The increasing volume of spatial data has amplified the need for their classification, sharing, and processing in disaster management. During a disaster, large-scale and macro-level decisions are required to manage the situation as quickly and efficiently as possible. In such critical conditions, the availability of decision support tools, rapid information collection, and agile reporting from up-to-date databases is essential. In this context, a Spatial Data Infrastructure (SDI) can provide a platform for the collection, standardization, and sharing of spatial data, thereby facilitating integrated management. This study investigates the role of spatial data infrastructure as a platform for achieving integrated management in disaster risk reduction, with an emphasis on land subsidence. The research methodology includes a systematic review of technical literature, content analysis of relevant laws and regulations, and the use of structured questionnaires and interviews to gather opinions from university professors and managers of responsible organizations. The findings indicate that existing laws primarily focus on controlling groundwater extraction, while neglecting other critical dimensions such as subsidence rate monitoring, hazard zonation, and infrastructure resilience. Data analysis led to the identification of five key categories of actions (phenomenon identification, monitoring, control, remediation and strengthening, and prediction) and the determination of data requirements for each responsible organization. Based on this research, it was determined that the establishment of an SDI based on a distributed database model, coupled with legal revisions and mandating organizations to share standardized data, can provide a platform for the integrated management of land subsidence crises.