Identifying damaged buildings from high-resolution satellite imagery in hazardous areas using morphological operators

Parape, Chandana Dinesh; Tamura, Masayuki

doi:10.1109/igarss.2011.6049495

Cited by 5 publications

(2 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The DMP was developed by feature detectors attempts to identify urban structures and it is constructed using morphological opening and closing by reconstruction operators IJDRBE 4,2 (Aytekin et al, 2009;Destival, 1986;Heijmans and Roerdink, 1998;Laporterie et al, 2001;Parape and Tamura, 2011). Mathematical morphology employs a set of image operators to extract and analyze image components based on shape and size of quasi-homogeneous regions in the image, has been used to a wide area of image processing field such as pre-processing, noise filtering, shape and target detection, segmentation, decomposition and pattern recognition (Pesaresi and Benediktsson, 2001;Soille, 2003;Shackelford and Davis, 2004).…”

Section: Differential Morphological Profilementioning

confidence: 99%

Detecting and assessment of tsunami building damage using high‐resolution satellite images with GIS data

Dinesh

Bari

Dissanayake

et al. 2013

International Journal of Disaster Resilience in the Built Environment

View full text Add to dashboard Cite

Purpose -The purpose of this paper is to present a method and results of evaluating damaged building extraction using an object recognition task in pre-and post-tsunami event. The advantage of remote sensing and its applications made it possible to extract damaged building images and vulnerability easement of wide urban areas due to natural disasters. Design/methodology/approach -The proposed approach involves several advanced morphological operators, among which are adaptive transforms with varying size, shape and grey level of the structuring elements. IKONOS-2 satellite images consisting of pre-and post-2004 Indian Ocean Tsunami site of the Kalmunai area on the East coast of Sri Lanka were used. Morphological operation using structural element are applied for segmented images, then extracted remaining building foot print using random forest classification method. This work extended further the road lines extraction using Hough transform. Findings -The result was investigated using geographic information system (GIS) data and global positioning system (GPS) ground survey in the field and it appeared to have high accuracy: the confidence measures produced of a completely destroyed structure give 86 percent by object-based, respectively, after the tsunami in one segment of Maruthamune GN Division. Research limitations/implications -This study has also identified significant limitations, due to the resolution and clearness of satellite images and vegetation canopy over the building footprint. Originality/value -The authors develop an automated method to detect damaged buildings and compare the results with GIS-based ground survey.

show abstract

Section: Differential Morphological Profilementioning

confidence: 99%

Detecting and assessment of tsunami building damage using high‐resolution satellite images with GIS data

Dinesh

Bari

Dissanayake

et al. 2013

International Journal of Disaster Resilience in the Built Environment

View full text Add to dashboard Cite

show abstract

“…The vast volume of data and reaching to conclusions in analysis of this data is a challenging task. However, the availability of high spatial resolution data offers the opportunity to visually recognize features such as vehicles, built up areas, roads, vegetation and any other object of interest [3] with ease. It is understood that the information vital to carry out a successful analysis comes as an input from human efforts as an interpretation of the satellite imagery.…”

mentioning

confidence: 99%

Object identification and classification in a high resolution satellite data using data mining techniques for knowledge extraction

Mantrawadi

Nijim

Lee

2013

2013 IEEE International Systems Conference (SysCon)

View full text Add to dashboard Cite

A mark improvement in spatial technology has happened over the last decade.Classification of objects, detection of change and interpretation of information from high resolution satellite imagery can only be carried out by human interpretation and using specialized tools capable of evaluating pixel level details.In this thesis, spatial information is stored using data mining. Automated classification and identification of objects are archived based on historical data set.Any object can be defined by three primary element color, shape and size. Secondary parameters such as texture, shadow and association help in increasing accuracy.

show abstract

A Review on Multi‐temporal Earthquake Damage Assessment Using Satellite Images

Taşkın

Erten

Alataş

2021

Change Detection and Image Time Series Analysis 2

View full text Add to dashboard Cite

Identifying damaged buildings from high-resolution satellite imagery in hazardous areas using morphological operators

Cited by 5 publications

References 8 publications

Detecting and assessment of tsunami building damage using high‐resolution satellite images with GIS data

Detecting and assessment of tsunami building damage using high‐resolution satellite images with GIS data

Object identification and classification in a high resolution satellite data using data mining techniques for knowledge extraction

A Review on Multi‐temporal Earthquake Damage Assessment Using Satellite Images

Contact Info

Product

Resources

About