Using the SAGA GIS to Analyze Fire Department Response Time Developed by Kim Cimmery

(kapcimmery at hot mail dot com) June 2015

Overview This tutorial presents a least cost path analysis related to networks. In this example the network is a road network supporting the delivery of fire suppression and emergency medical services from four combinations of fire stations in two neighboring fire districts. This scenario is hypothetical but quite close to a potential future situation for a small rural area of Mason County, Washington, U.S.A.

The tutorial was developed using the 64-bit version of SAGA 2.1.4 operating on a laptop. As you go through this tutorial, if you encounter mistakes please let me know. My e-mail contact address is kapcimmery at hotmail dot com.

The first part of the tutorial, Fire District Merging and Theoretical Response Times, provides a general description and the scenario. It is presented as a brief accounting of how SAGA procedures and modules are applied to explore the question of whether a small fire district should be absorbed by a much larger, surrounding fire district.

Four alternatives are described. Theoretical emergency response times are calculated and summarized along with identifying the closest fire stations to addresses in the fire district, whether they are the two stations in the district or four near ones in the neighboring fire district. Processing results are described along with some conclusions.

The general description of the scenario and results is followed in the Processing Steps section with detailed descriptions of how SAGA is applied in the development of theoretical response times and data for evaluation of the alternatives. The functions built-in to SAGA and the modules are described in detail. Here is a list of the sections appearing in the Processing Steps section of the tutorial.

1. Defining a study area. 2. Creating the transportation grid data layer. 3. Creating the roads travel time (cost) grid data layer. 4. Creating the destination grid data layers. 5. Developing the response time grid data layers. 6. Masking out areas outside of FD3. 7. Statistics for each output. 8. Recoding the response times into response classes. 9. Creating an allocation grid data layer. 10. Adding alternatives response time classes to the address data layer attribute table. 11. Creating an allocation data layer for nearest station. 12. Adding alternatives nearest station to the address data layer attribute table.

Module List Shapes Tools/Cut Shapes Layer [interactive] Grid Gridding/Shapes to Grid Grid Tools/Reclassify Grid Values Shapes Tools/New layer from selected shapes Grid Analysis/Accumulated Cost (Isotropic) Shapes - Tools/Split Table/Shapes by Attribute Shapes - Tools/Merge Layer Grid Tools/Grid Masking Spatial and Geostatistics - Grids/Save Grid Statistics to Table Grid Tools/Grid Proximity Buffer Shapes Grid/Add Grid Values to Points

Fire District Merging and Theoretical Response Times To merge or not to merge, that is the question.

How does a small fire district (about 11 square miles in size, 1700 addresses, a population of 2300), surrounded by a much larger one (area of about 121 square miles, 11000 addresses, population of 16000), decide whether to merge with the larger one or continue as a separate but neighboring entity?

A decision to merge is not based on a single factor. Possible factors for consideration include:

1. Differences in tax levy levels. 2. Paid employee and volunteer levels. 3. Equipment inventories. 4. Operational management. 5. Fiscal management. 6. Performance.

The last factor, performance, can be measured using a number of metrics. One of these is response times for emergency calls. There are conditions that impact response times. Whether on-call responders are paid employees working on a 24 hour, 7 day a week shift arrangement versus on-call volunteers responding from their residence makes an obvious difference. The transportation infrastructure is a factor such as the road miles of paved road versus miles of road of gravel or dirt surface. The metric that boils performance down to a single data value, regardless of any physical condition, is emergency response time or elapsed time.

Will fire department emergency response times, overall, shorten as a result of a merger? How can this question be evaluated? This tutorial is about one approach to accomplish such an evaluation using theoretical response times.

A theoretical response time, for the sake of this tutorial, starts when an emergency vehicle leaves its' station and ends upon its arrival at an emergency destination. This is

the elapsed time, in minutes and seconds, traveling at average speeds for different road surface types. The average vehicle speed will vary depending on whether the surface type is pavement, gravel, or dirt and the distance traveled for each surface type. It also will vary depending on road gradient and curvature. Gradient and curvature are not considered in this analysis.

This document describes how the SAGA GIS is applied to create theoretical elapsed time data for four alternative fire station service scenarios.

The Grapeview Situation The history of the Grapeview Volunteer Fire Department (GVFD), today known as Fire Protection District 3 (FD3), began around 1948 or 1949 when it was created. Eventually the GVFD evolved to become Fire District 3 encompassing about 11 square miles of what has become the unincorporated area referred to as Grapeview. FD3 includes 1676 addresses and a population of 2310. The portion of the original GVFD that included the hamlet of Allyn split from the GVFD and became what is known today as Fire District 5 (FD5).

