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4
Building Damage and Losses
CLASSIFICATION OF BUILDINGS
For loss estimation purposes, the buildings within a region are
put into a number of categories according to a construction classifi-
cation system. This is the starting point in the vulnerability analysis
process, as shown in Figure 4-1.
The primary consideration in developing a classification scheme
is differences in the resistance of various buildings to damage during
ground shaking. Some of the factors taken into account are the
type of structural system, the materials of construction, the size of
the building, and the degree to which structural features limiting
damage have been provided during design and construction. The age
of a building is sometimes used as an indirect indicator of seismic
design level in areas where seismic codes have been adopted, and it
can indicate typical construction practice in a given region.
In the planning stages for a study, the steps of selecting a clas-
sification system, developing methods to prepare the inventory, and
assembling motion-damage information are all interdependent. That
is, the choice of a classification system depends on the availability
of information for the inventory and the effort that can be put into
carrying out the inventory. The availability of data relating motion
and damage for various kinds of construction is also limited, and this
similarly restricts the classification options.
26
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27
This 14-story reinforced-concrete apartment building experienced extensive
damage to the spandrel beams during the 1964 Great Alaska earthquake (M
8.3-8.6~. Its twin in another location in Anchorage was similarly damaged.
Structures that have adequate strength to resist moderate shaking may not be
able to withstand strong ground shaking. Photo courtesy of G. Hou~r~cr.
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28
L
Facility Classification System
/
Inventory
_
\
\
Vulnerability ~
1
1
-
\
Motion-Damage-Loss |
-
FIGURE 4-1 Structure of the vulnerability analysis portion of an earthquake
loss estimate study for buildings, lifelines, facilities with essential emergency
roles, and facilities with potentional for large loss.
The most commonly used classification system in the United
States for estimation of earthquake Toss is that developed by AIger-
missen and Steinbrugge (1984~. As shown in Table 4-1, this scheme
has 21 categories, determined primarily by the type of information
readily available to property insurance companies. A more recent
classification system used in the ATC-13 study (Applied Technology
Council, 1985) has over 40 categories, with height emphasized as a
factor. Both of these systems have been heavily dependent on the
work of experts in California. For loss studies elsewhere in the United
States, these basic schemes should be reviewed and possibly modified
and simplified to take into account local construction variations and
problems of assembling an adequate inventory. For example, in the
study of six cities in the Midwestern United States (Allen and Hoshall
et al., 1985), only eight building construction categories were used.
INVENTORY
Preparation of the inventory is usually the most time-consuming
and costly aspect of a loss study. It is also often the most frustrating,
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29
TABLE 4-1 Construction Classes Used in the ISO and NOAA/USGS Methods
Building
Class Brief Description of Building Subclasses
1B
2A
2B
3A
3B
3C
3D
4A
4B
4C
lA-1 Wood-frame and stuccoed frame dwellings regardless of area and height
1A-2 Wood-frame and stuccoed frame buildings, other than dwellings not
exceeding three stories in height or 3,000 square feet in ground
floor area
Wood-frame and stuccoed frame structures not exceeding three stories
in height regardless of area
Wood-frame and stuccoed frame buildings not qualifying under class 1A
One-story, all metal; floor area less than 20,000 square feet
All metal buildings not under 2A
Steel frame, superior damage control features
Steel frame, ordinary damage control features
Steel frame, intermediate damage control features (between 3A and 3B)
Steel frame, floors and roofs not concrete
Reinforced concrete, superior damage control features
Reinforced concrete, ordinary damage control features
Reinforced concrete, intermediate damage control features (between 4A
and 4B)
Reinforced concrete, precast reinforced concrete, lift elate
Reinforced concrete, floors and roofs not concrete
Mixed construction, small buildings and dwellings
Mixed construction, superior damage control features
Mixed construction, ordinary damage control features
Mixed construction, intermediate damage control features
Mixed construction, unreinforced masonry
Buildings specifically designed to be earthquake resistant
4D
4E
5A
5B
5C
ED
5E
6
SOURCE: Algermissen and Steinbrugge (1984~.
since in principle it is possible to develop a perfect inventory, but
in practice compromises must always be made. Time and budget
constraints lead to shortcuts and extrapolations, but evaluation of
building seismic performance necessarily involves the use of reliable
building data not obtainable by shortcut methods.
