## 2 Identification and Supervision of Unauthorized Construction  
Ground object recognition and change detection based on remote sensing images constitute a complex process, especially for small targets such as buildings. Low-resolution remote sensing images are insufficient for extracting the features of ground objects and hence less useful for detecting changes in buildings to identify unauthorized construction. The high-resolution data sources used for change detection have some limitations; for example, it is difficult to obtain images from the QuickBird satellite, and high-resolution aerial images take large amounts of memory to store. At present, although some cities have carried out building change detection and research to identify illegal buildings, and have tried to establish a business application system for finding illegal buildings, there still is no complete theoretical and technological system for identifying illegal buildings, because these applications have not been widely promoted [7; 16].  
The basic idea of identifying illegal urban construction activity in this manner is to take the distribution of urban buildings as the monitoring object, then use UAV remote sensing technology to quickly obtain images and spatial distribution information for buildings through image processing, pattern recognition, and other methods. The results are then overlaid with planning map data that only experts can interpret, allowing managers to monitor current building information and identify unauthorized construction. This method can effectively deter unauthorized construction activities and aid in the supervision of overall urban planning. It also can provide high-quality, intuitive spatial information support for dealing with urban disasters and emergencies, and promote the sustainable development of urban planning and construction in China.  
In this study, using UAV remote sensing for the dynamic monitoring of construction and the collection of monitoring information involved three main modules.  
The first was the data processing and illegal building identification module. The aim of this module was to complete data acquisition and illegal building identification. High-resolution UAV remote sensing images were captured from the research objects. At the same time, automatic preliminary screening of changes in building height was carried out based on Model Builder in ArcGIS, and the changes were confirmed by manual visual interpretation. Then, unauthorized construction was verified using a 3D model and 720\({}^{\circ}\) panorama imaging to obtain accurate data on illegal buildings.  
In the second module, we handled the data based on the WebGIS network information management system. This provided a dynamic supervision platform for a series of functions: target image identification, field verification, investigation and penal process monitoring, and historical tracing. We employed the architecture of WebGIS in the OpenGeo Suite and related technologies to analyze the design and integration process of PostGIS based on an object-oriented spatial database. By building a complete prototype system, it is possible to use WebGIS technology for digital information management related to unauthorized urban construction.  
In the third module, we used a mobile grid management terminal system for data communication. This mobile intelligent terminal provided information support for daily operations so data could then be collected and analyzed in a timely manner for presentation to grid managers.  
The built detection and management platform is shown in Figure 1.