Fire District 5 is a much larger fire district . FD5 surrounds FD3 on three sides; the exception being the Puget Sound Case Inlet east side of FD3. FD5 is about 121 square miles in size and includes around 11000 addresses and a population of 15500.

Fire District 3 has two fire stations. The primary station, station 3-1, is located near the geographic middle of the district at the intersection of the Grapeview Loop and Eckert Roads. This intersection is about 3.7 miles from the northern intersection of the Loop Road with Highway 3 and 4.4 miles from the southern intersection of the Loop Road with Highway 3. The second fire station, station 3-2, is located adjacent to Krabenhoft Road at the extreme southern portion of the district. Figure 1 displays the fire district, major roads, and the locations of the two stations.

Figure 1. Grapeview Fire District #3.

The heavy red line in Figure 1 is the boundary for FD3. The red circles represent the two fire stations in FD3. Water areas are in blue.

FD5 has ten fire stations. Of potential significance to a FD3-FD5 merger are stations 5-1, 5-3, 5-6, and 5-7. These four stations are the closest stations to FD3; 5-1 is in the hamlet of Allyn about 1 mile north of FD3; station 5-7 is located near the southern boundary of FD3 about 1 mile due south of station 3-2; stations 5-6 and 5-3 are located 2 and 4 miles west of FD3. Figure 2 displays this same map as in Figure 1 showing the Fire District boundary and fire stations in both districts.

Figure 2. Grapeview Fire District #3 stations and adjacent FD5 stations.

The fire stations are labeled with two digits. The first digit is the district number followed by the station number. You can see that station 3-1 (District 3, station 1) is located just to the west of Stretch Island on the mainland. Station 3-2 is located on the northern edge in the southern portion of the district. The FD5 stations (5-1, 5-3, 5-6 and 5-7) are also displayed.

Four Alternatives This analysis of theoretical response times is structured around four alternatives.

1. Fire station 3-1 only. This is the current situation. Fire station 3-2 does not have a working fire engine.

2. Fire station 3-1 and 3-2. This alternative assumes FD3 has provided emergency equipment for station 3-2 and necessary volunteer staffing.

3. Fire stations 3-1, 5-1, 5-7. This alternative assumes a contract for emergency services with FD5 involving stations 5-1 and 5-7 for responding to FD3 emergency calls. FD5 has provided emergency equipment for station 5-7.

4. Fire stations 3-1, 3-2, 5-1, 5-3, 5-6, and 5-7. This alternative assumes stations 3-2 and 5-7 have necessary equipment and that a contract with FD5 for services with stations 5-1, 5-3, 5-6, and 5-7 or the merging of Fire District 3 and 5.

Note that references to the fire stations in the remainder of this document will drop the hyphens; i.e., 31, 32, etc.

Data Preparation Overview The Mason County GIS transportation layer is a vector line shapes data layer. As with all shapes data layers, it includes an attribute table that provides characteristics for the layer line objects, i.e., roads and road segments. One of the attributes is for surface type. The surface type attribute for roads specifies whether the surface is pavement, gravel, or dirt. The surface type will be used as an estimator of average speed for an emergency vehicle on a particular road surface in an emergency situation.

The SAGA GIS supports both raster and vector analysis. This analysis takes advantage of both environments as needed. In the raster environment, a map consists of a matrix (rows and columns) of grid cells; each cell being the same square size and being 90 on a side. The cost of traveling through a road cell is the amount of time it takes emergency vehicles to traverse the cell or travel 90' when a road with a specific surface is present in the cell. Data layers are referred to as shapes data layers in the vector environment.

The Mason County road network line shapes data layer is named 'MasonRoads'. Using SAGA modules, a study area road network shapes data layer is created named 'EMasonRoads1'. This layer is converted to a grid data layer named EMasonRoads1GR. The road network is portrayed by grid cell values representing surface type. A travel time layer is created from the transportation grid data layer and named 'EMasonTrans1GR'. The cell data values for this layer represent the time it takes a vehicle to traverse a 90' distance, i.e., a 90' grid cell. I use 40 miles per hour (MPH) as an average speed on paved surfaces, 20 MPH on gravel surface, and 7 MPH on dirt surface. The cell values for the times are:

Paved = 1.53 seconds, .0255 minutes. Gravel = 3.07 seconds, .0512 minutes. Dirt = 8.77 seconds, .1462 minutes.

This grid data layer (EMasonTrans1GR) is used for the input Cost Grid parameter in the SAGA Accumulated Cost (Isotropic) module. The data values in the road grid cells represent time in minutes as described above.