Facility inventories can be maintained and later used both for
updating initial loss estimates and in determining follow-up Toss
estimates for facilities or geographic areas or for other purposes
within a study region. Therefore, the pane] is persuaded that it is
wiser in the long run to compile systematically an inventory that
is as accurate as possible under the circumstances and resources
available. Guidelines for this approach to the inventory are suggested
in Working Paper D.
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30
There are three interrelates] factors to consider at the outset of
a project: the content of the inventory, the process of assembling the
information, and the manner in which the data are to be recorded or
stored.
Content of the inventory
What information concerning buildings is required? The basic
minimum data are:
Geographic location;
Category of seismic resistance;
Economic value of the building;
Number of occupants, at different times of day; ancI
Type of occupancy of the building (e.g., housing, commercial,
or essential facility).
Seisimic resistance must be derived from information on such
characteristics as construction class, age, height, and so on. The
meaning of economic value may differ according to the purpose of
the Toss study, as discussed below. Other information, such as the
function of the building (e.g., office or light manufacturing), may also
be desired.
A key problem is the degree of disaggregation or aggregation of
this information. At one extreme, the inventory may list only the
total economic value and total number of occupants aggregated for
all buildings in a given construction class within some geographical
area. At the other extreme each building might be listed separately
and then aggregated for purposes of predicting Tosses. Obviously this
question is strongly related to how the inventory is to be compiled
and how the information is to be recorded.
Another key question is the smallest geographical area to be
used. As discussed in the section on user needs, it should be possible
to disaggregate losses to any local political unit, which in the case of
a large city may mean wards, precincts, or districts. Census tracts or
postal zip codes also are convenient minimum geographical units, but
if used they may require localized modifications to make the tract or
zip code data correspond to other boundary lines.
There are a number of possible definitions for economic value,
and the choice depends primarily on the purpose of the loss estima-
tion study. Cash value and replacement cost have both been used.
For most studies, it seems appropriate to use replacement cost.
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31
Carrying Out the Inventory
The inventory process is a matter of assembling and using avail-
able sources of information, carrying out some amount of onsite
inspection, and applying some judgment. Census data are valuable,
particularly for housing, and generally some local records are avail-
able from, for example, planning departments and assessors' offices.
The most difficult information to pin down is the seismic resistance
or construction class. Here is where the experience of local engineers,
building officials, and architects, combined with judgment, have to
play a major role. Field sampling is also useful to define typical local
construction patterns.
It might seem ideal to develop a listing of all individual build-
ings, but this seldom is feasible. While some data files, such as
those maintained by assessors, are typically compiled for individual
properties, they are unlikely to contain adequate information for as-
signing seismic resistance. Moreover, for loss estimation purposes
it is quite satisfactory to have crude data for the more seismically
resistant buildings. Attention should be concentrated on developing
a reasonably good inventory of the seismically suspicious buildings
of high vulnerability that will incur the bulk of the serious damage
(Arnold and Eisner, 1984~. Onsite surveys to identify and enumerate
these buildings are vital to a satisfactory loss estimate. One example
of a seismucally suspicious construction class is unreinforced masonry,
which is often concentrated in recognizable districts.
ATC-13 describes three methods for assembling an inventory,
ranging from situations where detailed information is available in lo-
cal files to cases where very few data are available. For the common
latter situations, a method for abstracting an inventory from socioe-
conom~c data is described. The panel feels that extensive field studies
would be necessary to validate this approach, and that the varieties
of situations to be encountered make success unlikely. The pane!
believes that corresponding sums of money spent on direct observa-
tion of buildings to discern specific seismic performance indicators
would yield more useful results. There appears to be only a weak
correlation between socioeconomic characteristics, such as number
Of employees and the Standard Industrial Classification number in-
dicating economic sector, and construction characteristics relevant
to earthquake loss estunation. While a convenient data file, such
socioeconomic information is not particularly relevant to the task of
producing an inventory of facilities according to construction classes.
