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Working Paper D Inventory of Facilities This paper addresses the inventory problem. It limits the term inventory to the task of listing man-made facilities and their at- tributes, rather than the parallel task of producing an inventory of the attributes of different soil types or other geologic data, which is a seismic hazard analysis task. Structures other than buildings, such as lifeline facilities, can be inventoried similarly as for buildings, al- though the information sources and data collection techniques vary. Most major lifeline facilities are already inventoried to some extent by their owners, and it is the more difficult problem of conducting an inventory of buildings that is the focus of this paper. The number of buildings and other structures in the study area of most large-scale loss estimation studies is great. The earthquakes selected as the planning basis for large-scale loss est~rnation studies can be strong enough to shake 5,000 or more square miles, and the study area of most interest often contains a population of several million. Pre-existing files or data bases do not contain the amount or quality of information that is desired for the purpose of estimating earthquake losses. Inventories used for earthquake loss estimation purposes must be developed in a highly selective manner because this is the most time-consuming and costly step in the loss estimation process. Thus, the inventory task is often a matter of using the data that can be collected and organized within the budget allotted, rather than developing the ideal inventory. 130

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131 The losses of concern may be facilities damaged or rendered dys- functional, dollar losses to facilities or dollar value of lost production, casualties, or homelessness. The kind of loss information sought is a determinant of the kinds of inventory information needed in the analysis. Hence, the types of loss to be estimated must be specifically defined prior to selecting an inventory method. Theoretically speaking, a unique and all-purpose inventory might be created, but its contents would include so many descriptors and other items of information that it would not be feasible to assemble. Moreover, given the lack of understanding about motion and damage or ground failure and damage relationships and the prospect that this understanding will improve in tune, the chances of anticipating all relevant inventory data today for some future use are, indeed, slim. Efforts to create an exhaustive inventory of information about facilities would be a misguided, ineffective effort. HIERARCHY OF DATA Based on recent loss estimations prepared by different methods and people, the best hierarchy of data items seems to be: ~ Facility location (addresses are preferred for buildings and structures, but they are often listed only by zip code or census tract; the census tract or other appropriate zone is used for linear or area- wide facilities); Type of structure; Materialts) of construction (for the load-carry~ng system); Height (for buildings); Floor area (for buildings); Date constructed; Value (market or replacement value adjusted to a selected base year); Use of facility (occupancy or social function); and Number of people in facility at different times of day and season. Many other data might be added that, based on present knowI- edge of earthquake effects, could improve the accuracy of loss esti- mates. Among these (not necessarily in order of unportance) are: Type of foundation system; Configuration of facility (in plan and in elevation or section); Special-damage control features of facility;

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132 Code under which facility was constructed; and ~ Nonstructural features or contents with special fire or haz- ardous materials characteristics. Nevertheless, no loss estimates are possible without certain ba- sic information about facilities. Further, some kinds of inventory information are common for all loss estunation methods, that is, fa- cility location, construction classification, occupancy data (number of occupants and type of occupancy or use), and facility property value. According to current procedures, this information is assem- bled (inventoried) by (a) field observation or sampling, (b) review of other previously assembled records for a given community, or (c) extrapolation from conveniently available records to the end-form construction data desired, such as by inferring floor area from num- ber of employees or land-use acreage figures, degree of earthquake resistance incorporated in the design from date of construction, or value from floor area. When other economic losses are to be estimated, additional in- ventory information is needed, especially the facility's economic use, or "social function" in the terminology of ATC-13 (Applied Tech- nology Council, 1985), and facility contents. Economic relationships that are not a part of the inventory also must be modeled. Essential inventory information can be assembled in several ways, and no single inventory method can be recoin-mended. However, two major alternatives discussed in this paper are (~) the NOAA- USGS method of field observation, coupled with input from local building experts, lancI-use patterns, and census data, and (2) the FEMA/ATC-13 method, which would use existing detailed construc- tion class inventories where available but in practice would generally rely on extrapolations from economic data to impute almost all con- struction characteristics. The most important attributes of facilities other than buildings seem to be unique to the type of facility and are not addressed herein. For example, while underground pipelines can be treated in a parallel manner to buildings in classification systems, the general headings have very different meanings. The size of a pipeline would probably mean the diameter of a pipe, while for a building it would mean the square footage or height. The types of materials used for pipes are also different from buildings.

