Abstract
Abstract. At present, most of the researches on geometric change detection of vector data, they store the change detection results in the database, so they pay more attention to the accuracy of results, but not to the speed of processing. Nowadays, many applications require real-time change detection on vector data and rapid presentation of the result. Although the existing algorithms use spatial index technology to improve the processing speed, the processing time is still beyond the range that people can bear. In order to reduce processing time, this paper takes the vector surface feature set as the research object, trying to reduce the redundancy of the candidate set that seriously affects the efficiency of change detection. Based on the regular use of spatial index created with geometric Minimum Bounding Rectangle, this paper uses geometric shrinkage technique and precise query technique to reduce the size of the candidate set for detection, so as to achieve the goal of speeding up. Finally, using five years of farmland data and resident data from Ezhou City, Hubei Province, China, a change detection experiment was conducted. The experiment proved that the geometric shrinkage and precise query techniques can effectively improve the processing speed.
Highlights
Change detection technology is based on computer image processing system, to identify changes in different periods of the target or phenomenon state
The change detection technology based on remote sensing image has made considerable achievements, and the change detection based on vector data has gradually become a hot topic at home and abroad
Wang Wenjie (Wang, 2013) put forward the 1:1 geometric change detection method of multi feature similarity synthesis for space-time line and surface element, and a complex change detection method for multiple entities was proposed on this basis; Wang Huai (Wang, 2014) proposed a geometric matching similarity change detection method for geographical conditions, and Chen Zhanlong (Chen, 2016) gave a method of geometric similarity measurement; Liu Jie (Liu, 2017) designed a geographical factor change detection method based on different temporal homologous reference data
Summary
Change detection technology is based on computer image processing system, to identify changes in different periods of the target or phenomenon state. Using the MBR to determine the detection candidate set will, to some extent, cause redundancy in the detection candidate set, because the intersection of the two geometric MBR does not mean that the geometry itself will intersect; Secondly, in actual production, due to the influence of various errors originating from the machine, people and so on, the two actual adjacent geometries will show a phenomenon of boundary crossing on the data, which will cause ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume IV-4, 2018 ISPRS TC IV Mid-term Symposium “3D Spatial Information Science – The Engine of Change”, 1–5 October 2018, Delft, The Netherlands redundancy of detection candidate sets to some extent Both of these conditions reduce the quality of the selected detection candidate set and the speed of change detection. Only the surface data is studied, point and line data are not considered temporarily
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