Earthquake Predictor

CHAPTER 1

INTRODUCTION

1.1 How Earthquakes Work:

An earthquake is the result of a sudden release of energy in the Earth's crust that creates seismic waves. Earthquakes are recorded with a seismometer, also known as a seismograph. The moment magnitude of an earthquake is conventionally reported, or the related and mostly obsolete Richter magnitude, with magnitude 3 or lower earthquakes being mostly imperceptible and magnitude 7 causing serious damage over large areas. Intensity of shaking is measured on the modified Mercalli scale.

Fig 1.1: Global earthquake epicenters, 1963–1998 and

Global plate tectonic movement

At the Earth's surface, earthquakes manifest themselves by a shaking and sometimes displacement of the ground. When a large earthquake epicenter is located offshore, the seabed sometimes suffers sufficient displacement to cause a tsunami. The shaking in earthquakes can also trigger landslides and occasionally volcanic activity. In its most generic sense, the word earthquake is used to describe any seismic event whether a natural phenomenon or an event caused by humans that generates seismic waves. Earthquakes are caused mostly by rupture of geological faults, but also by volcanic activity, landslides, mine blasts, and nuclear experiments.

An earthquake's point of initial rupture is called its focus or hypocenter. The term epicenter means the point at ground level directly above this.

1.2 Naturally occurring earthquakes:

Most naturally occurring earthquakes are related to the tectonic nature of the Earth. Such earthquakes are called tectonic earthquakes. The Earth's lithosphere is a patchwork of plates in slow but constant motion caused by the release to space of the heat in the Earth's mantle and core. The heat causes the rock in the Earth to flow on geological timescales, so that the plates move slowly but surely. Plate boundaries lock as the plates move past each other, creating frictional stress. When the frictional stress exceeds a critical value, called local strength, a sudden failure occurs. The boundary of tectonic plates along which failure occurs is called the fault plane. When the failure at the fault plane results in a violent displacement of the Earth's crust, energy is released as a combination of radiated elastic strain seismic waves, frictional heating of the fault surface, and cracking of the rock, thus causing an earthquake. This process of gradual build-up of strain and stress punctuated by occasional sudden earthquake failure is referred to as the Elastic-rebound theory. It is estimated that only 10 percent or less of an earthquake's total energy is radiated as seismic energy. Most of the earthquake's energy is used to power the earthquake fracture growth or is converted into heat generated by friction. Therefore, earthquakes lower the Earth's available elastic potential energy and raise its temperature, though these changes are negligible compared to the conductive and convective flow of heat out from the Earth's deep interior.

The majority of tectonic earthquakes originate at depths not exceeding tens of kilometers. In subduction zones, where older and colder oceanic crust descends beneath another tectonic plate, Deep focus earthquakes may occur at much greater depths (up to seven hundred kilometers). These seismically active areas of subduction are known as Wadati-Benioff zones. These are earthquakes that occur at a depth at which the sub ducted lithosphere should no longer be brittle, due to the high temperature and pressure. A possible mechanism for the generation of deep focus earthquakes is faulting caused by olivine undergoing a phase transition into a spinel structure.

Earthquakes also often occur in volcanic regions and are caused there, both by tectonic faults and by the movement of magma in volcanoes. Such earthquakes can serve as an early warning of volcanic eruptions.

Sometimes a series of earthquakes occur in a sort of earthquake storm, where the earthquakes strike a fault in clusters, each triggered by the shaking or stress redistribution of the previous earthquakes. Similar to aftershocks but on adjacent segments of fault, these storms occur over the course of years, and with some of the later earthquakes as damaging as the early ones. Such a pattern was observed in the sequence of about a dozen earthquakes that struck the North Anatolian Fault in Turkey in the 20th century, the half dozen large earthquakes in New Madrid in 1811-1812, and has been inferred for older anomalous clusters of large earthquakes in the Middle East and in the Mojave Desert .

1.3 Size and frequency of occurrence:

Small earthquakes occur nearly constantly around the world in places like California and Alaska in the U.S. , as well as in Chile , Peru , and Indonesia , and Iran , the Azores in Portugal , New Zealand , Greece and Japan . Large earthquakes occur less frequently, the relationship being exponential; for example, roughly ten times as many earthquakes larger than magnitude 4 occur in a particular time period than earthquakes larger than magnitude 5. In the (low seismicity) United Kingdom , for example, it has been calculated that the average recurrences are:

• An earthquake of 3.7 - 4.6 every year
• An earthquake of 4.7 - 5.5 every 10 years
• An earthquake of 5.6 or larger every 100 years.

The number of seismic stations has increased from about 350 in 1931 to many thousands today. As a result, many more earthquakes are reported than in the past because of the vast improvement in instrumentation (not because the number of earthquakes has increased). The USGS estimates that, since 1900, there have been an average of 18 major earthquakes (magnitude 7.0-7.9) and one great earthquake (magnitude 8.0 or greater) per year, and that this average has been relatively stable. In fact, in recent years, the number of major earthquakes per year has actually decreased, although this is likely a statistical fluctuation. More detailed statistics on the size and frequency of earthquakes is available from the USGS.

Most of the world's earthquakes (90%, and 81% of the largest) take place in the 40,000-km-long, horseshoe-shaped zone called the circum-Pacific seismic belt, also known as the Pacific Ring of Fire, which for the most part bounds the Pacific Plate. Massive earthquakes tend to occur along other plate boundaries, too, such as along the Himalayan Mountains .

