Geographical spatial data models and using them to represent geographical entity-space relationships stand as the core of GIS theories and applications. This study introduces and discusses a newly proposed GIS spatial data model, spatial chromatic model (SCM), and its standard form, spatial chromatic tessellation (SCT). The concepts, structures, operations of SCM and SCT were introduced and their potential applications and implications for geoinformatics were discussed. The space in SCM consists of many spatial tiny data units, called cells, and these cells are assigned with unique codes (chromatic codes), which like the cellular genetic codes. The cells in SCM can be merged into larger subspace (clusters) with similar chromatic codes. The chromatic codes of cells and clusters provide abundant information for various GIS spatial analysis and computation. The essential foundation of SCM is based on the fundamental physical principle that entities are first and space is relative to entities. This principle can also be applied to geography and information science. SCM will help us to better understand geographical entity-space relationship from a new perspective.