On 20 October 2020, Associate Professor Rowan joined other teachers and some graduate students in the ENGAGE at workshop at CGI 2020 conference and gave an academic presentation entitled “Geometric algebra-base multilevel declassification method for geographical field data”, The report discusses the need for multi-layered GIS data decryption due to the diversity of GIS application patterns, for example, the need to decrypt publicly used data to hide confidential spatial information, the common arrangement of data that is not a regular encryption method, and the need to preserve general geospatial characteristics of the restored data. In addition, different levels of restore are required when faced with different levels of confidentiality.The report describes the use of geometric algebra (GA) to achieve a controlled method of precision decryption and restoration. The geographic field is represented as a GA object and further implements a uniform represent of the field. By introducing roary implementers and perturbation matrix, a decryption method for geographical data is proposed, which can gradually restore the characteristics of this field. In addition, geometric algebra decryption operators are constructed to realize the unified operation of field features and spatial coordinates. Quantitative performance evaluation can be provided by exploring the spatial error and spatial structure characteristics of the results. Experiments show that the method can be used for effective precision control, with good randomness and high degree of freedom. Experimental data show that the correlation coefficients of longitional directional field data are 0.945, 0.923 and 0.725, respectively, when decrypted at the lower, middle and upper levels. The characteristics of the algorithm meet the application needs of geographic data in data disclosure, secure transmission, encapsulation storage and so on.