With the rapid growth of mega-cities such as Mexico City , Tokyo or Tehran , in areas of high seismic risk, some seismologists are warning that a single quake may claim the lives of up to 3 million people.

 CHAPTER 2

PREDICTION OF EARTHQUAKES

 2.1 Predicting Earthquakes:

IMPENDING EARTHQUAKES HAVE BEEN SENDING US WARNIGS SIGNALS- AND PEOPLES ARE STARTING TO LISTEN

Figure 2.1: Overall Method of Prediction of Earthquake 

From the decades of researches the scientist are trying to yield pri-earthquake signals and at last they have been successful in detecting strange phenomena in form of radio noise, eire lights in the sky weeks and hours and days preceding earthquakes.

We understand earthquakes a lot better than we did even 50 years ago, but we still can't do much about them. They are caused by fundamental, powerful geological processes that are far beyond our control. These processes are also fairly unpredictable, so it's not possible at this time to tell people exactly when an earthquake is going to occur. The first detected seismic waves will tell us that more powerful vibrations are on their way, but this only gives us a few minutes warning, at most.

Figure 2.2: Damage in downtown Anchorage , Alaska , caused by the 1964 Prince William Sound earthquake.

Scientists can say where major earthquakes are likely to occur, based on the movement of the plates in the earth and the location of fault zones. They can also make general guesses of when they might occur in a certain area, by looking at the history of earthquakes in the region and detecting where pressure is building along fault lines. These predictions are extremely vague, however -- typically on the order of decades. Scientists have had more success predicting aftershocks, additional quakes following an initial earthquake. These predictions are based on extensive research of aftershock patterns. Seismologists can make a good guess of how an earthquake originating along one fault will cause additional earthquakes in connected faults.

Another area of study is the relationship between magnetic and electrical charges in rock material and earthquakes. Some scientists have hypothesized that these electromagnetic fields change in a certain way just before an earthquake. Seismologists are also studying gas seepage and the tilting of the ground as warning signs of earthquakes. For the most part, however, they can't reliably predict earthquakes with any precision.

So what can we do about earthquakes? The major advances over the past 50 years have been in preparedness -- particularly in the field of construction engineering. In 1973, the Uniform Building Code, an international set of standards for building construction, added specifications to fortify buildings against the force of seismic waves. This includes strengthening support material as well as designing buildings so they are flexible enough to absorb vibrations without falling or deteriorating. It's very important to design structures that can take this sort of punch, particularly in earthquake-prone areas. See this article on How Smart Structures Will Work for more on how scientists are creating new ways to protect buildings from seismic activity.

Figure 2.3: Bridge columns cracked by the
Loma Prieta , Calif. earthquake of 1989.

Another component of preparedness is educating the public. The United States Geological Survey (USGS) and other government agencies have produced several brochures explaining the processes involved in an earthquake and giving instructions on how to prepare your house for a possible earthquake, as well as what to do when a quake hits. 

In the future, improvements in prediction and preparedness should further minimize the loss of life and property associated with earthquakes. But it will be a long time, if ever, before we'll be ready for every substantial earthquake that might occur. Just like severe weather and disease, earthquakes are an unavoidable force generated by the powerful natural processes that shape our planet. All we can do is increase our understanding of the phenomenon and develop better ways to deal with it.

2.2 Methods of Predicting Earthquakes:

2.2.1 Ground Based Sensors:

Ground Based Sensors are not only mechanism for monitoring the signals given off by impending earthquakes. Above the ground, satellite-based instruments are picking up interesting patterns in low-frequency signals and detecting other oddities.

2.2.2 Quake Sat:

In 1989, after the devastating earthquake in Armenia , a Soviet Cosmos satellite observed ELF-frequency disturbances whenever, it passed over a region slightly south of the epicenter. The activ­ity persisted up to a month after the quake. Unfortunately, no data were gathered just prior to the initial quake. In 2003, the U.S. satel­lite Quake Sat detected a series of ELF bursts two months before and several weeks after a 22 December, 6.5-magnitude earthquake in San Simeon, Calif.

2.2.3 DEMETER:

In June 2004, a multinational consortium lead by the French government launched a new earthquake detection satellite called DEMETER (for Detection of Electro-Magnetic Emissions Transmitted from Earthquake Regions). DEMETER, much more sensitive than earlier satellites, has already detected some unusual

December 2005   IEEE Spectrum   INT    0 increases in ion density and ELF disturbances above large quakes around the world. Unfortunately, the satellite was malfunction­ing in the days before October's temblor in Kashmir . Because the project is so new, researchers are still working on the tools for processing DEMETER's data. Its backers are expecting more detailed analyses to be available this month.

2.2.4 Infrared Signals Given by Satellite:

Infrared radiation detected by satellites may also prove to be a warning sign of earthquakes to come. Researchers in China reported several instances during the past two decades of satellite-based instruments registering an infrared signature con­sistent with a jump of 4 to 5 °C before some earthquakes. Sensors in NASA's Terra Earth Observing System satellite registered what NASA called a "thermal anomaly" on 21 January 2001 in Gujarat , India , just five days before a 7.7-magnitude quake there; the anomaly was gone a few days after the quake. In both cases, researchers believe, these sensors may have detected an infrared luminescence gen­erated by the recombination of electrons and holes, not a real temperature increase.

2.2.5 Study of Under Ground Movements:

Even existing global position may serve as part of an earthquake warning system. Sometimes the charged particles generated under the ground in the days and weeks before an earthquake change the total electron content of the iono­sphere—a region of the atmosphere above about 70 km, con­taining charged particles. If the ground is full of positively charged holes, it would attract electrons from the ionosphere, decreasing the airborne electron concentration over an area as much as 100 km in diameter and pulling the ionosphere closer to Earth.

