Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide (2016)

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Gathering Software Tool Input Data 13 3.2 Airport Movements; Normal Operation Data (NOD) File To use the software tool, users should assemble a sample of the movements’ record at the airport. This sample should represent one full year of airport operations and be organized in a specific format in a comma separated value (.csv) spreadsheet. The spreadsheet, called a normal operation data (NOD) file, is then entered into the tool. A sample representing one year of movement data is recommended so as to ensure the findings account for seasonality in the weather condition. However, the analyst may choose to run the analysis for as many years as required. Findings from multiple years can then be averaged for an average annual risk, or the year with the highest risk can be selected as the worst case scenario. The NOD file is basically the schedule of airport landings and takeoffs. For every movement, the following characteristics are specified in the NOD file: • Date and time • Runway designation • Bound: “A” for arrival and “D” for departure • FAA aircraft code • Flight category: “COM” for commercial, “GA” for general aviation, “CAR” for cargo and “AIR” for air taxi and commuter • Flight type: “D” for domestic and “I” for international FAA aircraft codes can be obtained from the FAA Order JO 7360.1 “Aircraft Type Designators” (September 25, 2015). The document’s Appendix A includes the codes required for the NOD file. Users may also designate the flight number of the movement; however, it is not a required input for RPZ_RAT. Figure 3.1 presents a sample of the movements at an airport formatted for use as the NOD input file. As an example, the first line of the NOD file presented in Figure 3.1 presents the landing record of a Boeing 737-800 (B738) on Runway 15L at midnight on August 1, 2013, which was a domestic commercial flight. Various sources can provide the movement records of airports. Many airports with control towers record the movements in a way that can be formatted to the NOD file. FAA’s Air Traffic Activity Data System (ATADS) can provide the required data, and third-party vendors also track flights around the country. Realizing that movements at some airports may be unavailable or the input file may be burden- some to assemble for smaller airports, two sample NOD files are included with the RPZ_RAT installation package. These sample files include actual movement data at two airports. Sample NOD files include the following: • NOD_GA_L is movement data from a GA airport with more than 32,000 records where 68% of movements are general aviation and 22% are commercial. The remaining 10% of move- ments are mostly air taxi/commuter flights and some cargo flights. þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

14 Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide • NOD_GA_S is movement data from a general aviation airport with about 1,700 records where 69% of movements are general aviation and 23% are air taxi/commuter. The remaining 8% of movements are commercial flights. If sample files are selected for use instead of actual airport data, the user should pick the sample most similar to the actual airport condition and tailor the data as much as possible. In customizing the NOD file, do the following: 1. Assign appropriate airport runway designations to each movement. Try to achieve the airport’s actual number of landings to and departures from each runway. To add extra move- ments, enter the new data or copy and paste existing movements. To reduce the number of movements in a sample NOD file, delete the entire row so that no gaps remain between movements. Figure 3.1. Sample movement records (NOD) input file. HOD_ID DATE&TIME RUNWAY_DESIGNATION BOUND FLIGHT_NO FAA_Code FLIGHT_Category FLIGHT_Type 1 2013-08-01 0:00:33 15R A AAL1554 B738 COM D 2 2013-08-01 0:04:28 15R A SWA2354 B737 COM D D3 2013-08-01 0:07:11 15R A ATN510 B752 CAR 4 2013-08-01 0:09:09 15R A SWA2699 B737 COM D 5 2013-08-01 0:11:53 15R A UAL1575 B739 COM D 6 2013-08-01 0:14:49 15R A AAL406 B738 COM D 7 2013-08-01 0:17:06 15R A TRS1092 B737 COM D 8 2013-08-01 0:19:48 15R A SWA611 B737 COM D 9 2013-08-01 0:35:29 15R A SWA1641 B737 COM D 10 2013-08-01 1:11:05 15R A SWA3509 B737 COM D D D D D D D D D 11 2013-08-01 1:50:24 15R A UAL1608 B738 COM D D D 12 2013-08-01 1:58:35 15R A N310ME LJ35 GA 13 2013-08-01 2:01:10 15L A LBQ792 PC12 CAR 14 2013-08-01 2:12:32 15R D ATN510 B752 CAR 15 2013-08-01 2:21:35 15L D LBQ792 PC12 CAR 16 2013-08-01 2:27:46 15L D N310ME LJ35 GA 17 2013-08-01 3:43:09 15L A RAX81 BE10 AIR 18 2013-08-01 4:02:03 15L D RAX81 BE10 AIR 19 2013-08-01 4:26:07 15L A MTN8308 C208 AIR 20 2013-08-01 5:08:15 15L A MTN8305 C208 AIR 21 2013-08-01 5:23:41 15R A UPS1216 B752 CAR 22 2013-08-01 5:25:01 15R D AWE1851 A319 COM D 23 2013-08-01 5:36:50 15R A UPS1214 B763 CAR 24 2013-08-01 5:55:05 10 A FDX1730 A306 CAR 25 2013-08-01 5:56:01 15R D UAL1411 B739 COM D 26 2013-08-01 6:00:52 15R D EGF2986 E145 COM D D D 27 2013-08-01 6:07:00 10 A FDX1482 A306 CAR 28 2013-08-01 6:10:52 15R D UAL1059 B738 COM D D 29 2013-08-01 6:12:44 15R D JIA4601 CRJ2 AIR 30 2013-08-01 6:14:57 15L D JZA7927 DH8A COM I I þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

