sichuan earthquake 2008 case study

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Powerful Quake Ravages China, Killing Thousands

By Jake Hooker and Jim Yardley

• May 13, 2008

CHENGDU, China — A powerful earthquake struck Western China on Monday, toppling thousands of homes, factories and offices, trapping students in schools, and killing at least 10,000 people, the country’s worst natural disaster in three decades.

The quake, which was estimated preliminarily to have had a magnitude of 7.9, ravaged a mountainous region outside Chengdu, capital of Sichuan Province, just after lunchtime Monday, destroying 80 percent of structures in some of the towns and small cities near its epicenter, Chinese officials said. Its tremors were felt as far away as Vietnam and set off another, smaller quake in the outskirts of Beijing, 900 miles away.

Landslides, power failures and fallen mobile phone towers left much of the affected area cut off from the outside world and limited information about the damage. But snapshots of concentrated devastation suggested that the death toll that could rise significantly as rescue workers reached the most heavily damaged areas.

In the town of Juyuan, south of the epicenter in the city of Wenchuan, a school collapsed, trapping 900 students in the rubble and setting off a frantic search for survivors that stretched through the night. Two chemical factories in Shifang were destroyed, spilling 80 tons of toxic liquid ammonia, officials told Chinese state media.

The destruction of a single steam turbine factory in the city of Mianzhu buried “several thousand” people, the state-run Xinhua News Agency reported Tuesday morning.

The quake was already China’s biggest natural disaster since another earthquake leveled the city of Tangshan in eastern China in 1976, leaving 240,000 people dead and posing a severe challenge to the ruling Communist Party, which initially tried to cover up the catastrophe.

This time, officials quickly mobilized 50,000 soldiers to help with rescue efforts, state media said. Prime Minister Wen Jiabao flew to the scene and was shown coordinating disaster response teams from the cabin of his jet.

The prime minister was later shown on national television standing outside the damaged edifice of the Traditional Medicine Hospital in the city of Dujiangyan, shouting encouragement at people trapped in its ruins.

“Hang on a bit longer,” he said. “The troops are rescuing you. As long as there is the slightest hope, we will never relax our efforts.”

The quake was the latest in a series of events that have disrupted China’s planning for the Olympic Games in August, including widespread unrest among the country’s ethnic Tibetan population, which lives in large numbers in the same part of Sichuan Province where the earthquake struck.

The powerful initial quake struck at 2:28 p.m. local time, or 2:28 a.m. Eastern time, near Wenchuan County, according to China’s State Seismological Bureau. Most of the heavy damage appeared to be concentrated in nearby towns, which by Chinese standards are not heavily populated. Chengdu, the largest city in the area, with a population of about 10 million, is about 60 miles away and did not appear to have suffered major damage or heavy casualties.

But officials had yet to describe the impact in Wenchuan itself, which has a population of 112,000 and is home to the Wolong Nature Reserve, the largest panda reserve in China. The town of Beichuan, on the way from Chengdu to Wenchuan, suffered several thousand deaths, state media said.

China’s massive Three Gorges Dam, a few hundred miles east of the earthquake’s epicenter, reported no immediate problems.

At dawn on Tuesday morning in Chengdu, clusters of people were huddled outside, many saying they were too fearful of aftershocks to go indoors. Many wore plastic slickers to protect them from a steady drizzle. Wang Zihong, 35, a businessman from Gansu Province, had spent 12 hours outside his hotel, squatting with others on a street corner.

“It was a terrible shock,” he said. “I couldn’t stand up straight. We were on the second floor and we ran outside.”

Chengdu’s Huaxi Hospital, one of the largest in western China, started receiving patients from surrounding counties on Monday afternoon. By Tuesday morning, 180 patients had arrived from hard-hit surrounding counties.

“Seven thousand people have died in Beichuan, a single county, and we think Wenchuan will be similar, too, because it was the epicenter,” said Kang Zhilin, a spokesman for the hospital. He added: “The first patients who came had jumped from buildings because they were frightened.”

After the tremors shook Chengdu, roughly 4,000 frightened patients had been relocated from wards on the hospital’s upper floors to a courtyard outdoors. By Tuesday morning, the patients were sitting in the rain, covered in plastic.

A woman, Tang Hong, 50, sat beside her injured husband, Yan Chaozhong, in the hospital. They had arrived early in the morning from Dujiangyan County, one place that had suffered heavy damage. They had been inside their fourth-floor apartment when the quake hit. “It was violent,” she said. “Even when we crouched down, it flattened us.”

Ms. Tang said she and her husband had tried to escape down a stairwell, but a second tremor knocked her husband down the stairs, and he broke three ribs. She said four six-story buildings on her street had been flattened. She also wept as she described how a school for handicapped and deaf students collapsed while the children were in class. “It was horrible,” she said. “The entire school building collapsed.”

Minutes after the western temblor struck, a second, smaller quake struck Tongzhou, an outer district of Beijing. Thousands of office workers were evacuated in the capital city, but no damage was reported there.

“I suddenly felt very dizzy, as if I were heavily drunk,” said Zeng Hui, who works on the 22nd floor of an office tower in Beijing. “I thought I was seriously ill, then I looked around and saw my colleagues felt the same way.”

There were reports of fatalities in Chongqing Municipality, near Sichuan, where two primary schools were damaged. Four pupils died and more than 100 others were injured, state media reported. Xinhua devoted extensive coverage to the disaster, publishing regular updates on the situation, including latest death tolls, on its Chinese and English Web sites. The relatively vigorous flow of information and the fast response from top officials and rescue workers stood in stark contrast to the way China handled the Tangshan earthquake, or the way the military junta that rules neighboring Myanmar has managed the aftermath of a giant cyclone that killed nearly 32,000 people there this month, according to Burmese government estimates.

Efforts to reach people near the epicenter of the bigger quake in western China were hindered by damage to the telephone system. Some 2,300 towers used to transmit phone signals had fallen, the country’s main mobile phone company reported. The earthquake also disrupted air traffic control in western China, interfering with flights between Asia and Europe on Monday afternoon, although flight services were restored by the evening.

Cathay Pacific Airways announced that it had canceled two flights between Hong Kong and London — one in each direction — and had delayed the departure of a Monday afternoon flight from Hong Kong to London by 19 hours, to Tuesday morning.

While China Mobile acknowledged extensive damage to its cellphone towers, it is less clear how much damage occurred to the separate communications network that China’s authorities maintain for natural disasters and other contingencies.

Communications equipment vendors attending a police equipment exhibition in Beijing last month said that China maintained a separate network using different frequencies and other equipment from the main cellphone network. The separate network allows the police and other agencies to respond to emergencies even when the main landline and cellphone networks are overwhelmed with calls by residents.

Many Western countries also maintain separate communications systems for emergencies. China is still upgrading its emergency network by buying equipment from Motorola and other foreign companies, communications industry officials said at the exhibition.

Temporary disruption of the air traffic control system in western China strongly suggested that the authorities’ communications gear might also have been damaged at least temporarily. China has worked closely with the Federal Aviation Administration in the United States to improve air safety, and air traffic control operations in the United States have backup communications systems to avoid disruptions.

Jake Hooker reported from Chengdu, and Jim Yardley from Beijing. Ed Wong contributed reporting from Chengdu, and Keith Bradsher from Hong Kong. Zhang Jing contributed research..

Jake Hooker reported from Chengdu, and Jim Yardley from Beijing. Ed Wong contributed reporting from Chengdu, and Keith Bradsher from Hong Kong. Zhang Jing contributed research.

China's Wenchuan Earthquake Recovery Project

Jump to a section.

The initiative

The challenge

The public impact

• Stakeholder engagement Strong
• Political commitment Good
• Public confidence Good
• Clarity of objectives Good
• Strength of evidence Fair
• Feasibility Fair
• Management Good
• Measurement Good
• Alignment Good

Bibliography

In May 2008, an earthquake centred on Wenchuan County in Sichuan province hit Sichuan and the neighbouring province of Gansu. The Wenchuan Earthquake Recovery Project for China followed, bolstered by funding support from the World Bank and relief aid coming from around the world and from all over the People's Republic of China. The project succeeded in its reconstruction goals, rebuilding vital infrastructure and healthcare and education services.

The rebuilding process after the earthquake required significant investment, and the World Bank supported the PRC by helping to finance the Wenchuan Earthquake Recovery Project for China. "In February 2009, the World Bank's Board of Executive Directors sanctioned an emergency recovery project to assist the PRC in the recovery and reconstruction process. A loan of USD710 million to provide finance for the rebuilding of infrastructure and health and education projects in Sichuan and Gansu provinces was sanctioned." [2]

The objectives of the project were to restore essential infrastructure and healthcare and education services to at least the levels that obtained before the earthquake "and where appropriate, to provide for expansion of services, while reducing the vulnerability to seismic and flood hazards, and building capacity of local governments to manage the recovery programme". [3]

At national level, the Ministry of Finance and the National Development and Reform Commission were responsible for the coordination, while the Sichuan Provincial Government and the Gansu Provincial Government were the implementing agencies. The PRC government put together the National Masterplan for the Rehabilitation and Reconstruction of Wenchuan Earthquake (the Masterplan).