This change in electron content can be detected by alterations in the behavior of GPS navigation and other radio signals. Each GPS satellite transmits two signals. The relative phase difference between the two signals when they reach a receiver change, depending on the electron content of the ionosphere, so track­ing these phase changes at a stationary receiver allows researchers to monitor changes in the ionosphere.

Researchers in Taiwan monitored 144 earthquakes between 1997 and 1999, and they found that for those registering 6.0 and higher the electron content of the ionosphere changed significantly one to six days before the earthquakes.

2.2.6 Study of Ionosphere Changes:

Earthquake forecasters can also watch for changes in the iono­sphere by monitoring very-low-frequency (3- to 30-kilohertz) and high-frequency (3- to 3C-megahertz) radio transmissions. The strength of a radio signal at a receiver station changes with the diurnal cycle: it is greater at night than in daylight, as anyone who listens to late-night radio from far-off stations knows. The alti­tude of the ionosphere, which moves lower as the positive holes migrate to the surface, also has an effect on radio signals; the lower the ionosphere, the stronger the signals. So at dawn on an earth­quake day, curves drawn to represent the drop-off in radio sig­nal strength wifl appear markedly different from the normal curve for that signal at that location 

CHAPTER 3

BAM EARTHQUAKE PREDICTION AND SPACE TECHNOLOGY

3.1Introduction:
            The principal application of space technology to earthquake prediction has traditionally been measurements of ground motion. While this approach has contributed significantly to geophysical studies, it has not yet yielded an earthquake prediction method. An alternative approach that has recently shown great promise is satellite imaging of strange non- meteorological cloud formations and their correlation with earthquakes. Shou used such a cloud to predict the Bam earthquake of Dec. 26, 2003 to the public. Coarse and fine predictions were made public on the internet at 17:58 UTC, Dec. 25, 2003. The fine prediction stated that there would be an earthquake of magnitude more than or equal to 5.5 within 60 days along a fault described in Fig. 3.1.1, while the coarse prediction allowed magnitude 5 and above, within 98 days. The Bam earthquake occurred precisely on the predicted fault, and its magnitude was within the predicted magnitude windows.

Figure 3.1.1: The Bam Earthquake Cloud

This image of IndoEx satellite (@2) shows an earthquake cloud emerging from fault AB on Dec. 21, 2003, marked by a white arrow, by which Shou predicted an M5.5 or bigger earthquake in Fault AB within 60 days on Dec. 25, 2003 to the public (@1). On Dec. 26, an earthquake of 6.8 Ms happened in Bam (28.99N, 58.29E), Iran (marked by *), exactly where the cloud had emerged

Three kinds of earthquake clouds: rope-shaped, rib shaped (wave-shaped), and radiation-shaped, were announced. On the other hand, Shou made his first earthquake prediction in Hang Zhou China by a long line-shaped cloud with a tail pointing in the northwest direction on Jun. 20, 1990. 18 hours later, a magnitude 7.7 earthquake struck Iran , and killed or injured 370,000 people. Because the earthquake was the only one bigger than 7 to the northwest of Hang Zhou for 333 days from May 31, 1990 to Apr. 28, 1991, He believed that there must be a strong relationship between the cloud and the earthquake. As long as the epicenter was not located by Kagida's law, but on where the cloud's tail pointed toward, He believed that the method of earthquake clouds should not have been abandoned. Over the last 10 years, with the aid of satellite weather images available on the internet Shou has observed similar correlations in sufficient numbers to enable the development of a successful earthquake prediction method. He has used this method to generate 50 independent predictions certified by the United States Geological Survey (USGS), of which 36 were correct. We will describe a model to explain the correlations, a statistical analysis of the set of predictions, and prospects for improving the both precision and reliability of the predictions.        

3.2 Earthquake Cloud Model:        
             Shou first proposed a model for the formation of earthquake clouds. When a huge rock is stressed by external forces, its weak parts break first and small earthquakes occur. For example, the Southern California earthquake data show that small shocks happened before and around all large hypocenters there. The fact that a large earthquake produces a large gap suggests that small shocks generate small crevices, which reduce the cohesion of the rock. Next, underground water percolates into the crevices. Its expansion, contraction, and chemistry further reduce the cohesion. Friction heats the water and eventually generates vapor at high temperature and pressure. The vapor erupts from an impending hypocenter to the surface by the crevices, and rises up. It forms a cloud while encountering cold air. This kind of cloud, whose vapor is from an impending hypocenter, is denoted an earthquake cloud. Anecdotal evidence for high temperature and high pressure vapor is plentiful, as is evidence for the clouds themselves

Not only does the vapor forming the cloud originate in the Earth, but its creation is intimately linked to the subsequent earthquake. There are two important pieces of evidence. First, the USGS performed an experiment at the Rangely Oil Field in Western Colorado in 1969 , in which water was injected into and pumped out of oil wells. Researchers found that there was a strong positive correlation between the quantity of water injected and seismic activity. Above a threshold fluid pore pressure, seismic activity was observed to increase dramatically. Supporting this work is the results of laboratory studies of yield strength of saturated rock. As the rock is heated, the yield strength changes only gradually until a threshold temperature is reached. Past this threshold, the rock becomes dehydrated and its yield strength drops rapidly. Our earthquake model is that the vapor in an earthquake cloud is precisely what escapes at the beginning of dehydration, i.e. when the yield strength begins to drop sharply. Once the yield strength has dropped sufficiently, the rock yields and an earthquake occur. Thus, the atmospheric precursor we have discussed is directly linked to the generation of the earthquake itself.     
                An earthquake cloud can be distinguished from weather clouds by the following properties: a sudden appearance, a fixed source location (a fault), and a special shape such as a line, a snake, a few parallel lines, a bind of parallel waves, a feather, a radiation or a lantern pattern . These properties do not occur together in weather clouds . Fig. 3 reveals a time series of the Bam cloud that appeared suddenly from a fixed source (the Bam fault) at 2:00, Dec. 20, 2003. The dense cloud formed in the midst of light clouds and expanded eastward while remaining connected to its source.

