Damage Detection Using High-Resolution SAR Imagery in the 2009 L'Aquila, Italy, Earthquake

2013 ◽  
Vol 29 (4) ◽  
pp. 1521-1535 ◽  
Author(s):  
Pralhad Uprety ◽  
Fumio Yamazaki ◽  
Fabio Dell'Acqua
Keyword(s):  
High Resolution ◽  
Damage Detection ◽  
Correlation Coefficient ◽  
Ground Truth ◽  
Threshold Value ◽  
Building Damage ◽  
Urban Setting ◽  
Ground Truth Data ◽  
Emergency Situations ◽  
Sar Imagery

Satellite remote sensing is being used to monitor disaster-affected areas for post-disaster reconnaissance and recovery. One of the special features of Synthetic Aperture Radar (SAR) is that it can operate day and night and penetrate the cloud cover because of which it is being widely used in emergency situations. Building damage detection for the 6 April 2009 L'Aquila, Italy, earthquake was conducted using high-resolution TerraSAR-X images obtained before and after the event. The correlation coefficient and the difference of backscatter coefficients of the pre- and post-event images were calculated in a similar way as Matsuoka and Yamazaki (2004) . The threshold value of the correlation coefficient was suggested and used in detecting building damage. The results were compared with ground truth data and a post-event optical image. Based on the study, building damage could be observed in an urban setting of L'Aquila with overall accuracy of 89.8% and Kappa coefficient of 0.45.

Object-Based Method for Estimating Tsunami-Induced Damage Using TerraSAR-X Data

2016 ◽  
Vol 11 (2) ◽  
pp. 225-235 ◽  
Author(s):  
Hideomi Gokon ◽  
◽  
Shunichi Koshimura ◽  
Masashi Matsuoka ◽  
◽  
...  
Keyword(s):  
Correlation Coefficient ◽  
Tohoku Earthquake ◽  
Ground Truth ◽  
Test Site ◽  
Damage Function ◽  
Building Damage ◽  
The 2011 Tohoku Earthquake ◽  
Ground Truth Data ◽  
Object Based ◽  
The Relationship

The object-based method we developed to estimate building damage uses high-resolution synthetic aperture radar (TerraSAR-X) data from the 2011 Tohoku earthquake and tsunami. The damage function we developed involves the relationship between changes in the sigma nought values of pre- and postevent TerraSAR-X data and the damage ratio of washed-away buildings. We confirmed that the function performed as expected by estimating the number of washed-away buildings in homogeneous areas, agreeing well with ground truth data verified by a Pearson fs correlation coefficient of 0.99. The same damage function applied at another test site yielded a Pearson's correlation coefficient of 0.98. These results are sufficient to ensure transferability. We then simplified and semiautomated these processes in an ArcGIS environment, estimating building damage in the city of Sendai within 26 minutes.

ACCURATE EVALUATION OF BUILDING DAMAGE IN THE 2003 BOUMERDES, ALGERIA EARTHQUAKE FROM QUICKBIRD SATELLITE IMAGES

2011 ◽  
Vol 05 (01) ◽  
pp. 1-18 ◽  
Author(s):  
ABDELGHANI MESLEM ◽  
FUMIO YAMAZAKI ◽  
YOSHIHISA MARUYAMA
Keyword(s):  
High Resolution ◽  
Satellite Images ◽  
Ground Truth ◽  
Building Damage ◽  
Geographical Information ◽  
Ground Truth Data ◽  
Damage Level ◽  
Damage Grade ◽  
Damage Mapping ◽  
Collapsed Buildings

Using QuickBird satellite images of Boumerdes city obtained following the 21 May 2003 Algeria earthquake, our study examined the applicability of high-resolution optical imagery for the visual detection of building damage grade based on the ground-truth data on the urban nature, typology of a total of 2,794 buildings, and the real damage observed. The results are presented as geographical information system (GIS) damage mapping of buildings obtained from field surveys and QuickBird images. In general, totally collapsed buildings, partially collapsed buildings, and buildings surrounded by debris can be identified by using only post-event pan-sharpened images. However, due to the nature of the damage observed, some buildings may be judged incorrectly even if preevent images are employed as a reference to evaluate the damage status. Hence, in this study, we clarify the limitations regarding the applicability of high-resolution optical satellite imagery in building damage-level mapping.