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133 DISCUSSION OF ESSENTIAL DATA The following subsections discuss three aspects of the data re- quired for essentially every study. Construction CIasees The most frequently used approach to developing an inven- tory of building construction characteristics Is the construction class method. Once the facilities are described in terms of their location and construction class, and after construction classes are tied to motion-damage-Ioss relationships, this overall vulnerability analysis can be combined with the seismic hazard analysis to predict damage. Table 3-1 presented an example of a typical construction class system (see Chapter 33. Developed by the Insurance Services Office (ISO), this scheme has been widely used for insurance as well as noninsurance loss estimation purposes. Once the difficulties of prop- erly counting buildings and assigning them to the appropriate class are overcome, relationships between shaking intensity and resultant damage are used to project damage (see Working Paper E). The degree of approximation present in this approach Is typical of earthquake loss estimation studies. It is very expensive to col- lect precise data about construction characteristics, and these data are not already tabulated in inventories prepared for nonseismic purposes. Although this scheme may seem to categorize the building stock rather coarsely, it is usually more than precise enough to match the accuracy of the inventory work. The extreme case of what might be called a detailed inventory is the information an engineer collects concerning materials properties and geometric data on each structural member and connection in a building for the purposes of new design or an evaluation of a build- ing's earthquake vulnerability. This "inventory" is then subjected to detailed load and capacity calculations to design an adequately strong and stiff structure or to see if the existing building is ade- quately earthquake resistant. Even when an inventory of this detail is collected for a single building, the estimation of earthquake damage that would result from a specified earthquake is still an approxima- tion. Thus, while it is true that the better the inventory the better the accuracy of the resulting loss estimates, it is also true that even with a perfect inventory there would still be a large amount of am proclamation inherent in the process of estimating the losses that might occur in future earthquakes.

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134 A discussion of the extent of building stock inventory information already available for earthquake loss estimation purposes will be found In work conducted at Cornell University (Jones et al., 1986) and by the Association of Bay Area Governments (ABAG) (Perkins et al., 1986~. A rough estimate of the field work required in the ABAG project to survey commercial or industrial areas is that about five census tracts per day can be Windshields surveyed from a slowly moving auto with a two-person team. The study by Gauchat and Schodek (1984) is innovative for its use of aerial photo analysis, although it restricted itself to housing be- cause the construction characteristics of housing are easier to observe in this way; commercial and industrial building construction charac- teristics are more varied and less easily observed from the exterior. In a study of Los Angeles County earthquake losses by Scawthorn and Gates (1983), except for construction data on high-r~se and unre- inforced masonry buildings, inferences were used to convert land-use maps showing acreage of various uses into 13 construction classes and into building areas. A committee of engineers, building officials, and realtors was relied on for these extrapolations. The NOAA-USGS studies also capitalized on existing files con- cerning high-rise or other special categories of buildings, used census data to inventory most of the housing, and relied on field sampling of commercial-industrial areas coupled with land-use maps and local engineering knowledge of typical construction patterns. Occupancy When life safety impacts of an earthquake are to be estimated, as is almost always the case except for insurance or other property loss studies, the number of occupants in buildings must be estimated. Once the damage to a class of construction is estimated, the per- centage of occupants or passersby who would be slightly or seriously injured, or killed, is estimated. This allows for the number of persons to be multiplied by this ratio to produce estimated casualties. An- other approach used instead of or in combination with this method is to apply a casualty ratio to the overall population of an urban area. The number of people who would be outside of buildings must be estimated because for some classes of construction, notably un- reinforced brick buildings, the collapse of at least some brickwork off the outside the building to the sidewalk or other exterior area is more likely than complete collapse.

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135 The time of day must be taken into account. In many areas of the United States, people work, shop, and engage in other daytime activities in buildings that are on average more hazardous than the residences where they spend the night. E~tunating losses for different tunes of day is typical of loss studies for this reason. Fortunately, census data, planning department studies or economic data, and reliable inferences relating the number of occupants to land-use or building area data (Jones, et al., 1986) are usually available. This is not as difficult an inventory task or as prone to error as the listing of buildings according to construction classes. Another aspect of occupancy or use that must be collected for some studies is the type of occupancy or function of the building. For estimating the ability of emergency response agencies to experience an earthquake and yet be able to provide essential services, most loss studies pay particular attention to hospitab. In terms of the overall medical system in the area, the medical roles of other facili- ties, including ambulance garages, wholesale pharmaceutical supply locations, ~d blood banks, must also be properly inventoried. For estunat~ng economic losses, an estunate of the economic activity occurring in buildings must be made. The designation of type of use for facilities with essential emer- gency response functions (e.g., fire stations and hospitals) is almost always easily available from government agencies or other sources. Since these more essential facilities can be listed quickly, it is possi- ble to segregate them and address their inventory and analysis tasks differently. Detailed, facility-specific techniques are more costly, but relatively few essential facilities exist (and in some cases only the most essential among this small population need detailed attention). The greater cost is also justifiable on the grounds that the vuInera- bility analyses for these buildings should be more accurate because these facilities are more important for emergency planning and to some extent for hazard reduction purposes. In California, for example, there are (in about 1985) 520 hospi- tals, 433 essential communications facilities or emergency operating centers, and 441 police or sheriff stations (Office of Emergency Ser- vices, 1986~. There is a greater number of fire stations (3,155), but many of these are small in size or significance and are generally one of the easiest of the essential emergency function buildings to field survey. ~ the set c safety study for the general plan of the cities of El Cerrito, Richmond, and San Pablo in the San Francisco Bay Area (Cities of El Cerrito. Richmond, and San Pablo, 1973), every