Fig. 3.2.1 depicts several examples of suddenly-appearing earthquake clouds over Southern California , including a cloud that appeared over Northridge direction 9 days before the Northridge earthquake of 1994. Fig. 5, a photo looking towards Northern California on Aug. 3, 1997 shows a cloudless line marked 4 that appeared in the midst of clouds and became a linear cloud 6 minutes after the photo was taken. Before the photo was taken, four cloudless lines had emerged rapidly, much faster than a jet trail. Two, marked 1 and 2, had entirely become line-shaped clouds and one, marked 3, and had partially become a cloud for about 3 minutes. On Aug. 21, 1997 a pair of M4.9 earthquakes occurred in Northern California . The width of these features and their rapid emergence strongly support the theory that hot vapor emerges rapidly from a line-shaped region of ground (i.e. fault).

Figure 3.2.1: A Time Series of the Bam Earthquake Cloud This series of IndoEx satellite images (@2) shows how the Bam earthquake cloud appeared suddenly, at 2:00 on Dec. 20, 2003, expanded eastward from its point of emergence, then disappeared at 6:00 on Dec. 21.

             An earthquake cloud comes from an impending hypocenter, so its tail generally points toward or predicts an impending epicenter. The more mass an earthquake cloud has, the bigger the subsequent earthquake. By comparing the mass of an earthquake cloud with those of former clouds, whose relevant magnitudes are in an earthquake catalog, the cloud can be used to predict its magnitude. Based on statistics from about 500 events, the longest delay from an earthquake cloud to its earthquake is 103 days, and their average is 30 days, so an earthquake cloud can predict the time. Therefore, an earthquake cloud can predict an earthquake. The Bam cloud is an excellent example to show that an earthquake cloud does in fact come from the Earth.

Figure 3.2.2: Various Shapes of Earthquake Clouds shows six different shapes of earthquake clouds, photographed by Shou from Pasadena , California . Under each photo are the date and the direction Shou took the photo.

Figure 3.2.3: Northern California earthquake clouds This photo, taken by Shou from Pasadena, California toward the north on Aug. 3, 1997, shows four lines that had appeared about 10, 8, 3, and less than 1 minute respectively, before Shou took the photo. They all emerged suddenly looking like Line 4, straight, even width,

3.3 Geothermal Eruption:

The Bam cloud was unusual since it emerged exactly from the epicenter. This was likely because its hot vapor condensed into a cloud immediately due to very cold surroundings at night during the winter. However, in many cases the vapor released at the epicenter does not immediately encounter atmospheric conditions suitable for condensation into a cloud. As a result, there is often a large distance between the first appearance of an earthquake cloud and its source. Since the cloud’s travel time and direction are not well-known, this greatly reduces the precision, or specificity of the prediction.

In the search for a solution to this problem, Shou identified another atmospheric phenomenon in images from weather satellites, which we denote geothermal eruption, or geoeruption. Geoeruption is qualitatively different from earthquake cloud although they have the same source, the impending epicenter. There are two key ingredients enabling the observer to distinguish this phenomenon in satellite weather images. First, geoeruption emerges as a sudden localized atmospheric heating or disappearance of cloud, often occurring in the morning or evening, or covered by weather clouds or fog. In some cases the size of the emergence region is limited by the resolution of the public satellite images, about 10 km. Since the warm region often grows rapidly after its onset, to as large as 50x50 km2.      
            After one hour, variation in the size of the emergence is as likely to be an artifact of the finite frequency of the images, which varies from hourly to bi daily, as to have any physical significance. The second characteristic is the persistence of the warm region despite the presence of moving clouds overlapping or in the vicinity. Typically the warm region expands while its source point remains warm through the duration, which can be up to several days, but is normally less than one day. We believe that the emergence region of this phenomenon precisely identifies the impending epicenter.
Fig. 6 shows a snapshot of several simultaneous geoeruptions in Taiwan on Jan. 30, 2000. Over the next 46 days, one or more earthquakes of magnitude greater than 4 occurred at each of the warm regions pinpointed (Table 2).

