Appraisal data stored in computer assisted mass appraisal (CAMA) systems have been successfully analyzed for change by utilizing light detection and ranging (lidar). Spatial information derived from lidar data is used to create a structure footprint. Injecting the scale-accurate sketch vectors from CAMA into the lidar-derived structure footprint allows a direct comparison of the sketch with the footprint. This comparison process for detecting change in the CAMA data is highly automated, and various degrees of change classification allow more efficient follow-on desktop reviews and field checks by assessors.
Mapping in assessment
Cunningham, K. W. (2008). CAMA change detection with light detection and ranging. Journal of Property Tax Assessment & Administration, 5(1), 55-69. Retrieved from https://researchexchange.iaao.org/jptaa/vol5/iss1/3