Survival Analysis in Land Change Science: Integrating with GIScience to Address Temporal Complexities

Although land changes are characterized by dimensionality in both space and time, and a multitude of methods and techniques have been developed to model them, the temporal dimension has seldom been adequately addressed by commonly used methods. In the context of temporal complexities represented in different space–time data models, this study aims to establish a framework for applying survival analysis theory and techniques to geographical land change modeling. Our efforts focus on (1) introducing basic concepts in survival analysis and their connections to space–time data commonly used in land change analysis, (2) using survival metrics to describe temporal patterns that are not easily detected by other methods, and (3) applying survival analysis methods to disclose effects of varying temporal patterns and uncertainties. Our findings suggest that survival analysis, coupled with geographic information systems (GIS) and remote sensing data, can effectively disclose relationships in land changes, and in many instances excel in shedding light on the temporal patterns of land changes.