Figure 3.3.1: Taiwan geothermal eruption This image from the GMS satellite over Taiwan at 3:00 Jan. 30, 2000 was provided by Dundee Univ. , UK (@2). Several dark spots, indicating warm regions, appear in the midst of cloud cover. Their unusual appearance leads us to believe that they were not weather-related, but instead were geothermal eruptions. Over the next 46 days, a series of 8 earthquakes occurred at exactly the locations of the dark spots, as shown by the arrows

Fig. 3.3.2 shows a time series of images taken over the Eastern Mediterranean from 8:00 Feb. 23 to 2:00 Feb. 24, 2000. Based on these images, Shou made a prediction certified by the USGS on Feb. 28, 2000 that there would be an M5 or two M4 earthquakes within a coarse window of latitude 36.5N to 38.5N, longitude 36E to 39E (shown in the figure) and 50 days from Feb. 28 to Apr. 18, and a fine window of latitude 37N to 37.8N, longitude 36.8E to37.2E (too small to show) and 17 days from Mar. 25 to Apr. 10. The prediction was correct, as two earthquakes occurred at point B, well within the coarse window, at the edge of the fine window, and coinciding with a bulge in the geoeruption. No other earthquakes of magnitude bigger than or equal to 4 have occurred in the fine area window in more than 14 years since the beginning of the database on Jan.1, 1990. Within the fine time window, the predicted pair were the only earthquakes bigger than or equal to 4 in the region 29~44N, 31~48E, a region 637 times larger than the predicted area. Earthquakes also occurred later at points A and C, again coinciding with geo eruption features.    
              Similar to an earthquake cloud, a geoeruption can predict an earthquake for three reasons. First, its tail points toward the epicenter. Second, its mass indicates the magnitude. Third, its longest observed delay is 104 days, and the average is about 30 days.

Figure 3.3.2: Turkey geothermal eruptions This series of IndoEx satellite images of the Eastern Mediterranean was provided by Dundee Univ. (@2). A geoeruption had occurred in Turkey at Point A (37N, 36.1E) at 8:00 Feb. 23, 2000, and disappeared at 15:00. Meanwhile, another warm spot appeared at Point X and grew toward the northeast. Two small bulges appeared at Points B (37.8N, 37.2E) and C (38.2N, 38E) at 21:00. Based on the feature at Point B. Shou predicted an earthquake to the USGS. The coarse area window of the prediction is shown by the black rectangle and the fine area window coincides with Point B. Two earthquakes of magnitude 4.2 and 4.4 occurred at Point B on Apr. 2, 2000, 39 days later. Earthquakes also occurred at A on May 12 and C on May 7. All data are shown in Table 3.

Table 3: Turkey Geoeruption vs. Earthquakes

Note: P. Point of a geoeruption in Fig. 7. Lat. Latitude. Lon. Longitude. Mag. Magnitude. Dep. Depth. The earthquake data are from the USGS (@12), and the average latitude and longitude absolute errors between the earthquake data and the geoeruption data are 0.10° and 0.32°, respectively.

3.4 Statistical Significance and probability of earthquake predictions:
              To objectively evaluate the significance of an earthquake prediction, Shou proposed a probability calculation to simulate a random time guess. From a comprehensive earthquake database, select all earthquakes whose epicenters are within the predicted area and whose sizes are within the predicted magnitude range. Consider all time windows of the same time span as the prediction, using 1-day resolution. If a time window guess contains one or more of those selected earthquakes, it is a hit. Let A be the number of all hits, and B be the number of all time windows, then the probability for a random guess with the same time span to be correct is A/B (2). Table 4 selects all earthquakes of magnitude more than or equal to 5 in Fault AB from the World Earthquake Catalog of the USGS (@12) from Jan. 1, 1990 to Dec. 20, 2003, together 5102 days. The coarse time span of Shou’s Bam prediction is 98 days, so B= 5102-98+1=5005. The table reveals A=98, so the probability is A/B=1.96% for the coarse prediction. For the fine prediction, there was no earthquake in the database, so its probability is close to 0. Therefore, the Bam earthquake prediction shows that earthquakes can be predicted in practice.

Table 4: The probability of the Bam earthquake prediction

Note: The period from Jan. 1, 1990 to Dec. 20, 2003 contains 5102 days. For the coarse prediction, it has 5102-98+1 = 5005 different time windows, whose spans are as the same as the predicted span, 98 days, such as (19900101~19900408), (19900102~19900409), etc. The database lists only one M5.4 earthquake in the coarse prediction area window. Together 98 time windows, those beginning from Mar. 5, 1998 to Jun. 10, include the M5.4, so A=98 and its probability is 98/5005, or 1.96%. The database lists no earthquakes of magnitude 5.5 or greater in the fine prediction area window. Out of 5043 time windows of length 60 days, there are no hits, so the fine prediction probability is negligibly small (less than ~1/5000).

Based on observations of earthquake clouds and geoeruptions, both visible and infrared satellite images, Shou submitted 50 earthquake predictions between 1994 and 2001 to be certified by the USGS. Table 5 exhibits all of them, and their subsequent earthquakes, as reported in USGS databases. Assuming all earthquake data is without error, so called “Peer on”, 34 predictions or 68% of them are correct in time, location, and magnitude. They are called “hits”, while the others “misses”.           

3.5 Impact of Space Technology:   
             Clearly, the use of space technology has been essential to the development of an earthquake prediction method based on atmospheric precursors. Satellite imagery is by far the most practical way to obtain global round-the-clock coverage.

Figure 3.5.1: The M6.1 Afghanistan earthquake cloud This image was taken from a composite of the GMS satellite, provided by University College London (@3). At about 7:32 Jan.1, 1998, a hole with a line-shaped cloud inside appeared in a large weather cloud. The line-shaped cloud disappeared at about 16:25. Shou predicted an earthquake of magnitude larger than or equal to 6 in Afghanistan and its neighbors, with a coarse window of 25~41N and 53~105E from Jan. 5 to Feb. 18, and a fine window of 30~37N and 58~95E, from Jan.5 to Feb.4, 1998 to the USGS. The 6.1 Afghanistan earthquake at Rustaq (36.83~ 37.31N, 69.5~70.11E) (@19) marked by the tip of the arrow, on Feb. 4 proved the both coarse and fine predictions correct.

