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In order to improve the supervision efficiency and accuracy of the supplementary cultivated land projects, and ensure that the quantity of the supplementary cultivated land is accurate, the land type meets the requirements, and the location is reasonable. It was based on spatial big data to research on the automatic discriminant technology of supplementary cultivated land compliance. The automatic identification rules and indicator system for the compliance of supplementary cultivated land was designed based on the big data framework, parallel computing technology, GIS spatial analysis, and the technical process, algorithm and software for the automatic identification of the compliance of supplementary cultivated land were developed. Daily and special supervision and verification of supplementary cultivated land were carried out, which became an increasingly important technical means for supervision and verfication of supplementary cultivated land projects. Practical operations demonstrated that the average analysis time for the project was 2~4 minutes, and the average of over 5700 problematic projects were prevented from being included in the database each month. This research provided technical means for compliance identification in the initiation, inplementation, and acceptance of supplementary cultivated land projects, enhancing the rationality of project initiation and improving the technical level of information verification, supervision of supplementary cultivated land. It played a crucial technical support role in ensuring the implementation of the system of the cultivated land requisition compensation balance in China.