The second input for the Accumulated Cost (Isotropic) module is a grid data layer identifying destination points. In this case, the destination points are fire stations. Although referred to as destination points, they are in fact the starting points, fire stations, for emergency vehicles. The accumulated times that are output from this module represent the elapsed time for a vehicle from the nearest station to reach a specific road grid cell. There are four variations of this grid data layer; one for each of the four alternatives described earlier. The alternative number is concatenated with the root name EMasonFireStn as follows: EMasonFireStns1aGR, EMasonFireStns2aGR, EMasonFireStns3aGR, and EMasonFireStns4aGR.

The EMasonFireStns1aGR layer has one cell containing the data value 31 representing the location of fire station 31. All other cells contain the value 99999 for no data. This layer represents alternative 1 or the current situation. The EMasonFireStns2aGR grid

layer has a cell containing the data value 31 and another cell containing the value 32. These two cells represent the locations of the two fire stations in Fire District 3. This layer depicts the stations for alternative 2. The remaining layers, EMasonFireStns3aGR and EMasonFireStns4aGR, are populated with grid cells containing data values representing the combinations of stations for alternatives 3 and 4.

Outputs The SAGA Accumulated Cost (Isotropic) module produces two grid data layer outputs, one is an accumulated cost layer. The road grid cells on the Accumulated Cost output layer display the accumulated time, for each road cell, from the nearest fire station in the alternative. In this application the accumulated time represents the elapsed time it takes an emergency vehicle from the nearest destination to reach a road grid cell. These output layers are named EMcost1aGR through EMcost4aGR. The second output, Closest Point, identifies, by road grid cell, the nearest fire station for the cell. These layers were named EMclose1aGR through EMclose4aGR.

Analysis Descriptive statistics are summarized in Table 1 for each of the four travel time outputs. The values are minutes. Remember that the number in the layer name refers to the alternative number.

Table 1. Descriptive statistics for the response time grid data layers. Mean Sd. Dev. Range EMcost1aGR 6.043 4.484 18.455 EMcost2aGR 4.274 3.125 15.425 EMcost3aGR 4.230 2.719 11.761 EMcost4aGR 3.482 2.445 11.761

In addition, the response times are categorized into five response time classes:

Table 2. Definitions for the response classes. Data Class Min. Max. 1 0 3.69 2 3.69 7.38 3 7.38 11.07 4 11.07 14.76

5 14.76 20.0

These data classes are used to facilitate discussion and comparison of the alternatives. A module in SAGA is used to determine which data class each residential address in FD3 is located, by alternative. The result of applying this module is summarized and displayed in tables 3.

Table 3. Comparison of response classes by alternative.

Table 3 lists the number of addresses, for each alternative, by response class in the columns labeled with the # sign. In addition, the percentage of the total number of addresses for that class is listed in the column immediately to the right of the # of addresses column.

Table 4. Comparison of addresses by station by alternative.

Table 4 lists the number of addresses nearest to each station by alternative. You will notice that alternative 1, the current situation, shows all the addresses being nearest to station 31. This is because station 32 does not have a fire engine so station 31 is the only station in this current alternative.

Discussion Alternative 1 This is the current situation alternative. Fire Station 31 is the only station of the two district stations with a fire engine. Overall, the distribution of response times is the poorest for the four alternatives.

Alternative 2 This alternative, in addition to Fire Station 31, assumes a fire engine and staffing is available for the Fire District 3 Station 32. This alternative establishes the number of addresses that could be theoretically served by station 32 as 428 and the number served by station 31 as 1248.

Alternative 3 Along with station 31, the two nearest fires stations in FD5 are included in this alternative. Since station 32 is not included in this alternative, this alternative shows the trade-off between station 32 and stations 51 and 57. Station 51 is located in Allyn about half a mile from the northern edge of the boundary between the two districts. Station 57 is located about 3 miles from station 32 by road and is close to the southern boundary of District 3.

The results show that station 51 is closer to 186 addresses than station 31. These are addresses in the northern portion of the district.

Station 57 is closer to 330 addresses of the 428 identified as closest to station 32 in alternative 2. The difference between 330 and 428 (i.e., 98) represents the tradeoff between station 32 and station 57.

Alternative 4 This alternative includes the two FD3 stations, 31 and 32, plus four FD5 stations: 51, 53, 56 and 57. The analysis results show that stations 53 and 56 do not have significance in this alternative.

The four stations, 31, 32, 52 and 57, result with the best overall response times. The most addresses for any alternative were in the quickest response class (1). The next two response classes, 2 and 3, had the lowest numbers for any of the alternatives. Classes 4 and 5, as in alternatives 2 and 3, did not have any addresses.