A good example is the magnitude 6.1 Afghanistan quake of Feb. 4, 1998. The portion of a global composite shown in Fig. 9 reveals the distinctive cloud that was used to make a successful prediction to the USGS.

Using satellite images of atmospheric precursors, Shou has successfully predicted 50 earthquakes, including a pair of 6.0 Xinjiang, China earthquakes on Apr. 5 and 6, 1997, the 6.4 Mexico Feb. 3, 1998, the 6.1 Afghanistan Feb. 4, 1998, the 6.6 S Iran Mar. 4, 1999, the 7.0 Mexico on Jun. 15, 1999, the 6.2 Japan Jul. 1, 2000, and the 6.5 Japan Jul. 30, 2000 to the USGS. He has also predicted the 7.0 Mexico earthquake on Jun. 15, 1999, the 7.4 Hector Mine, S California Oct. 16, 1999, the 6.2 Japan Jul. 1, 2000, the 6.5 Japan Jul. 30, 2000, the 6.8 Seattle Feb. 28, 2001, the 6.5 W Iran Jun. 22, 2002, the 7.6 Mexico Jan. 22, 2003, the 6.4 Gulf of California Mar. 12, 2003, the 7.0 Japan May 26, 2003, the 6.8 Chile on Jun. 20, 2003, the 6.0 Yunnan, China Jul. 21, 2003, the 6.8 Bam, Iran Dec. 26, 2003, the couple of 5.5 Pakistan Feb. 14, 2004, among others, to the public .

CHAPTER 4

EARTHQUAKE PREDICTION USING ANIMALS

 4.1 Introduction:

 Research being carried out in China has indicated that recognition of unusual animal behavior in a systematic way can lead and be used, in conjunction with other methods, as a means of predicting large and potentially destructive earthquakes. The following are examples of observed unusual animal behavior before major earthquakes occurred.

4.2 Unusual Animal Behavior:

In 1920, the largest earthquake to hit China with a magnitude of 8.5 occurred in Haiyuan County , Ninghsia Province . According to reports of eyewitnesses, prior to this earthquake, wolves were seen running around in packs, dogs were barking unusually, and sparrows were flying around wildly. It is reported that prior to the 6.8 magnitude earthquake in 1966 in Hsingtai County , Hopei Province , in Northern China , all the dogs at a village near the epicenter had deserted their kennels and thus survived the disaster.

Prior to the earthquake of July 18, 1969, (magnitude 7.4) in the Pohai Sea , unusual behavior was observed in seagulls, sharks, and five different species of fish. Based on observations of unusual behavior of giant pandas, deer, yaks, loaches, tigers and other animals, a warning was issued at the Tientsin People's Park Zoo, two hours before the earthquake struck.

The Chinese began to study systematically the unusual animal behavior, and the Haicheng earthquake of February 1975 was predicted successfully as early as in mid-December of 1974. The most unusual circumstance of animal behavior was that of snakes that came out of hibernation and froze on the surface of the earth. Also a group of rats appeared. These events were succeeded by a swarm of earthquakes at the end of December 1974. During the following month, in January 1975, thousands of reports of unusual animal behavior were received from the general area. Local people saw hibernating snakes coming out from their holes and into the snow. In the first three days in February the activity intensified even more and unusual behavior of the larger animals such as cows, horses, dogs and pigs was reported. On February 4, 1975, an earthquake of magnitude 7.3 struck the Haicheng County, Liaoning Province.

More instances of unusual animal behavior were reported. A stock breeder in northern China , feeding his animals before dawn on July 28, 1976, in the area of the Kaokechuang People's Commune, approximately 40 kilometers away from the city of Tangshan , reported that his horses and mules instead of eating were jumping and kicking until they finally broke loose and ran outside. A few seconds later, a dazzling white flash illuminated the sky. Tremendous rumbling noises were heard as a 7.8 magnitude earthquake struck the Tangshan area.

Other reports of unusual animal behavior prior to the occurrence of earthquakes have been reported in the literature and in books. Such unusual animal behavior included goats refusing to go into pens; cats and dogs picking up their offspring and carrying them outdoors; pigs squealing strangely; chickens dashing out of the coops in the middle of the night; fish dashing about aimlessly; and birds leaving their nests. It has also been reported that zoo animals refused to go back into their shelters at night; snakes, lizards and other small mammals evacuated their underground nests; insects congregated in huge swarms near the seashores; cattle sought higher ground; domestic animals became agitated; and wild birds left their usual habitats.

Surveys done in China show that the largest numbers of cases of unusual animal behavior precede the earthquake, particularly in the 24 hours before it strikes. In other parts of China where major earthquakes have been preceded by foreshocks, unusual behavior in rats, fish, and snakes were observed as early as three days prior to the earthquake, but continuing to several hours, or even a few minutes before.

4.3 Studies of Animal Behavior:

Throughout China 's long history, unusual behavior has been observed in every kind of common animal. Most of the behavior falls into the category of unusual restlessness and disorientation. Since animals have the capability of acting as predictors of earthquakes, the Chinese scientists have carried out surveys of animal behavior variations prior to earthquakes. A team of scientists including biologists, geophysicists, chemists, meteorologists, and biophysicists conducted a survey in the Tangshan area and in 400 communes in 48 counties around it after the 1976 earthquake. The scientists visited a number of places that were hit by other destructive earthquakes and, through interviews and discussions with local people, collected information on over 2,000 cases of unusual animal behavior occurring prior to an earthquake. The majority of the reports involved domestic animals. Based on this survey a preliminary report was prepared by the Chinese identifying 58 kinds of domestic and wild animals that had demonstrated unusual behavior.