Wenchuan County is located in Sichuan Province in the southwest of the People's Republic of China (PRC). "On May 12, 2008, an earthquake of magnitude 8.0 struck southwestern China, centred in Wenchuan County. More than 69,000 people were killed, 374,000 were injured and 18,000 went missing. 34,000 kilometres of highways were destroyed, more than 1,200 reservoirs were damaged, 7444 schools, 11,028 hospitals and many clinics were damaged. Additionally, 5.5 million homes in rural areas and 860,000 in urban areas were severly damaged or destroyed. The estimated loss was RMB855 billion (USD123 billion)." [1]

The Wenchuan Earthquake Recovery Project for China was able to deliver all the strands of its reconstruction work - infrastructure, healthcare, education and defence against future earthquakes - to satisfactory levels. "In Sichuan Province, restoration of essential infrastructure is largely satisfactory with 100% of water supply services completed and 95% of the roads have been completed, with only one road extending beyond loan closing. The health facilities have been 100% restored and are fully operational. The project-financed health and water facilities are operating at levels higher than before the earthquake. The vulnerability to flood and seismic hazard of all project-financed infrastructure has been reduced through much improved seismic engineering standards and relocating facilities to less vulnerable sites." [4]

The 2013 Lushan earthquake demonstrated that the defensive and other work had been carried out effectively. "[It] affected project areas, but the infrastructure and facilities financed by the project withstood the earthquake and little damage was reported compared to other infrastructure in the region. The health and infrastructure agencies at the county level benefited from training to reduce vulnerability to natural hazards and improve operation and maintenance practices." [5]

Stakeholder engagement

The PRC government, the Chinese banks that provided financial loans towards rebuilding, the provincial governments who were the coordinators, the Ministry of Finance, the National Development and Reform Commission were the main internal stakeholders; members of the the international community, such as the World Bank and man foreign nations, were the primary external stakeholders of the recovery project. There was strong involvement from the internal as well as external stakeholders, as the government not only initiated immediate efforts but also planned province-wide reconstruction. Different groups, like the Provincial Programme Leading Group, formed part of the implementation plan. Moreover, the government also requested the international community to provide support, and the World Bank sanctioned a loan to finance the project.

A phased plan was put in place: the first part involved the recovery of Sichuan, followed by a second part which involved the recovery of Gansu province. The PRC government took a strong leadership role, conducted damage and needs assessment and carried out the initial reconstruction planning. There was support from all parts of the society, and many citizens contributed to the relief effort. "The food handout in Jiangyou, a small city 115km (70 miles) east of the epicentre, was being carried out by volunteers from an ad hoc group of private catering companies from another province." [6]

Many countries also offered help, some in terms of financial assistance and others in terms of humanitarian aid. "Immediately after the massive earthquake, the government initiated relief efforts and mobilised 100,000 personnel to aid in the rescue efforts. However, within two days, the Government of China made a formal request to the international community asking for support in the relief efforts." [7] There was aid from countries such as Germany, the UK and Saudi Arabia: "Saudi Arabia's King Abdullah bin Abdul-Aziz has decided to donate 50 million US dollars in cash and 10 million dollars worth of relief materials".[8]

The stakeholders in the provinces of Sichuan and Gansu were also engaged. "At the provincial level, each province has established a Provincial Programme Leading Group (PPLG), chaired by a vice-governor and including directors of relevant agencies.  The PPLGs will set project policy and guide implementation." [9]

Political commitment

There was strong political will directed towards relief and reconstruction activities after the earthquake. The relief effort was initiated immediately after the earthquake, and the prime minister, Wen Jiabao, flew to Sichuan within hours and was involved in its direction. "The prime minister, Wen Jiabao, appears to have earned considerable kudos by rushing to the scene and staying there for five days to direct relief operations, at one point in tears." [10] He told state-run media that China faced “a major disaster” and called for “calm” and “courage”.

President Hu Jintao has called for an “all-out” effort to rescue survivors and to provide for the injured.

"More than 100,000 troops and police have been deployed to help survivors and to rescue people trapped by rubble and landslides. Hopes of finding more are fast dwindling." [11]

Public confidence

The prime minister's visit to Sichuan drew praise from the public. "'He really loves the common people and we can see this is not an act,'" said Wang Liangen, 72, a retired maths teacher from the devastated city of Dujiangyan, who watched last week as the prime minister climbed over the wreckage of a school where hundreds of children were buried. 'He has brought the people closer together and brought the people closer to the government.'" [12]

This increase in public confidence was thought to be likely to persist. "'Wen's efforts will absolutely leave a long-lasting influence on government work in the future,' said Fang Ning, a political scientist at the China Academy of Social Science in Beijing. 'His quick response and immediate appearance will set a precedent for other officials.'" [13]

Clarity of objectives

The objectives of the Wenchuan Earthquake Recovery Project for China were clearly defined by the PRC government, and its Masterplan indicated that there was a well-thought-out strategy. Moreover, the outcome objectives address the relevant issues of:

Reconstructing the essential infrastructure.

Restoring healthcare and education services.

Reducing the vulnerability of the region to seismic and flood hazards.

Building the capacity of local government to manage the recovery programme.

Strength of evidence

The PRC government worked on the Masterplan, which addressed needs assessment, initial reconstruction planning, and other activities. People were then consulted and the plan was finally signed off by the State Council. "The Masterplan was approved by the State Council on August 27, 2008, following public consultation." [14]

Moreover, the World Bank, which has decades of global experience in providing post-disaster reconstruction, management and prevention, assisted the government by providing additional support and sector-specific best practice. "The Bank has also provided considerable support to the government on the knowledge side, including a June 12, 2008 an international workshop, Earthquake Recovery and Reconstruction: International Experience and Best Practice, co-organised with the Ministry of Finance. Immediately following the workshop, the Bank provided 17 sector-specific good practice notes to support reconstruction planning that informed the development of the Masterplan." [15]

Feasibility

The financial feasibility was partly addressed by the funding of USD710 million from the World Bank, along with foreign aid from around the world. The PRC government also encouraged firms to donate. "The government has been encouraging firms to give more generously to worthy causes. From this year it has increased tax incentives for corporate donations to charities." [16]

The prime minister mobilised the available human resources in the relief efforts, including 100,000 troops and police (see Political Commitment above) and local citizens.

The Ministry of Finance and the National Development and Reform Commission coordinated the relief effort at the national level. "At the provincial level, each province has established a Provincial Programme Leading Group (PPLG), chaired by a Vice-Governor and including Directors of relevant agencies.  The PPLGs will set project policy and guide implementation.  In Sichuan, the provincial government has established a coordination office to act as a secretariat for the PPLG.  In Gansu, the Provincial Finance Bureau will assume this role... Sichuan will utilise two existing PPMOs, each headed by a director, one reporting to the Provincial Construction Commission and the other reporting to the Provincial Health Bureau. County level PLGs and Project Implementation Units (PIUs) are being established in the project counties, in a similar manner to the provincial level." [17]

Measurement

The impact of the project has been monitored consistently and the results have been published on the World Bank website. Moreover, the indicators capture the exact amount of work completed in both provinces, Sichuan and Gansu, and clearly provide information on the status of the project. The main parameters include: the proportion of water supply services completed (100%); the proportion of road reconstruction that has been completed (95%); and the proportion of health facilities that have been restored (100%).

There was good alignment between the various stakeholders of the project. In terms of financial support, it was provided by the World Bank, which released the required funding resources. Consulting services were also made available by the World Bank for external monitoring. The planning for the Wenchuan Earthquake Recovery Project for China was done at national government level and set out in the Masterplan, while implementation was done at province level through the PPLGs and PPMOs. Coordination responsibility was with the Ministry of Finance and the National Development and Reform Commission.

Wenchuan Earthquake Recovery Project (Report No. AB4291) , 31 October 2008, The World Bank

The earthquake in Sichuan: China helps itself , 22 May 2008, The Economist

More countries offer aid to quake-hit China , 15 May 2008, www.news.cn

In Quake, Apotheosis of Premier ‘Grandpa' , Andrew Jacobs, 21 May 2008, The New York Times

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Benchmarks: May 12, 2008: Earthquake devastates western China

by Sam Lemonick Monday, August 31, 2015

Damage by earthquake-induced landslides in May 2008 was catastrophic and accounted for many casualties. Deadly debris flows hit the town of Qushan, which was destroyed by strong shaking and landslides. Credit: USGS, David Wald.

Just before 2:30 p.m. local time on May 12, 2008, a magnitude-7.9 earthquake shook Sichuan province in Western China. One eyewitness recalls seeing a mountain “blowing up” and boulders two-stories tall crashing into gorges. Another recalls thinking there had been a natural gas explosion, while a third described a hill split in half. It was the country’s largest earthquake in more than 50 years, and it left 18,000 people missing and presumed dead, nearly 375,000 injured and more than 69,000 confirmed fatalities.

