Aixia Dou

Study on quantitative earthquake damage of Dujiangyan city, caused by 2008 MS=8.0 Wenchuan, China earthquake based on aerial imagery

The paper introduces quantitative earthquake damage estimation method based on remote sensing data. The quantitative remote sensing seismic damage index based on building damage extracted from the aerial image of Dujiangyan city proper, southwest Chinas Sichuan province, which acquired after 2008 Ms=8.0 Wenchuan earthquake. The actual seismic damage indices were determined by the ground-based investigation in the city proper. Then their quantitative relationship was established. The results indicate that it is possible to build quantitative model of remote sensing seismic damage, which will enhance significantly the practicality applying the remote sensing in emergency acquisition and analysis of seismic disaster.

Disaster mapping from medium spatial resolution alos palsar images

All-day and all-weather Synthetic Aperture Radar (SAR) can measure both intensity and phase of the reflected signal. The backscattering coefficients measured by SAR reflect the backscatter characteristics of surface targets. Changes happened to a targets surface roughness, geometric and structural characteristics will result in the change of its backscattering intensity recorded in SAR image. The 2008 Wenchuan earthquake, China have caused widely distributed geological disasters, such as landslides, mudfloods and barrier lakes, which resulted in the difference between pre- and post-earthquake SAR images. Comparison between the pre- and post-earthquake SAR intensity images will reveal the damage information. In this study, PALSAR Level 1.0 data acquired for the Wenchuan earthquake were used to analyze the geological disasters. Results show that medium spatial resolution SAR data, such as 10 m resolution ALOS PALSAR data, especially when both pre- and post-earthquake images are available, are useful in revealing the distribution of landslides and barrier lakes.

Study on extraction of earthquake damage information based on regional optimizing change detection from remote sensing image

After the devastating earthquake, change detection with pre-earthquake images and post-earthquake images can find the seriously damaged area quickly, which provides important information for rescue. Shen et al. (2011) researched the influence of image registration error on change detection with high resolution RS images[1]. Rathje (2005), Zhang et al. (2013) made an intense research on the method of change detection to acquire earthquake damage[2][3]. In this paper, we identify earthquake damage by means of regional optimizing correlation coefficient method with processed pre-earthquake ratio image and post-earthquake ratio image, compared with the result acquired only with single band image. The result shows that the effect of the new method is improved obviously.

Study on the precision evaluation method for a specific category in the classification of remote sensing image

The Kappa value mainly reflects the overall classification accuracy, but it is hard to evaluate whether a specific classification is optimal or not. In earthquake forecast, an indicator, R-value, is widely used to evaluate the predicting effect of a forecasting method. This paper introduces the R-value to evaluate the classifying accuracy of a specific category in image classification. The range and implication of R-value for a specific category are described and compared. As an example, analyses are performed to determine the R-value of classified building damage grade extracted from RS image, compared with building damage grade determined according to ground survey in order to get the best corresponding relationship between them. The results demonstrate that the best corresponding scheme with maximum R-values is consistent with the subjective understanding. It indicates that the R-value method gives richer classification accuracy assessment information than the Kappa method. It is expected to be applied to the evaluation of classifying accuracy of a particular category and the determination of the best scheme in image classification.

Study on model base system of earthquake damage extraction from RS in ENVI/IDL environment

The emergency decision-making by government for rescue and rebuilding after a catastrophic earthquake depends on fast, accuracy and quantitative disaster information. The development of GIS, GPS, RS and other high techniques make it possible to quick acquisition of airborne or satellite images. Among them, the fast identification of damages to earthquakes from images becomes the key techniques. A new model base system for earthquake damage identification from images has been developed in ENVI/IDL environment to build and management such models. The system realized main functions such as model base building, management and application system creation, model selection and running. By using the model base system, an emergency Earthquake Damage and Losses Evaluate System based on Remote Sensing (RSEDLES) has been developed and applied in practice. The basic components, system structure, key procedures of the model base system realized in ENVI/IDL and its primary application are introduced in the paper.

Earthquake-induced building damage detection method based on normal computation of neighboring points searching on 2D-plane

Earthquake-induced building collapse is one of the main reason for casualties. Airborne Laser Scanning (ALS) can acquire high resolution three-dimensional point cloud data. It is possible to detect building damage use post-earthquake ALS point cloud data. Due to the height difference of buildings, earthquake-induced building collapse cannot detect by height change directly, especially in large area. This paper proposed a neighboring points searching method to calculate the normal vector of damage building roof point cloud data, then compute the angle between normal vector and zenith direction, α. Through calculate α of typical damage building, we found that the angle can be used to detect building damage. After test with the large area using this method and select local region to evaluate the result, the kappa value is 0.75 shows it is an effective method to detect building damage.

The development of Tianjin Remote Sensing Processing System Earthquake Damage Analysis

This paper introduces damage extraction and loss assessment methods and key technologies of earthquake emergency four work modes based on remote sensing, which are quickly display of post-earthquake images, rapid and rough damage assessment mode, standard damage assessment mode and detailed damage assessment mode. According to their workflows, Tianjin Remote Sensing Earthquake Damage Analysis and Processing System (TJ-RSEDAPS) was designed and developed to achieve image management, damage degree identification of buildings, key-objects and major facilities, losses assessment of life and economic, damage distribution mapping, and information service. The main functions are performed in detail.

Study on the fractal analysis of SAR images and its application to the extraction of seismic damage of 2010 Yushu, China Ms=7.1 earthquake

The SAR image can be acquired without the affection of cloud or rain and the limitation of sunlight, so it is widely used in many fields, especially in the disaster management. The paper is concentrated on the research of the method to extract disaster information quickly from SAR images, which is important and useful for emergency remote sensing processing. The fractal analyzing methods are described and applied to extract the building damage of 2010 Yushu Ms 7.1 earthquakes from SAR images. The results are compared with the interpretation of building damage from the high resolution airborne and satellite optical images.

Damage assessment of Haiti earthquake emergency using high resolution remote sensing imagery

This paper introduces the procedure of emergency remote sensing assessment for Haiti earthquake happened on Jan 12 2010. The procedure is divided into 4 steps: data preparation, data processing, information extraction and damage assessment, and contains three key targets which are damage information extraction, quantitative assessment and estimation of casualties and economic losses. In the first stage, the damage information of the buildings is the basis, and the other information, including building type, damage grade, built-over area, would be extracted by visual interpretation and automatically statistic with human-computer interaction from the high resolution disaster imageries. Then the remote sensing damage index and equivalent ground damage index of building could be counted in the second stage. According to this result, the specialists sketch a more exact intensity distribution in different regions of the metropolis. At last, the number of casualties is estimated by an empirical model adapting to worldwide earthquake as the detailed construction damage has been known. To assess the economic losses, we use a macro economic-based model which only needs population, per capita GDP and statistical macro-economic fragility related to seismic intensity. In this case, it is the first time to implement the methods of remote sensing assessment in foreign serious earthquake emergency, which is proven of being applicable outside China.

Study on GIS and RS based seismic prevention and disaster reduction management information system

This paper describes the requirement of seismic prevention and disaster reduction. Based on the requirement, an GIS and RS based system is introduced, the main sub-system and functions have been described. Some user interfaces are shown as examples which demonstrates the combination of assess modes and data with the GIS.