scholarly journals Estimation of sea-ice physical parameters using polarimetric SAR: results from Okhotsk and Lake Saroma campaign

2001 ◽  
Vol 33 ◽  
pp. 120-124 ◽  
Author(s):  
Hiroyuki Wakabayashi ◽  
Takeshi Matsuoka ◽  
Kazuki Nakamura ◽  
Fumihiko Nishio
Keyword(s):  
Sea Ice ◽  
Correlation Coefficient ◽  
Ground Truth ◽  
Open Water ◽  
Physical Parameters ◽  
Dual Frequency ◽  
Ground Truth Data ◽  
National Space ◽  
Airborne Sar ◽  
Interferometric Sar

AbstractWe have acquired ground-truth data at Lake Saroma, northeast Hokkaido, Japan, and the surrounding area since 1993 in order to collect data on regional sea ice in the Sea of Okhotsk. The data were acquired in 1999 by polarimetric and interferometric SAR (Pi-SAR), the dual-frequency, fully polarimetric airborne SAR system jointly developed by the National Space Development Agency of Japan (NASDA) and the Communications Research Laboratory (CRL), simultaneously with ground experiments. This paper describes the results of polarimetric data analysis of typical sea ice observed in the offshore region near Lake Saroma. The polarimetric parameters used were correlation coefficient and phase difference. Based on the analysis of these parameters, we found that the correlation coefficient between RR and LL polarizations can discriminate four categories including three types of ice and open water.

scholarly journals POST-FIRE FORESTRY RECOVERY MONITORING USING HIGH-RESOLUTION MULTISPECTRAL IMAGERY FROM UNMANNED AERIAL VEHICLES

2019 ◽  
Vol XLII-3/W8 ◽  
pp. 301-305 ◽  
Author(s):  
L. Pádua ◽  
T. Adão ◽  
N. Guimarães ◽  
A. Sousa ◽  
E. Peres ◽  
...  
Keyword(s):  
High Resolution ◽  
Unmanned Aerial Vehicles ◽  
Tree Height ◽  
Ground Truth ◽  
Cost Effective ◽  
Forest Disturbances ◽  
Ground Truth Data ◽  
High Resolution Data ◽  
Aerial Vehicles ◽  
Fire Scenarios

<p><strong>Abstract.</strong> In recent years unmanned aerial vehicles (UAVs) have been used in several applications and research studies related to environmental monitoring. The works performed have demonstrated the suitability of UAVs to be employed in different scenarios, taking advantage of its capacity to acquire high-resolution data from different sensing payloads, in a timely and flexible manner. In forestry ecosystems, UAVs can be used with accuracies comparable with traditional methods to retrieve different forest properties, to monitor forest disturbances and to support disaster monitoring in fire and post-fire scenarios. In this study an area recently affected by a wildfire was surveyed using two UAVs to acquire multi-spectral data and RGB imagery at different resolutions. By analysing the surveyed area, it was possible to detect trees, that were able to survive to the fire. By comparing the ground-truth data and the measurements estimated from the UAV-imagery, it was found a positive correlation between burned height and a high correlation for tree height. The mean NDVI value was extracted used to create a three classes map. Higher NDVI values were mostly located in trees that survived that were not/barely affected by the fire. The results achieved by this study reiterate the effectiveness of UAVs to be used as a timely, efficient and cost-effective data acquisition tool, helping for forestry management planning and for monitoring forest rehabilitation in post-fire scenarios.</p>

scholarly journals Retinal blood vessel segmentation from retinal image using B-COSFIRE and adaptive thresholding

2019 ◽  
Vol 13 (3) ◽  
pp. 1199 ◽  
Author(s):  
Aziah Ali ◽  
Wan Mimi Diyana Wan Zaki ◽  
Aini Hussain
Keyword(s):  
Retinal Image ◽  
Ground Truth ◽  
Threshold Value ◽  
Adaptive Thresholding ◽  
Computer Assisted ◽  
Segmentation Method ◽  
Ground Truth Data ◽  
Segmentation Methods ◽  
Otsu’S Method ◽  
Benchmark Datasets