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136 fire station in the three cities was enumerated according to address and location on a seismic hazard map, and the type of framing of walls and floor or roof was noted; this was a minor aspect of the overall project and only a small effort was devoted to it. These different types of inventory data that relate to the con- struction class and the various occupancy-related information items are not centrally collected by any agency or organization, and their availability can vary from one local jurisdiction or region to the next. Skiff inventory development is largely a matter of carefully ex- tracting the useful but inexpensive data from pre-existing sources, such as local planning or assessor's departments, or from field survey work and then moving on to a completely different source to obtain other information to fill gaps. Facility Location Typically seismic hazard maps of ground failure or ground shak- ing are only available on a relatively coarse scale. Either census tracts or zip codes often provide a more detailed scale than is required to match the detail of the seismic hazard mapping. Where detailed geo- logic maps showing the distribution of soft soil or high ground-water areas are not available, and where the seismic sources are relatively distant rather than located within the study area, facilities some- tunes need not be located more accurately than by general district of a city, or even by city, for the purposes of that particular study. Because refinements in the geologic data base or changes in the analysis of seismic sources may occur and because the inventory may be useful for nonseismic purposes, it is always desirable to locate facilities according to a scale at least as fine as zip codes or census tracts, unless especialRy rapid and inexpensive studies are to be at- tempted. Since Bureau of the Census data include an enumeration of one- to four-family dwellings, dwelling lomes are generally esti- mated from an inventory that is already conveniently broken down into census tracts, block groups, and blocks. Census tract boundaries are redrawn periodically by the Bureau of the Census, and zip codes are also rearranged by the Post Office, which create an updating problem. While not a major problem, census tract, zip code, and political jurisdiction boundaries must also be reconciled; a census tract, for example, may extend into more than one municipality. Disaggregating the inventory down to a small geographic level is

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137 a goal sought by users, but they also face problems of confidential- ity or controversy if specific facilities are identified. In the seismic safety study for San Francisco's general plan (UEtS/Blume and As- sociates, 1974), a building-specific inventory of the larger seismically hazardous or suspicious buildings of the city and county was pro- duced, based on a rapid technique using county assessors' data and a walk-by of each major building by an experienced engineer. This de- tailed and potentially very useful informationthe detail that users often request was also very controversial and never made public. According to the engineer in charge of the study and the head of the planning department, the information was withheld at the direc- tion of the city government out of fear of lawsuits. The head of the building department at that tune advised in a memo that publicizing the list would do no good and would cause "panic, accusations, etc." (Finefrock, 1980~. On the other hand, failing to disclose information about hazards may increase liability exposure, so this issue of the specificity of an inventory should be considered with legal advice. It ~ also true that earthquake hazard inventories required by state or local law, as distinct from inventories compiled in loss estimation studies, have withstood legal tests over more than a decade. Another approach to defining location is to use an arbitrary grid or rectangular cell system. The I-hectare cell (about 2.5 acres) system used by ABAG in a recent earthquake loss inventory project was found to be generally adequate. In Japan, a grid is often used to map both seismic hazards and building inventories using similar small-scale ceils. Where local government assessors' files contain construction- related or other useful information, the assessor's parcel can be used as the basic mapping unit. Assessor's parcels conform to land owner- ship patterns, which are usually much finer-scaled in urban areas than zip codes or census tracts, or even census blocks. Census tract, zip code, arbitrary grid, and assessor's parcel boundaries are unrelated to each other, although with extra cost they can be cross-referenced. Geographic information systems using digitized maps provide several advantages once their initial cost is paid and funding for their maintenance is assuredly. Changes in seismic hazard zones or contours can be easily accommodated. Changes in the facility inventory, once the new information is collected, can be included inexpensively in new calculations of loss. In addition, the mathematical manipulation of units within geographic areas (such as calculating the number