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32
Recording the Inventory
There are several reasons for collecting the inventory data in
a format consistent with computerization. At a m~nunum the data
should be stored in such a way that losses from several different
earthquakes can be evaluated. It is desirable that data be retained
so that updated loss estimates can be made In the future. Finally, in-
formation in an inventory is potentially valuable for entirely different
purposes, such as economic development planning and city planning.
It is vital to include meetings with various potential users of
inventory information at the beginning of a loss estimate study. Such
discussions will indicate how much effort is justified in obtaining and
formatting the inventory so that it can be accessed and used by
various governmental agencies. A key question is whether there is
the will and the means to maintain the inventory in an updated
condition. Where a significant long-term effort appears warranted,
use can be made of some impressive digital mapping technology well
along in its development by USGS and others (Alexander, 1987;
Brabb, 1985; Schulz et al., 1983~.
Role for a National Data Base
Creation and maintenance of a complete nationwide data base
on the construction characteristics of all buildings is an unpracti-
cal idea. However, some incremental, less geographically complete
projects, or efforts limited to simplified construction classifications,
may be feasible and desirable and should be investigated. Modest
improvements in the compilation of ciata might include:
. Comparing classification schemes so that future Toss studies
collect and organize their data in a format similar to either the ATC-
13 or NOAA-USGS construction classes, or to some new scheme.
. Suggesting data that could be reliably collected at virtually
no additional cost by the U.S. Bureau of the Census. Noting the
height of a building (e.g., placing it in one of three or four ranges of
height in terms of numbers of stories) may be such a possibility.
~ Investigating the potential of using the FEMA Multihazard
Vulnerability Survey method (FEMA, 1985) in connection with large-
scale earthquake loss estimation rather than for the field survey of
individual essential emergency operation facilities and life support
systems, which was the initial purpose for devising this multihazard
survey method. Field sampling of buildings previously surveyed by
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33
this method and easy access by earthquake loss estimators to Mul-
tihazard Survey data computerized by FEMA, are promising ideas.
The applicability of the data collection and analysis components
of the FEMA Multihazard Vulnerability Survey method (which in-
cludes wind and flood hazards in its scope as well as earthquakes,
depending on the site's location) should be evaluated in the context
of loss estimation.
MOTION-DAMAGE RELATIONSHIPS
Identifying the relationship between the intensity of ground shak-
ing and the damage experienced by a group of generally similar struc-
tures, or a construction class, is essential to vulnerability analyses.
One intensity/da~nage relationship is needed for each type of facility
in the classification system.
There are several ways in which this relationship may be ex-
pressed and evaluated. Additional discussion appears in Working
Paper E.
Use of Mean Values
The most common method for presenting the relationship be-
t~veen ground shaking and darnage is by a loss ratio curve. Typical
curves, developed some years ago by Steinbrugge et al. (1984) for
the Insurance Services Office (ISO), are shown in Figure 4-2. The
curves truncate at MM! OX because of the interpretation by ISO of
the MMI scale: intensities above OX were taken to represent ground
failures rather than ground shaking. (The classes of construction are
those in Table 4-1.) Percent loss, also called mean damage ratio or
mean damage factor, is the cost of damage expressed as a percentage
of replacement value. This is a mean value for a large population of
buildings of a given class.
Relationships of this form are particularly useful when only the
expected value of the dollar cost of damage is evaluated in a loss
study.
Irlfo~mation About Distribution of Damage
For some purposes, knowing only the mean level of damage is
inadequate. For example, serious casualties and injuries are usually
related to extreme damage experienced by a minority of buildings.
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34
Splh-level houses that were deAclent in earthquake resistance collapsed durlog
the 1971 San Fernando, C~ll~rnla earthquake (~ 6.6~. ~lLbulk houses in the
area supplied, experlenclug only cracks in plater.
Compton Boulevard between Alameda and Second streets ~llowlng the
March 10' 1933, Long Be=h e~hqu~ke (~ 6.2]. So many ages coped that
the street w~ completely blocked ~ bricks. Tbe poor pe~rm~nce of these
buildings led to chants in the bulldlog code It problbRed the construction
of unreln~rced-brlck bulldlugs.