The principal focus of research work in China has been on the behavior of pigeons. Biological studies on pigeons determined that a hundred tiny units exist between the tibia and fibula on a pigeon's leg. These nerve units are connected to the nerve center, and are very sensitive to vibrations. Scientists determined that prior to an earthquake of magnitude 4.0, which occurred in the area of the study, fifty pigeons that had severed connections between the tibia, fibula, and the nerve centers, remained calm before the earthquake, while those with normal connections became startled and flew away.

Because of the success in monitoring unusual animal behavior for the prediction of certain earthquakes, the Chinese, who have pioneered this work, have looked into ways to construct instruments that would duplicate the sensory organs of animals which were able to monitor, and sense, stimuli preceding an earthquake. Researchers found it very difficult to understand the mechanism of response stimuli. Physical or chemical stimuli come out of the earth prior to an earthquake and these must be the stimuli that animals can sense. For example, dogs may be able to hear the microfacturing of rocks a few milliseconds before a quake shock reaches the surface. Electromagnetic changes in the earth prior to an earthquake may be sensed by such animals as sharks and catfish which have low or high frequency receptors and sense such changes actively or passively. Also such electromagnetic field changes could be affecting migrating birds and the navigational ability of fish.

4.4 Mechanisms of Animal Responses:

What is the sensory mechanism of animals that controls their responses to changes related to an impending earthquake? As mentioned earlier, the behavior of an animal might be subject to changes in the magnetic field transfer at the electron level which, in turn, cause changes in the cellular behavior, or response. The living cell is essentially an electrical device and a micro molecular structure, and the sensory organs are all interconnected. Electro mechanic changes occurring prior to the occurrence of a large earthquake may be sensed by certain animals and filtered, then instinctively interpreted. Thus animals may have the means and sensitivity to sort out and discriminate the threatening precursory signals of an impending earthquake, thus activating a behavior pattern for survival.

These precursory electromagnetic or electro mechanic changes which precede an earthquake, although mixed with background noise, must be filtered by animals and coordinated through their sensory response to the total environment. Thus, behavior is determined by the sensitivity of the different component parts of the living system to the surrounding medium. Experiments with new instruments and electronic solid state sensors are being used now to determine animal response to impending catastrophic occurrences.

The benefit from such research would be in duplicating the sensory responses of animals to construct equally responsive instruments that can record or monitor these precursory changes. Thus, observing and studying animal behavior could lead to better earthquake prediction instrumentation.

CHAPTER 5

DEMETER

(Detection of Electro-Magnetic Emissions Transmitted from Earthquake Regions)

5.1 INTRODUCTION:

The ionospheric data recorded by DEMETER since the beginning of the mission are of high quality, and important events have been already registered. The following figures give a good idea of the DEMETER possibilities. They are related to the main scientific objectives of DEMETER:

1] The survey of the Earth electromagnetic environment.

2] The emissions linked to the anthropogenic activities.

3] The ionospheric perturbations linked to the seismic activity. The main purpose of the project is to perform a statistical analysis with many events in order to determine the main characteristics of the seismo-electromagnetic effects. It is too early to perform such statistics but data recorded during selected events are useful to determine the sensitive parameters which must be particularly surveyed in this statistical analysis.

5.2 THE FUNCTION OF DEMETER ACCORDING TO QUAKEFINDER ORGANISATION:

Figure 5.2.1: Function of DEMETER

• Satellite monitoring uses Magnetic Fields  (1Hz-1000Hz and higher)
• Electric Field  (1Hz- 100,000Hz and higher)
• Particle densities (electron and ion)

Advantages:

• See entire world, if in polar orbit (e.g. 700-800 km sun synch)
• More large quakes encountered per year (e.g. 100-200 >M6)

Disadvantages:

• Revisit time 2-3 days, for a few minutes each time
• Longer distance (lower signal strength)

Unique propagation mechanism

• Whistler mode propagation.
• Low loss waveguide up mag. field line.

CHAPTER 6

QUAKE FINDER

Quake Finder is a private company located in Palo Alto , CA conducting pioneering research in the area of earthquake forecasting. Conceived in 2000 as an education outreach concept by the successful aerospace engineering services company Stellar Solutions, Quake finder’s goal firmly developed into a broader vision—to save lives by conducting research with the aim to make global forecasts of seismic activity a reality in order to provide communities, within the next decade, with early warnings of potentially destructive earthquakes.

Tom Bleier – President, Founder and CTO – Over thirty years experience in remote sensing at The Aerospace Corporation and Stellar Solutions and twenty years background in ULF sensors

6.1 CALL MAGNET/MAGNETOMETERS:

There are many instruments used to detect the pre earthquake signals such as ELF. ELF/VLF are very low frequencies below 0.3 hz. Each system is dedesigned to detect and store ULF/VLF. Some of these observations are as follows

Figure 6.1.1: Satellite-based ELF monitorsdetect pre-quake (or post quake)

signals near large earthquakes (M6+)One example on left:

Note: Aureol-3 (M. Parrot) also claimedto detect ELF signals near quakes

 These are the observations taken by an satellite based call magnet prior to earth quake the California grid. Same readings but from ground based magnetometers some the above observation  we can see that ELF and ULF  before earthquake can be dected.

ground-based extremely low

Figure 6.1.2: Frequency (ELF) monitors reliably

Predict large earthquakes (M6+), days

to weeks prior to the quake?