<span>Segmentation of blood vessels (BVs) from retinal image is one of the important steps in developing a computer-assisted retinal diagnosis system and has been widely researched especially for implementing automatic BV segmentation methods. This paper proposes an improvement to an existing retinal BV (RBV) segmentation method by combining the trainable B-COSFIRE filter with adaptive thresholding methods. The proposed method can automatically configure its selectivity given a prototype pattern to be detected. Its segmentation performance is comparable to many published methods with the advantage of robustness against noise on retinal background. Instead of using grid search to find the optimal threshold value for a whole dataset, adaptive thresholding (AT) is used to determine the threshold for each retinal image. Two AT methods investigated in this study were ISODATA and Otsu’s method. The proposed method was validated using 40 images from two benchmark datasets for retinal BV segmentation validation, namely DRIVE and STARE. The validation results indicated that the segmentation performance of the proposed unsupervised method is comparable to the original B-COSFIRE method and other published methods, without requiring the availability of ground truth data for new dataset. The Sensitivity and Specificity values achieved for DRIVE and STARE are 0.7818, 0.9688, 0.7957 and 0.9648, respectively.</span>

Long-Range Geo-Monitoring Using Image Assisted Total Stations

2014 ◽  
Vol 8 (3) ◽  
Author(s):  
Andreas Wagner ◽  
Ben Huber ◽  
Wolfgang Wiedemann ◽  
Gerhard Paar
Keyword(s):  
High Resolution ◽  
Long Range ◽  
Ground Truth ◽  
Monitoring Methods ◽  
Ground Truth Data ◽  
Areal Coverage ◽  
Achievable Accuracy ◽  
The Eu

AbstractImage Assisted Total Stations (IATS) unify geodetic precision of total stations with areal coverage of images. The concept of using two IATS devices for high-resolution, long-range stereo survey of georisk areas has been investigated in the EU-FP7 project DE-MONTES (www.de-montes.eu). The paper presents the used methodology and compares the main features with other terrestrial geodetic geo-monitoring methods. The theoretically achievable accuracy of the measurement systemis derived and verified by ground truth data of a distant clay pit slope and simulated deformations. It is shown that the stereo IATS concept is able to obtain higher precision in the determination of 3D deformations than other systems of comparable sensor establishment effort.

scholarly journals Study on the Intensity and Coherence Information of High-Resolution ALOS-2 SAR Images for Rapid Massive Landslide Mapping at a Pixel Level

2019 ◽  
Vol 11 (23) ◽  
pp. 2808 ◽  
Author(s):  
Ge ◽  
Gokon ◽  
Meguro ◽  
Koshimura
Keyword(s):  
High Resolution ◽  
Correlation Coefficient ◽  
Ground Truth ◽  
Intensity Difference ◽  
Event Correlation ◽  
Sar Images ◽  
Calculated Parameter ◽  
Landslide Mapping ◽  
Qualitative Observation ◽  
Earthquake Potential

A rapid mapping of landslides following a disaster is important for coordinating emergency response and limiting rescue delays. A synthetic aperture radar (SAR) can provide a solution even in harsh weather and at night, due to its independence of weather and light, quick response, no contact and broad coverage. This study aimed to conduct a comprehensive exploration on the intensity and coherence information of three Advanced Land Observing Satellite-2 (ALOS-2) SAR images, for rapid massive landslide mapping in a pixel level, in order to provide a reference for future applications. Applied data were two pre-event and one post-event high-resolution ALOS-2 products. Studied area was in the east of Iburi, Hokkaido, Japan, where massive shallow landslides were triggered in the 2018 Hokkaido Eastern Iburi Earthquake. Potential parameters, including intensity difference (d), co-event correlation coefficient (r), correlation coefficient difference (∆r), co-event coherence (γ), and coherence difference (∆γ), were first selected and calculated based on a radar reflection mechanism, to facilitate rapid detection. Qualitative observation was then performed by overlapping ground truth landslides to calculated parameter images. Based on qualitative observation, an absolute value of d (dabs1) was applied to facility analyses, and a new parameter (dabs2) was proposed to avoid information loss in the calculation. After that, quantitative analyses of the six parameters (dabs1, dabs2, r, ∆r, γ and ∆γ) were performed by receiver operating characteristic. dabs2 and ∆r were found to be favorable parameters, which had the highest AUC values of 0.82 and 0.75, and correctly classified 69.36% and 64.57% landslide and non-landslide pixels by appropriate thresholds. Finally, a discriminant function was developed, combining three relatively favorable parameters (dabs2, ∆r, and ∆γ) with one in each type, and achieved an overall accuracy of 74.31% for landslide mapping.

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