Gathering Software Tool Input Data 15 2. If the airport has multiple runways of different use and varying lengths, screen the type of aircraft assigned to the runways to make sure that unreasonable runway allocations (e.g., operation of a large commercial aircraft on a short GA runway) are avoided. Flight numbers are not used for the analysis and may be left blank. If adding or deleting many movements, spread them throughout the year to account for seasonal weather conditions. For example, if adding or deleting 1,200 movements from a sample NOD file, a hundred movements can be added to or removed from each month. If resources for additional refinement of the sample NOD file are available, adjust the aircraft mix to reflect that of the airport as closely as possible. Do not add or delete columns in the NOD file. Do not change the headings of the columns. 3.3 Weather Data Input File Various weather elements are found to contribute to the likelihood of accidents. Therefore, an airport-specific weather condition report is used for the analysis. To use the software tool, the user should assemble a weather input file in comma separated value (.csv) format similar to the NOD file. The weather input file should contain 1 year of weather reports corresponding to the period captured in the NOD file. Most weather stations report conditions at hourly intervals. RPZ_RAT automatically matches the closest weather report with every movement in the NOD file. Several weather elements are required for the analysis. Each weather report should contain the following: • Date and time • Visibility • Ceiling height • Temperature • Tailwind and crosswind • Various forms of precipitation • Presence of fog, electrical storms, and gusty winds • Nighttime or daytime Figure 3.2 presents a snapshot of a sample weather report input file. As shown, either the mag- nitude or the presence of the weather elements must be specified in each weather report, as well as the date and time of the report. The format and the sequence illustrated must be followed. If a weather event (e.g., rain) is present in a report, it is assigned a “True” value in the spreadsheet; otherwise, the value is set to “False.” Although hourly weather reports are accurate for the analysis, some stations may record multiple reports during adverse weather conditions. Also, it is very common that the compilation of reports from a station lags the actual occurrence of the conditions by several hours. The average of the closest weather reports may be used to fill in the gaps. In any situation, the tool matches the closest weather report available to the time of movement. þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

Figure 3.2. Sample weather records input file. Date&Time Visibility _SM Wind Direction_deg Wind Speed_knots Air Temp_F Ceiling_ Thunder- storms Rain Rain Showers Freezing Rain Freezing Drizzle Snow Snow Pellets Ice Crystals Snow Showers Ice Pellets Ice Pellet Show Fog Gusts Night 8/1/2013 0:00 8 0 0 71 10000 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE 8/1/2013 1:00 10 210 5 71 6500 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE 8/1/2013 2:00 10 190 4 72 1200 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE 8/1/2013 3:00 7 190 3 68 5000 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE 8/1/2013 4:00 4 170 3 68 3300 FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE 8/1/2013 5:00 8 120 4 68 2700 FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE 8/1/2013 6:00 2 110 4 68 4000 FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE 8/1/2013 7:00 2 0 0 68 600 FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 8/1/2013 8:00 2.5 0 0 70 1100 FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 8/1/2013 9:00 4 230 5 72 800 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 8/1/2013 10:00 1.5 230 5 72 800 FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 8/1/2013 11:00 4 230 5 72 800 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 8/1/2013 12:00 6 240 6 73 1700 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 8/1/2013 13:00 8 210 3 73 900 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 8/1/2013 14:00 10 160 5 77 5000 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 8/1/2013 15:00 10 160 4 78 6000 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 8/1/2013 16:00 10 200 4 80 10000 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 8/1/2013 17:00 10 210 5 79 10000 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 8/1/2013 18:00 10 210 3 78 10000 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 8/1/2013 19:00 10 0 0 77 10000 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 8/1/2013 20:00 10 0 0 75 10000 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE 8/1/2013 21:00 10 0 0 74 10000 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE 8/1/2013 22:00 10 100 3 74 7000 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE 8/1/2013 23:00 10 0 0 73 10000 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE þÿR unw ay P rotection Z ones (R P Z s) R isk A ssessm ent T ool U sers  G uide C opyright N ational A cadem y of S ciences. A ll rights reserved.

