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Overview

In this section we are going to discuss the steps for ingesting building data into a format that MAEviz can understand and use in the building analyses. Before we launch the software, we will go over the MAEviz building data format so that if any changes need to be made, we can make those now.

Data Format

We will need two datasets for running a building damage analysis, a building dataset ingested into MAEviz and a Fragility Mapping dataset ingested into MAEviz. The building dataset will contain columns such as structure type, year built, etc and the fragility mapping dataset tells MAEviz which fragility curves should be used for which buildings.

Building Data

Let's start out by looking at the building data requirements. The building data for MAEviz needs to be in ESRI's Shapefile format. Below you will find the column names, a short description and the column types that MAEviz requires. Only the column types (e.g. integer, double, string, etc) must explicitly match what is listed in the table. We do not need to worry about column names matching because when we ingest the dataset, MAEviz will ask you to map your columns to the columns that MAEviz needs. For example, your structure type information might be in a column called s_type and MAEviz expects it to be called str_type so you can tell MAEviz that s_type maps to str_type and thus no changes need to be made to your dataset. The columns are categorized into three categories: Very Important, Less Important and Least Important.

Building Columns:

Very Important

Field Name

Field Description

Field Type

STRUCT_TYP

General structure type of the building

string

Less Important

Field Name

Field Description

Field Type

OCC_TYPE

Broad HAZUS Occupancy Category (e.g. RES3 - multi-family residential)

string

APPR_BLDG

Appraised value for the building

double

SQ_FOOT

total building area in square feet

integer

DWELL_UNIT

total number of dwelling units in the building

integer

NO_STORIES

total number of stories for the building

integer

CONT_VAL

value of building contents

double

STR_TYP2

detailed structure type as per HAZUS MR-3 specifications

string

EFACILITY

essential facility designation

string

Least Important

Field Name

Field Description

Field Type

PAR_ID

parcel identifier

string

PARID_CARD

improvement identifier

string

BLDG_ID

building identifier (unique)

string

STR_PROB

probability that the structure type specified is correct

double

YEAR_BUILT

the year the structure was built

integer

A_STORIES

the number of above ground stories

integer

B_STORIES

the number of below ground stories

integer

BSMT_TYPE

the basement type

string

GSQ_FOOT

total ground floor area of the building in square feet

integer

OCC_DETAIL

specific occupancy category, describing the detailed use of the building

string

MAJOR_OCC

major occupancy category for the parcel in which the building is sited

string

BROAD_OCC

general occupancy categories

string

REPL_CST

replacement cost for the building from R.S. means square foot cost

double

STR_CST

structural component of the replacement cost

double

NSTRA_CST

acceleration sensitive component of replacement cost

double

NSTRD_CST

drift sensitive component of replacement cost

double

DGN_LVL

design level for the building as per HAZUS MR-3 specifications

string

OCC_TYP2

detailed HAZUS occupancy category for the building

string

TRACT_ID

census tract identifier

string

Now, it's ok if you don't have all of the above information for your buildings; however, the more detail you have about your building means you can be more explicit in mapping your fragilities to your buildings for the damage analysis. Only in the more advanced analyses will MAEviz start requiring some of those other attributes (e.g. estimating structural damage cost requires the APPR_BLDG column since the cost of the structure needs to be known). One stipulation, all of these columns do need to be present in the dataset, even if they contain no data because MAEviz will expect all of the columns to be there upon ingestion. In the next version of MAEviz, this restriction of all columns being present, even with no data, should be eliminated.

Ingest Building Dataset

First, we will need to launch the MAEviz application. The default installation directory for MAEviz is a folder with the same name, "MAEviz" so you should be able to launch the software by going to Start -> Programs -> MAEviz.

Ingestion Steps

In this section we will go through the steps to create a new local data repository for ingesting data into and then through the steps to ingest a building dataset and a fragility mapping dataset.

Create Local Repository

This step is optional if you have already created a local repository to ingest your data into, otherwise the steps below will take you through the process of creating a local repository for MAEviz. With MAEviz open, you should see a Catalog View similar to the one in the image below:

Steps to create repository:

  1. Click on the New Repository button that is highlighted by the mouse in the above image and a dialog box similar to the one in the image below should open and walk you through the steps of creating a new repository.
  2. Select Local Repository from the drop down menu and click the Next button. You should now see a dialog similar to the one below.
  3. Enter a name for the repository and browse for a directory to use to store ingested datasets. Click Finish to create the new repository. You should now see your new repository in the Catalog View and it is ready to store data.

Building Dataset

  1. Go to the File menu near the top of the application and select Import. This should bring up the dialog seen below.
  2. From the dialog box, expand the Data selection and select Dataset and click Next. You should see something similar to the image below.
  3. From the dialog drop down menu, select Shapefile and click Next. You should see a dialog similar to the one in the image below.
  4. From the dialog, click the Browse button and select the building shapefile you want to ingest and click the Next button. You should see a dialog similar to the one below.
  5. From the dialog drop down menu, select Building Inventory v5.0 and click Next. You should see a dialog similar to the one below.
  6. From this dialog, you will notice each field has a drop down menu next to it. The field name on the far left is the field MAEviz expects to find in your dataset and the drop down menu next to the field contains all of the fields in your dataset that you could map it to. Select the appropriate mappings (e.g. as we mentioned above, you could map s_type to struct_typ). For some fields, there will also be a unit type drop down selection (e.g. dollars for building value). Currently, if other currency types besides dollar and turkish lira are required we will need to add the conversion to MAEviz. When finished, click Next.
  7. If other fields are present, the next dialog screen will give you some options to assign friendly names and units to those fields. You can safely ignore this and click the Next button. You should now see the dialog below.
  8. From this dialog you can select the repository to ingest the dataset to, provide a descriptive name for the dataset (e.g. Memphis Residential Buildings), and a version number. After entering the required information, click the Finish button.

If your dataset is large, you may need to wait a few minutes for MAEviz to ingest the dataset. A progress bar will indicate if MAEviz is still working on the dataset. Once that finishes, your dataset should now be available in the repository you ingested to.

Conclusion

At this point, you should have all of the data required to be able to use the building damage tutorial to create a building damage result from your ingested buildings provided they default fragilities and fragility mapping files work with your dataset. If not, you will need to create a set of fragilities and fragility mappings for your dataset. You can find more information about that here.

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