Five years later, the wounds have begun to heal: Buildings have been rebuilt and lives are returning to normal. Despite that, deep grief and resentment remain about what locals see as the government’s failure to adequately protect people — especially children — and opinions differ on the success of rebuilding efforts.

The Great Sichuan Earthquake

A woman is rescued from the rubble following the Sichuan earthquake, which struck on May 12, 2008. Credit: courtesy of Miniwiki.org, Creative Commons Attribution-ShareAlike 3.0 Unported.

The Sichuan, or Wenchuan, quake struck on the eastern edge of the Tibetan Plateau, in an area with some of the most extreme topography on the planet. The rupture occurred on the Longmenshan Fault, a thrust fault associated with the collision between the Indo-Australian and Eurasian plates; the collision is uplifting Western China at a rate of roughly 5 millimeters a year. Walking across the fault, one would climb nearly 6,000 meters in 50 kilometers from the low-lying Sichuan basin to the tops of the tallest peaks.

The U.S. Geological Survey (USGS) located the epicenter of the quake about 80 kilometers west-northwest of Sichuan’s capital, Chengdu, and about 1,500 kilometers southwest of Beijing. From its hypocenter 19 kilometers below the surface, slip during the earthquake propagated northeast along the fault. According to both seismic data and survivor accounts, the earthquake lasted about two minutes. When the shaking stopped, the two sides of the fault had been offset by nine meters.

Reports of tremors came from thousands of kilometers away in Russia, Taiwan and Thailand, where office buildings reportedly swayed for several minutes. Workers evacuated office buildings in Beijing and in Shanghai, more than 1,600 kilometers away, about the distance from Boston to St. Louis.

Despite its proximity to the epicenter, downtown Chengdu — a city of 6.7 million people — suffered only minor damage. Reporters touring the city after the disaster saw cracks in the walls of buildings, although none had collapsed. In fact, all of the major cities in Sichuan suffered only moderate damage. Meanwhile, some towns in the surrounding countryside were destroyed.

Local and international engineers ascribe this dichotomy in part to China’s adoption of new building codes after a 1976 earthquake in northeast China that killed several hundred thousand people. New construction in China’s fast-growing cities was held to the stricter standards, while older buildings were often not upgraded.

Structures built with brick, mud and other materials before the codes were in place failed, often with tragic results. Among the most visible of these were the many schools that collapsed entirely. News reports worldwide featured heartbreaking pictures of parents who lost their children in devastated school buildings. A year after the quake, the education minister of Sichuan province reported that 5,335 schoolchildren had died in the earthquake.

Aftershocks and Landslides

This elevated highway was taken down by the Chinese Army because it was damaged beyond repair by the magnitude-7.9 quake. The road was the main route into the Beichuan area. Credit: USGS, Lynn Highland.

Numerous aftershocks — as many as 100 within the first three days — threatened survivors and delayed rescue efforts in the weeks following the main shock. As late as August, three months after the main shock, the area was hit by a magnitude-6 aftershock.

In addition to the danger of the aftershocks, numerous landslides in the mountainous region blocked rivers, forming 34 so-called quake lakes. The government evacuated hundreds of thousands of people downstream from some of these lakes in fear that the natural dams would burst, and the army airlifted in construction equipment to build sluices to release the water. Some feared that man-made dams might also give way. Despite damage to many, none failed.

Landslides that occurred both during and after the quake severely hampered the relief effort. Bridges and many vital roads were destroyed or covered in rubble. The Chinese military deployed tens of thousands of soldiers within a day of the quake, but they could not reach all of the remote areas most in need of help. One village reportedly spent five days without food and water until a rescue team could reach it.

Relief teams and supplies were flown in from neighboring countries and as far away as the U.S., while money came from around the world. Survivors in Chengdu also made extensive use of the Internet to get information and help coordinate relief and rescue operations.

The Agriculture Ministry reported that among the nonhuman victims of the earthquake were as many as 12.5 million farm animals, mostly chickens. Sichuan is also home to many of the world’s giant pandas, as well as a number of preserves and breeding centers. One panda in captivity died when the wall of its enclosure collapsed after a landslide at the Wolong Nature Reserve. Mud and debris flows also destroyed large swaths of bamboo forest, critical habitat for the wild panda population.

In the Aftermath, Seeking a Cause

An elderly woman in an emergency shelter after the quake. Credit: USGS.

As was apparent in Italy following the 2009 L’Aquila earthquake, many people expect geologists to be able to predict earthquakes, and the same was true in the aftermath of Sichuan. Many blamed the government for failing to take earthquake predictions seriously, pointing to a 2002 statistical analysis by Chinese seismologist Chen Xuezhong that suggested a strong possibility in the coming years of an earthquake in Sichuan greater than magnitude 7.

But the most contentious issue following the disaster was the charge that by overlooking corruption in the construction of schools, the government had failed to keep Sichuan’s children safe. Ultimately, the government’s tally of collapsed classrooms came to 6,898. Observers were quick to note that many schools collapsed while other nearby buildings suffered little damage.

The updated building codes announced after the 1976 earthquake held schools to an even stricter standard than residential buildings, and the government set out to renovate or rebuild schools that were out of code. After the 2008 quake, parents, journalists, activists and others accused school builders of ignoring the 1976 codes. Chinese critics use the colloquialism “tofu-dreg projects” to describe the shoddy construction of many schools.

An investigation by the Chinese magazine Caijing into why five schools in Sichuan had collapsed found multiple structural failures. Concrete walls, ceilings and floors in the schools had not been reinforced with steel rods called rebar, which gives concrete strength and flexibility, the investigation found. During the earthquake, the concrete simply cracked and crumbled without this internal steel structure.

As one headmaster interviewed by the magazine pointed out, the new schools replaced mud buildings that had leaked in the rain. Prior to the quake, parents and students had been happy to even have a new school, regardless of whether it met earthquake building standards. Bureaucracy, the magazine added, bogged down building inspections.

The Chinese government offered monetary compensation to parents who lost children and lifted its one-child policy for those who had lost an only child. In late May 2008, the government also promised a thorough investigation and severe punishments for construction companies and officials involved in building substandard schools. Despite several further announcements that year indicating the inquiry was in progress, no final report has been announced, at least in Western media. The government has, however, released new, stronger building codes.

Efforts to Rebuild

A residential building in Hanwang that was destroyed by the earthquake. Credit: USGS, Sara C. Behan.

Five years after the quake, the Chinese government and mainstream Chinese media have proclaimed “victory” in the rebuilding effort. The government committed $146 billion to relief, rescue and rebuilding. The World Bank reports that the Chinese government commissioned more than 41,000 reconstruction projects and completed 99 percent of them within two years.

In addition, China drew praise for its willingness to accept help from the rest of the world. In particular, the World Bank praised the government’s ability to marshal and direct the combined efforts of agencies, private organizations and individuals. One innovation was to pair counties in unaffected parts of the country with Sichuan counties to help rebuild.

The Chinese government also reformed building codes once again. City layouts were reorganized and damaged hospitals and sanitation plants were modernized. Schools were rebuilt.

Others, however, say that some parts of Sichuan still look like they did five years ago and some people are still living in temporary shelters. One Chinese writer who visited the area near the epicenter last summer reported that many roads remained unrepaired. He wrote that a 26-kilometer car ride took more than three hours because of damaged roads, and suggested the roads are ignored by officials focused on more visible “vanity” projects.

It may ultimately take years before the region fully recovers from the disaster.

In the meantime, the quake continues to be studied by seismologists both in China and around the world. After the quake, the China Geological Survey began a joint project with the USGS to study how to better predict landslide risks. A 2009 study in Science suggested that a dam in Sichuan completed in 2006 might have contributed to the earthquake. The authors proposed that the weight of the impounded water — 320 million metric tons by their estimate — could have altered the pressure on the fault and triggered the earthquake.

If there is a silver lining to the tragedy, it’s that researchers have studied the response to the quake to find better ways to save lives in the future. A study published last year looked at the medical response to the quake, from the initial search for survivors to epidemic outbreak programs in areas that lacked basic sanitation and medical care long after the quake. Experts have pointed to China’s coordinated response — between military and civilian leadership, between national, provincial and local governments, and between affected and unaffected parts of the country — as one of the most successful and important elements in the quake’s aftermath.

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Sovereignty Issues in a Humanitarian Emergency: The 2008 Sichuan Earthquake

• First Online: 02 September 2018

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• Wooyeal Paik 6  

Part of the book series: Security, Development and Human Rights in East Asia ((SDHRP))

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China’s political decision to accept foreign humanitarian aid and workers during the Sichuan Earthquake was occasioned by its greater political and economic capacity and national confidence. The Chinese government was confident in its political and economic capacities; the country had seen economic development owing to the reforms and open policies that had taken place since 1978, and the consolidation of the party-state system and improved political legitimacy. At the same time, Beijing was concerned about the possibility that some anti-regime forces might take advantage of the foreign presence during chaotic disaster situations. This political logic revolves around the issue of sovereignty and has important implications for human security in disaster situations.