It is clear that on the south end of Fire District 3, station 32 serves 376 of the 428 identified in alternative 1 and station 57 pulls the difference (52) between the 376 and 428. On the north end, station 51 is closer for 186 addresses; the same result as for alternative 3.

The optimum response performance would appear to be the use of stations 31, 32, 51, and 57. The question becomes, can this station combination be realized through a contract between FD3 and FD5 or a merger between the two districts?

Conclusion The SAGA GIS, making use of GIS data layers available from the Mason County GIS Group, has been successfully applied to develop theoretical elapsed response time data for emergency fire vehicles from fire stations in FD3 and selected stations in FD5. This first part of the tutorial provides an overview of the analysis process. The second part describes in more detail how the SAGA GIS was applied.

The initial question implies two options related to merging the two fire districts, to merge or not to merge. The data show that the optimum elapsed times for the residents of FD3 are achieved with four stations: 31, 32, 51, and 57.

The fastest elapsed time class (Class 1) was 0 to 3.69 minutes. Fifty-four percent of the addresses in alternative 1 were in this response class. Alternative 1 is the current situation. Adding a fire engine to station 32 is an improvement with 71 percent of the addresses falling in Class 1. However, when you include the two FD5 stations (51 and 57), the percentage of addresses in Class 1 jumps to 83 percent with a corresponding lessening of addresses in the slower Class 2 and 3.

Processing Steps 1. Defining a study area. Related to the topic of this tutorial, the most important criteria for a study area is that the area include all roads potentially used by emergency vehicles of the six fire stations considered in the four alternatives. The study area, therefore, includes a portion of the county road network that is within FD3 and adjacent in FD5.

A large spatial area centered on FD3 is defined using the SAGA module Shapes Tools/Cut Shapes Layer [interactive]. Figure 3 displays the parameter window for this module.

Figure 3. The parameter window for the Shapes Tools/Cut Shapes Layer [interactive] module.

The Mason County GIS transportation layer ('MasonRoads') is chosen as input to the module. The "" option is used for the output '

This is an interactive module. This means that once the rectangular area is interactively defined, execution of the module is terminated by moving the mouse pointer over the 'Geoprocessing' title on the Menu Bar and clicking. A drop-down list of options displays. Near the bottom you will see the module name with a check preceding it. Move the mouse pointer over the module name and click. A dialog window displays (Figure 4).

Figure 4. 'Tool Execution' dialog window.

Move the mouse pointer into the 'Yes' button and press the left mouse button. This stops execution of the module.

The default name for the output is 'MasonRoads [Cut]'. I rename the layer EMasonRoads1. The 'EMasonRoads1' line shape data layer includes 1469 line objects defining the road network for the selected area. Figure 5 displays a map view window that includes the 'EMasonRoads1' line shape data layer.

Figure 5. The 'EMasonRoads1' line shapes data layer.

The thick dark gray lines display the study area road network. The study area boundary is where the road network outside of the study area is displayed with thin black lines. The six fire stations involved in the four alternatives are located by the labeled red circles.

The EMasonRoads1 line shapes data layer is used as input to the Grid Gridding/Shapes to Grid module to create the grid data layer version of the study area road network and also a grid system definition for the study area.

2. Creating the transportation grid data layer. A grid data layer version of the line shapes data layer 'EMasonRoads1' is produced using the Grid Gridding/Shapes to Grid module. The module parameter window is displayed in Figure 6. An attribute in the attribute table linked to the shapes data layer provides the data values for the output grid data layer. In this case the attribute is "SURFNUM" and it is used to identify the road surface type as pavement, gravel or dirt. The data values for this attribute are from 1 to 3. A 1 indicates the surface is pavement, a 2 gravel, and 3 is dirt.

On the original line shape data layer for roads, two types of roads are categorized as private or not applicable and do not have a surface cover identified. A 0 was used for these categories. I edited these 0 values changing them to 2. A future, detailed review of road objects for these categories could result with more appropriate road surface codes. In many cases these roads are short access roads from a main road to a residence.

Figure 6. The parameter window for the Grid Gridding/Shapes to Grid module.

The 'EMasonRoads1' line shapes data layer is chosen for the input parameter '>> Shapes'. One of the input parameters for the vector to raster conversion process is to identify the numeric attribute in the attribute table linked to the input shapes data layer that is to provide the data values for the output grid data layer. In this case, as discussed earlier, the numeric attribute is one called "SURFNUM".

