Extraction of City Roads Through Shadow Path Reconstruction Using Laser Data

Zhu, Ping; Lu, Zhong Le; Honda, Kiyoshi; Eiumnoh, Apisit

doi:10.14358/pers.70.12.1433

Cited by 32 publications

(13 citation statements)

References 5 publications

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“…The key concepts of the method were the detection of the occurrence of small height jumps on road sides, neighbouring adjacent LiDAR points and filtering based on the heights. The analysis result of the study showed that the completeness varied between 50% and 86% and that the accuracy was about 0.18 m. Zhu et al [19] developed the Road Extraction Assisted by Laser (REAL) method of automatically extracting city roads through a shadow path using both digital aerial images and aerial LiDAR data. Yang et al [20,21] proposed a method of automatically extracting road markings and street-scene objects from mobile LiDAR data.…”

Section: Mapping Methods By Type Of Objectmentioning

confidence: 99%

Frequent Unscheduled Updates of the National Base Map Using the Land-Based Mobile Mapping System

et al. 2013

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This paper focuses on the use of the Land-based Mobile Mapping System (LMMS) for the unscheduled updates of a National Base Map, which has nationwide coverage and was made using aerial photogrammetry. The objectives of this research are to improve the weak points of LMMS surveying for its application to the updates of a National Base Map (NBM), which has rigorous accuracy and quality standards. For this, methods were suggested for the (1) improvement of the accuracy of the Global Positioning System/Inertial Navigation System (GPS/INS) in the long-term exposure of environments with poor GPS reception; (2) elimination of mutual deviations between LMMS data obtained in duplicate to meet resolution standards; (3) devising an effective way of mapping objects using LMMS data; and (4) analysis of updatable regions and map layers via LMMS. To verify the suggested methods, experiments and analyses were conducted using two LMMS devices in four target areas for unscheduled updates of the National Base Map.

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Section: Mapping Methods By Type Of Objectmentioning

confidence: 99%

Frequent Unscheduled Updates of the National Base Map Using the Land-Based Mobile Mapping System

et al. 2013

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“…On the contrary, roads in airborne LiDAR data are less frequently disturbed by higher objects due to LiDAR's higher penetrability into vegetation and its smaller field of view. Considering these complementary clues, Zhu et al (2004) detected most road objects without shadows from high-resolution colour image data, then used LiDAR data to identify and connect roads across shadowed regions.…”

Section: Fusion Of Lidar Data and Imagesmentioning

confidence: 99%

Multi-source remote sensing data fusion: status and trends

Zhang

2010

International Journal of Image and Data Fusion

585

325

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With the fast development of remote sensor technologies, e.g. the appearance of Very High Resolution (VHR) optical sensors, SAR, LiDAR, etc., mounted on either airborne or spaceborne platforms, multi-source remote sensing data fusion techniques are emerging due to the demand for new methods and algorithms. The general fusion techniques have been well developed and applied in various fields ranging from satellite earth observation to computer vision, medical image processing, defence security and so on. Despite the fast development, the techniques remain challenging for multi-source data fusion within varying spatial and temporal resolutions. This article reviews current techniques of multi-source remote sensing data fusion and discusses their future trends and challenges through the concept of hierarchical classification, i.e., pixel/data level, feature level and decision level. This article concentrates on discussing optical panchromatic and multi-spectral data fusing methods. So far, the pixel level fusion methods have mainly focused on optical data fusion; high-level fusion includes feature level and decision level fusion of multi-source data, such as synthetic aperture radar, optical images, LiDAR and other types of data. Finally, this article summarises several trends tending to broaden the application of multi-source data fusion.

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“…This integration of model knowledge stabilises the extraction and is able to bridge gaps in the structure lines in the vicinity of roads, which are often not continuous in nature. Road extraction can also be improved by fusing height and image data (Zhu et al, 2004) as well as GIS data (Oude Elberink & Vosselman, 2006).…”

Section: Related Workmentioning

confidence: 99%

Network Snakes for Adapting Gis Roads to Height Data of Different Data Sources – Performance Analysis Using Als Data and Stereo Images

Göpfert

Rottensteiner

Heipke

2012

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:In order to tackle the problem of consistently integrating 2D vector data and a DTM, we presented an approach for the adaptation of 2D GIS road objects to airborne laser scanning (ALS) data using active contours (snakes) in (Göpfert et al., 2011). In this paper the algorithm is modified for the integration of stereo images as an alternative data source for area-wide height information. For that reason, a new image energy is developed that exploits geometric and radiometric features derived from the image data. Afterwards, we compare the applicability of our method with respect to the ALS data and stereo images as input. In addition, a new approach is suggested that analyses the different energy terms of active contours after the optimisation process in order to automatically detect contour parts that did not reach a suitable position in the sensor data. This concept of an internal evaluation is able to guide the user during post processing. Experiments show that the snake approach with an image energy based on stereo images is generally able to adapt GIS road centrelines to the sensor data and thus to improve the quality of the 2D vector data. However, the comparison to the results for ALS data demonstrates that the algorithm perform slightly worse for image data in the high precision level.

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Extraction of City Roads Through Shadow Path Reconstruction Using Laser Data

Cited by 32 publications

References 5 publications

Frequent Unscheduled Updates of the National Base Map Using the Land-Based Mobile Mapping System

Frequent Unscheduled Updates of the National Base Map Using the Land-Based Mobile Mapping System

Multi-source remote sensing data fusion: status and trends

Network Snakes for Adapting Gis Roads to Height Data of Different Data Sources – Performance Analysis Using Als Data and Stereo Images

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