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35
30
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MM INTENSITY
FIGURE 4-2 Loss ratio versus Modified Mercalli Intensity (mean damage ratio
curves). Designations on curves refer to Table 4-1 construction classes. Source:
Algermissen and Steinbrugge (1984~.
One method for expressing the distribution of damage is a dam-
age probability matrix (DPM) (Table (2).t The spectrum of damage,
iIn Table 4-2, the original source (ATC-13) used MMI levels XI and XII
to represent increasingly severe shaking severities beyond MMI X. As noted
earlier, confusion results when this is not explicitly stated, because a literal
reading of XI and XII indicates ground failure and at XII ~total" damage. In
Table 4-2 the DPM has been truncated at MMI X to avoid different portrayals
of MMI when definitions for MMI XI and XII may not be clear to the reader.
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36
TABLE 4-2 A Damage Probability Matrix Form
D amage Central
Factor Damage Probability of Damage (in Percent)
Range Factor by MMI and Damage State
Damage State (percent) (percent) VI VII VIII IX X
1--None 0 0.0 95.0 49.0 30 14 3
2--Slight 0-1 0.5 3.0 38.0 40 30 10
3--Light 1-10 5.0 1.5 8.0 16 24 30
4--Moderate 10-30 20.0 0.4 2.0 8 16 26
5--Hea~ry 30-60 45.0 0.1 1.5 3 10 18
6--Major 60-100 80.0 -- 1.0 2 4 10
7--Destroyed 100 100.0 -- 0.5 1 2 3
NOTE: These definitions are used as a guideline:
1--None: no damage.
2--Slight: limited localized minor damage not requiring repair.
3--Light: significant localized damage of some components generally not
. . .
requlrlng repair.
4--Moderate: significant localized damage of many components warranting
repair.
5--Heavy: extensive damage requiring major repairs.
6--Major: major widespread damage that may result in the facility being
razed.
7--Destroyed: total destruction of the majority of the facility.
aExample values are listed.
S OURCE: Applied Technology Council ( 1985~.
from none to total, is divided into damage states, each of which is
described both by words and by a range of damage ratios. For each
intensity of ground shaking, numbers in a column give the fractions
of buildings experiencing different damage states; the numbers in
each column sum to unity.
Fragility curves (Figure ~3) provide essentially the same infor-
mation as does a DPM, but in graphical rather than tabular form.
Each curve gives, as a function of the intensity of ground shaking, the
probability that the indicated damage state is squalled or exceeded.
While the curves shown in Figure 4-3 are only for one construction
class (wood frame), the general form is typical. The steeper the slope
of a curve, the less the variability in expected performance for that
damage state. The steep slope of low-damage curves 1 and 2 implies
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37
that it is relatively easy to predict that this class will have only slight
structural damage or only nonstructural damage at low intensities.
DPMs and fragility curves provide the same information in dif-
ferent formats. Thus, the choice between DPMs and fragility curves
is a matter of style and precedent. The DPM originated in connection
with loss est~rnates for buildings. Use of fragility curves developed in
studies of the performance of mechanical equipment and have been
applied in seisrn~c risk studies for facilities such as nuclear power
plants. It is important to note that mean loss ratios may be cal-
culated from the information in DPMs or fragility curves, but the
reverse is not true; information about the distribution of damage
about a mean cannot be inferred from a mean loss ratio curve.
Evaluating Motion-Damage Relationships
The loss ratio curves in Figure ~2 were constructed, employ-
ing considerable judgment, using loss data gathered during various
earthquakes, principally those occurring in California and a few other
western states, along with data from foreign earthquakes where con-
struction has been compatible. Actual data of this type are most
complete for wood-frame dwellings (these data do not appear in Fig-
ure 4-2), and more judgment has been required to construct curves
applicable to other buildings.
In a few cases, DPMs have been constructed using data from
actual earthquakes, tempered with judgment. A recent report com-
piled data on earthquake damage from a variety of sources (Thief and
Zsutty, 1987) and indicates the usefulness of hard data about past
performance in studies that attempt to estimate future performance.