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Xinhuanet. 2008a. Quanwei Fabu: Sichuan Wenchuan Dizhen Kangzhen Jiuzai Jinzhan Qingkuang [Report on Progress of Sichuan Earthquake]. Xinhua News Agency , August 25. http://news.xinhuanet.com/newscenter/2008-08/25/content_9707753.htm .

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Expert Source #2. 2017. Interviewed by author in Seoul, March 16.

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Expert Source #5. 2017. Interviewed by author in Seoul (via email and phone), March 25.

Expert Source #6. 2017. Interviewed by author in Seoul, April 6.

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Paik, W. (2019). Sovereignty Issues in a Humanitarian Emergency: The 2008 Sichuan Earthquake. In: Hernandez, C., Kim, E., Mine, Y., Xiao, R. (eds) Human Security and Cross-Border Cooperation in East Asia. Security, Development and Human Rights in East Asia. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-95240-6_3

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Lessons from the Sichuan earthquake

• Issue 43 The role of affected states in disaster response
• 1 Aid and access in Sri Lanka
• 2 When the affected state causes the crisis: the case of Zimbabwe
• 3 Humanitarian governance in Ethiopia
• 4 The silver lining of the tsunami?: disaster management in Indonesia
• 5 Land and displacement in Timor-Leste
• 6 Lessons from the Sichuan earthquake
• 7 Britain and Afghanistan: policy and expectations
• 8 Are humanitarians fuelling conflicts? Evidence from eastern Chad and Darfur
• 9 Lessons from campaigning on Darfur
• 10 Supporting the capacity of beneficiaries, local staff and partners to face violence alone
• 11 Stuck in the 'recovery gap': the role of humanitarian aid in the Central African Republic
• 12 Out of site, out of mind? Reflections on responding to displacement in DRC
• 13 Making cash work: a case study from Kenya
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A t 2:28pm on 12 May 2008, a powerful earthquake struck China’s Sichuan Province. Some 87,500 people were killed, 45.5m affected and 14.4m displaced . Economic losses were estimated at $86 billion, with 21m buildings damaged. According to a recent DFID report, the earthquake drove an estimated 10m people below the poverty line, with overall poverty in badly affected areas increasing from 11% to 35% of the population . Despite the extent of the devastation, this earthquake was not China’s first experience with natural disaster. In fact, four of the ten most destructive earthquakes on record have occurred in the country, giving China extensive experience in coping with such emergencies – experience that was put to good use in the response to the Sichuan earthquake.

The role of the state in the earthquake response

The response to the earthquake was dominated by the Chinese government. Although the government invited international humanitarian assistance, few international NGOs engaged directly in emergency response, for a number of reasons. First, Sichuan was probably not a priority for organisations already involved in responding to concurrent disasters including Cyclone Nargis, which made landfall in neighbouring Myanmar just ten days before the earthquake. Second, lack of access and local experience may have prevented some INGOs from initiating operations in Sichuan. Third, in the context of an economic boom with over 10% annual growth since 2002, it is possible that international actors believed that the Chinese government had the capacity to respond. Although full recovery remains a distant reality for many, the Chinese state-led response to the Sichuan earthquake has generally been characterised as efficient and comprehensive. According to the government, despite the extent of the devastation, disease outbreaks were avoided, populations in danger from subsequent flooding or landslides were safely relocated, medical services were generally restored rapidly and a return to the baseline mortality rate was achieved relatively quickly. The direct provision of aid by the Chinese military was a key element in the emergency response phase. Officials reported that, within 14 minutes of the earthquake, the central government had dispatched the People’s Liberation Army (PLA) to the affected areas, and within days 113,000 soldiers and armed police had been mobilised. Of the nine government working groups set up for the relief effort, six were supported by the military.

One challenge to learning from the earthquake response is that data has not been made widely available by the government. For example, in the health sector Xinhua News reported that, as of late May, 45,000 medical workers were contributing to care following the earthquake, with 650 devoted to epidemic control . A Health Ministry representative also announced that the relief effort had eliminated the risk of a disease outbreak , and had even brought about a decline in infectious disease incidence in the worst-hit areas, compared to previous years. Unfortunately, evidence is not offered to support this statement, or similar statements in other sectors. Information from the few active organisations (including Médecins Sans Frontières, UNCEF, AmeriCares Foundation and Oxfam-Hong Kong) only capture the relatively small-scale activities of these agencies.

While working for a US-based organisation in two of the worst-affected counties in Sichuan directly following the earthquake, over the course of three months I encountered no other international NGO working on the ground. This is consistent with the general pattern of minimal INGO engagement in the emergency response. To accomplish our mission to re-establish referral care and provide urgently needed medical supplies, I coordinated all efforts in direct partnership with government agencies and the provincial and county-level Health Bureaus. In my day-to-day work, it became clear that the overall success of the government’s response was made possible by its authoritarian position, its experience of managing large population movements and natural disasters and the rapid deployment of the military. These three elements enabled the government to avoid or minimise many of the problems common to disaster response.

Mitigation strategies included an immediate emphasis on controlling infectious disease through widespread medical care and surveillance, the provision of tents for shelter (albeit insufficient in number at the outset and eventually upgraded to temporary, prefabricated structures), maintenance of security and the rule of law through substantial police and military deployments, traffic and supply-chain management at the regional and local level, as well as the triage of patients, the deployment of qualified volunteers and the efficient management of in-kind donations. For instance, as large quantities of unsolicited foreign medicines and supplies accumulated in airport warehouses (donated primarily by organisations without a physical presence in Sichuan), the provincial health bureau coordinated with the government body in charge of volunteers to assign pharmacology students on holiday to sort, translate and test these donations. Additionally, the movement of people was strictly regulated in the affected areas. For months, police and military roadblocks prevented non-essential personnel from entering the disaster zone (personnel also sprayed traffic passing through with disinfectant in the belief that this would reduce the risk of disease). These authoritarian measures largely succeeded in saving lives and reducing the secondary disasters of disease, flooding and damage from strong aftershocks; however, these results came at the expense of personal liberties, access to affected areas and, in some cases, the unquestioned acceptance of sub-standard living conditions.

Although the Chinese and foreign press have reported outrage among some parents who lost children in collapsed schools, the overall reaction of direct beneficiaries as regards the government aid they received was outwardly positive. Affected populations worked to reconstruct markets and establish a home in their government-issued tents, while awaiting further instructions from the local authorities. This differs from my experience in the North-West Frontier Province (NWFP) in Pakistan following the 2005 earthquake, where there was an elevated sense of anxiety, especially in remote rural areas. For example, in the Allai Valley of NWFP (population around 100,000), insufficient assistance saw virtually every family electing to migrate to camps at a lower elevation or moving to live with relatives elsewhere. Although some seasonal migration takes place annually in the region, post-earthquake migration occurred on a large scale, and was even encouraged by some NGOs. By contrast, the millions of people affected by the Sichuan earthquake, even those living in mountainous rural areas, stayed in close proximity to their destroyed homes.

In the days and months following the earthquake, many familiar disaster response tools and mechanisms were not utilised: there were no cluster meetings, and the Sphere Standards and other guidelines common in the humanitarian community were not in evidence. Instead, a coordinated response was achieved through the government’s hierarchical approach, and decisions followed the chain of command from national to provincial and down to the prefecture and county levels. In terms of coordination, after working side-by-side with my health bureau counterparts daily for nearly three months, I did not observe a single complaint about unwarranted time spent meeting donors or international aid groups (though there were complaints about the unaccompanied relief material pouring into the provincial airport and bonded warehouses). Unlike the direction eventually chosen by the government of Pakistan following the 2005 earthquake, the Chinese authorities did not immediately establish a parallel relief agency. Instead, relief activities were partitioned along the lines of the cluster approach , with the formation of working groups roughly corresponding with government agencies – an important approach for ongoing coherence in policy and practice.

Another partnership strategy used in the aftermath of the earthquake which may prove a model for long-term recovery was the ‘twinning’ of several badly affected counties and cities with other Chinese provinces and municipalities. These partnerships aimed to assist affected areas with resources, personnel and moral support for recovery. Teams of doctors, public health professionals and sanitation and disease control experts were immediately dispatched to the affected partner county; a reported 1–3% of the annual gross domestic product of sponsor provinces was pledged towards long-term recovery efforts in the affected county for at least three years. For example, Wenchuan County, the epicentre of the earthquake, was paired with wealthy Guangdong Province for long-term reconstruction assistance, including the provision of medical personnel to replace staff lost in the earthquake, and the training of Wenchuan-based staff in teaching hospitals in Guangdong.

The state-led response focused on efficiency in providing resources and services to the largest number of people possible. However, this came at a price; for instance, in order to get food to everyone who needed it nutritionally deficient instant noodles were provided for days on end in some locations. Shelter could not be manufactured quickly enough (despite temporary state seizure of suitable textile factories), resulting in up to 12 individuals sharing one family-size tent. The absence of water-borne diseases may actually be attributed to a culture of boiling water, rather than the government’s pervasive disinfection campaign. It is clear that action to protect against a secondary disaster did not come from abroad but from within China. Although the state deserves praise for its handling of the response, there are areas for improvement.

