TY - JOUR

T1 - Graph-supported verification of road databases

AU - Gerke, Markus

AU - Butenuth, Matthias

AU - Heipke, Christian

AU - Willrich, Felicitas

N1 - Funding Information: Part of this work was funded by the BKG; the test data was provided by the Hessische Landesvermessungsamt. We would like to thank the Chair of Photogrammetry and Remote Sensing at TU Munich, especially C. Wiedemann, for the support in using his road extraction software. We would also like to thank Marcel Ziems for his work regarding the evaluation of the system.

PY - 2004/1

Y1 - 2004/1

N2 - The verification of existing data is an important task in order to ensure a high level of data quality, such as is needed in geographic information systems (GIS). Today, this work is carried out manually by an operator, who compares vector data from databases with remotely sensed imagery. In this paper, a system for automated road data verification using digital image processing for the extraction of roads from aerial imagery and topological analysis in order to optimise the whole process in terms of reliability and efficiency is presented. The main goal is to call the operator's attention only to parts of the network, where the automated process did not find sufficient evidence of a road. The road extraction is supported by the use of prior knowledge on the global level (whether the road is situated in rural, urban or forest areas), and information on the road geometry and its attributes. The road extraction is executed twice. Firstly, with a strict parameter control ensuring the minimization of false positives and a subsequent evaluation, which denotes roads from the database being accepted or rejected. In a second step, a graph-based search algorithm detects connections, which are missing for an optimised road network. If rejected roads are part of these connections, they are checked again using a more tolerant parameter control. A detailed performance analysis of results shows the applicability of the proposed method for quality control of topographic road databases.

AB - The verification of existing data is an important task in order to ensure a high level of data quality, such as is needed in geographic information systems (GIS). Today, this work is carried out manually by an operator, who compares vector data from databases with remotely sensed imagery. In this paper, a system for automated road data verification using digital image processing for the extraction of roads from aerial imagery and topological analysis in order to optimise the whole process in terms of reliability and efficiency is presented. The main goal is to call the operator's attention only to parts of the network, where the automated process did not find sufficient evidence of a road. The road extraction is supported by the use of prior knowledge on the global level (whether the road is situated in rural, urban or forest areas), and information on the road geometry and its attributes. The road extraction is executed twice. Firstly, with a strict parameter control ensuring the minimization of false positives and a subsequent evaluation, which denotes roads from the database being accepted or rejected. In a second step, a graph-based search algorithm detects connections, which are missing for an optimised road network. If rejected roads are part of these connections, they are checked again using a more tolerant parameter control. A detailed performance analysis of results shows the applicability of the proposed method for quality control of topographic road databases.

KW - Database verification

KW - GIS

KW - Knowledge-based image analysis

KW - Parameter settings

KW - Performance analysis

KW - Quality control

KW - Reliability

KW - Road network extraction

UR - http://www.scopus.com/inward/record.url?scp=1642528365&partnerID=8YFLogxK

U2 - 10.1016/j.isprsjprs.2003.09.003

DO - 10.1016/j.isprsjprs.2003.09.003

M3 - Article

AN - SCOPUS:1642528365

VL - 58

SP - 152

EP - 165

JO - ISPRS Journal of Photogrammetry and Remote Sensing

JF - ISPRS Journal of Photogrammetry and Remote Sensing

SN - 0924-2716

IS - 3-4

ER -