Visual Damage Assessment using High-Resolution Satellite Images following the 2003 Bam, Iran, Earthquake

2005 ◽  
Vol 21 (1_suppl) ◽  
pp. 309-318 ◽  
Author(s):  
Keiko Saito ◽  
Robin Spence ◽  
Terence A. de C Foley
Keyword(s):  
High Resolution ◽  
Damage Assessment ◽  
Satellite Images ◽  
Building Damage ◽  
Absolute Difference ◽  
Visual Interpretation ◽  
Damage Distribution ◽  
Visual Damage ◽  
High Resolution Satellite Images ◽  
Damage Map

Visual interpretation of the building damage distribution in Bam, Iran, caused by the earthquake on 26 December 2003 has been carried out using pre- and post-earthquake QuickBird panchromatic high-resolution satellite images to produce a damage map. Two experienced interpreters carried out the assessments, and their results were compared to analyze the reasons for discrepancies likely to occur from interpretations by different interpreters. The first damage interpretation was carried out on the post-earthquake image, whereas the second interpretation compared the pre- and post-earthquake images. The analysis revealed that when using only the post-earthquake image, interpreters tend to underestimate the levels of damage, since both interpreters assigned higher damage levels when the pre- and post-earthquake image were compared than when only using the post-earthquake image. The absolute difference in the damage levels the two interpreters assigned in the post-only assessment and pre-and post-event comparison assessment remained the same.

Using High-Resolution Satellite Images for Post-Earthquake Building Damage Assessment: A Study following the 26 January 2001 Gujarat Earthquake

2004 ◽  
Vol 20 (1) ◽  
pp. 145-169 ◽  
Author(s):  
Keiko Saito ◽  
Robin J. S. Spence ◽  
Christopher Going ◽  
Michael Markus
Keyword(s):  
Damage Assessment ◽  
Satellite Images ◽  
Satellite Image ◽  
Building Damage ◽  
Large Area ◽  
Rapid Visual Screening ◽  
High Resolution Satellite Images ◽  
Collapsed Buildings ◽  
Optical Satellite Images ◽  
The City

Newly available optical satellite images with 1-m ground resolution such as IKONOS mean that rapid postdisaster damage assessment might be made over large areas. Such surveys could be of great value to emergency management and post-event recovery operations and have particular promise for earthquake areas, where damage distribution is often very uneven. In this paper three satellite images taken before and after the 26 January 2001 Gujarat earthquake were studied for damage assessment purposes. The images comprised a post-earthquake cover of the city of Bhuj, which was close to the epicenter, and pre- and post-earthquake cover of the city Ahmedabad. The assessment data was then compared with damage surveys actually made on-site. Three separate experiments were conducted. In the first, the satellite image of Bhuj was compared with detailed ground photos of 28 severely damaged buildings taken at about the same time as the satellite image, to investigate the levels and types of damage that can and cannot be identified. In the second experiment, the whole city center of Bhuj was damage mapped using only the satellite image. This was subsequently compared with a map produced from a building-by-building damage survey. In the third experiment, pre- and post-earthquake images for a large area of Ahmedabad were compared and totally collapsed buildings were identified. These sites were subsequently visited to confirm the accuracy of the observations. The experiment results indicate that rapid visual screening can identify areas of heavy damage and individual collapsed buildings, even when comparative cover does not exist. The need to develop a tool with direct application to support emergency response is discussed.

scholarly journals ИНВЕНТАРИЗАЦИЯ ЗАЩИТНЫХ ЛЕСНЫХ НАСАЖДЕНИЙ  НА ЗЕМЛЯХ СЕЛЬСКОХОЗЯЙСТВЕННОГО НАЗНАЧЕНИЯ

2019 ◽  
pp. 73-78
Author(s):  
S.V. Bogomazov ◽  
O.S. Balakireva ◽  
E.V. Efremova ◽  
O.A. Tkachuk ◽  
A.V. Lyandenburskaya ◽  
...  
Keyword(s):  
High Resolution ◽  
Satellite Images ◽  
Legal Status ◽  
Visual Interpretation ◽  
Agricultural Lands ◽  
Ndvi Index ◽  
Current Location ◽  
High Resolution Satellite Images ◽  
Village Council ◽  
Economic Use

В статье приводится анализ хозяйственного использования лесных защитных насаждений на землях сельскохозяйственного назначения. Целью исследований являлась инвентаризация лесных защитных насаждений на территории Волчковского сельсовета Белинского района с целью сохранения и восстановления агролесомелиоративного фонда. В камеральных условиях создан актуальный картографический материал на базе космических снимков высокого и сверхвысокого разрешения, проведено визуальное дешифрирование с составлением векторного полигонального слоя текущего местоположения защитных лесных насаждений, определено количество дешифрированных объектов, их правовой статус и общая площадь (199,2 га). Расчет индекса NDVI показал, что состояние, не требующее проведения мероприятий по восстановлению (обновлению), имеют 77 лесных полос общей площадью 127,1 га состояние, требующее мероприятий по восстановлению (обновлению), актуально для 31 лесной полосы площадью 70,4 га полностью утраченная одна лесная полоса площадью 1,7 га. Разработана дорожная карта мероприятий по сохранению агролесомелиоративного фонда.The article provides an analysis of economic use of shelterbelt forests on agricultural lands. The aim of the research was a compartment description of shelterbelt forests on the territory of the Volchkovsky village council of the Belinsky district in order to preserve and restore the stock of reclamative afforestating land. In the laboratory conditions, an up-to-date cartographic material was created on the basis of high-resolution and ultra-high-resolution satellite images, visual interpretation was made with the preparation of a vector polygonal layer of the current location of the shelterbelt forests, the number of decrypted objects, their legal status and total area (199.2 ha) were determined. The calculation of the NDVI index showed that the state, not requiring restoration (updating) measures, had 77 forest strips with a total area of 127.1 hectares a condition requiring restoration (renewal) measures was relevant for 31 forest strips with an area of 70.4 ha one forest strip with an area of 1.7 hectares was completely lost. A roadmap for the conservation of the stock of reclamative afforestating land was developed.

