Automated Tax Mapping from UAV Multispectral Imagery

Abstract

Tax mapping is an essential element for efficient management of real estate property and tax management, paving the way for effective implementation of g-governance practices in India. Conventional mapping of individual buildings and their attributes involves large effort and is time-consuming. The use of high-resolution UAV imagery facilitates the process of automatic extraction of land parcel, roof area and height by providing accurate and latest building and landuse information for improved tax assessment and collection. Image segmentation has been performed on UAV imagery applied to differentiate rooftop surfaces from other features such as roads and vegetation using gray level thresholding. An example-based feature extraction algorithm was adopted to extract the land parcel and rooftop surfaces from the segmented image. Further, DSM and DTM derived from UAV imagery were used to determine the height of the buildings by extraction of terrain points and rooftop points. The extracted building height was used to estimate the numbers of floors in the building using thresholding. The number of floors and rooftop area were used to derive the total floor area of each building. The property tax to be levied for each building was calculated automatically using total floor area in efficient and scientific manner. The UAV imagery used in the study enabled rapid mapping of buildings parcels for tax assessment compared to conventional mapping methods.