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138 of dwellings located where the intensity is estimated at a certain level) can be easily accommodated. A recent conference devoted to geographic information systems indicates the range of possible natural hazard as well as other applications (American Society for Photogrammetry and Remote Sensing, 1987~. Another great advantage of computerized approaches is in deal- ing with problems where various combinations of layers of informa- tion on the map must be compared. A study of regional southern California earthquake response issues (Haney, in progress) is digitiz- ing pre-existing information, some of which is related to lifelines, from a California Division of Mines and Geology (CDMG) report (Davis et al., 1982a). Broadcast coverage areas for Emergency Broadcast System stations can be compared with the CDMG study's projection of intensities and with the languages of residents as determined from census data, for example. No files on building structures are being added to the data base, although there are plans to use the AT~13 method in its present form for this purpose. Two disadvantages of computerized systems are the initial costs of establishing the system and the costs of maintaining the system. The first-year cost of establishing a Regional Information Manage- ment System in southern California using the earthquake loss esti- mation method applied to a pilot project area in San Bernardino County was estunated at about $1 million (Schulz et al., 1983), although other nonseism~c benefits were postulated. The work in southern California that is jointly funded by FEMA and the state of California (Haney, in progress) and three recent projects illustrate this evolving approach: digitizing of several dif- ferent types of seismic hazard and facility data for Sugar House quadrangle in Utah by the USGS Rocky Mountain Mapping Center (Alexander, 1987~; digitizing of seismic hazard maps for San Mateo County, California (Brabb, 1985~; and digitizing of a small study area in San Bernardino County, California (Schulz et al., 1983~. None of these projects deal very specifically with the problem of enumerating buildings in terms of construction characteristics, which is by far the single biggest inventory problem in the earthquake loss estimation field. This is not what computerized approaches do best. Manipula- tion of already collected information, rather than data collection, is the strong point of the computer-aided inventory approach. Portions of the USGS map system for the United States, the familiar topography maps produced at scales as fine as 1:24,000, are now digitized and the remainder of the USGS maps will eventually

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139 be converted to this format, allowing for various types of digitized data to be related directly without having to convert via paper maps. The U.S. Bureau of the Census will digitize the results of the 1990 census (Marx, 1986~; future earthquake loss studies that tie into a geocoded information system may benefit more than at present. Many local organizations, such as utility companies, planning depart- ments, emergency services departments, and others are investigating the potential of combining resources to produce multipurpose maps. SUGGESTED SOURC1:S OF INVENTORY INFORMATION Guidelines are suggested here for preparing rapidly an inventory of facilities when the preferred ideal inventory cannot be done for an earthquake loss estimation study. A number of ways have been used or proposed. These have typically been uniquely tailored for a particular type of loss study in a particular area. The techniques suggested or followed in preparing such inventories have been shaped not only by the kinds of data needed for the particular study, but also by the kinds of information readily available in the particular area. An additional element of expert judgment from persons familiar with the study locality has been an important part of these inventory techniques, because it typically has been necessary to infer needed end-form data from other types of information. Inventories that are less than the ideal type have advantages as well as limitations that must be recognized In the beginning. Foremost among the advantages are: in general, they are less costly to prepare, and they typically can be completed in less tune than an ideal inventory would take. Foremost among the disadvantages are: more sophisticated ex- pert knowledge must be employed in extrapolating essential data from available raw data, and they are less accurate than more de- ta~led inventories and these inaccuracies carry over to the loss esti- mates. Poor-quality input information leads to poor output results. Rarely have earthquake loss estimation studies quantified their un- certainties, so a study with less accurate inventory, and thus less accurate loss estimates, may appear to be as valid as a more accurate study, but this is not the case. Owing to the diverse types and forms of readily available data about facilities in a study area, a ste~by-step procedure cannot be suggested for preparing an inventory, nor can it be suggested that

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140 one source of data is better than another. The process to be followed depends on several factors, among them: Financial resources available for the study; ~ Type of loss study, which establishes the type of end-data needed for the inventory and which relates to the geographic scale, kinds of facilities and losses, and time frame as discussed earlier; and ~ Kinds of existing data (i.e., what kinds of data have been com- piled on, for example, schools, dwellings, publicly owned buildings, and high-rise buildings). From earthquake loss estimate studies prepared by others and from examination of basic elements of loss estimation methods, some general guidelines for an inventory procedure can be inferred. First, the end-form of the inventory data for the particular loss study must be established, which in most cases consists of: ~ Numbers of facilities of various types that are located in specified zones (e.g., blocks and census tracte), in short, a count of facilities. Classification of facilities according to the classes in the motion-damage relationships to be used in the analysis phase. Value of facilities, normalized to some base year. . Occupancy information, since casualty loss estimates are in- cluded in many studies. E unction or use classification, if economic sector loss estimates are to be prepared and if essential emergency response facilities are to be identified. Second, the inventory must be built at least partly from ex- isting data sources. Inventories created from field observation are much more costly than those based on reuse of existing data. More- over, some of the end-form data can be extrapolated with reasonable accuracy from existing data sources, especially when someone knowI- edgeable about the study area is utilized. The degree of extrapolation that is acceptable is a significant msue In this regard and relates to the required overall accuracy of the result from the user's viewpoint. Following is a brief list, with some discussion of the existing data sources most often used for preparing earthquake loss estimation inventories. 1. For housing: ~ U.S. census information. These data, giving dwelling unit counts, occupancy numbers, and relatively precise locations, are

