Updating topographic mapping in Great Britain using imagery from high-resolution satellite sensors

Holland, David A.; Boyd, Doreen S.; Marshall, Paul

doi:10.1016/j.isprsjprs.2006.02.002

Cited by 67 publications

(36 citation statements)

References 4 publications

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“…Holland and Marshall (2004) and Holland et al (2006) conducted a qualitative evaluation of the potential of QuickBird imagery for updating topographic maps in Great Britain, concluding that the imagery can be used as source of some feature types at scales up to 1:6000 and should be used in a supplementary way to conventional data sources. Gianinetto (2008) tested roads and buildings extracted from pansharpened QuickBird imagery for updating large-scale topographic databases of urban areas, considering mapping specifications of the Lombardia Region.…”

Section: Introductionmentioning

confidence: 99%

Introducing mapping standards in the quality assessment of buildings extracted from very high resolution satellite imagery

Freire

Santos

Navarro

et al. 2014

ISPRS Journal of Photogrammetry and Remote Sensing

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a b s t r a c tMany municipal activities require updated large-scale maps that include both topographic and thematic information. For this purpose, the efficient use of very high spatial resolution (VHR) satellite imagery suggests the development of approaches that enable a timely discrimination, counting and delineation of urban elements according to legal technical specifications and quality standards. Therefore, the nature of this data source and expanding range of applications calls for objective methods and quantitative metrics to assess the quality of the extracted information which go beyond traditional thematic accuracy alone. The present work concerns the development and testing of a new approach for using technical mapping standards in the quality assessment of buildings automatically extracted from VHR satellite imagery. Feature extraction software was employed to map buildings present in a pansharpened QuickBird image of Lisbon. Quality assessment was exhaustive and involved comparisons of extracted features against a reference data set, introducing cartographic constraints from scales 1:1000, 1:5000, and 1:10,000. The spatial data quality elements subject to evaluation were: thematic (attribute) accuracy, completeness, and geometric quality assessed based on planimetric deviation from the reference map. Tests were developed and metrics analyzed considering thresholds and standards for the large mapping scales most frequently used by municipalities. Results show that values for completeness varied with mapping scales and were only slightly superior for scale 1:10,000. Concerning the geometric quality, a large percentage of extracted features met the strict topographic standards of planimetric deviation for scale 1:10,000, while no buildings were compliant with the specification for scale 1:1000. Ó

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Section: Introductionmentioning

confidence: 99%

Introducing mapping standards in the quality assessment of buildings extracted from very high resolution satellite imagery

Freire

Santos

Navarro

et al. 2014

ISPRS Journal of Photogrammetry and Remote Sensing

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“…The detailed form of A is presented as: (10) where all of the parameters a 10 ∼ a 19 , a 20 ∼ a 29 in matrix A and c 1i , c 2i in matrix C are the partial derivatives of the corresponding parameters in Equation (3). …”

Section: Overall Adjustment Of Rigorous Lbtmmentioning

confidence: 99%

“…High Resolution Satellite Imagery (HRSIs) has high spatial, radiometric and temporal resolution. It can supply accurate and abundant information of the Earth's surface [1,2] and has been an important data source for accurate mapping at large scales (up to 1:10,000) and map updating (up to 1:5000) [3]. Thus, the geometric rectification technology of HRSIs needs improvement to fit more various and higher precision demands in actual applications.…”

Section: Introductionmentioning

confidence: 99%

Rigorous Line-Based Transformation Model Using the Generalized Point Strategy for the Rectification of High Resolution Satellite Imagery

Shi

2016

Remote Sensing

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Abstract:High precision geometric rectification of High Resolution Satellite Imagery (HRSI) is the basis of digital mapping and Three-Dimensional (3D) modeling. Taking advantage of line features as basic geometric control conditions instead of control points, the Line-Based Transformation Model (LBTM) provides a practical and efficient way of image rectification. It is competent to build the mathematical relationship between image space and the corresponding object space accurately, while it reduces the workloads of ground control and feature recognition dramatically. Based on generalization and the analysis of existing LBTMs, a novel rigorous LBTM is proposed in this paper, which can further eliminate the geometric deformation caused by sensor inclination and terrain variation. This improved nonlinear LBTM is constructed based on a generalized point strategy and resolved by least squares overall adjustment. Geo-positioning accuracy experiments with IKONOS, GeoEye-1 and ZiYuan-3 satellite imagery are performed to compare rigorous LBTM with other relevant line-based and point-based transformation models. Both theoretic analysis and experimental results demonstrate that the rigorous LBTM is more accurate and reliable without adding extra ground control. The geo-positioning accuracy of satellite imagery rectified by rigorous LBTM can reach about one pixel with eight control lines and can be further improved by optimizing the horizontal and vertical distribution of control lines.

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“…Geodatabases have a large information potential. Geometry, meaning of objects and contextual relations between them are important for change detection analysis in very complex environments (Baltsavias, 2004;Holland et al, 2006). Recent studies are based on the combination of different data sources (such as ALS point clouds, aerial images and existing building information) and a prior knowledge (Bouziani et al, 2010;Chen et al, 2012).…”

Section: Previous Studiesmentioning

confidence: 99%

Use of Aerial Images for Regular Updates of Buildings in the Fundamental Base of Geographic Data of the Czech Republic

Hron

Halounová

2015

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

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ABSTRACT:Digital aerial images (DAI) include position, elevation and also spectral information (visible bands and near-infrared band) about the captured area. The aim of this paper is to present the possibilities of automatic analysis of DAI for updating of the Fundamental Base of Geographic Data of the Czech Republic with a focus on buildings. Regular updates of buildings (automatic detection of new and demolished buildings) are based on the analysis of coloured point clouds created by an automatic image matching technique from each time period. The created approach compares point clouds from different time periods to each other. The advantage of this solution is that it is independent of the manner of keeping the buildings in the database. It does not matter whether the buildings in the database have correct positions and their footprints correspond to the roof shapes or external walls. The involved method is robust because a digital surface model generated by image matching techniques can contain numerous errors. Shaded areas and objects with blurred textures are problematic for automatic image correlation algorithms and lead to false results. For this reason, derived layers containing additional information are used. Shadow masks (layers with modelled shadows) are used for the verification of indications and to filter out errors in the shaded areas using a contextual evaluation. Furthermore, additional information about the road and railway networks and morphological operations of opening and closing were used to achieve more accurate results. All these information sources are then evaluated using decision logic, which uses the generally applicable rules that are available for different datasets without the need for modification. The method was tested on different datasets with various types of buildings (villages, suburbs and city centres) which cover more than 20 square kilometres. The developed solution leads to very promising results without the need of acquiring new data.* Corresponding author. This is useful to know for communication with the appropriate person in cases with more than one author.

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Updating topographic mapping in Great Britain using imagery from high-resolution satellite sensors

Cited by 67 publications

References 4 publications

Introducing mapping standards in the quality assessment of buildings extracted from very high resolution satellite imagery

Introducing mapping standards in the quality assessment of buildings extracted from very high resolution satellite imagery

Rigorous Line-Based Transformation Model Using the Generalized Point Strategy for the Rectification of High Resolution Satellite Imagery

Use of Aerial Images for Regular Updates of Buildings in the Fundamental Base of Geographic Data of the Czech Republic

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