The "user defined" option is used for the 'Target Grid System' parameter. The spatial extent of the input line shapes data layer defines the spatial extent of the output grid data layer. A cell size of 90 is entered for the 'Cellsize' parameter. The resulting grid data layer is a matrix of cells 876 rows by 611 columns. The default name for the output grid data layer is 'EMasonRoads1 [SURFNUM]'. The "user defined" option also defines a new grid system representing the study area. The output grid data layer, renamed

EMasonRoads1GR, contains three data values: 1, 2 or 3. This layer is now ready for further processing.

3. Creating the roads travel time (cost) grid data layer. Rough estimates were made for the average speed of emergency vehicles according to the road surface type. The most important aspect of these estimates is that they remain constant for all alternatives. This supports relative comparisons of results rather than absolute comparisons. It can be stated that a number is larger or smaller than another but absolute differences would require more precise speed values rather than average values by surface type.

The average speed values could be refined. A new attribute could be added to the line shapes 'EMasonRoads1' data layer attribute table for speed. The value would be based on surface type, the category of road (i.e., road, lane, street, avenue, etc.) and the average slope of the road overall. This could be a future enhancement of this process.

The vehicle average speed estimates are 40 miles per hour (MPH) for paved roads, 20 MPH for gravel, and 7 MPH for dirt surfaces. A calculator was used to determine how much time in seconds it takes an emergency vehicle to travel 90 at these three speeds. Here are the results of those calculations:

Paved = 1.53 seconds, .0255 minutes. Gravel = 3.07 seconds, .0512 minutes. Dirt = 8.77 seconds, .1462 minutes.

The SAGA module Grid Tools/Reclassify Grid Values is used to recode the EMasonRoads1GR values to produce a transportation cost grid data layer. Figure 7 displays the parameter window for the module.

Figure 7. The parameter window for the Grid Tools/Reclassify Grid Values module.

The 'EMasonRoads1GR' grid data layer is chosen for the input parameter '>> Grid'. The default "" option is used for the output parameter '

4. Creating the destination grid data layers. The SAGA module Grid Analysis/Accumulated Cost (Isotropic) refers to its input point shapes data layer as a destination points layer. In this tutorial these input point shapes data layers for the four alternatives are actually starting points layers. I will continue using the SAGA module terminology, but please keep this distinction in mind.

A destination grid data layer is created for each of the four alternatives. Each of these layers includes point objects for a station (as in alternative 1) or stations (as in alternatives 2 through 4) in the specific alternative.

The Mason County GIS point shapes data layer for fire stations is used as the source for this grid data layer. This layer is named Fire_stations. The 14 fire districts in Mason County include 52 fire stations. The layer was loaded. A zoomed in portion of the layer is displayed in a map view window (Figure 9) in the SAGA workspace.

Figure 9. Map view window for the 'Fire_Stations' data layer.

The red dots in the map view window represent fire district stations. The thick red line is the boundary for FD3. FD3 has two fire stations; one is located just to the west of Stretch Island near the center of the district. The second one is just outside of the northern boundary in the southwest area of the district. The six stations involved with this analysis appear in the map view window with circles surrounding their red dot locations. The six include the two stations in FD3 plus the nearest 4 stations in FD5.

Using the Action tool from the toolbar, the two point objects for fire stations in FD3 are selected and highlighted. Next, the four stations in FD5 are chosen and highlighted. This results in six point objects highlighted in the map view window. The Shapes Tools/New layer from selected shapes module is executed to create a new point shapes data layer

containing the selected and highlighted point objects on the Fire_stations layer. This new layer is renamed EMasonFireStns. The new layer includes six point objects for the six fire stations.

An important requirement related to the application of the Grid Analysis/Accumulated Cost (Isotropic) module is that the grid cells for a destination or destinations must overlap a cost grid cell or in this case a road network grid cell.

None of the six fire stations meet this requirement. The stations are not more than 50 feet distant from a road but do not overlap a road.

Figure 10. Stations 31 and 57.

The zoomed in area, Figure 10, is the extreme southwest portion of FD3. Near the top of the area is a red dot representing station 32 (70 feet from the road) and near the bottom is a dot representing station 57 (adjacent to the road). You can see that the locations are adjacent and not overlapping any road network grid cell. I manually adjust the fire station location to overlap the nearest road network grid cell. I do this using on-screen digitizing tools prior to creating the alternative point shape data layers. These adjustments are saved in the 'EMasonFireStns1' data layer.

In the attribute table linked to the 'EMasonFireStns1' point shapes data layer is the attribute named "DSN" for district station number. The "DSN" data values for the two stations in FD3 are 31 and 32; for the four stations in FD5 the data values are 51, 53, 56 and 57. A two step procedure is used to create first a point shape data layer for each station (having a single point object) and then merge them together into the four alternative data layers.