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148 . dwellings and for population distribution, the best source of data was found to be the United States Census data. The Census provider information of the numbers and geographical distribution of dwellings according to census tract. Census tracts are a convenient unit since the number of one to four family dwellings in each tract seldom exceeds 2000 units in the Salt Lake area. The most accurate cost estimates for housing were obtained from boards of realtors or realtor associa- tions which compile frequent (usually monthly) summaries of actual dwelling sales. Aerial photos and appropriate sampling techniques were used to develop the construction characteristics of dwellings since there is a great difference in vulnerability between wood frame and other types of housing construction. Studies (Steinbrugge and others, 1969) have shown that the number of brick, concrete block and related types of construction used for dwellings in, for example, California is small (less than a few percent). It was found that brick, concrete block and related construction types made up about 60 per- cent of dwellings in the Salt Lake City area. A detailed inventory of buildings by classes of construction other than dwellings was un- dertaken by the H.C. Hugh Company of Salt Lake City for the U.S. Geological Survey. The development of the inventory was supervised by K.V. Steinbrugge. Air photos and drive-by inspection of buildings in-each census tract were conducted. Construction type was noted and the dimensions of the buildings were obtained either from the air photos or from actual measurements. Replacement cost per unit area for the various classes of construction was estimated by a professional building inspector in Salt Lake City with long experience in the re- gion. It is believed that the inventory obtained in Salt Lake City is extremely accurate for the purposes of an earthquake loss study and that the errors in the estimation of ground motion are likely to be much larger than the inventory errors in this particular study. In contrast, the inventory method for the San Etrancmco Bay Area was based on building information extrapolated from census data (dwellings) and modified fire insurance property values (other buildings). AIgermissen and Ste~nbrugge (1984) give the following description of the inventory method in this case. Data on dwellings was obtained in the same manner as described in the Salt Lake City study i.e., from census data and summaries of real estate transactions. For buildings other than dwellings a novel ap- proach was used. Quoting from Steinbrugge and others (1981~: `'The initial data were fire insurance property values by county for north- ern California and an assumed 8.3 magnitude earthquake on the San Andreas fault. These values included dwellings, commercial buildings, manufacturing plants, warehouses, offices, and all other fire-insured properties. These property values were increased to include non- insured private property as well as increased to include under-insured property. Adjustments were made on a judgement basis to include the value of Federal, State of California, and local governments-owned buildings. Intensities from the NOAA report's isoseismal maps were

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149 converted into loss {actors, or the percent loss based on an im- personal definition basis. These percentages were multiplied by the property values to obtain the total impersonal 1088 by county in the study area, then summed to obtain the total aggregate loss. In this process, values were adjusted to compensate for inflation to 1980. Building contents for the aforementioned San Andreas earthquake were analyzed in a similar manner to derive the total contents aggre- gate loss. A strong point of this NOAA-USGS inventory approach is its balancing of accuracy versus detail pushing the available data as far as appropriate and then stopping short of making further assump- tions that would be necessary to obtain more detailed estimates. The expertise used in these studies appears to be appropriate to the task: While earthquake engineering experts were employed, the expertise of real estate, building inspection, insurance, or other local sources of knowledge concerning the distribution of classes of construction was also utilized. A weak point in the method is that complete documen- tation of the techniquecomplete enough for others to replicate or test the technique in an updating study of the same area or to apply it elsewhereis lacking. Since the experience of a few key individuals has been heavily relied on in these studies, documentation may be inherently difficult, and to some extent it would be more a matter of teaching an art rather than specifying the precise steps that could be mechanically followed. The 1?EMA/ATC-13 Inventory Method The method for estunat~ng losses from earthquakes described in the AT~13 report (Applied Technology Council, 1985) was designed to provide Formation on damage, casualties, and immediate func- tional loss to be combined with an economic model for predicting economic losses, that is, direct building and structure lopes, loss of equipment, production losses, losses to infrastructures such as utilities and transportation systems, and losses due to interrupted business. To serve its original intended purpose, the inventory and loss estimates had to be compatible with the economic sectors to be used in the interindustry input-output model. Accordingly, this method ~ comprehensive in the inventory it seeks. Forty classes of building construction and 38 nonbudding structure ciames are de- fined, and each facility must also be defined In terms of one of 35 occupancies or asocial functions.