However, for many types of buildings, and especially for those in
areas that have experienced few if any damaging earthquakes, actual
data are either very sparse or nonexistent. For such buildings, it
is necessary to rely on expert opinion to develop loss ratio curves,
DPMs, or fragility curves.
A systematized Delphi method approach was used to synthesize
diverse expert opinions into the family of DPMs found in the AT~13
study. The pane! examined the method used to develop these DPMs
and considered the credibility of the results (see Working Paper E).
Concern was expressed that the ATC-13 DPMs underestimated the
dispersion in the damage because zero probabilities were assigned in
each column to damage states away from the predominant damage
state. However, in the ATC-13 method, each matrix is meant to
OCR for page 38
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OCR for page 39
39
apply for average California design and construction, and the AT~13
report provides a method for combining adjacent columns in a DPM
~ . .. . ~ · · . . · ~
to renect the dispersion Introduced when good, average, and above-
average construction are lumped together. The pane} recommends
the development of new DPMs that incorporate this range of different
qualities of construction.
For common building types, loss ratio curves calculated from
the DPMs in AT~13 are very close to the corresponding curves
developed by the ISO. For less common buildings (e.g., tilt-up wall
construction) for which there are only limited data, the differences
in loss ratios expressed by the ISO and ATC-13 methods are within
the range of uncertainty in the data. The best use of the ATC413
DPMs, in the panel's view, is for building types for which there are
no ISO curves.
Both the ISO loss ratio curves and the ATC-13 DPMs are in-
tended primarily for use in California. The question then is: How
should motion-damage relationships be developed for use in loss em
timates for other areas? One answer lies in using expert opinion to
modify the California-based information for the types of buildings
found in the area to be studied. Analysis of some selected build-
ings can assist by indicating the general level of seismic resistance of
generic examples of building types in relation to the resistance of the
buildings forming the data base.
A Look to the Fature
It is clear that there are major gaps and uncertainties in the state
of the art for evaluating damage from an earthquake. Improvements
in this situation can come about only by systematically collecting
data from actual earthquakes. More effort should be devoted to
this purpose, not only for earthquakes in the United States but also
for earthquakes in other countries. In all such future studies, the
distribution of damage should be documented not just the mean
loss ratios, and not just by documenting interesting or dramatic
individual failures in a reconnaissance overview.
There has been an effort to develop and use empirical relations
connecting damage directly to magnitude and distance from an earth-
quake (Steinbrugge et al., 1984~. This approach bypasses the need to
evaluate the intensity of ground shaking at sites, and avoids di~cul-
ties in using MMI. Initial efforts to establish such relations are under
way using data from earthquakes in California. This is an interesting
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40
idea and should be pursued, but there are obvious limitations and
difficulties. First, different relations will be necessary for different
soil and topographic conditions. Second and more important, dif-
ferent relations will be required for different regions of the country
according to variations in attenuation of motion with distance.
LOSSES ASSOCIATED WITH BUILDINGS
One form of loss the cost of repair has already been discussed
in the previous section. The total cost of repair may be obtained by
simple summations, such as:
(dollar value in each category) x MAR,
all building categories
or
(average dollar value) x (number of buildings) x MERE,
all building categories
where MART is the loss ratio (or mean damage ratio) for the intensity
of the scenario earthquake. Such summations are made for subareas
of constant intensity and are then combined.
Considering uncertainties that will inevitably exist in the inven-
tory and the additional uncertainties in motion-damage relations,
the accuracy of the estimated loss for a given scenario is not great.
A prudent claim would-be accuracy to within a factor of 1.5 for
the aggregation of singI+family, wood-frame California dwellings, 3
for commercial, industrial, and institutional buildings, and an order
of magnitude (factor of 10) for an area with no recent earthquake
history.2 However, even such uncertain estimates are still very useful
for hazard reduction efforts and emergency planning.
600.
2 these expressions of uncertainty indicate the panel's judgment as to the
accuracy with which losses can be estimated. A precise statement about the
meaning of these ranges is not possible with the present state of the art, but
the following example indicates a reasonable interpretation:
Statement: "Uncertain by a factor of 3.~
Interpretation: Best estimate, 1,000; high estimate, 1,800; and low estimate,
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41
The estimation of other types of losses-casualties and homeless-
ness-is more complex and difficult.