One example on left:

6.1.1 Experiment to test hypothesis:

   Use the existing Cal Magnet ground-based Search coil (AC) magnetometers

- 55 sensors over State of California (2000-2004)

- 3 axis search coils (three configurations)

- 0.3 to 4 Hz BW

- 20 Hz sample rate, raw data stored @ site

- 300 sec RMS data displayed daily on web site

Ten ELF monitor kits were given to ten high schools in the greater San Francisco area, and each were asked to build and install their unit near the San Andreas, Hayward , or Calaveras faults. Each system was designed to detect and store ULF/ELF data as low as the sensor could operate (0.3Hz),and to ignore the Schumann Resonance at 7.5 and 15 Hz ()a noise source for this project). The lower frequency response was limited by the core material, the number of turns, and the quality of the preamp chips. There was a conscious effort to use the limited funds to get more sensors into the field in order to be closer to the possible quakes, rather than to have a few, very sensitive monitors.

6.1.2 Ground Magnetometers:

.

Figure 6.1.2.1: Search Coils: Two 25K turn coils each

Low noise feedback preamp (GSFC)

Hy Mu-80 core 13 in length, 1 lb

Quake Finder started the ELF network as a high school educational outreach program in 1999. In the early days, the funding was supplied by Stellar Solutions, the parent company of Quake Finder. Ten ELF monitor kits were given to ten high schools in the greater San Francisco area, and each were asked to build and install their unit near the San Andreas, Hayward , or Calaveras faults.

Each system was designed to detect and store ULF/ELF data as low as the sensor

could operate (0.3Hz),and to ignore the Schumann Resonance at 7.5 and 15 Hz ()a noise source for this project). The lower frequency response was limited by the core material, the number of turns, and the quality of the preamp chips. There was a conscious effort to use the limited funds to get more sensors into the field in order to be closer to the possible quakes, rather than to have a few, very sensitive monitors. Ultimately, we received further funding fro the high school units from a State of California grant, plus funding from Stellar Solutions for the improved QF-1000 units, and from NASA Hq for the improved QF-1003 units.

6.1.3 Coverage Area:

High School

• 3 axis mag. QF-1003

• 3 axis mag.

• GPS

• Global Star

• Air Conduct.

• Geophone QF-1000

• 3 axis mag.

Figure 6.1.3.1: Coverage Area

This map illustrates the placement of the high school monitors, the QF-1000 Commercial units and the QF-1003 NASA-funded units. The NASA units were built and deployed in the southern California desert areas in Conjunction with a prediction of Dr. Kellis-Borok (UCLA) for a M6+ quake in that Region between Feb ’03 and Sept ’03. They were also deployed near areas that Dr. John Rundle (UC Davis) had identified as having a significantly higher probability for Earthquakes based on a chaos theory and past earthquake history.

6.2 Satellite-Based Monitoring (QuakeSat):

• QuakeSat on orbit (June 30, 2003 to Nov 2004)

– 840 km circular, sun synch orbit (dawn-dusk)                         

– Single axis search coil magnetometer, small E-field dipole

– 4 channels (one at a time)

• 1-10 Hz B

• 10-150 Hz B (primary channel)

• 130-150 Hz E and B

• 10-1000 Hz B

– Sensitivity – noise floor

• 5pT at 1000 Hz

• 15 pT at 100 Hz

• 30 pT at 10 Hz

– 2 ground stations                                                                                               Figure 6.2.1: Quake Sat

• Stanford

• Fairbanks Alaska

• 9600 baud, half duplex

Quake Sat was a collaborative effort between Quake Finder, Stanford University (Prof. Bob Twiggs), Lockheed Martin training department, Cal Poly at San Luis Obispo (Dr. Jordi Puig-Suari), and Stellar solutions. The satellite was built in 18 mos, and weighs 4.5 kg. The launch was part of an 8 satellite launch from Pleysetsk Russia aboard a Eurokot launcher on June 30, 2003. The satellite achieved a good orbit of 840 km, sun synch, and dawn-dusk orbit. The orbit was very conducive to power generation, but less optimum for quiet ELF data collections since the collections occurred during the more turbulent ionosphere Periods at dawn and dusk. The flight was supported with a Ham radio ground station at Stanford ( Durand Building roof) fro the first 4 mos., and then a second ground station was built and Deployed at the UCLA HIPAS facility approximately 30 miles east of Fairbanks , Alaska . The satellite communicates with the ground at 436 MHz and uses a simplex communication scheme at 9600 baud.

CHAPTER 7

CONCLUSION

From this we can conclude that prediction of earthquake using Space Technology is simple and accurate with the help of Space Technology it is possible to save many life of human being. There are some other methods are also there like Ground Based Sensors, DEMETER, Study of Under Ground Movements, Study of Ionosphere Changes with the co-ordination of all this with Space Technology it is possible to predict earthquake very accurately.

The use of space technology has been essential to the development of an earthquake prediction method based on atmospheric precursors. Satellite imagery is by far the most practical way to obtain global round-the-clock coverage

If all country putting together there man capacity, research and money opens one company like Quake Finder to predict earthquake then this approach is also most effective for prediction of earthquake. There are some other methods are also there like earthquake prediction using animals if government of particular country teach there people how to observe the animal behavior and how to predict any Natural Disaster like earthquake from there behavior then it is also help to save many life’s of human being.   

CHAPTER 8

REFERENCES