The EMasonFireStns1a layer is going to contain the location for fire station 31; EMasonFireStns2a for stations 31 and 32; EMasonFireStns3a for stations 31, 51, and 57; and EMasonFireStns4a all the stations (31, 32, 51, 53, 56, and 57). These point shape data layer will be converted to grid data layers.

The Shapes - Tools/Split Table/Shapes by Attribute module is used to create a point shapes data layer for each district station. The parameter window for the module is displayed in Figure 11.

Figure 11. The parameter window for the Shapes - Tools/Split Table/Shapes by Attribute module.

The 'EMasonFireStns1' point shapes data layer is chosen for the input parameter '>> Table / Shapes'. The "DSN" attribute contains the data values for each district station number. This attribute is chosen for the 'Attribute' parameter. The six output point shape data layers are named 'EMasonFireStns1 [DSN = 31]' through 'EMasonFireStns1 [DSN = 57]'.

The Shapes - Tools/Merge Layer module is used to create a point shapes data layer for each of the four alternatives. The parameter window for the module is displayed in Figure 12.

Figure 12. The parameter window for the Shapes - Tools/Merge Layer module.

The Shapes - Tools/Merge Layer module parameter window in figure 12 is an example of how the EMasonFireStns2a data layer is created from the two input data layers 'EMasonFireStns1 [DSN = 31]' and 'EMasonFireStns1 [DSN = 32]'. The two input layers are chosen for the '>> Layers' parameter. The "" option is used for the output '

The parameter window displayed in the figure shows how the 'EMasonFireStns1a' alternative point shapes data layer is converted to its' grid data layer equivalent. The "grid or grid system" option is chosen for the 'Target Grid System' parameter. This is the grid system created when the study area was defined. The "" option is used for the output parameter '> Cost Grid' parameter. The data values of this layer represent the time, in fractions of

minutes, it takes a vehicle to move 90 feet at a specific speed. The grid data layer for the first alternative, 'EMasonFireStns1aGR', is chosen for the '>> Destination Points' input parameter. This grid data layer has one grid cell with a data value of 31. All the other grid cells in the layer contain the no data value -99999.

The output grid data layers for the four executions of the module are renamed, by alternative, AccCost1aGR through AccCost4aGR and Close1aGR through Close4aGR.

The station numbers used as data values in the 'EMasonFireStns1aGR' through 'EMasonFireStns4aGR' grid data layers are automatically recoded by the model to 1, 2, etc., in the output data layers. The output layers 'Close1aGR' through 'Close4aGR' are used for further processing in the tutorial. These recoded data values, for each alternative layer, are converted back to the district station numbers (i.e., 31, 32, 51, 53, 56, and 57) using the Grid - Tools/Reclassify Grid Values module.

It is relatively easy to determine the recode values of the nearest point layers by displaying the corresponding station alternative point shape data layers ('EMasonFireStns1aGR' through 'EMasonFireStns4aGR') with the nearest point layer in the same map view window. For example, the data values for the 'Close2aGR' data layer are 1 and 2. The data value 2 is actually for station 31 and the data value 1 is for station 32. I used the "simple table" method in the Grid - Tools/Reclassify Grid Values module to change all the 1's to 32 and the 2's to 31 on the 'Close2aGR' layer. The no data value -1 (on the nearest point layers) is converted to the no data value -99999. I resaved the output grid data layer using the same name.

6. Masking out areas outside of FD3. Up to this point, the input and output grid data layers represent the entire study area which includes area outside of the FD3 boundary. However, as noted earlier, it is necessary to use a larger area to ensure that the entire potential road network is available in the analysis. At this point, the larger road network has served its purpose, and the study area can be narrowed to FD3 for developing data for analysis.

The Grid Tools/Grid Masking module is used to apply the FD3 boundary as a mask for the outputs representing the travel time grid data layers. The parameter window for the module is displayed in Figure 15.

Figure 15. The parameter window for the Grid Tools/Grid Masking module.

A grid data layer for FD3 is available ('FD3threeGR') with grid cells within the district containing 1s and cells outside of the district contain the value 99999. This layer is entered for the '>> Mask' input parameter and used to mask out all data outside of the fire district for the travel time grid data layers ('AccCost1aGR' through 'AccCost4aGR') as well as the layers containing the data values of the nearest dest ination ('Close1aGR' through 'Close4aGR'). The travel time and nearest destination data layers are each chosen for the input parameter '>> Grid'. The module is executed once for each data layer to be masked. The default name for the output grid data layer is 'Masked Grid'.