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150 The broader nature of the ATC-13 inventory makes it only par- tially comparable with the NOAA-USGS method, and only the por- tion of the ATC-13 inventory method that dead with buildings is discussed here. It should be noted that the breadth of the AT~13 method which encompasses lifelines, industrial structures, ground failures, and functional losses in a quantitative manner ~ one of its significant accomplishments. The FEMA/ATC-13 inventory method aims at compiling loca- tions and quantitative measures for ad facilities plus descriptors of the construction that allow classification for use In estimating dam- age. Facility values are also needed, as is information about each facility's economic use for input into an economic mode} that begins with damage and reduction In functional levels and then forecasts longer-term econorn~c impacts. The portion of the loss study that inventories the information and analyzes it to produce estimates of immediate losses is called FEDLOSS by FEMA in its automated form. The portion of the loss study that would employ an economic input-output mode} to est~ate longer-term econorn~c losses ~ called FElMS (FEMA Earthquake hnpacts Modeling System). The AT~13 report states its preferred source of inventory data as pre-existing inventories of facilities containing the required con- struction class detail, but because even less demanding classification systems cannot be supported by data that have already been col- lected, this preference will in most cases be unfulfilled. This hoped for pre-ex~sting inventory is called a Level ~ inventory. A Level 2 inventory, the one necessary in most cases, wiD be described below. A Level 3 inventory ~ sunply a complete synthesis of an inventory based only on overall population data, such as by a~um~ng both the number and construction types of all buildings in a city on the basis of its population. In the Level 2 approach, the location and descriptors of con- struction are obtained by extrapolation from a variety of economic and census data. The sources for these data are discussed in ATC-13, and are described in detail in the FEMA Data Base Catalog (FEMA, 1985b), which lists the many different computer data files acquired by FEMA from other agencies, through marketing or economic anal- ysis services, or in some cases from within the FEMA organization. These data bases have been accumulated and funded primarily as a function of the civil defense program of FEMA and its predecessor agencies and have been used in nuclear war loss estimations. Corre- lations between facility and use classification were developed in the

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151 ATC-13 project to allow for the transformation of economic data into construction data. The relationships imputed In the ATC-13 study were developed only in the context of California. ~ some ways, facility classifications of the ATC-13 method are similar to those of the USGS method, but are more detailed. The ATC-13 method has almost two tones as many classes of construc- tion as the NOAA-USGS method (40 versus 2l, comparing building classes only), and each individual facility must also be amigned one of 35 use categories. There are, however, some buildings whose construction would be more precisely defined by the NOAA-USGS inventory (or ISO) scheme, such as a steel moment-resisting (rigid frame, or rigidly connected joints) building with flexible diaphragms (or floors acting to resist lateral forces). Clearly more information is required to construct an inventory for the 40 ATC-13 classes of facilities than for 21 classes. Given any comparable inventory budget, the accuracy of the assignment of a facility to its proper class in the ATC-13 method would usually be less than in the NOAA-USGS method. The greatest advantage of the ATC-13 method ~ that it is very powerful: it can assemble a very large and detailed inventory inex- pensively by using already computerized socioeconomic data. This is also its biggest disadvantage compared to methods that use ac- tual inventory data obtained from or checked by fieldwork with less extrapolation. The large amount of extrapolation and reliance on rules of thumb developed by combining the opinions of earthquake engineering ex- perts can be seen from a typical example of how the inventory method would operate. First, the ATC-13 method would probably start with the number of employees who work at a commercial or industrial business. (For some small number of industrial facilities, the FEMA data bases may contain construction data and thus make the Level 2 extrapolations unnecessary. The number of ones to four-family dwellings can be obtained directly from census data.) One of a few data bases, such as the Census Bureau's Manufacturing Establish- ments by Industry Sequence, would be used in which the known information (excluding economic data on value of goods produced, for example) is simply number of employees and the location by zip code, along with the detailed (four-digit) Standard Industrial CIas- sification (SIC) code that defines the type of economic activity. The precision of the location is sometimes but not usually an issue. For

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152 example, the zip code location listed for a supermarket company in a city wall lump Al of the employees at the headquarters' zip code. These data number of employees, type of economic activity, and location- are the only data known directly for the facility in most cases, and the remainder of the necessary data ~ synthetic. As ATC-13 notes, The FEMA Manufacturing Establishment File, the Wholesale Trade Establishment File, and other business establishment/company files do not include either the size, location, or structural characteristics of facilities. This information must be estimated based on economic data such as the number of employees or annual production amounts. . . . Few if any existing facility databases or the inventories synthesized using Level 2 and 3 procedures contain sufficient information to allow the accurate determination of Earthquake Engineering Facility Classifications. The second step in the AT~13 inventory method Is to relate the number of employees to the building size, according to estimat- ing factors for different occupancies. These relationships are gener- ally drawn from transportation studies, especially those of Caltrans (California's highway department). In the ABAG inventory method (Perkins et al., 1986), similar relationships were used to estimate building square footage, using instead Federal Highway Administra- tion data. This extrapolation is more accurate than those of the other steps and is not a major source of error. As noted in the work of Jones et al. (1986), stable and reliable relationships exist for square footage per person estimating factors, although a curious effect of this relationship ~ that an inventory would show buildings swelling and shrinking in size as fluctuations in the economy cause the number of employees in a building to rise or fan. The third step ~ to divide up the buildings, known at this point only in terrors of location and, by extrapolation from number of employees, the size, into construction classes. The height of the approximately 3,000 high rises in California can be known from files specific to high rises assembled by the Council on Tall Buildings of Lehigh University. For the majority of buildings that remain, they can be divided into mid-rise and low-rise categories based on rules of thumb developed by a process of asking earthquake engineering experts their opinions. In this third step of developing a synthetic construction class distribution, the other basic task is to assign a construction class (e.g., reinforced masonry shear wall with moment-resisting frame, reinforced masonry shear wall without moment-resisting frame) to