Casualties
Of all the losses to be estimated, deaths and injuries are perhaps
the most important to governmental organizations. Protection of
life is a primary function of government and a prime incentive for
undertaking hazard reduction. Estimates of casualties are desired
for different times of day-typically mid-day, at night, and perhaps at
a commuting hour-and sometimes for different seasons of the year.
Unfortunately, the ability to predict casualties is not as good as
In the case of property loss. Data on which rational, systematic esti-
mates can be made are very sparse. The early NOAA-USGS studies
generally used historical rates of casualties per unit of populaton for
wood-frame dwellings and estimated rates for other types of con-
struction, or used city-wide casualty rates from previous earthquakes
applied to the population as a whole, adjusted up or down based
on changes in construction practice. These estimates were In effect
crude extrapolations of the limited data available, primarily from
California earthquakes.
A method specifically intended to estimate life safety risk factors
for most of the ISO construction classes was devised by McClure
et al. (1979) and applied to the problem of prioritizing engineering
studies for buildings owned by the State of California.
More recently (e.g., in the ATC-13 project) the tendency has
been to relate casualties to levels of damage. For example, Table 4-3
gives casualty rates tied to the damage states described in Table (2.
These rates are then multiplied by the estimated numbers of people
in buildings of varying classes.
This information is based on limited data plus considerable judg-
ment. This does represent a rational approach to estunating casual-
ties, and the pane} recommends use of this method combined with
careful judgment and comparison with historical data, where com-
parable cases pertain. It is essential that it be used with a DPM
that reflects the considerable dispersion of damage among buildings
of any one type, and the recommendations in ATC-13 for noting
variations in construction quality should be followed.
.
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42
TABLE 4-3 Injury and Death Rates in Relation to Damagea-
Central
D amage
Damage Factor Fraction Injured
State (percent) Minor
Fraction
Serious Dead
1 0.0 0 0 0
2 0.5 3/100,000 1/250,000 1/1,000,000
3 5.0 3/10,000 1/25,000 1/100,000
4 20.0 3/1,000 1/2,000 1/10,000
5 45.0 3/100 1/250 1/1,000
6 80.0 3/10 1/25 1/100
7 100.0 2/5 2/5 1/5
aEstimates are for all types of construction except
light steel construction and wood-frame construction.
For light steel construction and wood-frame construction,
multiply all numerators by 0.1.
SOURCE: Applied Technology Council (1985~.
It is evident that estimates of casualties will be very crude and
uncertain, and this uncertainty should be represented by, for exam-
ple, giving ranges of estimates, along with providing the best estimate
figures.
Homele~nese
Estimates for the number of people requiring shelter by public
agencies are also important for planning postdisaster operations. It
is even more difficult to make such estimates, partly because data
are scarce and partly because potential need ~ a function of weather
conditions and the ability and inclination of the population to find
their own shelter, such as with friends and relatives.
The NOAA-USGS studies used a 50 percent dwelling damage ra-
tio as an indicator of the need for alternative shelter. The most com-
plete effort at systematic estimation of homelessness is by Gulliver
(1986), who suggested a 20 percent damage ratio as the threshold
point past which homelessness results. Clearly, great judgment is re-
quired when estimating homelessness, and any estimate will involve
a high level of uncertainty.
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43
Estimates of casualties and homelessness should be regarded as
having an order of magnitude (factor of 10) uncertainty, although
it is possible to provide a tighter range of estunates when a study
is restricted to a few well-understood classes of construction. These
obviously are both matters for which far more data from actual
earthquakes are required to advance the state of the art.
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44
An example of the effects of landslides and debris flows triggered by the March
5, 1987, earthquakes (M 6.1 and 6.9) along the eastern flank of the Andes in
north-central Ecuador. Destruction can be seen of the Trans-Ecuadorian oil
pipeline (indicated by arrows) and adjacent highway by a debris flow issuing
from a minor tributary of the Coca River. Photo courtesy of R. L. Schemer.
Representative terms from entire chapter:
control features
