Remote sensing effects refer to any factors that need to be considered in remote sensing processes, while remote sensing invariants represent features that remain stable throughout these processes. Both remote sensing effects and invariants are fundamental to the study of remote sensing systems, methods, algorithms, products, and applications. Many studies have explored different effects and invariants independently, yet these studies are scattered across the literature and a comprehensive synthesis is lacking within the community. This paper intends to synthesize various remote sensing effects and invariants under a unified framework. The characterization, underlying principles, and potential applications of a selected group of remote sensing effects were first examined. Subsequently, a suite of nine key effects, atmospheric effects, background effects, clumping effects, directional effects, heterogeneity effects, saturation effects, scaling effects, temporal effects, and topographic effects, were addressed. Furthermore, a list of remote sensing invariants, including spectral, spatial, temporal, directional, and thematical invariants, were analyzed. Potential directions for future studies were further discussed. This synthesis represents a concerted effort to advance the theoretical understanding of fundamental principles in remote sensing science.