Lessons for the future

In the aftermath of every major recent natural disaster, from the Indian Ocean tsunami to the Pakistan earthquake and even the cyclone in Myanmar, a deluge of assistance from international non-governmental organisations has had a significant impact. This was not the case in China, where very little international assistance was provided and the response was very largely state-led – a vast relief effort launched by the Chinese government and carried out by hundreds of thousands of soldiers, civil servants and civilian volunteers. The government’s approach to the emergency response was effective in several respects; the setting of clear criteria and appropriate restrictions on unsolicited in-kind medical or other supplies, for instance, led to the more efficient use of resources and eased the supply-chain bottlenecks common in other disasters of similar magnitude, and overall the response was crucial in saving many lives. At the same time, however, greater efforts could have been made to enlist the support of specialised international agencies in specific areas, including emergency shelter, livelihoods and health. In the health sector, for instance, very little attention was paid to psychosocial and mental health programmes, especially among elderly people, who may well have benefited from specialised support from the humanitarian community. Finally, although the state deserves praise for its handling of the response, a lack of transparency in terms of specific data and details of the response have concealed many of these successes, as well as obscuring areas for improvement.

Brian Hoyer is an independent consultant. His email address is [email protected] .

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Issue 43 Contents

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• The geography ...
• Sichuan Earthq...

Sichuan Earthquake (2008): lessons learnt?

Key questions.

How do earthquakes happen?

What can be done to reduce the impact of earthquakes on people and places?

Earthquakes affect a huge number of people

The earth's crust is made up of huge tectonic plates which move slowly on the molten mantle beneath the earth's crust. The plates meet on conservative (plates slide past each other), destructive (plates collide into each other) and constructive (plates move away from each other) plate boundaries. Earthquakes occur along these plate boundaries or fault lines.

The impact of the 2008 Sichuan earthquake

The Sichuan earthquake occurred along a destructive plate margin, where the Indo-Australian Plate and the Eurasian Plate collide. The earthquake occurred along a mid-fracture (known as the Yingxiu-Beichuan fracture). The earthquake in Sichuan was a magnitude 7.9 on the Richter Scale, occurred at a depth of 19 meters and its epicentre was in Wenchuan, north-east in the Sichuan Province.

Dams - it is estimated that approximately 400 dams have been affected by the Sichuan earthquake (2008). The safety of these dams is a concern as many may not have been designed to withstand earthquakes. Some Chinese and US scientists believe that the quake could have been triggered by the huge Zipingpu dam. The dam is 50 stories tall and holds back several hundred million tons of water in the Zipingpu reservoir. It is situated just 500 meters from the Beichuan fault, only 5.5 kilometres from the epicentre of the earthquake. The Beichuan fault would have been under natural stress but this would have been multiplied by 25 times due to the weight of the water in the reservoir.

The Sichuan earthquake killed approximately 70,000 people, although other estimates put the total far higher. More than 10,000 children were killed when their schools collapsed or were buried beneath landslides. At least 4,727 children were orphaned as a result of the quake. The quake also left five million people homeless and 375,000 people injured. The impacts of this quake will be felt for generations to come especially as families tend to have only one child due to China's strict ‘One Child Policy'. Other impacts of the quake include: the collapse of buildings, particularly in the Beichuan County, the collapse of two chemical plants which led to the leakage of 80 tons of liquid ammonia which buried many people. Schools, homes and buildings were destroyed.

Reducing the impact of Earthquakes on people and places

The Sichuan earthquake killed many people due to unsafe building construction, particularly that of schools which were referred to by local people as ‘tofu dregs'. There is a great deal in modern construction techniques which can be done to reduce the impact of earthquakes on people and reduce the death toll. Within the USA, there are strict building codes for buildings within earthquake zones. These can help ensure minimum standards of building. In addition, instruments are installed in public buildings to measure the response of buildings to earthquakes. The response of buildings to earthquakes can be measured and then alterations to their construction can be made. It is also considered that metal buildings are far better at withstanding an earthquake than concrete ones because metal ones are more ductile (they can bend and flex without breaking). It is also important to consider the distribution of weight. A building which is top heavy is much more likely to fall than a building which is light weight on the top. Therefore, an earthquake building should be constructed of steel rebar but should be framed with lighter materials in the upper floors and have a heavily reinforced lower section. However, just because it is made of metal, does not mean it will not fall down during an earthquake.

In the USA, residential buildings are designed so that the roof falls directly in the middle of the room but stays up near the wall. People are then advised to take shelter in the doorways and away from the middle of the room. Scientists have considered the side to side movements during an earthquake in the design of earthquake proof buildings. However, they are now considering the up and down (vertical) movements also. To ensure that buildings are able to move in all directions, scientists suggest isolating the building from the ground in order to reduce the vibrations from an earthquake. Instead of having the foundation rest directly on soil or rock, use a material that will provide a cushioning effect and reduce the energy transfer from the ground to the building. Also, using liquid dampers. These are like putting a water tank at the top of the building. These are particularly useful where there are high winds.

Use the BBC's interactive earthquakes resource (online or print out) to explore how earthquakes happen. Note down key words from this resource and write a short paragraph summarising how earthquakes happen.

Main Activity

Comparing two earthquakes in China: Tangshan (1976) and Sichuan (2008)

Watch and read the PowerPoint China Earthquakes : Learning from the past and read the Sichuan quake factfile, referring particularly to the section "Poorly constructed schools".

Complete the card sort activity entitled Learning from the past: Tangshan and Sichuan compared. By doing this you start to think about how the two earthquake case studies are similar/different to each other.

Then produce a Venn-diagram on a large piece of paper to compare the two earthquakes. How were the earthquakes similar? How were they different? Once you have completed your diagram discuss and share your ideas with the class.

For the second part of this activity use the resource sheet Learning from the past: Changing the future. Write an email response to the Chinese Government with recommendations of how they could prepare better for another earthquake. Use this ScienceDaily link and search ‘Earthquake resistant building' in Google images to help.

Feed back your recommendations on how the Chinese government could reduce the impact of earthquakes in China to the class.

Extension activity

Design your own earthquake resistant building. Here are some key points to think about in planning its construction: How will you stop the building from falling down? If the building does not fall down, how will you prevent accidents both inside and outside as it moves? What about falling glass and rubble on the people outside?

File name Files

The Geography of Science Lesson 3 Teacher's Notes

The Geography of Science Lesson 3 Teacher's Notes (1)

The Geography of Science Lesson 3 China Earthquakes: Learning From The Past

The Geography of Science Lesson 3 Learning From The Past: Tangshan and Sichuan Compared

The Geography of Science Lesson 3 Learning From The Past: Tangshan and Sichuan Compared (1)

The Geography of Science Lesson 3 Learning From The Past: Changing The Future

The Geography of Science Lesson 3 Learning From The Past: Changing The Future (1)

The Geography of Science Lesson 3 Sichuan Earthquake Factfile

The Geography of Science Lesson 3 Sichuan Earthquake Factfile (1)

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Open Access

Peer-reviewed

Research Article

Rapid determination of seismic influence field based on mobile communication big data—A case study of the Luding Ms 6.8 earthquake in Sichuan, China

Roles Formal analysis, Software, Writing – original draft, Writing – review & editing

Affiliation Zhejiang Earthquake Agency, Hangzhou, China

Roles Data curation, Formal analysis, Methodology

* E-mail: [email protected]

Affiliation Beijing Earthquake Agency, Beijing, China

Roles Resources, Software, Supervision

Affiliation Zhejiang Development and Planning Institute, Hangzhou, China

Roles Data curation, Formal analysis

Roles Conceptualization

Roles Data curation

• Dongping Li, 
• Qingquan Tan, 
• Zhiyi Tong, 
• Jingfei Yin, 
• Min Li, 
• Huanyu Li, 
• Haiqing Sun

• Published: May 10, 2024
• https://doi.org/10.1371/journal.pone.0298236
• Peer Review
• Reader Comments

Smartphone location data provide the most direct field disaster distribution data with low cost and high coverage. The large-scale continuous sampling of mobile device location data provides a new way to estimate the distribution of disasters with high temporal–spatial resolution. On September 5, 2022, a magnitude 6.8 earthquake struck Luding County, Sichuan Province, China. We quantitatively analyzed the Ms 6.8 earthquake from both temporal and geographic dimensions by combining 1,806,100 smartphone location records and 4,856 spatial grid locations collected through communication big data with the smartphone data under 24-hour continuous positioning. In this study, the deviation of multidimensional mobile terminal location data is estimated, and a methodology to estimate the distribution of out-of-service communication base stations in the disaster area by excluding micro error data users is explored. Finally, the mathematical relationship between the seismic intensity and the corresponding out-of-service rate of communication base stations is established, which provides a new technical concept and means for the rapid assessment of post-earthquake disaster distribution.

