Performance Evaluation of Three Different High Resolution Satellite Images in Semi-Automatic Urban Illegal Building Detection

Abstract

ABSTRACT:The problem of overcrowding of mega cities has been bolded in recent years. To meet the need of housing this increased population, which is of great importance in mega cities, a huge number of buildings are constructed annually. With the ever-increasing trend of building constructions, we are faced with the growing trend of building infractions and illegal buildings (IBs). Acquiring multitemporal satellite images and using change detection techniques is one of the proper methods of IB monitoring. Using the type of satellite images with different spatial and spectral resolutions has always been an issue in efficient detection of the building changes. In this research, three bi-temporal high-resolution satellite images of IRS-P5, GeoEye-1 and QuickBird sensors acquired from the west of metropolitan area of Tehran, capital of Iran, in addition to city maps and municipality property database were used to detect the under construction buildings with improved performance and accuracy. Furthermore, determining the employed bi-temporal satellite images to provide better performance and accuracy in the case of IB detection is the other purpose of this research. The Kappa coefficients of 70%, 64%, and 68% were obtained for producing change image maps using GeoEye-1, IRS-P5, and QuickBird satellite images, respectively. In addition, the overall accuracies of 100%, 66%, and 83% were achieved for IB detection using the satellite images, respectively. These accuracies substantiate the fact that the GeoEye-1 satellite images had the best performance among the employed images in producing change image map and detecting the IBs.

A New High-Precision and Lightweight Detection Model for Illegal Construction Objects Based on Deep Learning

“…Building detection is made possible by a building-detection adaptive technique that Chen et al [49] developed for seed placement and region growth. Xu et al [50] proposed an approach for the automatic detection and classification of building changes from airborne laser scanning data over two periods, where changes are confirmed by setting rules on the difference image map. Khalilimoghadam et al [51] used a city map, municipal property database, and three dual-temporal highresolution satellite images to detect buildings under construction to improve performance and accuracy.…”

High-precision automatic detection method of illegal construction object images in complex scenes

“…20 Multitemporal satellite images and change detection techniques have also been used to detect illegal construction. 21 However, these two methods were severely limited by space and required official maps for comparison. Chinese urban planning departments combine global positioning systems and geographic information systems (GISs) and use remote sensing dynamic monitoring technology to monitor illegal construction.…”

“…Another study proposed a digital city illegal construction monitoring method based on high-performance computing for the automatic and rapid detection of illegal buildings 20 . Multitemporal satellite images and change detection techniques have also been used to detect illegal construction 21 . However, these two methods were severely limited by space and required official maps for comparison.…”