A framework for selecting a fit-for-purpose data collection method in land administration

The majority of the world's population do not have access to proper land administration systems to register their land and property information. The land community has come to believe that this problem is strongly related to the data collection process, where the use of highly accurate, expensive and time-consuming spatial data collection methods such as field surveying, is overemphasised. To overcome this, innovative spatial data collection methods are employed in many jurisdictions (e.g. using GPS for low-cost boundary surveys, using the power of citizen in the process of data collection). However, little is known about the parameters that affect the choice of a spatial data collection method to be appropriate for its intended purposes. Arguably, establishing a fit-for-purpose data capture method for collecting or updating RRRs related to land and property is essential for enabling the range of land administration functions around the world. This paper reports on a systematic study to determine a set of parameters that could influence the choice of a spatial data collection method in land administration. Data was collected using a Delphi study, which establishes consensus among land administration experts. This method allowed us to unlock knowledge through an iterative process with controlled feedback. For the first time in this study, an international group of land administration experts reached consensus regarding a set of parameters that should be considered in the process of selecting a fit-for-purpose spatial data collection method. These findings are incorporated to formulate a generic and innovative framework, which could potentially serve as a basis for ensuring that the choice of a spatial data collection method in land administration is fit for purpose.