Gathering Software Tool Input Data 17 The first line of the sample weather report shown in Figure 3.2 illustrates that on August 1, 2013, the visibility was 8 statute miles with a ceiling height of 10,000 feet and air temperature of 71 degrees Fahrenheit. There was no wind, and other weather elements were not present at this time. The sample was taken at night. The weather elements must be recorded in the spreadsheet with the correct unit system. The tool anticipates visibility in statute miles, wind speed in knots, air temperature in Fahrenheit, and ceiling height in feet. There are various sources of weather reports. Most are publicly available at no charge. How- ever, weather reports are usually recorded in METAR reporting format. Weather input file ele- ments from the METAR reports should be interpreted using a spreadsheet, which requires basic familiarity with the spreadsheet software to develop “if-then” statements. The National Oceanic and Atmospheric Administration (NOAA) maintains National Centers for Environmental Information (NCEI) which are responsible for preserving, monitoring, and providing public access to the national climate and historical weather data and information. The agency maintains quality-controlled climatological data from numerous weather stations around the country. This information is publicly available. Data from NOAA could be supple- mented from other online sources, usually available free of charge. Assembling the weather input file requires effort, even when a weather station is at or near the airport. Given that some users may not have the resources to obtain and format the data required to use RPZ_RAT, four sample weather files are included with the software tool installation package. These sample input files are actual data from four different weather stations across the country. In selecting the weather stations, the goal was to cover differ- ent climates. The country was divided into dry-freeze, dry no freeze, wet-freeze, and wet no freeze zones, and a random weather station was selected from each zone. Figure 3.3 shows the extent of each region. The sample weather files are available from the RPZ_RAT installation package. Figure 3.3. Climate zones. þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

18 Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide The States in each of these climate zones are as follows: (1) wet-freeze: Connecticut, Delaware, Illinois, Indiana, Iowa, Kentucky, Maine, Maryland, Massachusetts, Michigan, Minnesota, Missouri, New Hampshire, New Jersey, New York, Ohio, Pennsylvania, Rhode Island, Vermont, Virginia , and West Virginia; (2) wet no freeze: Alabama, Arkansas, northwest coastal areas of California, Florida, Georgia, Louisiana, Mississippi, North Carolina, Oklahoma, coastal area of Oregon, South Carolina, Tennessee, eastern part of Texas, and coastal area of Washington; (3) dry-freeze: northern Arizona, interior central and northern California, Colorado, Idaho, Kansas, Montana, Nebraska, Nevada, northwestern New Mexico, North Dakota, interior Oregon, South Dakota, Utah, interior Washington, and Wyoming; (4) dry no freeze: central and southern Arizona, the central and southern coastal area of California, all but the northwestern part of New Mexico, and the western part of Texas. 3.4 Land Use and Population Data The number of people concentrated in the accident area is the land use characteristic most closely tied to the consequences of aircraft accidents. Limiting the concentration of the people near the airport is the most direct way to reduce the consequences of a potential accident. To conduct the risk assessment, a user must identify the areas within RPZs that may contain people on the ground. Either estimates of the number of people within each identified land use or the population densities of these areas must be identified. If the user provides the average number of people present within a land use, the software obtains its population density by first automatically measuring the land use area and then dividing the two. If the user provides the population density of a land use, it is directly used by the tool. Only populated areas that overlap with the departure or arrival RPZs are accounted for in the risk analysis. If an area is completely outside of the RPZs, the tool assigns no risk to it, although people may still be fatally injured in these non-RPZ areas. Lands surrounding airports may have various uses. Common occupied land use types around airports include farm houses, public roads, railroads, residential and commercial/industrial buildings, recreational areas, and parking lots. Given that the number of people present can change over time, an estimate of the average population present over time can be used. However, conservatively, a user may choose to use the land use capacity (maximum number of people that it can accommodate) as a worst-case scenario. This could cause large differences in results, depending on the type of land use being analyzed. Basing the population density of a land use on its capacity implies that an accident would occur simultaneously with the maximum occupancy of the site. Although this might be a fair and conservative assumption for places that operate at or near their capacity for an extended period on a daily basis (e.g., manufacturing plants), it could unreasonably skew the findings for others such as a stadium. There are various ways to obtain an estimate of the number of people likely present at a land use. One approach is to rely on the maximum occupancy standards available from the Uniform Building Code (as presented in Appendix A) or other resources [e.g., California Airport Land þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