scholarly journals BUILDING DAMAGE ASSESSMENT AFTER EARTHQUAKE USING POST-EVENT LiDAR DATA

2015 ◽  
Vol XL-1-W5 ◽  
pp. 595-600 ◽  
Author(s):  
H. Rastiveis ◽  
F. Eslamizade ◽  
E. Hosseini-Zirdoo
Keyword(s):  
Damage Assessment ◽  
Satellite Image ◽  
Building Damage ◽  
Lidar Data ◽  
Visual Interpretation ◽  
Data Set ◽  
Vector Map ◽  
Damage Degree ◽  
Map Generation ◽  
Damage Map

After an earthquake, damage assessment plays an important role in leading rescue team to help people and decrease the number of mortality. Damage map is a map that demonstrates collapsed buildings with their degree of damage. With this map, finding destructive buildings can be quickly possible. In this paper, we propose an algorithm for automatic damage map generation after an earthquake using post-event LiDAR Data and pre-event vector map. <br><br> The framework of the proposed approach has four main steps. To find the location of all buildings on LiDAR data, in the first step, LiDAR data and vector map are registered by using a few number of ground control points. Then, building layer, selected from vector map, are mapped on the LiDAR data and all pixels which belong to the buildings are extracted. After that, through a powerful classifier all the extracted pixels are classified into three classes of “debris”, “intact building” and “unclassified”. Since textural information make better difference between “debris” and “intact building” classes, different textural features are applied during the classification. After that, damage degree for each candidate building is estimated based on the relation between the numbers of pixels labelled as “debris” class to the whole building area. Calculating the damage degree for each candidate building, finally, building damage map is generated. <br><br> To evaluate the ability proposed method in generating damage map, a data set from Port-au-Prince, Haiti’s capital after the 2010 Haiti earthquake was used. In this case, after calculating of all buildings in the test area using the proposed method, the results were compared to the damage degree which estimated through visual interpretation of post-event satellite image. Obtained results were proved the reliability of the proposed method in damage map generation using LiDAR data.

Visual Damage Interpretation of Buildings in Bam City using QuickBird Images following the 2003 Bam, Iran, Earthquake

2005 ◽  
Vol 21 (1_suppl) ◽  
pp. 329-336 ◽  
Author(s):  
Fumio Yamazaki ◽  
Yoshihisa Yano ◽  
Masashi Matsuoka
Keyword(s):  
High Resolution ◽  
Rural Areas ◽  
Strong Earthquake ◽  
Satellite Images ◽  
Field Survey ◽  
Visual Damage ◽  
High Resolution Satellite Images ◽  
Macroseismic Scale ◽  
The City ◽  
Event Image

A strong earthquake struck the city of Bam in southeast Iran on 26 December 2003. The earthquake brought massive destruction to the city and its surrounding rural areas. QuickBird, a high-resolution satellite, captured a clear image of Bam on 03 January 2004, eight days after the event. The city was also observed by QuickBird on 30 September 2003, about three months before the event. In this paper, using the pre-event image, the location of individual buildings was registered on GIS and the city blocks surrounded by major roads were assigned. Then, the visual damage interpretation based on the European Macroseismic Scale (EMS-98) was carried out building by building, comparing the pre-event and post-event images. The result of the damage inspection was compared with field survey data, and the accuracy and usefulness of the high-resolution satellite images in damage detection was demonstrated.

Updating GIS Building Inventory Data Using High-Resolution Satellite Images for Earthquake Damage Assessment: Application to Metro Manila, Philippines

2006 ◽  
Vol 22 (1) ◽  
pp. 151-168 ◽  
Author(s):  
Hiroyuki Miura ◽  
Saburoh Midorikawa
Keyword(s):  
High Resolution ◽  
Damage Assessment ◽  
Satellite Images ◽  
Remote Sensing Data ◽  
Earthquake Damage ◽  
Inventory Data ◽  
Building Inventory ◽  
High Resolution Satellite Images ◽  
Metro Manila ◽  
Earthquake Damage Assessment

In order to conduct earthquake damage assessment, a methodology for updating GIS building inventory data in Metro Manila, Philippines, using remote sensing data is proposed. The locations of newly constructed mid- and high-rise buildings are detected from high-resolution satellite images using the image analysis technique, while the number of low-rise buildings is estimated from the built-up areas on a land cover classification map. The building inventory data is updated by incorporating the data on the newly constructed buildings into the existing data. The number of buildings in the updated inventory data shows good agreement with the results of the manual interpretation and a recent survey. A building damage assessment for a scenario earthquake is conducted using the updated inventory data.

An Approach for Building Rooftop Border Extraction from Very High-Resolution Satellite Images

2021 ◽  
pp. 1-11
Author(s):  
Yasser Mostafa ◽  
Mahmoud Nokrashy O. Ali ◽  
Faten Mostafa ◽  
Mohamed Yousef
Keyword(s):  
High Resolution ◽  
Satellite Images ◽  
High Resolution Satellite Images ◽  
Very High
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