Digital terrain analysis (DTA) in practical application is typically a workflow-building process which needs to organize the various DTA tasks properly and assign the algorithm (and its parameter settings) for each task. During this process it is crucial to use knowledge on specifying the proper algorithm and parameter settings for each DTA task according to the application context (such as the target task, the terrain condition of the study area, the DEM resolution, etc.), referred to as application-context knowledge. However existing DTA-assisted tools often cannot use application- context knowledge because this type of DTA knowledge has not been formalized to be available for inference in these tools. This is mainly because this type of DTA knowledge often exists in the minds of domain experts and is implicit in the text of case studies published in academic papers. This situation makes the DTA workflow-building process difficult for users, especially for non- experts. This study proposes a case-based formalization for application-context knowledge in the DTA domain and a corresponding case-based reasoning method. A preliminary experiment demonstrates the usability of the proposed case-based method.