A land use zoning method based on clonal selection optimization includes the steps of constructing a land use zoning foundation database through integrating land use data and relative thematic data, taking data in the database as input data, taking land use pattern spots as data processing units, establishing mapping for questions to be solved to a clonal selection algorithm, constructing a land use zoning protomodel based on clonal selection to solve a land use optimization layout result, and finally combining the pattern spots adjacent to a same land type though a method of a geographical information system to pick up boundary lines of the combined pattern spots to obtain a land use zoning boundary line so as to generate a land use zoning map. Through the adoption of technologies and research results related to artificial intelligence, intelligent behaviors of humans are simulated to construct the intelligent and automated land use zoning method based on the clonal selection optimization. Accordingly, the scientificity, the rationality and the operability of land use zoning are improved, and technical support for land use planning and land use control and management is provided.