Citation: Li D, Tan Q, Tong Z, Yin J, Li M, Li H, et al. (2024) Rapid determination of seismic influence field based on mobile communication big data—A case study of the Luding Ms 6.8 earthquake in Sichuan, China. PLoS ONE 19(5): e0298236. https://doi.org/10.1371/journal.pone.0298236

Editor: Rahul Priyadarshi, Siksha O Anusandhan, INDIA

Received: September 15, 2023; Accepted: January 19, 2024; Published: May 10, 2024

Copyright: © 2024 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: This study was supported by the Scientific Research Fund of Institute of Engineering Mechanics, China Earthquake Administration (2021D07), Project of Spark Program of Earthquake Sciences, China Earthquake Administration (XH23001B), Zhejiang Provincial Natural Science Foundation of China(LTGG24D040002).The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

For a long time, most of the disaster distribution data related to post-earthquake rescue has been obtained by using expensive special equipment. However, due to the uncertainty of when and where an earthquake disaster may occur, the large-scale deployment and maintenance of professional equipment can incur considerable costs. It is also difficult to ensure the connectivity of this equipment and the full coverage of all affected people when an earthquake occurs [ 1 ]. With their ever-increasing popularity, smartphones, as the most widely used electronic devices, have been equipped with computing, communication, storage, and sensing capabilities. Even in disaster scenarios, the probability of people holding smartphones is still very high. Therefore, smartphones are capable of constructing direct field disaster distribution data with low cost and high coverage. The large-scale continuous sampling of mobile device location data provides a new way to estimate disaster distribution with higher temporal–spatial resolution [ 2 ].

Several earthquakes in recent years have shown that when the intensity of the epicenter reaches VIII, communication base stations will usually be out of service, which directly leads to a precipitous drop in the acquisition of smartphone location data after an earthquake. A large amount of smartphone location data disappears at a large scale after an earthquake, and the closer to the hardest hit area, the more obvious the data drop is. In addition, in the event of a nondestructive earthquake, there will be such phenomena as an increase in communication volume at the epicenter and location changes due to the flow of people avoiding the disaster. The change and distribution of mobile communication big data play an indicative role in estimating the extent of devastation in the first instances [ 3 ]. After the Wenchuan earthquake in 2008, communication facilities in the disaster area were severely damaged, and many mobile base stations stopped service, resulting in communication outages in the areas where these stations are located. We analyzed the affected areas and the extent of devastation by collecting the out-of-service data of mobile base stations and mapped the distribution range of the affected areas, which was highly consistent with the intensity distribution data obtained from the post-earthquake field survey ( Fig 1 ).

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

https://doi.org/10.1371/journal.pone.0298236.g001

(We have collected information after the Wenchuan Ms 8.0 earthquake through 2 specialized BBS forums: https://www.txrjy.com/ ; https://club.mscbsc.com/ . Although the data we collected are incomplete and limited, we still have relatively and accurately demonstrated the distribution of the seismic influence field and the approximate area of the macroscopic epicenter through spatial interpolation).

With the prevalence of smartphones and the development of mobile Internet services, in combination with the popularization of global positioning technology, the technology of population data estimation based on precise geographic location has become increasingly mature [ 4 ]. When a user enters a certain geographic space, it is possible to obtain and verify the user’s location information, and the current population size of a geographic space can be inferred through a differentiated model. After an earthquake, we can use the changes in smartphone thermal data to infer the extent of damage to mobile communication infrastructure caused by the earthquake [ 5 , 6 ]. The data sources involved in this work are the various smartphone APP vendors. Because the data is location data of point groups reported in a certain area, personal privacy is not involved, and the data size covers billions of terminals.

Since 2012, telecom operators have successively applied location data analysis to mobile networks. Verizon, a U.S. operator, engages in business consulting by collecting information on the apps used and websites visited by its users, as well as their geographic locations [ 7 ]. The highway monitoring project of French telecom operator Orange and the smart footprint project of Spanish telecom company Telefonica are designed to provide location-derived information to users. Represented by the I-LOV project in Germany, many research institutions have participated in the construction of disaster emergency rescue systems based on smartphone signal searches [ 8 ]. At the World Internet Conference in Wuzhen in November 2014, the comprehensive analysis of China Mobile big data demonstrated a dynamic people flow big data analysis platform, and in December of the same year, the mobile location of big data provided decision-making information for the government in the emergency response to the stampede at the Bund in Shanghai [ 9 , 10 ]. "Location big data" is not merely the result of technological transformation in the computer industry. Cross-border thinking and big data thinking are also applicable to various other industries. Similar work has been conducted in the field of natural disaster research, where MyShake has been developed and built as a global smartphone seismic network that can detect and be triggered by P waves. With the constant downloading of MyShake, the scale of the seismic network has been rapidly developed, forming a global seismic network that utilizes personal smartphones to provide acceleration waveforms [ 11 ]. Since 2017, experts have started participating in the research on rapid acquisition of disaster situations and post-earthquake crowd flow analysis based on mobile Internet location data, and some scholars have begun using mobile location information data to study and track the distribution of earthquake-stricken areas and the responses of people after the earthquake [ 12 ]. Researchers have used smartphone data to analyze the crowd dynamics during the 2017 Jiuzhaigou earthquake. By analyzing the call and SMS data, they identified the densely populated areas and the migration trajectories during the evacuation process, which provided support for the development of effective urgent evacuation strategies [ 13 ]. The MIT Media Lab used smartphone data to analyze changes in human mobility and access to critical urban services in the aftermath of the 2015 Nepal earthquake, and the findings underscored the importance of considering post-disaster mobility dynamics in emergency response and recovery planning [ 14 ]. European-Mediterranean Seismological Centre used smartphone data to dynamically assess post-earthquake population displacement. By analyzing detailed call records [ 15 ], EMSC identified changes in human mobility patterns in the affected areas and quantified the displacement level, which provided information for post-disaster recovery and planning work. Taking an earthquake-stricken area as the main research object, Gao Na compared the demographic data obtained by smartphone location and found the role of annual difference data in the field of sudden disaster emergency relief [ 16 ]. The Nie group from the Institute of Geology, China Earthquake Administration used smartphone location data to analyze the indicators related to earthquake disasters and proposed to regard seismic intensity as a sensitive indicator for smartphone location data [ 17 ]. Zhang used the pre-earthquake and post-earthquake Internet smartphone location data in an earthquake area and adopted the standard deviation ellipse model in spatial econometric analysis to analyze the spatial distribution characteristics of the disappeared smartphone location data in the earthquake area and the oriented direction of its discrete point sets, which determined the direction of the seismic influence field, and further provided technical support for post-disaster situation assessment and emergency response services [ 18 ]. In the process of seismic data processing, relevant experts can address earthquake emergency response, rescue guidance, and other studies by integrating and mining a large amount of complex and multisource data [ 19 ]. In conclusion, the application of "mobile location big data" during earthquake emergency responses can improve the scientificity and accuracy of the decision-making processes during an earthquake and enhance the capabilities of earthquake early warnings and emergency responses [ 20 ].

Materials and methods

Principles of smartphone location big data.

The popularity of smartphones and the development of the Internet (according to the report of "Worldwide Quarterly Smartphone Tracker" of the International Data Corporation (IDC), as of the first quarter of 2022, the global smartphone penetration rate is approximately 82%) has ushered in the era of mobile Internet. In addition, with the development and wide use of the global positioning system (GPS), the generation and development of location-based services have become inevitable trends. Location-based services not only offer convenience but also provide new data sources and possibilities for business intelligence analysis, public affairs management, academic research, and other efforts. A large number of users around the world generate numerous information for sharing every day, and the shared information can be accessed via application interfaces [ 21 ]. The geographic data generated through smartphone location sharing services has brought a new revolution to GIS. The most fundamental issue involved in research using the shared data in mobile networks as a data source is the acquisition of data and the supporting platforms for the analysis and computation of acquired data. Population data estimation applies geo-fencing technology to push notifications. When a smartphone enters a geographical spatial scope, the location information of the smartphone can be acquired and logged. Since the size of a population is highly correlated to the number of smartphones, the current population size can be inferred by means of model simulation at different times and in different areas [ 22 ]. The volume of shared information in mobile networks is huge, which poses a great challenge in storing and analyzing this massive amount of data. Therefore, most of the research on mobile terminal location information focus on studying and predicting individual mobility patterns. Such analysis of individual mobility patterns, combined with the information from users’ social network applications, can be suitably applied to public affairs management, such as user profiling, service recommendations, and market predictions [ 23 ]. Communication data providers can also upload smartphone location data to cloud servers for real-time analysis and storage. Cloud servers can process large-scale location data, and the results of these cluster location data analyses can facilitate the development of more targeted emergency strategies in response to natural disasters. With the support of a large amount of data, the study of human activities on a larger scale will be of greater significance for urban and rural planning, population distribution, socio-economic indicators, and other aspects [ 24 , 25 ].