Gathering Software Tool Input Data 19 Use Planning Handbook (2011) and San Diego International Airport Land Use Compatibility Plan (SDIA ALUCP, 2014)]. Estimates of the number of people occupying a land use can be derived from square footage of the particular use. Judgments may be needed to average the number of people present at the land use throughout the year or throughout the day. Surveys of actual occupancy levels conducted by various agencies have indicated that many retail and office uses are generally occupied at no more than 50% of their maximum occupancy levels, even at the busiest times of day. As another approach, when land use depends on access by vehicles, the number of parking spaces provided may be a good indication of capacity. This number, along with assumptions about the number of people per vehicle, can lead to the number of people present at the land use. Field surveys are another way to estimate the number of people occupy- ing land uses. If little is known about a particular land use, field surveys may be the most effective way of obtaining the data. Estimating average population present within transportation corridors or hiking/biking trails may be difficult. RPZ_RAT has built-in routines to support such estimations. The estimates are based on several usually easily attainable variables. One variable is the average annual daily traffic (AADT). Intuitively, the higher the AADT, the higher the population density when other vari- ables are kept equal. State highway agencies usually track traffic counts on major highways and state roads and can provide the required AADT statistics. Many state agencies make traffic volume maps publicly available on line (e.g., Maryland State Highway Agency and Pennsylvania Depart- ment of Transportation traffic volume maps). Metropolitan Planning Organizations (MPOs), which are responsible for regional transportation planning, maintain traffic data collected by state and local highway and road agencies and are a good source of data for activity on arterial and collector streets. For commuter railways and light rail lines, transit authorities and Amtrak maintain daily train schedules that can be used to estimate the average annual daily passages trains make through the RPZ. Trainmasters of individual railroad companies are often willing to provide information on the number and size of freight trains. Also, government agencies (e.g., natural resources departments and State parks) usually collect statistics on hiking/biking trail use which can be requested if analyzing trails through an RPZ. Another variable used by RPZ_RAT to estimate the population at land uses is the speed at which vehicles and people move through the RPZ. The faster the speed at which vehicles pass through the RPZ, the lower the number of people in the RPZ during any given period of time, all other variables being equal. In estimating the population density of a roadway, the posted speed limit is usually a good indication of the actual speed. For trains, data on speed may be obtained from the transit administration, Amtrak, or the individual freight railroad companies. The tool uses an average speed of 5.7 mph for people in the hiking/biking trails. This is a rough estimate and depends largely on the mix of hikers and bikers on a trail. It is based on the 60–40 split assumption between hikers and bikers. Another variable used for roadway population density assessment is average vehicle occu- pancy. Various studies at national and local levels have assessed the average vehicle occupancy. In the absence of a specific study for the community in which the airport is located, using a range of 1.6 to 2 people per vehicle is recommended. The equivalent concept of vehicle occupancy in trains is ridership—the number of people transported in every passage of a train. The tool requires the annual average of ridership per pas- sage of train and the average length of the trains passing through. These data are usually available from transit authorities, Amtrak, or individual freight railroad companies. The tool also requires the user to obtain the length of the roadway, railway, or trail that is within the RPZ. This could be measured from the airport layout plan or by using online resources, such as Google Earth. þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

