**2.3.1 Road blockage and damage conditions in badly stricken areas**

The main remote sensing road blockage and damage condition detection focuses on national and provincial highways. There are 5 national and provincial highways in the badly stricken

Fig. 2. Map of damaged roads after the Wenchuan earthquake

Earth Observation for Earthquake Disaster Monitoring and Assessment 299

landslides, and debris flows. Using investigations by remote sensing and field survey results combined with the Ministry of Land and Resources, PRC emergency investigation data, a secondary geological hazards information acquisition model was established. It allowed for the monitoring and rapid extraction of secondary geological disaster data. Researchers studied the characteristics and distribution of secondary geological disasters, completed the interpretation of 11 heavily-damaged area's geologic disasters and their geological background, and analyzed the geological hazards' distribution, intensity, scale and distribution regularity. The study revealed that the development of secondary geological disasters had obvious clustering. In the area, seismic geological hazards were along the Longmen Mountain Fault Zone and mainly caused by the Beichuan-Yingxiuwan

**2.4.1 Remote sensing information extraction method for secondary geological** 

and supports the job of disaster evaluation and post-disaster reconstruction.

The special weather conditions in Wenchuan make the ratio of vegetation coverage higher. The study on vegetation destruction in this area shows the severity of geological disasters

First, remote sensing data were acquired from before and after the earthquake. Extracting the information map of vegetation was done with standardized resolution and registration. Second, high spatial resolution images were used to check causes of vegetation change including geological disasters, human destruction, agricultural changes and so on. The third step was to remove the vegetation change information caused by non-geological disasters and make a classification according to remote sensing image identification of secondary geological disasters. Last, statistics were calculated and analysis conducted to make a

In order to reduce the extraction difference of vegetation caused by different spatial resolutions, we standardized the spatial resolution of the images by two-dimensional cubic convolution before the vegetation information extraction. Then map-to-map control points were adopted and registered by a polynomial method. Because the registration method uses vegetation information difference extraction before and after the disaster, the registration

According to the special vegetation spectrum, we can efficiently extract the vegetation

*R R NDVI*

where NDVI is vegetation index, ܴேூோ is reflectivity of near infrared wave, and ܴோ is reflectivity of infrared wave. Comparing the results with a real vegetation coverage map to fix the threshold, we can extract the vegetation coverage map and change it into a vector

Based on the extraction of a vegetation information vector graph, the difference between the two figures can be extracted by doing differential operation. The high spatial resolution data can be used to correct elements caused by the difference and then reject the difference in

 *NIR R NIR R*

*R R* (4)

information from pre- and post-disaster images. The formula is as follows:

iii. extracting the vegetation information difference from geological disasters

fracture control.

difference map.

diagram.

i. Standardize resolution and make registration

precision should be controlled within 1 pixel.

ii. extract vegetation information

**disasters** 

area, with an overall length of 573.82 km. This includes 3 national roads with a total length of 394.07 km: National Highway 213 (239.563 km) from Xuankou Town, Wenchuan County to Minjiang Village, Mao County, National Highway 212 (31.814 km) from Baolun town, Guangyuan City to Lijia Ping, Qingchuan County, National Highway 317 (122.692 km) from Siboguo Village, Li County to Wenchuan County. It also includes 2 provincial highways with a total length of 179.75 km: Provincial Road 105 (50.85 km) from Anchang Town, An County to Beichuan County and Provincial Road 302 (128.90 km) from Mao County, Jiangyou City.

The Wenchuan earthquake caused more than five national and provincial road blockages and damage, including 808 points in total with a total length of 170.17 km, which accounted for 29.66% of the total length of paths in the badly stricken area, in which, National Road 213 was most seriously damaged, then National Road 317 and Provincial Road 105. Damage to the others was comparatively light. The conditions of damaged roads is described in Figure 2.

#### **2.3.2 Damage level and distribution condition of hard-hit areas**

The blocked roads were obviously segmented and the worst parts appeared to have a cluster distribution. Outside of the observed areas, the roads were light damaged and without major disasters such as landslips.

#### **2.3.3 Category, scale and causation of damaged paths**

According to remote sensing monitoring and analysis, the blockage paths of the worstdamaged places were caused by geological disasters such as landslips, falling debris, mudrock flows and ground fissures. The distribution of these disasters was related to the break structure, drape structure, and rock broken under stress.

Fracture tectonic belt was the most important role in road damage. The magnitude-8 earthquake happened on the fault zone of Longmen Mountain, which is composed of many approximately parallel disruptions oriented towards the northeast with a length of more than 500 km and 50 km in width. The Yingxiu-Beichuan fault and Wenchuan-Maoxian fault were the most important parts of the Longmen Mountain fault zone, and the most serious damage to National Road 213 was along these two fault zones.

