Details
| Original language | English |
|---|---|
| Journal | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives |
| Volume | 35 |
| Publication status | Published - 2004 |
| Event | 20th ISPRS Congress on Technical Commission VII - Istanbul, Turkey Duration: 12 Jul 2004 → 23 Jul 2004 |
Abstract
The automated interpretation of aerial image data is a task with increasing significance for several applications, e.g. quality control and automatic updating of GIS data, automatic land use change detection, measurement of sealed areas for public authority uses, monitoring of land erosion etc. The use of additional sensors could improve the performance of the automated classification; however, because of additional costs or simple unavailability of data, this approach should be avoided. One possibility to stabilize an automatic image analysis is using remote sensing data of the same region of different dates that is often existing. This paper presents a method how a monotemporal knowledge representation can be expanded by a temporal component to take advantage of previous classifications of the same scene and knowledge about the time dependency of the object classes. The present approach proposes the combination of a semantic network, representing the generic description of the scene, and a state transition diagram, modeling the possible state transitions for each one of the classes of interest. The probabilities of the state transition diagram are introduced as a priori knowledge in a statistical classification procedure. Experimental results from a series of three aerial images from 1983 up to 2001 of a suburban region near Hannover are shown in order to illustrate the potential of the proposed multitemporal approach.
Keywords
- Aerial, Classification, Knowledge base, Land use, Multitemporal, Urban
ASJC Scopus subject areas
- Computer Science(all)
- Information Systems
- Social Sciences(all)
- Geography, Planning and Development
Sustainable Development Goals
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In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, Vol. 35, 2004.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - Multitemporal interpretation of remote sensing data
AU - Müller, Sönke
AU - Mota, Guilherme Lucio Abelha
AU - Liedtke, Claus Eberhard
N1 - Publisher Copyright: © 2004 International Society for Photogrammetry and Remote Sensing. All rights reserved.
PY - 2004
Y1 - 2004
N2 - The automated interpretation of aerial image data is a task with increasing significance for several applications, e.g. quality control and automatic updating of GIS data, automatic land use change detection, measurement of sealed areas for public authority uses, monitoring of land erosion etc. The use of additional sensors could improve the performance of the automated classification; however, because of additional costs or simple unavailability of data, this approach should be avoided. One possibility to stabilize an automatic image analysis is using remote sensing data of the same region of different dates that is often existing. This paper presents a method how a monotemporal knowledge representation can be expanded by a temporal component to take advantage of previous classifications of the same scene and knowledge about the time dependency of the object classes. The present approach proposes the combination of a semantic network, representing the generic description of the scene, and a state transition diagram, modeling the possible state transitions for each one of the classes of interest. The probabilities of the state transition diagram are introduced as a priori knowledge in a statistical classification procedure. Experimental results from a series of three aerial images from 1983 up to 2001 of a suburban region near Hannover are shown in order to illustrate the potential of the proposed multitemporal approach.
AB - The automated interpretation of aerial image data is a task with increasing significance for several applications, e.g. quality control and automatic updating of GIS data, automatic land use change detection, measurement of sealed areas for public authority uses, monitoring of land erosion etc. The use of additional sensors could improve the performance of the automated classification; however, because of additional costs or simple unavailability of data, this approach should be avoided. One possibility to stabilize an automatic image analysis is using remote sensing data of the same region of different dates that is often existing. This paper presents a method how a monotemporal knowledge representation can be expanded by a temporal component to take advantage of previous classifications of the same scene and knowledge about the time dependency of the object classes. The present approach proposes the combination of a semantic network, representing the generic description of the scene, and a state transition diagram, modeling the possible state transitions for each one of the classes of interest. The probabilities of the state transition diagram are introduced as a priori knowledge in a statistical classification procedure. Experimental results from a series of three aerial images from 1983 up to 2001 of a suburban region near Hannover are shown in order to illustrate the potential of the proposed multitemporal approach.
KW - Aerial
KW - Classification
KW - Knowledge base
KW - Land use
KW - Multitemporal
KW - Urban
UR - http://www.scopus.com/inward/record.url?scp=85044519287&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:85044519287
VL - 35
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 - 20th ISPRS Congress on Technical Commission VII
Y2 - 12 July 2004 through 23 July 2004
ER -