The new masked grid data layers are renamed EMcost1aGR through EMcost4aGR for the travel time layers and EMclose1aGR through EMclose4aGR for the layers identifying the nearest station for each road cell.

7. Statistics for each output. Descriptive statistics are available for every grid data layer. They can be viewed by making the grid data layer active by choosing the layer in the Data tab area of the Manager. When you click on the Description tab in the Object Properties window, the descriptive information for the layer displays. The important information for this analysis will be the values for the cost layers for these items: Minimum, Maximum, Value Range, Arithmetic Mean, and Standard Deviation. These statistics help to understand the distribution of the grid data layer data values.

I use the Spatial and Geostatistics - Grids/Save Grid Statistics to Table module to create a table with the statistics for the four cost grid data layers 'EMcost1aGR' through 'EMcost4aGR'.

Table 5. Comparing Descriptive Statistics for the Alternative Cost Grid Data Layers.

Alternative 1 is considered the "current" situation. The mean response time is the highest for the four alternatives. You can see that the response time range is the longest at a little over 18 minutes. This range is going to be used to define five equal interval response time categories to facilitate making comparisons across all four alternatives. The fastest response time class is 1 and the slowest response time class is 5. The moderate class is 3. Classes 2 and 4 are "in-between" classes.

The default output table 'Statistics for Grids' is renamed 'ResponseStats'.

I use the "Create Lookup Table" function available for each data layer in the 'Data' tab area of the Manager. I define a table having 5 classes using the "equal intervals" option for the 'Classification Type' parameter. This resulted with the class definitions displayed in Figure 16.

Figure 16. Theoretical response time classes defined.

The "Create Lookup Table" function is a display only tool, it does not change data values. It is only used to change how data is displayed. The Grid Tools/Reclassify Grid Values module is used for re-coding or changing grid data layer values. This step is described in the next section.

8. Recoding the response times into response classes. The value ranges for the four cost output grid data layers are compared along with their data histograms. The following data categories are identified:

Class Min. Max. 1 0 3.69 2 3.69 7.38 3 7.38 11.07

4 11.07 14.76 5 14.76 20.0

The SAGA module Grid Tools/Reclassify Grid Values is used to recode the elapsed travel time data values for each of the time related output grid data layers into the five classes, 1 through 5. Figure 17 displays the parameter window for the module.

Figure 17. The parameter window for the Grid Tools/Reclassify Grid Values module.

Each of the cost grid data layers, 'EMcost1aGR' through 'EMcost4aGR', is reclassified using this module. You can see in the example that the cost grid data layer is identified for the '>> Grid' input parameter. The "" option is used for the output parameter '

Figure 18. The "simple table" for the Reclassify Grid Values module.

I am going to save the table (using the 'Table' button on the dialog window) in case I need to re-use the table in future work sessions. I save it as 'RECLASScost.txt'. The simple table with the classes defined is displayed above.

The reclassified grid data layers are renamed ReEMcostcat1aGR through ReEMcostcat4aGR.

9. Creating an allocation grid data layer. Before response time class can be added as an attribute for FD3 addresses, an allocation grid data layer must be created using the Grid Tools/Grid Proximity Buffer module. This data layer uses the reclassified grid data layers produced by the Grid Tools/Reclassify Grid Values module in the previous step as input to identify for every no data grid cell the "source" grid cell it is nearest up to a specified maximum distance away from the source cell.

The source cells are the road grid cells that now contain a data value for the response class they fall in. Road grid cells contain class data values between 1 and 5. All non-road grid cells contain the no data value -99999. One of the inputs for the Proximity Buffer module is a buffer distance. The allocation grid data layer identifies the response class for every grid cell up to the buffer distance away from a source cell (i.e., a road network cell containing a response class value).

Figure 19. An example for the allocation grid data layer.

The map view window in Figure 19 displays a zoomed in area of FD3. The red line is the district boundary. The black lines are line objects on the road network shapes data layer 'EMasonRoads1'. The dimmed colors (set at 50%) are allocation data layer values. The heavy colored grid cells are on a source grid data layer for reclassified road values for response classes. Data values of 1 are displayed in dim blue and dark blue; data values of 2 are light blue; data values of 3 are yellow; and data values of 4 are red. Let's look at the red and dark blue area near the center of the map view window.

