Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 13-18 |
| Seitenumfang | 6 |
| Fachzeitschrift | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Jahrgang | 1 |
| Publikationsstatus | Veröffentlicht - 16 Juli 2012 |
| Veranstaltung | 22nd Congress of the International Society for Photogrammetry and Remote Sensing: Imaging a Sustainable Future, ISPRS 2012 - Melbourne, Australien Dauer: 25 Aug. 2012 → 1 Sept. 2012 |
Abstract
Comparison of geospatial databases presenting similar spatial extent might show substantial differences. This is the consequence of different factors, such as: accuracy, scale, data collection and processing methods, level-of-detail, data models – to name a few. The differences are reflected in the geometric structure of objects, location, topology and the accompanying information. Geometric discrepancies are emerging, and sometimes even contradictions exist between the various data sources. Thus, the demand for processes that enable alignment of different data sources while maintaining spatial consistency is growing. Global solution strategies, such as an affine transformation, are incomplete solutions since discrepancies are still likely to exist due to the inability of such a global solution to account for the remaining errors due to local distortions. In order to account for the resulting random distortions, e.g., geometric conflicts, a localized geometric alignment process is implemented in this research. During this process the distortions (deviations) are quantified locally via sets of specifically selected observation constraints, to assure the spatial consistency of the vector data. This strategy exploits local spatial topologic and geometric relationships between corresponding line-features prior to the implementation of Least Squares Adjustment for the alignment, and observes local distortions and ambiguities that might exist. The outcome presents a significant improvement of the initial state by resolving local geometric distortions and discrepancies, suggesting a reliable solution for the problem on a statistically sound basis.
ASJC Scopus Sachgebiete
- Erdkunde und Planetologie (insg.)
- Erdkunde und Planetologie (sonstige)
- Umweltwissenschaften (insg.)
- Umweltwissenschaften (sonstige)
- Physik und Astronomie (insg.)
- Instrumentierung
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in: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Jahrgang 1, 16.07.2012, S. 13-18.
Publikation: Beitrag in Fachzeitschrift › Konferenzaufsatz in Fachzeitschrift › Forschung › Peer-Review
}
TY - JOUR
T1 - GEOMETRICAL ADJUSTMENT TOWARDS the ALIGNMENT of VECTOR DATABASES
AU - Dalyot, Sagi
AU - Dahinden, Tobias
AU - Schulze, Malte Jan
AU - Boljen, Joachim
AU - Sester, Monika
PY - 2012/7/16
Y1 - 2012/7/16
N2 - Comparison of geospatial databases presenting similar spatial extent might show substantial differences. This is the consequence of different factors, such as: accuracy, scale, data collection and processing methods, level-of-detail, data models – to name a few. The differences are reflected in the geometric structure of objects, location, topology and the accompanying information. Geometric discrepancies are emerging, and sometimes even contradictions exist between the various data sources. Thus, the demand for processes that enable alignment of different data sources while maintaining spatial consistency is growing. Global solution strategies, such as an affine transformation, are incomplete solutions since discrepancies are still likely to exist due to the inability of such a global solution to account for the remaining errors due to local distortions. In order to account for the resulting random distortions, e.g., geometric conflicts, a localized geometric alignment process is implemented in this research. During this process the distortions (deviations) are quantified locally via sets of specifically selected observation constraints, to assure the spatial consistency of the vector data. This strategy exploits local spatial topologic and geometric relationships between corresponding line-features prior to the implementation of Least Squares Adjustment for the alignment, and observes local distortions and ambiguities that might exist. The outcome presents a significant improvement of the initial state by resolving local geometric distortions and discrepancies, suggesting a reliable solution for the problem on a statistically sound basis.
AB - Comparison of geospatial databases presenting similar spatial extent might show substantial differences. This is the consequence of different factors, such as: accuracy, scale, data collection and processing methods, level-of-detail, data models – to name a few. The differences are reflected in the geometric structure of objects, location, topology and the accompanying information. Geometric discrepancies are emerging, and sometimes even contradictions exist between the various data sources. Thus, the demand for processes that enable alignment of different data sources while maintaining spatial consistency is growing. Global solution strategies, such as an affine transformation, are incomplete solutions since discrepancies are still likely to exist due to the inability of such a global solution to account for the remaining errors due to local distortions. In order to account for the resulting random distortions, e.g., geometric conflicts, a localized geometric alignment process is implemented in this research. During this process the distortions (deviations) are quantified locally via sets of specifically selected observation constraints, to assure the spatial consistency of the vector data. This strategy exploits local spatial topologic and geometric relationships between corresponding line-features prior to the implementation of Least Squares Adjustment for the alignment, and observes local distortions and ambiguities that might exist. The outcome presents a significant improvement of the initial state by resolving local geometric distortions and discrepancies, suggesting a reliable solution for the problem on a statistically sound basis.
KW - Adjustment
KW - Algorithms
KW - Automation
KW - Cartography
KW - Databases
KW - Geometry
KW - GIS
KW - Matching
UR - http://www.scopus.com/inward/record.url?scp=84874285346&partnerID=8YFLogxK
U2 - 10.5194/isprsannals-I-4-13-2012
DO - 10.5194/isprsannals-I-4-13-2012
M3 - Conference article
AN - SCOPUS:84874285346
VL - 1
SP - 13
EP - 18
JO - ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
JF - ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
SN - 2194-9042
T2 - 22nd Congress of the International Society for Photogrammetry and Remote Sensing: Imaging a Sustainable Future, ISPRS 2012
Y2 - 25 August 2012 through 1 September 2012
ER -