Automated Techniques for Change Detection Using Combined Edge Segment Texture Analysis, GIS, and 3D Information

2014 ◽  
pp. 325-352 ◽  
Author(s):  
Manfred Ehlers ◽  
Natalia Sofina ◽  
Yevgeniya Filippovska ◽  
Martin Kada
Keyword(s):  
Change Detection ◽  
Texture Analysis ◽  
Edge Segment ◽  
3D Information

scholarly journals AUTOMATIC BUILDING CHANGE DETECTION USING MULTI-TEMPORAL AIRBORNE LIDAR DATA

2020 ◽  
Vol XLII-3/W12-2020 ◽  
pp. 19-24
Author(s):  
R. C. dos Santos ◽  
M. Galo ◽  
A. C. Carrilho ◽  
G. G. Pessoa ◽  
R. A. R. de Oliveira
Keyword(s):  
Change Detection ◽  
Average Density ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Qualitative And Quantitative ◽  
Multi Temporal ◽  
Quantitative Analyses ◽  
3D Information ◽  
Airborne Lidar Data ◽  
Area Monitoring

Abstract. The automatic detection of building changes is an essential process for urban area monitoring, urban planning, and database update. In this context, 3D information derived from multi-temporal airborne LiDAR scanning is one effective alternative. Despite several works in the literature, the separation of change areas in building and non-building remains a challenge. In this sense, it is proposed a new method for building change detection, having as the main contribution the use of height entropy concept to identify the building change areas. The experiments were performed considering multi-temporal airborne LiDAR data from 2012 and 2014, both with average density around 5 points/m2. Qualitative and quantitative analyses indicate that the proposed method is robust in building change detection, having the potential to identify small changes (larger than 20 m2). In general, the change detection method presented average completeness and correctness around 97% and 71%, respectively.

scholarly journals 2D vs. 3D Change Detection Using Aerial Imagery to Support Crisis Management of Large-Scale Events

2018 ◽  
Vol 10 (12) ◽  
pp. 2054 ◽  
Author(s):  
Veronika Gstaiger ◽  
Jiaojiao Tian ◽  
Ralph Kiefl ◽  
Franz Kurz
Keyword(s):  
Change Detection ◽  
Crisis Management ◽  
Large Scale ◽  
Three Dimensional ◽  
Aerial Imagery ◽  
Added Value ◽  
Detection Methods ◽  
Protestant Church ◽  
Existing Structures ◽  
3D Information

Large-scale events represent a special challenge for crisis management. To ensure that participants can enjoy an event safely and carefree, it must be comprehensively prepared and attentively monitored. Remote sensing can provide valuable information to identify potential risks and take appropriate measures in order to prevent a disaster, or initiate emergency aid measures as quickly as possible in the event of an emergency. Especially, three-dimensional (3D) information that is derived using photogrammetry can be used to analyze the terrain and map existing structures that are set up at short notice. Using aerial imagery acquired during a German music festival in 2016 and the celebration of the German Protestant Church Assembly of 2017, the authors compare two-dimensional (2D) and novel fusion-based 3D change detection methods, and discuss their suitability for supporting large-scale events during the relevant phases of crisis management. This study serves to find out what added value the use of 3D change information can provide for on-site crisis management. Based on the results, an operational, fully automatic processor for crisis management operations and corresponding products for end users can be developed.

scholarly journals 3D-information fusion from very high resolution satellite sensors

2015 ◽  
Vol XL-7/W3 ◽  
pp. 651-656 ◽  
Author(s):  
T. Krauss ◽  
P. d'Angelo ◽  
G. Kuschk ◽  
J. Tian ◽  
T. Partovi
Keyword(s):  
High Resolution ◽  
Change Detection ◽  
Information Fusion ◽  
Renewable Energy Sources ◽  
Open Pit ◽  
Open Pit Mining ◽  
Surface Model ◽  
Digital Terrain ◽  
3D Information ◽  
Very High

In this paper we show the pre-processing and potential for environmental applications of very high resolution (VHR) satellite stereo imagery like these from WorldView-2 or Pl´eiades with ground sampling distances (GSD) of half a metre to a metre. To process such data first a dense digital surface model (DSM) has to be generated. Afterwards from this a digital terrain model (DTM) representing the ground and a so called normalized digital elevation model (nDEM) representing off-ground objects are derived. Combining these elevation based data with a spectral classification allows detection and extraction of objects from the satellite scenes. Beside the object extraction also the DSM and DTM can directly be used for simulation and monitoring of environmental issues. Examples are the simulation of floodings, building-volume and people estimation, simulation of noise from roads, wave-propagation for cellphones, wind and light for estimating renewable energy sources, 3D change detection, earthquake preparedness and crisis relief, urban development and sprawl of informal settlements and much more. Also outside of urban areas volume information brings literally a new dimension to earth oberservation tasks like the volume estimations of forests and illegal logging, volume of (illegal) open pit mining activities, estimation of flooding or tsunami risks, dike planning, etc. In this paper we present the preprocessing from the original level-1 satellite data to digital surface models (DSMs), corresponding VHR ortho images and derived digital terrain models (DTMs). From these components we present how a monitoring and decision fusion based 3D change detection can be realized by using different acquisitions. The results are analyzed and assessed to derive quality parameters for the presented method. Finally the usability of 3D information fusion from VHR satellite imagery is discussed and evaluated.

scholarly journals Combined Edge Segment Texture Analysis for the Detection of Damaged Buildings in Crisis Areas

2012 ◽  
Vol 5 (4) ◽  
pp. 1118-1128 ◽  
Author(s):  
S. Klonus ◽  
D. Tomowski ◽  
Manfred Ehlers ◽  
Peter Reinartz ◽  
Ulrich Michel
Keyword(s):  
Texture Analysis ◽  
Edge Segment
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