20 Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide When all of the data are combined, the tool estimates the number of people present on average. Then, the tool measures the size of the area inhibited by the land use and derives the population density by dividing the two. The tool may be used to conduct sensitivity analyses with respect to many changes being considered. For example, a user may compare the safety gain in rerouting a major highway farther from the runway with the safety gain from tunneling a portion of the highway. The change in risk could even be assessed with respect to circumstances such as an increase in the vehicular AADT, or increased ridership of trains. þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

21 C H A P T E R 4 4.1 Installing the Software Tool The installation of Runway Protection Zone Risk Assessment Tool (RPZ_RAT) is similar to that of other Microsoft Windows programs. The installation package is available from the TRB website. The package is about 700 MB and includes a “setup.exe” file for installation. Similar to other programs, administrative rights to the computer are required to successfully install the software. Upon acceptance of the default settings, the program creates a folder named “ACRP” in the “Program Files” folder of the “C” drive. The installer creates a shortcut named RPZ_RAT in the Start menu for running the software. Table 4.1 provides the minimum requirements for the software to run properly. A user must have the appropriate SQL version installed on the computer to use the tool. The software is compatible with both 32-bit and 64-bit versions of the SQL server. The required version of SQL server depends on the computer system type. The system type can be identified by right-clicking on the computer icon and viewing the properties window. Most recent computers require the 64-bit version. The installation files of both SQL versions, named sqlLOCALDB32bit and sqlLOCALDB64bit, can be found in the “program files” folder of the installation package. As described in the previous chapter, a user must assemble two input files specific to the airport being analyzed in order to run the analysis: Normal Operation Data (NOD) and weather input files. Assembling these files can be time-consuming and demanding. If resources are not available to undertake the effort, the user may use one of the sample files provided with the RPZ_RAT installation package. 4.2 Operating the Software Tool To open RPZ_RAT, click on the software icon created in the Start menu. The software opens with a dialog box to either create a new project or to open an existing one, as shown in Figure 4.1. If starting a new project, the user must name the project. A sidebar navigation tree scheme is provided for data input and modification, providing great ease of use and flexibility for data entry. The sidebar navigation tree is shown in Figure 4.2. Getting Started with RPZ_RAT þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

22 Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide The assigned project name appears at the top of the sidebar. Initially, a red “X” is placed next to the project name until all data are entered; the red X then changes to a green checkmark. A user can start by entering basic airport information (e.g., elevation, annual movement volume, expected annual growth in movements, and whether a hub or a non-hub airport is being ana- lyzed). To enter such information, the user must click on Characteristics in the input sidebar, which will expand as shown in Figure 4.2 for the airport characteristics to be entered. Next, the NOD file is entered by clicking on the Normal Operating Data icon and navigating to the file location. The file must be saved in a .csv format and should not be open or in use by any other program. Upon successful reading of the file by the software, the red X icon will change to a green checkmark and the file name will appear in the sidebar. The same procedure should be followed for entering the weather input file. After reading the NOD file, the software identifies the runway designations from the file and lists them as shown in Figure 4.2. The Sample Airport project had one runway, 15-33, as shown in the figure. Figure 4.1. Main window of RPZ_RAT. Component Requirement Computer and processor 500 megahertz or higher Memory 256 megabyte or higher Hard disk 1.5 gigabyte Display 1024*768 or higher resolution monitor Operating system Microsoft Windows 7 or later Other Appropriate version of SQL server (32 or 64 bit), and Microsoft Office Suite 2013 Table 4.1. System requirements for using RPZ_RAT. þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

Getting Started with RPZ_RAT 23 4.3 Entering Runway Data Runways are drawn on the airport map. To locate the airport on the RPZ_RAT map, type the airport FAA code or its full name in the search box in the top ribbon. A user can also manually navigate to an airport location by zooming in and out on the map. To enter runway data, right click on the runway name in the sidebar and choose Draw. The mouse cursor will change to a pen. Navigate to the beginning of the runway on the map, zoom in, and click on the runway centerline at the landing threshold. The tool will mark the beginning of the runway with a red dot. Next, navigate to the other end of the runway and click again on the centerline. The tool will automatically measure the distance between the two clicks and assign Figure 4.2. Input sidebar window. þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.