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153 each facility. This was done by obtaining collective expert opin- ion from the engineers involved in the ATC-13 project, assigning a certain percentage of the buildings in each use category to each of the construction classes. In each use category (e.g., s~gle-family dwelling) the fractions for low-r~se wood frame, low-rme reinforced or unreinforced mansonry, and so on sum to 100 percent. The result ~ the end-form data: construction class (and high- , mid-, or low-r~se subclass designation), floor areas, use, and zip codes for ad buildings in the study area. Steps one and two involve relatively noncontroversial extrapolations common to many loss esti- mation methods. It ~ the third step, where the inventory variable of central importance construction class is synthesized on the basis of opinion, that involves untested relationships. Essentially, the con- struction class inventory ~ synthesized knowing only the number of employees, the zip code of the business, and the economic function. Comparison of the NOAA-USGS and FEMA/ATC-13 Inventory Methods A full application of the ATC-13 method has not yet been re- ported in the literature. The NOAA-USGS method is a general method that can be extracted from the reports of its application, for example, the large-scale NOAA-USGS loss study of San Franc~sco. ATC-13 is a report that describes its method very specifically, but there ~ no loss estimation study or actual application to refer to as a concrete case. This makes a comparison of the two inventory methods difficult. Also, the two methods were devised for different purposes. Although the comparative information given in Table D-1 on the type of end-form data implies that inventories would be much the same for both methods, this is not precisely true. Somewhat different characteristics are used for classifying the facilities In the two methods, and this affects the details for each. However, the striking difference in the two methods ~ not the data they seek, but how they assemble them. While both methods use judgment in the inventory process, the ATC-13 method is more reliant on judgment. The application of judgment in the ATC-13 method is, however, generally more apparent, In that it would be easier for other investigators to rely on the published description of the method, reuse it, and replicate the results obtained by others. Descriptors used in the classification process for each method

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154 TAl3LE D-1 Comparison of ATC-13 and NOAA-USGS Inventory Data FEMA/ATC-13 NOAA-USGS Seventeen basic building construction classes with subclasses for low, mid-, or high-rise heights, and combinations of systems (such as shear wall and frame); 40 classes total Primary categories Wood frame Light metal Unreinforced masonry Reinforced-concrete shear wall Reinforced-masonry shear wall Braced steel frame Moment-resisting steel frame Moment-resisting concrete frame Precast concrete Long span Tilt-up Mobile home Descriptorsa Structural material Framing system Floor area Height Ductility Economic use, social function Thirty-five classes that are cross- referenced to the broader range of SIC classes; each facility inventoried is assigned a class Nine basic building construction classes, with subclasses for size and degree of earthquake- resistant design; 21 classes total Primary categories Wood frame Light metal Unreinforced masonry Reinforced-concrete shear wall Reinforced-masonry shear wall Steel frame Concrete frame Precast concrete Tilt-up Descriptorea Structural material Framing system Floor area Height Earthquake-resistant design Economic use, social function Collected for some essential facilities (e g., hospitale) but not collected for each building aAll of these descriptors are not necessarily inventoried for all classes. vary in detail in some cases but would be identical for the two meth- ods in other cases, for example, construction material or height. The lists shown in Table D-1 are in a different form than they appear in either method and are organized more generically to allow for comparisons. For example, the NOAA-USGS approach contains a class for mixed construction (different was and diaphragm mate- rial) that includes buildings with wood roof and floors with walls

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155 of tilt-up, reinforced masonry (brick or block) or poured-in-place, reinforced-concrete construction. Variations in earthquake-resistant quality ratings can result in these buildings then being assigned to different classes (Insurance Services Office, 1977~. In Table D-l, these variations on the mixed NOAA-USGS class of construction are listed as separate classes to allow for closer comparison with ATC-13. Inventories for the two methods contain much of the same type of information, although the broader purpose of the AT~13 method (economic loss estunation) leads it to develop two additional detailed sets of information, one on economic function and the other on lifelines and nonbuilding structures. The PEPPER Study In~rento~ Method The method for estunating earthquake lodes used ~ the PEP- PER (Pre-Earthquake Planning for Post-Earthquake Rebuilding) study (Spangle, 1984) relied on automated data already collected by the planning department of the City of Los Angeles. No new field surveys were conducted, partly because of budget limitations and partly to try to test the usefuIne" of this large data base, which had been assembled from assessors' tax records and other sources. As partial checks on the accuracy of this comprehensive data base of about ~ million buildings, files containing information specific to building construction characteristics were consulted. An accurate inventory of pre-1934 (preseism~c code) unreinforced masonry build- ings was already in existence because of the city's retroactive seismic ordinance, and the characteristics of high-rme buildings were tabu- lated in a real estate survey. Census data on population and housing from the 1980 census were used, along with a 1974 city study. Buildings were (~) aggregated in planning areas of the city, and (2) classified according to type of construction ~ five classes: steel, concrete, masonry, wood, and special. Use was classified according to four classes: residential (with three subcIames), commercial, in- dustrial, and other. No other details appear in the report to suggest the way in which buildings were allocated to each class. As noted in the study's engineering report, The inventory of structures . . . is probably the least reliable component of the various factors that determine the damage pattern" (Degenkolb, 1984~. The building classification method might be described as an adjusted NOAA-USGS method. The PEPPER method adjusted the basic ISO or NOAA-USGS construction classification system