Data preprocessing

A magnitude 6.8 earthquake struck Luding County, Sichuan Province (at 29.59 degrees north latitude and 102.08 degrees east longitude) at 12:52 p.m. Beijing time on September 5, 2022, with a focal depth of 16 kilometers. The earthquake caused heavy casualties, with 46 deaths, and severe damage to water, electricity, transportation, and communication facilities and other infrastructure. The region was highly deformed due to crustal movements, and there have been other violent earthquakes. Since 1900, 21 earthquakes with a magnitude of 6.0 or greater have occurred within 200 km of the epicenter, and a 6.2-magnitude earthquake occurred 27 km from the epicenter in 1975. At the epicenter, we collected a total of 1,806,100 smartphone location records and 4,856 spatial grid locations within a range of 300 km from east to west and 220 km from north to south, and the collection scope covers areas of VI degree and above.

The analysis in this study used GIS data is obtained from the open-source data Open Street Map (OSM), which is available for free and can be downloaded from the portal website of Digital Crete ( https://www.openstreetmap.org/ ) The OSM data contains a series of data layers such as highways, railways, water systems, buildings, transportation facilities, etc. In this study, we only used data from residential points and areas, The DEM data adopts Copernicus DEM, which is a global open-source DEM data released by the European Space Agency(ESA) and can be downloaded from the ESA portal website ( https://panda.copernicus.eu/panda ). The DEM data of ESA has a 10 meter (EA-10) resolution for the European part and a 30 meter resolution for the global range. In this study, we used a 30 meter resolution in a raster format (Tif).The above data does not require authorization. The smartphone location records data obtained was authorized by the telecommunications company to the Zhejiang Earthquake Agency and provided to the author for use. The smartphone location records data used in this article uses Geohash encoding with an accuracy of Geohash7 (approximately 120m * 150m). This data is used to count the number of mobile devices in each Geohash grid within the earthquake zone range per minute.The data is group smartphone location data and does not involve the personal privacy of individual mobile phone users, so there is no concern about personal privacy leakage. All maps in this article are created using ARCGIS 10.6, The coordinates of the map are WGS84,The maps are oriented with North as up, and at this scale all maps in this article have an extent of 300km × 200km.The GIS data is obtained from open-source data websites and has been verified against the place name data of the epicenter area. All data does not involve copyright or legal disputes.

The epicenter of this earthquake was a mountainous area. The population density near the epicenter was not high, with only a few settlements and scenic areas for tourists. After the earthquake, the communication facilities in the disaster area were damaged, which led to a substantial reduction in mobile terminal connections. The disaster avoidance behavior of people and the rapid repair of mobile communication facilities also caused changes in the number of mobile terminals in the disaster area. In addition, there was also a huge quantitative difference between different time periods and areas. Therefore, we extracted the population information in different time periods. Specifically, starting from 10:00 a.m. on the 9th day, the data coverage was extracted every 1 hour, with 24 time periods in total. In this way, the dynamic damage condition of communication facilities in the earthquake area could be reflected in a relatively comprehensive way. In this work, due to the vast data size, accuracy and efficiency contradicted each other. Although the adoption of high precision could contribute to a more detailed representation of population distribution, the problem of high computational complexity would occur. Moreover, the terrain of the disaster area was complicated, and the shadowing effect of the mountains had a certain impact on the accurate positioning of smartphone locations [ 26 ]. Therefore, an excessive pursuit of accuracy would result in a certain amount of repeated calculation points and affect the calculation efficiency. In order to analyze the population in the earthquake area in a faster way, while balancing accuracy and efficiency, we selected a 150 m grid size to analyze terminal location distribution.

Population distribution simulation based on density analysis

Principle of kernel density analysis..

Within the 150 m grid, the population is not perfectly uniformly distributed. Thus, a mathematical approach is needed to simulate population density. We regard the center of the grid as a point. The value of the point is the size of population in the grid, and the distribution of population density is represented by calculating point density [ 27 ]. There are three commonly used methods for calculating point density: the quadrat density method, the kernel density method, and the Voronoi diagram density method. The quadrat density method randomly selects a number of quadrats in the space of the area being simulated and calculates the density of each quadrat by counting the number of individuals in each quadrat, with the average of the density of all quadrats as the density of the large area. However, random sampling is characterized by a certain degree of subjectivity, so the simulation results are relatively larger. This method is applicable to the sampling survey of a static population, but it has a poor effect in simulating a population with strong mobility and high density. The Voronoi diagram density method calculates a distance-based plane partition in geometric space by using data points as generators of a Voronoi diagram. There are n non-coincident seed points in the plane, and the plane is divided into n regions in such a way that the distance from a point in each region to the seed point in the region in which the point is located is closer than the distance from it to any seed point in any other region, and each region is called a Voronoi seed point region. Due to the abrupt density changes at cell junctions and the neglect of continuity in the occurrence of spatial phenomena, Voronoi diagrams also have certain limitations in population distribution estimation [ 28 , 29 ].

However, the above problems can be solved by the kernel density method. The value of kernel density gradually decreases with increasing center radiation distance, with consideration to the distance attenuation effect of the center point on its surrounding locations [ 30 ]. Conceptually, each point is covered with a smooth curved surface, and the surface value is highest at the location of that point. As the distance increases, the surface value decreases until the value turns to zero at a distance equal to the search radius. Each pixel value of the output raster is the sum of all surface values superimposed on the pixel. Thus, the kernel density estimation method can transform a point set into a surface that exhibits continuous density variation. It also is possible to transform a discrete set of points into a smooth density variation diagram, thus demonstrating their spatial distribution pattern. The higher the density value, the greater the aggregation extent of the point is. Kernel density analysis has obvious advantages in the simulation of population distribution, as population distribution is featured with clustering, and the farther away from the center, the less dense the population distribution is [ 31 ].

Spatial calculation method of kernel density.

https://doi.org/10.1371/journal.pone.0298236.g002

Population distribution simulation based on kernel density analysis.

We adopted the kernel density method and used the collected smartphone point data to simulate the population distribution within a range of 300 km from east to west and 220 km from north to south. Figs 3 and 4 show the simulated population distribution of Luding based on smartphone data. As shown in Fig 3 , the area near the epicenter is sparsely populated, with only a certain amount of population distributed in Moxi Town, Detou Town, and Dewei Township. In particular, the population density is very low in the west of the epicenter, with few large settlements located in the area. The population is concentrated in the eastern plain areas, which are far from the epicenter. Among these areas, Luding County is 40 km away from the epicenter, while Shimian County is 47 km away from the epicenter. The rest of the population is sporadically distributed along the bottom of the terrain ditches and the traffic lines. Fig 5 shows a heat map of population near the epicenter at 12:00 p.m. on September 5. It can be seen in Fig 5 that at 12:00 p.m., the area near the epicenter, where the government of Moxi Town is located, was densely populated, with only a few people sporadically distributed in the surrounding area. There were also few people in Detuo Town, and its neighboring township Dewei had a certain amount of population.

https://doi.org/10.1371/journal.pone.0298236.g003

https://doi.org/10.1371/journal.pone.0298236.g004

https://doi.org/10.1371/journal.pone.0298236.g005

To reflect the population change before and after the earthquake, we compared the population density at 13:00 pm after the earthquake on September 5 ( Fig 6 ) with the data at 12:00 pm before the earthquake ( Fig 5 ) and calculated the density difference between the 2 time periods so that the communication outage and the movement of people caused by the earthquake can be reflected more objectively. Figs 5 and 6 show the changes in smartphone density before and after the earthquake in the earthquake area and the epicentral area, respectively. As shown in Fig 6 , after the earthquake, the population density of highly seismic regions near the epicenter in the IX degree zone in the southern part of Luding County, such as Moxi Town, decreased significantly; as shown in Fig 7 , the population density of areas farther away from the epicenter (such as Hanyuan County) did not change much, and the overall density decrease and increase of Xingjing County in the VI degree zone were relatively in balance. Yucheng District in Ya’an City, the most densely populated area, in the V degree zone, experienced an increase in the number of smartphones turned on. In the earthquake area of Luding County, the population density in Moxi Town, Detou Town, Yanzigou Town, Dewei Town and its surrounding area, as well as Wanggangping Township, Caoke Township and its surrounding area in Shimian County dropped sharply, from which it could be inferred that a significant number of out-of-service base stations and power outages occurred in these areas. Along National Highway 318 from Luding County to Tianquan County, there was a certain increase in population density, and the population on the periphery of Luding County also increased to a certain extent, indicating that tourists had already begun to evacuate out of the scenic areas half an hour after the earthquake.

https://doi.org/10.1371/journal.pone.0298236.g006

https://doi.org/10.1371/journal.pone.0298236.g007

Results and discussion

Analysis of population change in the segmented zones of the disaster area.

After the earthquake, the population distribution in the disaster area displayed a dynamic change. Starting from the size of population affected by out-of-service base stations after the earthquake, to the repair of communication and electric lines, and then to the subsequent evacuation to the outside along the traffic lines, the number and location of the population had been changing.