The background of the badly stricken area's geological structure is very complex with a long evolutionary history. The rocks in hard-hit areas were squeezed extremely because of the long-term activities of well-developed faults and fold faults. These broken rocks provide a large amount of material for potential falling, mud-rock flows (with fragment flows) and landslips. This material slipped rapidly under the force of gravity and piled up on the lower roads and caused blockage in the harder-hit area.

In addition, the earthquake's power is the reason that roads in harder-hit area were blocked and damaged. When the earthquake occurred, there were both southeast-direction thrust extrusion and dextral shear in the Longmen Mountain Fault Zone ( Chen Yuntai etc., 2008 ), which made steep mountains, high-angle clockwise slope and extremely broken rock strata lose their balance and dependence. Then under the action of gravity, broken rock rapidly slid downward, or collapsed and accumulated in low-lying areas on the highway, which damaged and blocked the road.

#### **2.4 Secondary geological disaster analysis of Wenchuan earthquake**

Using high-resolution ADS40 optical aviation remote sensing images and comprehensive, conventional data, we evaluated secondary geological disasters, such as collapses,

area, with an overall length of 573.82 km. This includes 3 national roads with a total length of 394.07 km: National Highway 213 (239.563 km) from Xuankou Town, Wenchuan County to Minjiang Village, Mao County, National Highway 212 (31.814 km) from Baolun town, Guangyuan City to Lijia Ping, Qingchuan County, National Highway 317 (122.692 km) from Siboguo Village, Li County to Wenchuan County. It also includes 2 provincial highways with a total length of 179.75 km: Provincial Road 105 (50.85 km) from Anchang Town, An County to Beichuan County and Provincial Road 302 (128.90 km) from Mao County,

The Wenchuan earthquake caused more than five national and provincial road blockages and damage, including 808 points in total with a total length of 170.17 km, which accounted for 29.66% of the total length of paths in the badly stricken area, in which, National Road 213 was most seriously damaged, then National Road 317 and Provincial Road 105. Damage to the others was comparatively light. The conditions of damaged roads is described in Figure 2.

The blocked roads were obviously segmented and the worst parts appeared to have a cluster distribution. Outside of the observed areas, the roads were light damaged and

According to remote sensing monitoring and analysis, the blockage paths of the worstdamaged places were caused by geological disasters such as landslips, falling debris, mudrock flows and ground fissures. The distribution of these disasters was related to the break

Fracture tectonic belt was the most important role in road damage. The magnitude-8 earthquake happened on the fault zone of Longmen Mountain, which is composed of many approximately parallel disruptions oriented towards the northeast with a length of more than 500 km and 50 km in width. The Yingxiu-Beichuan fault and Wenchuan-Maoxian fault were the most important parts of the Longmen Mountain fault zone, and the most serious

The background of the badly stricken area's geological structure is very complex with a long evolutionary history. The rocks in hard-hit areas were squeezed extremely because of the long-term activities of well-developed faults and fold faults. These broken rocks provide a large amount of material for potential falling, mud-rock flows (with fragment flows) and landslips. This material slipped rapidly under the force of gravity and piled up on the lower

In addition, the earthquake's power is the reason that roads in harder-hit area were blocked and damaged. When the earthquake occurred, there were both southeast-direction thrust extrusion and dextral shear in the Longmen Mountain Fault Zone ( Chen Yuntai etc., 2008 ), which made steep mountains, high-angle clockwise slope and extremely broken rock strata lose their balance and dependence. Then under the action of gravity, broken rock rapidly slid downward, or collapsed and accumulated in low-lying areas on the highway, which

Using high-resolution ADS40 optical aviation remote sensing images and comprehensive, conventional data, we evaluated secondary geological disasters, such as collapses,

**2.3.2 Damage level and distribution condition of hard-hit areas** 

**2.3.3 Category, scale and causation of damaged paths** 

structure, drape structure, and rock broken under stress.

damage to National Road 213 was along these two fault zones.

**2.4 Secondary geological disaster analysis of Wenchuan earthquake** 

roads and caused blockage in the harder-hit area.

damaged and blocked the road.

without major disasters such as landslips.

Jiangyou City.

landslides, and debris flows. Using investigations by remote sensing and field survey results combined with the Ministry of Land and Resources, PRC emergency investigation data, a secondary geological hazards information acquisition model was established. It allowed for the monitoring and rapid extraction of secondary geological disaster data. Researchers studied the characteristics and distribution of secondary geological disasters, completed the interpretation of 11 heavily-damaged area's geologic disasters and their geological background, and analyzed the geological hazards' distribution, intensity, scale and distribution regularity. The study revealed that the development of secondary geological disasters had obvious clustering. In the area, seismic geological hazards were along the Longmen Mountain Fault Zone and mainly caused by the Beichuan-Yingxiuwan fracture control.

