An Airport Knowledge-Based Method for Accurate Change Analysis of Airport Runways in VHR Remote Sensing Images

Abstract

Due to the complexity of airport background and runway structure, the performances of most runway extraction methods are limited. Furthermore, at present, the military fields attach greater importance to semantic changes of some objects in the airport, but few studies have been done on this subject. To address these issues, this paper proposes an accurate runway change analysis method, which comprises two stages: airport runway extraction and runway change analysis. For the former stage, some airport knowledge, such as chevron markings and runway edge markings, are first applied in combination with multiple features of runways to improve the accuracy. In addition, the proposed method can accomplish airport runway extraction automatically. For the latter, semantic information and vector results of runway changes can be obtained simultaneously by comparing bi-temporal runway extraction results. In six test images with about 0.5-m spatial resolution, the average completeness of runway extraction is nearly 100%, and the average quality is nearly 89%. In addition, the final experiment using two sets of bi-temporal very high-resolution (VHR) images of runway changes demonstrated that semantic results obtained by our method are consistent with the real situation and the final accuracy is over 80%. Overall, the airport knowledge, especially chevron markings for runways and runway edge markings, are critical to runway recognition/detection, and multiple features of runways, such as shape and parallel line features, can further improve the completeness and accuracy of runway extraction. Finally, a small step has been taken in the study of runway semantic changes, which cannot be accomplished by change detection alone.

Framework for Runway's True Heading Extraction in Remote Sensing Images Based on Deep Learning and Semantic Constraints

“…Generally, the runway is narrow and built on a flat terrain [14] influenced by the direction of local prevailing wind, the available land area, airport throughput, and runway structures of an airport may appear as single, parallel, cross-runways, or combined runways [15,16], as shown in Fig. 1(a).…”

“…Accurately identifying the runways of different materials and structures in an airport is challenging. Previous studies have focused on small areas [16][17][18][19], asphalt/concrete materials with good marking [20][21][22][23], and autonomous landing [24,25]. Research on runway heading extraction from a database perspective for an extensive range of multiple materials is scarce and thus urgently needed.…”

“…Earlier airport runway extraction methods can be classified into traditional and deep-learning methods. The traditional method takes advantage of the runway's flatness, homogeneous surface, and chevron marking [16] to extract low-level features such as line features [17,19,[26][27][28], texture features [29][30][31], local features [16,32] and shape features [29,33] to locate and extract the runway. Ding et al [16] used the presence of chevron markings at the end of runways to extract runways based on visual saliency analysis, grayscale template matching, and line-segment detection.…”

Innovative Business Model for the Management of Airports in Purpose to Identify Runway Damage in Time

“…Geodetic methods are non-invasive and enable the accurate detection of on the surface data. D'Apuzzo et al [20] concludes that accurate monitoring and prediction of runway conditions are the main elements of developing measurement models (terrestrial, Global Navigation Satellite System-GNSS methods, and Light Detection And Ranging-LiDAR technology and Synthetic Aperture Radar-SAR interferometry) for researching runway deformities (i.e., deformities on the surface) [21,22]. The usage of these approaches has not been researched sufficiently in the accessible literature.…”

Modelling of Evenness of Runways as an Element of Sustainable Airport Maintenance

“…The authors mainly describe data capture technologies, data processing accuracy, and presentation methods. Data capture methods, as described by the authors, must also be feasible during airport operation [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25].…”