Details
| Original language | English |
|---|---|
| Pages (from-to) | 54-59 |
| Number of pages | 6 |
| Journal | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives |
| Volume | 36 |
| Publication status | Published - 2005 |
| Event | 2005 ISPRS Workshop Laser Scanning 2005 - Enschede, Netherlands Duration: 12 Sept 2005 → 14 Sept 2005 |
Abstract
The paper concerns the generalization of DTM extracted from LiDAR data. The essence of generalization is reducing details while enhancing important features at the same time; so for the purpose of terrain surface visualization special attention has to be given to the enhancement and generalization of topographic objects like dams, roads etc. The focus of this work is laid on the extraction of road objects and their contribution into the enhancement of the generalized terrain model. An algorithm for the extraction of roads is developed and is followed by a generalization algorithm that weights together road networks and filtered LiDAR point clouds. Following the presentation of the algorithm results for this approach are shown and evaluated.
Keywords
- DTM, Extraction, Generalization, High Resolution, LiDAR, Representation, Road detection
ASJC Scopus subject areas
- Computer Science(all)
- Information Systems
- Social Sciences(all)
- Geography, Planning and Development
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In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, Vol. 36, 2005, p. 54-59.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - Dense DTM generalization aided by roads extracted from LiDAR data
AU - Abo Akel, Nizar
AU - Kremeike, Katrin
AU - Filin, Sagi
AU - Sester, Monika
AU - Doytsher, Yerach
N1 - Funding information: The research was funded by the Deutsche Technion Gesellschaft e.V.
PY - 2005
Y1 - 2005
N2 - The paper concerns the generalization of DTM extracted from LiDAR data. The essence of generalization is reducing details while enhancing important features at the same time; so for the purpose of terrain surface visualization special attention has to be given to the enhancement and generalization of topographic objects like dams, roads etc. The focus of this work is laid on the extraction of road objects and their contribution into the enhancement of the generalized terrain model. An algorithm for the extraction of roads is developed and is followed by a generalization algorithm that weights together road networks and filtered LiDAR point clouds. Following the presentation of the algorithm results for this approach are shown and evaluated.
AB - The paper concerns the generalization of DTM extracted from LiDAR data. The essence of generalization is reducing details while enhancing important features at the same time; so for the purpose of terrain surface visualization special attention has to be given to the enhancement and generalization of topographic objects like dams, roads etc. The focus of this work is laid on the extraction of road objects and their contribution into the enhancement of the generalized terrain model. An algorithm for the extraction of roads is developed and is followed by a generalization algorithm that weights together road networks and filtered LiDAR point clouds. Following the presentation of the algorithm results for this approach are shown and evaluated.
KW - DTM
KW - Extraction
KW - Generalization
KW - High Resolution
KW - LiDAR
KW - Representation
KW - Road detection
UR - http://www.scopus.com/inward/record.url?scp=84864501686&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:84864501686
VL - 36
SP - 54
EP - 59
JO - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
JF - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
SN - 1682-1750
T2 - 2005 ISPRS Workshop Laser Scanning 2005
Y2 - 12 September 2005 through 14 September 2005
ER -