#### **2.4.1 Remote sensing information extraction method for secondary geological disasters**

The special weather conditions in Wenchuan make the ratio of vegetation coverage higher. The study on vegetation destruction in this area shows the severity of geological disasters and supports the job of disaster evaluation and post-disaster reconstruction.

First, remote sensing data were acquired from before and after the earthquake. Extracting the information map of vegetation was done with standardized resolution and registration. Second, high spatial resolution images were used to check causes of vegetation change including geological disasters, human destruction, agricultural changes and so on. The third step was to remove the vegetation change information caused by non-geological disasters and make a classification according to remote sensing image identification of secondary geological disasters. Last, statistics were calculated and analysis conducted to make a difference map.

i. Standardize resolution and make registration

In order to reduce the extraction difference of vegetation caused by different spatial resolutions, we standardized the spatial resolution of the images by two-dimensional cubic convolution before the vegetation information extraction. Then map-to-map control points were adopted and registered by a polynomial method. Because the registration method uses vegetation information difference extraction before and after the disaster, the registration precision should be controlled within 1 pixel.

ii. extract vegetation information

According to the special vegetation spectrum, we can efficiently extract the vegetation information from pre- and post-disaster images. The formula is as follows:

$$NNDVI\ \ = \frac{R\_{NIR} - R\_R}{R\_{NIR} + R\_R} \tag{4}$$

where NDVI is vegetation index, ܴேூோ is reflectivity of near infrared wave, and ܴோ is reflectivity of infrared wave. Comparing the results with a real vegetation coverage map to fix the threshold, we can extract the vegetation coverage map and change it into a vector diagram.

iii. extracting the vegetation information difference from geological disasters

Based on the extraction of a vegetation information vector graph, the difference between the two figures can be extracted by doing differential operation. The high spatial resolution data can be used to correct elements caused by the difference and then reject the difference in

Earth Observation for Earthquake Disaster Monitoring and Assessment 301

County, Qinghai Province, China, on April 14, 2010, as the research object and use RADARSAT-2 and ALOS-PALSAR repeat-pass SAR interferometry data to analyze

The Yushu earthquake occurred in the Garzê-Yushu Fault Zone. The fault strike runs in a northwest direction for a length of nearly 500 km, and has a fracture width from 50 to several hundred meters. From analysis of the plate tectonics, it can be concluded that the source of this earthquake was in the Qinghai-Tibetan Plateau, located in the north of the collision zone in the Himalayas, which was formed by the subduction of the Indian plate toward the Eurasian continent. Because of this plate subduction, lateral sliding of the internal blocks of the Qinghai-Tibetan Plateau occurred, which caused the northward shift of the plateau and its internal blocks and finally, the formation of strike-slip fault systems with different scales at the edge of the blocks. Zhang et al. (2010) inverted the moment tensor solution using wave-form data from global stations. From this solution and the background of the fault tectonics, it can be concluded that the fault with a trend of 119° and a dip of 83° was the earthquake rupture. The breaking process was determined based on teleseismic data from the 35 global stations. Two active regions on the fault surface were identified. One was located near the micro-epicenter, and the other was located to the southeast at a distance of 10 to 30 km. The latter had the greater slip, 2.4 m, and was a near

The study uses SAR data including RADARSAT-2 wide-mode data and ALOS PALSAR repeat-pass data. The RADARSAT-2 wide-mode data was acquired on April 21, 2010, with a spatial resolution of 40 meters and an incident angle of 21 degrees. ALOS PALSAR data, including two pre-earthquake and post-earthquake scenes, were acquired on January 15, 2010, and April 17, 2010, respectively. Table 1 shows the PALSAR data parameters for

baseline (m)

Temporal baseline (d)

Sensor Date Orbit Frame Perpendicular

PALSAR 2010-1-15 487 650 700.5 92 PALSAR 2010-4-17 487 650

**3.2 The method of extracting earthquake geological characteristics and surface** 

Ground-fissuring phenomena are often a reflection of different lithological characteristics. SAR image brightness and texture structure can reflect the degree of fissuring. In addition, radar waves are sensitive to the linear structure (Guo, 1996, 1997), so using SAR imagery can

Interferometric SAR is an important means of extracting surface deformation because it can measure it precisely in three-dimensional space, including small deformations of the surface, and can achieve high spatial resolution observation of surface changes in large areas. Interferometric SAR images of the same area at different times by SAR sensor were obtained at different time SAR complex images. Then we process SAR images acquired at different times to obtain an interferogram. SAR interferograms show electromagnetic wave

earthquake deformation characteristics.

vertical sinistral strike-slip fault.

repeat-pass SAR interferometry.

Table 1. PALSAR parameters for SAR interferometry

**deformation information from SAR data** 

help interpret tectonic information.

**3.1 Yushu earthquake area background and data acquisition** 

vegetation information caused by non-geological factors. Finally, according to remote sensing image identification of secondary geological disasters, they can be classified.
