**Earth Observation for Earthquake Disaster Monitoring and Assessment**

Huadong Guo, Liangyun Liu, Xiangtao Fan, Xinwu Li and Lu Zhang *Key Laboratory of Digital Earth Science, Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, Beijing China* 

### **1. Introduction**

292 Earthquake Research and Analysis – Statistical Studies, Observations and Planning

[19] Binning G. and Rohrer H. (1980) "Scanning Tunneling Microscope". *U.S. Patent* 

[22] Bikov V.A. (2000) "Topical review on Probe Microscopes". *Russian Doctoral Degree* 

[24] Roger A. (1996). Coil-based Micromachined Sensor Measures Speed & Position for Automotive Applications. *Electronic Design*, December 16, pp. 34-37.

[23] Spiral Chip Inductors (U.S. Microwaves production – *www.usmicrowaves.com*).

Sciences, No.3(226), pp. 47-51.

*4,343,993*, Aug.10, 1982. Field: Sep.12. [20] Binning G. et al. (1982) *Appl. Phys. Lett.*, Vol.40, p.178.

*Dissertation*, Moscow – in Russian.

[21] Binning R., Quate C., et al. (1986), *Phys. Rev. Lett*., Vol.56, p.930.

layer flat coils. *Proceedings of the Yerevan State University*, Physical and Mathematical

China is a country where earthquakes and many other disasters happen often. After earthquakes, roads are damaged, traffic is blocked off, secondary disasters occur frequently, weather conditions become adverse, and communications are interrupted, which makes it difficult to gather data from stricken regions. And the big problem for recovery operations is that there is no accurate information about the situation. Earth observation technology, which has many advantages including high-speeds, maneuverability, and macro- to microlevel observation, has shown its importance for gathering information about stricken regions and making reasonable recovery decisions.

Optical Earth observation technology can provide vivid images for target interpretation and disaster information extraction. Maneuverable, flexibile airborne optical observation technology can especially provide real-time surface images, which also obtains information about collapsed houses, broken roads, geological disasters, barrier lakes and so on. It plays an important part in disaster mitigation activities (Guo et al., 2010a). Synthetic aperture radar (SAR) not only has the capability of all-weather monitoring, but also is sensitive to geometric shape and movement, which becomes an efficient tool to analyze and evaluate recent earthquakes (Guo et al., 2000; Guo et al., 2010b). Multi-mode SAR data can provide many kinds of information for disaster research. Wide-mode SAR images and In-SAR images are important methods for detecting terrain deformation. Wide-mode SAR images can analyze the faulted zone and lithologic characteristics in stricken regions from a macrolevel,because it acquires large-scale image (Guo et al., 2000). In-SAR images yield information about surface deformation size and spatial distribution acquired from twoscene repeat-pass data (Massonnet & Feigl, 1998). Polarimetric SAR images, due to the sensitivity to target structures, can be used to extract the distribution of collapsed buildings. After the Wenchuan and Yushu earthquakes, some departments took full advantage of airborne and satellite remote sensing technology, or unmanned aerial vehicles, to obtain images of the disaster area, which played a very important role in disaster emergency monitoring and disaster assessment and reconstruction (Guo et al., 2010ab; Singh et al., 2010; Liou et al., 2010). Besides monitoring targets directly affected by the disaster, such as collapsed buildings (Lei 2009), remote sensing can observe secondary damage such as barrier lakes, collapse, landslide, debris flow et al. (Cui et al, 2008; Wang et al, 2008; Liu et al., 2009; Huang et al., 2009; Ge et al., 2009; Xu et al., 2009; Han et al., 2009; Zhuang et al., 2010; Zhang et al., 2010; Xu et al., 2010).

Earth Observation for Earthquake Disaster Monitoring and Assessment 295

The water level and area of the barrier lakes were first estimated using high-resolution airborne images. The capacity of the barrier lake was then calculated using elevation contours, and the calculation was based on DEM data with a resolution of 25 m, which were

The water surface area was derived from high-resolution airborne images. Then the water surface elevation *(*ℎ�*)* was acquired by overlapping the water surface with the DEM data, since the elevation of the water surface is a constant. If there is some small shift between the orthorectified ADS40 image and the DEM data, the interpreted water surface should be adjusted slightly to ensure all interpreted water surfaces' borderline is located at the same altitude. Meanwhile, the elevation of the midline of the river *(*ℎ�*)* was directly recorded from the 1:50,000-scale topographic map. Therefore, the elevation difference and the water level

The capacity of the barrier lake was calculated by an integral approach. The capacity V at

*n i i VH S h* 

where ∆ℎ is the integration interval, *n* is the equally parted cells number of the elevation drop from the water surface elevation *(*ℎ�*)* to the elevation of the midline of the river, *(*ℎ�*)*, ∆ℎ = (ℎ� − ℎ�)�� is the integration interval of each cell, and��� is the water surface area at the elevation of ℎ� − (� − �)∆ℎ , which can be automatically derived from the DEM data. The capacity and area of all the 51 barrier lakes were calculated by this method. According to their capacities, the barrier lakes were clustered into three types: Type I (large-sized) with a capacity over 3,000,000 m³; Type II (medium-sized) with a capacity between 1,000,000 and

Barrier lakes formed in an earthquake will result in extreme flooding when they burst. Therefore, the risk assessment of barrier lakes becomes very important. The dimensionless blockage index (DBI) was introduced by Casagli and Ermini (Ermini et al, 2003; Liu et al.,

where �� is the volume of the dam, which is the dominant parameter of stability since it determines the gravity of the dam; �� is the area of the basin, which is the primary parameter of instability since it determines the runoff in the basin; and �� is the height of the dam, which is an important parameter for evaluating the stability of the barrier lake when confronted with overflow. The smaller the DBI value, the more stable the barrier lake. It is difficult to calculate the dam volume with the remote sensing image without in-situ measurement. An approximate estimation of dam volume is to multiply the dam area with

�� � �� ��

(1)

) (2)

( )

3,000,000 m³; and Type III (small-sized) with a capacity less than 1,000,000 m³

��� = ���(

The method to calculate the reservoir capacity involves the following steps:

**2.2.1 Barrier lake volume detection algorithm** 

could be calculated.

the water elevation of H is:

interpolated from a 1:50,000-scale topographical map.

1

**2.2.2 Risk assessment of the barrier lakes** 

2009) to evaluate the stability of a dam:

its height, and thus Eq. (2) can be written as:

The Chinese Academy of Sciences (CAS) immediately arranged a cooperative data acquisition program of airborne and satellite remote sensing data after Wenchuan and Yushu earthquakes and obtained 17 categories of more than 500 scenes of satellite images and high-resolution optical and microwave airborne remote sensing data. 8.7 TB of high-resolution data were freely provided initially to 16 ministries and 28 units, and an additional 3.5 TB were later downloaded from the network. At the same time, a study on remote sensing monitoring methods for post-earthquake secondary geological disasters was carried out, which played an important role in the disaster response. This paper focuses on three aspects, including optical Earth observation technology for monitoring secondary geological disasters, multi-mode radar Earth observation for post-earthquake deformation analysis, and an earthquake disaster simulation evaluation system using the results of seismic disaster remote sensing.
