Building Change Detection Method to Support Register of Identified Changes on Buildings

Dušan Jovanović,Milan Gavrilović,Aleksandra Radulović,Dubravka Sladić,Miro Govedarica

doi:10.3390/rs13163150

Abstract

Based on a newly adopted “Rulebook on the records of identified changes on buildings in Serbia” (2020) that regulates the content, establishment, maintenance and use of records on identified changes on buildings, it is expected that the geodetic-cadastral information system will be extended with these records. The records contain data on determined changes of buildings in relation to the reference epoch of aerial or satellite imagery, namely data on buildings: (1) that are not registered in the real estate cadastre; (2) which are registered in the real estate cadastre, and have been changed in terms of the dimensions in relation to the data registered in the real estate cadastre; (3) which are registered in the real estate cadastre, but are removed on the ground. For this purpose, the LADM-based cadastral data model for Serbia is extended to include records on identified changes on buildings. In the year 2020, Republic Geodetic Authority commenced a new satellite acquisition for the purpose of restoration of official buildings registry, as part of a World Bank project for improving land administration in Serbia. Using this satellite imagery and existing cadastral data, we propose a method based on comparison of object-based and pixel-based image analysis approaches to automatically detect newly built, changed or demolished buildings and import these data into extended cadastral records. Our results, using only VHR images containing only RGB and NIR bands, showed object identification accuracy ranging from 84% to 88%, with kappa statistic from 89% to 96%. The accuracy of obtained results is satisfactory for the purpose of developing a register of changes on buildings to keep cadastral records up to date and to support activities related to legalization of illegal buildings, etc.

Highlights

With advanced technology related to collecting geospatial data in the 21st century, each organization is faced with growing volumes of spatial data
Since there are no additional data for Serbia other than high-resolution images, we propose the use of pixel-based and object-based classification, over Very high spatial resolution (VHR) images from two epochs, 2016 and
Our tests with VHR images containing only RGB and NIR bands showed object identification accuracy ranging from 84% to 88%, with kappa statistic from 89% to 96%

Summary

Introduction

With advanced technology related to collecting geospatial data in the 21st century, each organization is faced with growing volumes of spatial data. Geospatial data can originate from different satellites, airplanes or even UAV platforms. Collected data vary from large amounts of LiDAR data to the satellite and aerial images with different spatial resolutions. Very high spatial resolution (VHR) optical satellite imageries have increased their usability in applications of change detection and urban monitoring. Classification of VHR images requires a significant research task in remote sensing and image analysis; it has great importance in infrastructure planning and change detection in the urban area, etc. Often, focus on these applications is on the classification of urban structures and identification, characterization and quantification of change detection on footprints of buildings or buildings’ rooftops

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