Spatial sampling, data models, spatial scale and ontologies: Interpreting spatial statistics and machine learning applied to satellite optical remote sensing

This paper summarizes the development and application of spatial statistical models in satellite optical remote sensing. The focuses on a conceptual model that includes measurement sampling processes inherent We organized this into five main sections: introducing basis sensing, including sampling; variation, variation through object-based data model; advances modelling; machine learning explainable AI; hierarchical ontological nature remotely sensed scenes. finishes with summary. conclude sensing provides an important source information for techniques that, turn, serve as powerful tools to obtain from images.