Automated Correction and Updating of Road Databases from High-Resolution Imagery

Fortier, Maxandre; Ziou, Djemel; Armenakis, Costas; Wang, S.

doi:10.1080/07038992.2001.10854922

Cited by 31 publications

(17 citation statements)

References 8 publications

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“…Some of the approaches include object extraction using 'snakes' (Klang 1998, Fortier et al 2001, map matching (Maillard and Cavayas 1989), and artificial neural networks (ANNs) (Fiset et al 1998). Updating GIS road layers with semi-automated image-based procedures is still in a premature stage of development and there appear to be no existing methods for reliable, operational use.…”

Section: Updating Gis Feature Databasesmentioning

confidence: 99%

Monitoring cross-border trails using airborne digital multispectral imagery and interactive image analysis techniques

Cao

Stow

Kaiser

et al. 2007

Geocarto International

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The objective of this study was to evaluate image-based procedures for monitoring cross-border foot trails in the US-Mexico border zone in eastern San Diego County using airborne remote sensing techniques. Specifically, digital multi-spectral and multi-temporal imagery from an airborne digital multi-spectral imaging system, digital image processing, and visual image analysis techniques were explored in the context of detecting and delineating new trail features and updating trail GIS layers. Three trail updating approaches: map-to-image (M-I) overlay, map and image-to-image (M/I-I) differencing, map and image-to-image (M/I-I) swiping and two types of spectral transform, PCA and NDVI, were tested and compared. The M-I overlay was found to be the most reliable trail updating approach. The optimal image enhancement method for the M-I overlay approach varied with vegetation structure. PCA imagery yielded better results than NDVI imagery in a highly disturbed area and NDVI imagery performed better in a densely vegetated area. The M/I-I swiping approach was useful for distinguishing misregistered extant trails from new trail features.

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Section: Updating Gis Feature Databasesmentioning

confidence: 99%

Monitoring cross-border trails using airborne digital multispectral imagery and interactive image analysis techniques

Cao

Stow

Kaiser

et al. 2007

Geocarto International

View full text Add to dashboard Cite

show abstract

“…Finally, a comparison of the extraction result and the corresponding database object provides the human operator with a number of potential objects for the updating process. The system was extended in relation to the task of the National Topographic Database of Geomatics Canada (Fortier et al 2001). Another relevant project in our context is the Automated reconstruction of Topographic Objects from aerial stereo images using Map Information (ATOMI) of Switzerland (Zhang, 2004).…”

Section: Related Workmentioning

confidence: 99%

Multiple-Model Based Update of Belgian Reference Road Data

Ziems

Beyen²,

Mueller

et al. 2012

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:This paper describes a semi-automatic system for road update based on high resolution orthophotos and 3D surface models. Potential update regions are identified by an object-wise verification of all existing database records, followed by a scene-wide detection of redevelopment regions. The proposed system combines several road detection and road verification approaches from current literature to form a more general solution. Each road detection / verification approach is realized as an independent module representing a unique road model combined with a corresponding processing strategy. The object-wise verification result of each module is formulated as a binary decision between the classes "correct road" and "incorrect road". These individual decisions are combined by Dempster-Shafer fusion, which provides tools for dealing with uncertain and incomplete knowledge about the statistical properties of the data. For each road detection / verification module a confidence function for the result is introduced that reflects the degree of correspondence of an actual test situation with an optimal situation according to the underlying road model of that module. Experimental results achieved with data from the national Belgian road database in a test site of about 134 km² demonstrate the potential of the method.

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“…Finally, a comparison of the extraction result and the corresponding database object provides the human editor with a number of potential objects for the updating process. The system was extended for updating the National Topographic Database of Geomatics Canada (Fortier et al 2001). Zhang (2004) uses aerial stereo imagery to extract a complete road network by introducing information from an existing database, e.g.…”

Section: Introductionmentioning

confidence: 99%

Multiple-Model Based Verification of Road Data

Ziems

Breitkopf

Heipke

et al. 2012

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

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ABSTRACT:This paper describes a semi-automatic system for road verification based on high resolution imagery and 3D surface models. Potential update regions are identified by an object-wise verification of all existing database records. The proposed system combines several road detection and road verification approaches from current literature to form a more general solution. Each road detection / verification approach is realized as an independent module representing a unique road model combined with a corresponding processing strategy. The object-wise verification result of each module is formulated as a binary decision between the classes "correct road" and "incorrect road". These individual decisions are combined by Dempster-Shafer fusion, which provides tools for dealing with uncertain and incomplete knowledge about the statistical properties of the data. For each road detection / verification module a confidence function for the result is introduced that reflects the degree of correspondence of an actual test situation with an optimal situation according to the underlying road model of that module. A comparison with results from an EuroSDR test on road extraction demonstrate the strengths and limitations of the method.

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Automated Correction and Updating of Road Databases from High-Resolution Imagery

Cited by 31 publications

References 8 publications

Monitoring cross-border trails using airborne digital multispectral imagery and interactive image analysis techniques

Monitoring cross-border trails using airborne digital multispectral imagery and interactive image analysis techniques

Multiple-Model Based Update of Belgian Reference Road Data

Multiple-Model Based Verification of Road Data

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