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156 because the available data were not that finely subdivided. This also had implications for the analysis task, because the hybrid or combined construction classes of the PEPPER inventory had to be analyzed using hybrid motion-damage relationships. The beginning form of the data In the city planning department's data base did not differentiate high rises according to their type of enclosure system (e.g., curtain wall, poured-in-place concrete). Inferences based on year of construction (e.g., assuming that post-1960 high rises were predorn~nantly of curtain wall exterior) were used. One point made by this study is that even if a very large com- puterized file of buildings exists, this does not necessarily mean that the data are detailed or accurate. Lack of detail is evident from the fact that all steel buildings, or aD concrete buildings, for example, were lumped together In one class. This level of detail is a common constraint in the use of assessors' or local planning department data. The accuracy of the inventory was also limited and was related to the fact that this data base was assembled for nonseism~c, nonengineer- ing purposes. An example of a major type of inaccuracy concealed in the data bee was that high-rise buildings were sometunes described as having wood-frame structures. Another problem was that this data base was not current because the cost of updating it had been considered too high by the planning department a few years after it had been created. POSTEARTlIQUA1lE STUDIES OF LOSS Related to the pre-earthquake inventory problem ~ the task of postearthquake inventory of damage by class of construction, loca- tion, ground conditions, and intensity or measured ground motion. Although all loss estunation investigators bemoan the fact that there are not more historical loss data available, there are few ongoing ef- forts outside of the insurance industry to collect this type of data after earthquakes occur. As pointed out in the Earthquake Engineering Research Institute's guide to postearthquake investigation (Earth- quake Engineering Research Institute, 1977), und~naged as well as damaged buildings should be tabulated. Statistical techniques pro- vide many tools for analyzing damage data, and these are explained in the guide in a special section. However, most earthquake recon- naissance reports or detailed studies do not comprehensively report damage or loss data, but rather concentrate on the more unique or instructive individual cases of damage.

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157 Because the types of pre-earthquake inventory data and con- struction classes that are generally used are known prior to initiating postearthquake investigations, damage data could be collected effi- ciently, on a sampling basis where necessary, to try to fill gaps in historical loss data. Although in theory systematic studies of build- ing damage could result in complete data for estimating purposes, in practice this is not so. Construction innovation will always be ahead of recorded earthquake experience. Earthquakes in Chile and Mexico in 1985 tested the building construction methods in use in these coun- tries of the 1950s, 1960s, and 1970s. There are no data, however, on the performance, under moderate to severe ground motion, of tall welded perimeter tube structures, modern m~d-rme steel-braced frame structures, or large t~vo-story tilt-up concrete structures that are common in many parts of the United States. SUMMARY In theory, a perfect inventory can be created. However, it will never be achieved because of cost and tune constraints. Therefore, ways of obtaining the most useful, imperfect inventory are being studied. The attempt to start from an econorn~cally based inven- tory, as in ATOLL, is not advised. Although the final output is intended to be economic, economic loss can only be estunated on the basis of an estimate of earthquake damage. Earthquake damage can only be estimated accurately when building construction data are directly sought. Converting economic data into construction cIassifi- cation data ~ not recommended because this can greatly reduce the accuracy of the inventory. If the focus is to be on building damage, then the inventory should focus on vulnerable or ~seisrn~ca]ly suspicious" buildings. Pro- cedures that provide an initial screening by low-cost means, leading to a more detailed survey to provide accuracy, make more sense than an attempt to develop a complete inventory from which the hazardous buildings must be selected. Facilities with a potential for large loss, or with essential emer- gency functions, should be inventoried on a case-by-case, field survey basis. The insurance industry, particularly in California, has much in- formation both on building damage and on building inventory. This information is generally unobtainable due to industry's confiden- tiality requirements and competitiveness, although the California

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158 Department of insurance obtain this Information, aggregated by geographic zone and clam of construction, on an annual basis. 0~ tanning some of this information would benefit national or regional interests, solve some of the data problems of earthquake damage estimating, and yet-preserve such proprietary information as the industry deems necessary.