The red area extending to the northwest from the response class 4 road grid cells stops at the white area. The scale bar indicates that the red/white boundary is 1500 feet from the class 4 road segment. The light blue/red boundary to the west of the class 4 road segment is half-way between the end of the road segment and the end of the light blue class 2 road segment. The red/dark blue boundary to the south and east of the class 4 road segment is also half-way. This illustrates how allocation grid data layer data values are determined. They are based on which source grid cell they are nearest within the distance entry for the buffer distance parameter.

The Grid Tools/Grid Proximity Buffer module produces three grid data layers: a distance layer, an allocation layer, and a buffer layer. These layers are determined from

an input 'Source Grid'. The data values of the 'Source Grid' are source features and all non-source features contain no data values of -99999. In this case, the source features are data category values for response time classes stored in road grid cells. As noted earlier, these data category values range between 1 and 5.

Grid cells of the Allocation Grid output layer indicate the data value for the source feature the grid cell is nearest. The 'Buffer distance' parameter entry defines the maximum distance for the buffer width. Grid cells beyond the maximum distance contain no data values on the output grid data layers.

Figure 19. The parameter window for the Grid Tools/Grid Proximity Buffer module.

The Grid Tools/Grid Proximity Buffer module is executed once for each of the grid data layers containing data values for elapsed response time classes, 'ReEMcostcat1aGR' through 'ReEMcostcat4aGR'. The example parameter window in Figure 19 shows that the 'ReEMcostcat1aGR' layer is chosen for the '>> Source Grid' input parameter. The buffer distance specified is 1500. It was pre-determined that all addresses in FD3 are within 1500 feet of a road. The output grid data layers are renamed EMalloc1aGR through EMalloc4aGR. These grid data layers provide attribute data values for the FD3 address point shape data layer.

10. Adding alternatives response time classes to the address data layer attribute table. I use the Shapes Grid/Add Grid Values to Points module to add attributes for the response time class, for each address point object, by alternative to the attribute table linked to the MasonFD3addpts point shapes data layer. Figure 20 displays the parameter window for this module.

Figure 20. The Shapes Grid/Add Grid Values to Points module parameter window.

The input point shapes data layer MasonFD3addpts is chosen for the input parameter '>> Points'. In addition, the four grid data layers EMalloc1aGR' through EMalloc4aGR are chosen to provide the grid data values for four new attribute fields.

The new columns in the attribute table for the output point shapes data layer are, by default, labeled with the names of the grid data layers entered for the Grids parameter in the settings for the Shapes Grid/Add Grid Values to Points module. I edited the names changing them to RsCLAlt1, RsCLAlt2, RsCLAlt3, and RsCLAlt4.

11. Creating an allocation data layer for nearest station. Attributes with data values for the nearest station, for each of three alternatives, need to be added to the attribute table linked to the 'MasonFD3addpts' point shapes data layer. An attribute for nearest station is not needed for alternative 1 because there is only one station in the alternative.

The discussion in step 9 on how an allocation grid data layer is created applies in this step also. In summary, the Grid - Analysis/Accumulated Cost (Isotropic) module produced two output grid data layers, one for accumulated cost and a second one for closest point. The closest point grid data layer identifies for each road network grid cell the nearest fire station. The closest point grid data layers for the alternatives are named 'Close1aGR' through 'Close4aGR'. The Grid - Tools/Grid Masking module was used to clip grid cell data values lying outside of FD3. These grid data layers are named 'EMclose1aGR' through 'EMclose4aGR'.

The layers 'EMclose2aGR' through 'EMclose4aGR' are inputs to the Grid Tools/Grid Proximity Buffer module in this step. This module creates an allocation grid data layer for each of the input layers. These layers are named 'EMnear2aGR' through 'EMnear4aGR'. They serve the same purpose in this analysis as the earlier created cost class data layers 'ReEMcostcat1aGR' through 'ReEMcostcat4aGR'. The difference here is that the data values data values represent the nearest station.

12. Adding alternatives nearest station to the address data layer attribute table. The Shapes Grid/Add Grid Values to Points module is applied to add attributes for the nearest station, for each address point object, by alternative to the attribute table linked to the MasonFD3addpts point shapes data layer. Figure 21 displays the parameter window for this module.

Figure 21. The Shapes Grid/Add Grid Values to Points module parameter window.

The input point shapes data layer MasonFD3addpts is chosen for the input parameter '>> Points'. In addition, the three grid data layers named 'EMnear2aGR' through 'EMnear4aGR' are chosen to provide the grid data values for three new attribute fields.

The new columns in the attribute table for the output point shapes data layer are, by default, labeled with the names of the grid data layers entered for the Grids parameter in the settings for the Shapes Grid/Add Grid Values to Points module. I edited the names to NStnAlt2, NStnAlt3, and NStnAlt4.