We selected several typical settlements in the Ⅸ and VII degree zones for the time series analysis of communication terminal volume. Moxi Town, Caoke Township, and Detou Town in the Ⅸ degree zone were chosen, of which Moxi Town was closer to the epicenter and was also one of the settlements heavily struck by the earthquake. Fig 8 shows an analysis of the population data by area and time period within 24 hours since 12:00 pm on September 5. At 1:00 pm, communication and power systems were severely damaged after the earthquake, resulting in a sharp drop in communication terminal volume. However, the communication repair was made very quickly. After the emergency communication vehicles entered the earthquake area, communication was partially restored. As of 7:00 pm that night, part of the communication and power systems had been restored. The communication terminal volume began to grow slowly. At 06:00 am on September 6, the population evacuated from the scenic areas and the rescue forces entering the disaster area were superimposed. As shown in Fig 8 , the crowd flow in the three settlements showed a sharp increase; the situation in Caoke Township and Detou Township was basically similar, and the time series curves of the communication terminal volume in the two places were highly consistent.

https://doi.org/10.1371/journal.pone.0298236.g008

We also examined statistics on changes in Shimian County, Luding County, and Yidong Town in the VII degree zone ( Fig 9 ) within 24 hours. Because of the extremely uneven population distribution in this zone, in which Shimian Town and Luding County Town were relatively densely populated and the damage to communication facilities after the earthquake was less serious than that in the Ⅸ degree zone, the decline in communication terminal volume was relatively slower than that in the other zones. At 11:00 pm, the communication terminal volume showed a natural decline due to equipment shutdowns. Similarly, the population change in the three typical settlements in the VII degree zone is highly consistent. What is different from the Ⅸ degree zone is that there was a continuous outflow of people after the partial restoration of communication.

https://doi.org/10.1371/journal.pone.0298236.g009

Simulation of out-of-service base station situations in the disaster area

https://doi.org/10.1371/journal.pone.0298236.g010

https://doi.org/10.1371/journal.pone.0298236.g011

After the intensity map was officially released, we also calculated the changes in simulated population based on smartphones in different intensity zones before and after the earthquake, and in order to exclude the impact of smartphone shutdowns for lunch breaks on the out-of-service situation, we also calculated the changes in the smartphone-based population in the same time period and the same area on September 4. In the calculation of the final result, as the base, the data on September 4 was subtracted so that we could obtain the real out-of-service situation on September 5. Table 1 shows the statistics of the out-of-service rate based on smartphone population data. In Table 2 , it can be seen that the out-of-service rate in the VI degree zone is -1.62%, while the out-of-service rate on September 4 is 1.32%. The out-of-service rate decreased after the earthquake, which means that after the earthquake, some people in this zone were affected and kept learning about the disaster through their mobile terminals. By using the same method and after deduction of the base, we finally calculated that the out-of-service rate in the VII degree zone at 19.42%, which is contrary to the traditional view that service outages at communication base stations will occur only in the VIII degree zone; thus, it is inferred that there exists a certain out-of-service rate in the VII+ degree zone. In the VIII degree and IX degree zones, we believe that the number of people who were strongly affected by the earthquake and turned off their smartphones at 1:00 pm was small. Thus, the final results of the out-of-service rate in VIII degree and IX degree zones are 48.40% and 78.11%. The reduction in the number of smartphones after the earthquake may be affected by multiple factors, but an out-of-service base station is the most important one. Therefore, the above results can objectively reflect the base station out-of-service rate in different intensity zones.

https://doi.org/10.1371/journal.pone.0298236.t001

https://doi.org/10.1371/journal.pone.0298236.t002

With the same method, we tracked back to the population heat map data of earthquakes with a magnitude of 6.0 or above in mainland China since 2017 in the database, analyzed and processed the communication location big data in the zones of VII degree or above during multiple post-earthquake time periods in the course of earthquake emergency response, used the spatial change of terminal data to infer the damage of communication base stations and the response of people, and summarized the regression modeling so that we can spatially infer the distribution range of the hardest hit areas. Based on the change trend of terminal location data, the research proceeded with the extraction of seismic damage information to correct the empirical isoseismal line so as to make up for the lack of first-hand field data of the existing rapid assessment system. Finally, a rapid assessment method of the seismic influence field based on communication big data is established, and an operable software system is formed, which can provide technical support for earthquake emergency rescues. At present, the related research results have been popularized and applied in many regions.

https://doi.org/10.1371/journal.pone.0298236.g012

Conclusions

With good timeliness and high data accuracy, smartphone population heat map data can be applied to the actual practice of earthquake emergency response. Taking the Luding Ms 6.8 earthquake as an example, we have obtained the simulation data of the population distribution in the earthquake area in real time with the support of smartphone location data. Having been tested by dozens of large and small earthquakes, the data model has become more mature. Based on the cross-corroboration of multiple validation channels, we find that the data obtained at this time is consistent with the actual situation. In the hours after an earthquake, smartphone location data can provide strong support for the government’s disaster relief work when the actual disaster situation is still uncertain. The application of this method in the emergency management field is also widely recognized. Compared with traditional modes of disaster information acquisition, smartphone location data has obvious advantages in terms of cost, accuracy, efficiency, and other aspects. With high timeliness and good continuity of data, as well as the absence of additional investment in hardware equipment and organization of large-scale field investigations, this method can realize the rapid acquisition of the location change rule of communication terminal population in a disaster area after an earthquake. By analyzing the characteristics of spatial–temporal changes in smartphone location big data before and after the earthquake, we can infer the strength and distribution range of earthquake intensity. In addition, unlike the “black box period” in previous earthquakes, this work enables us to provide the government with a sufficient and reliable information basis for disaster relief within one hour after the earthquake, even when a more accurate and complete picture of the disaster situation is not available. This approach can greatly complement the shortcomings of the existing rapid seismic assessment systems and enables the rapid obtainment of highly credible disaster information in a timely manner when a sudden and destructive earthquake occurs ( Table 3 ).

https://doi.org/10.1371/journal.pone.0298236.t003

An out-of-service base station will cause a large amount of mobile terminal location data to disappear after an earthquake. During this earthquake, the magnitude reached 6.8, the maximum intensity of the epicenter was IX degree, and the hardest hit area experienced power interruptions and out-of-service base stations, which directly led to a cliff-like drop in the mobile terminal location data we obtained after the earthquake. The closer to the epicenter, the more obvious this phenomenon was. After the communication and power lines were repaired, the acquisition of smartphone location data began to recover gradually. Determining the base station out-of-service rate plays an important indicative role in estimating the seismic intensity of the hardest hit area in the first moments. This further helps us to obtain the seismic intensity, isoseismal line, and other critical information in the affected areas. With the support of communication big data, we can correct the empirical isoseismal lines based on the seismic damage information extracted from the model. In addition, we can also verify the locations that cannot be accurately assessed and dynamically modify the isoseismal lines to gradually improve the assessment accuracy. By combining empirical models and automatic computer processing technologies, we can obtain the earthquake disaster information in a faster manner. In the meantime, we still need to discover the characteristics of seismic damage in different regions and of different magnitudes, and on this basis, we can establish the basis of determining seismic intensity according to the performance of smartphone location data in different situations. This will ultimately further improve the method of obtaining the seismic intensity influence field based on mobile Internet data and enhance our earthquake response capability.

In practice, we have also found some shortcomings in using mobile terminals to judge disaster situations. Even in modern society, the utilization rate of smartphones is still closely related to factors such as age, geographic location and economic status. Large-intensity earthquakes usually occur in mountainous and sparsely populated areas. In the disaster area of this Luding earthquake, there was also an extreme situation where the population in the mountainous area in the northwest of the disaster area was extremely small and there was a clear gap in population composition, as most of the population were aged over 60 or children, with low smartphone usage rates, which may have led to underestimated location data. In contrast, Moxi Town and Detou Town near the epicenter were relatively densely populated. As Moxi Town is a scenic location, most of the population here were tourists, with a high smartphone usage rate, which may have led to overestimating the pre-earthquake data to a certain extent if a unified model was used. Therefore, in order to estimate and judge disaster situations more accurately, it is necessary to customize a suitable regional population model to take these differential factors into account. In the Luding Ms 6.8 earthquake, the research team applied different population models to adapt to the special conditions in Moxi Town and the northwestern mountainous areas. This has fully demonstrated the importance of flexibility and customization strategies. This approach can not only make up for the data bias caused by uneven smartphone usage rate but also help improve the accuracy of disaster assessment.

Smartphone-based location big data has great application potential in future earthquake emergency management. This technology can not only realize the real-time estimation of population distribution during an earthquake but also achieve in-depth analysis based on its rich attribute information, such as tracking the places of origin of the population, the population movement vector, traffic jams, etc., which could not be accomplished in past earthquake emergency responses. The mining of smartphone data can derive richer applications to better serve earthquake emergency responses. The application of mobile location big data sources can replace the traditional field investigation of seismic damages. We can calculate the spatial distribution of a disaster based on the disaster information reflected in big data so as to obtain the simulated results of disaster distribution, which will greatly improve the efficiency of seismic damage information acquisition.

Supporting information

S1 file. calculation on out-of-service rate based on mobile terminal location data in this earthquakes..

https://doi.org/10.1371/journal.pone.0298236.s001

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