CALIFORNIA STATE UNIVERSITY, NORTHRIDGE
A GIS-BASED ANALYSIS OF WHY CHILDREN DO NOT WALK TO SCHOOL IN
LOMITA, CALIFORNIA
A thesis submitted in partial fulfillment of the requirements
For the degree of Master of Arts in Geography
BY
AFSANEH RAFII
December 2014
The thesis of Afsaneh Rafii is approved:
__________________________
____________
Dr. James W. Craine
Date
_____________________________
______________
Dr. Soheil Boroushaki
Date
___________________________
_____________
Dr. Steven Graves, Chair
Date
California State University, Northridge
ii
Acknowledgments
I would like to give thanks to my chair Dr. Steve Graves, for giving me his time and
spending hefty amounts to help me for two semesters. I would also like to give thanks to
Dr. James Craine as well as Dr. Soheil Boroushaki for helping me every single time I
would ask for it. I would like to give a special thanks to the department chair Dr. Shawna
Dark for giving me motivation and help for the beginning of my Masters. I would also
like to give thanks to the Department of Geography and all the professors that have
taught and encourage me every day. In addition, I would like to give thanks to Lani
Kiapos, DARS coordinator who consistently was able to help me in the times that I need
it the most. I would also like to give thanks to Maggie Shiffrar, Assistant VP for Graduate
Studies who gave me the opportunity to complete this thesis despite the hurdles I came
across. I would like to give all the credit and thanks to my two daughters Sheila & Shaina
for supporting me and helping me in each moment of my time in school. I would like to
give thanks to my late mother who supported me all of my life, including this journey. I
also extend my thanks to all of my classmates and family for helping me through this
journey. Thank you so much Dr. Graves for giving me the opportunity to complete this
thesis successfully.
iii
Table of Contents
Acknowledgments………………………………………………………………………. iii
Table of Contact…..…………………………………………………………………….. iv
Table of Figures ...................................................................................................................v
ABSTRACT ..................................................................................................................... viii
Chapter 1: Introduction ........................................................................................................1
1.1 Background ................................................................................................................1
1.2 Significance of the Study .......................................................................................... 2
Chapter 2: Walkability Literature ........................................................................................5
2.1 Walkability................................................................................................................ 5
2.2 Barriers to Walkability.............................................................................................. 6
2.2.1 Safety ................................................................................................................. 7
Chapter 3: Distance and Walkability - Los Angeles County ...............................................9
Chapter 4: Lomita, California as Case Study.....................................................................14
4.1 Lomita Field Observations...................................................................................... 16
4.2 Measuring Walkability in Lomita. .......................................................................... 23
4.2.1 Sidewalk Availability....................................................................................... 23
4.2.2 Measuring Crime Rates .................................................................................... 27
4.2.3 Measuring Traffic Accident Density................................................................ 29
4.2.4 Walkability Index ............................................................................................. 31
Chapter 5: Conclusions ......................................................................................................33
5.1 Policy Implications and Recommendations ................................................................ 34
References ..........................................................................................................................38
iv
Table of Figures
Figure 3-0-1:Map of School Closures in the Western San Fernando Valley with Drive
Time Buffers……………………………………………………………………………. 13
Figure 4-0-1:Map of Lomita's Census Block Group Boundaries and Schools…………. 15
Figure 4-2:Major street in front of Lomita’s School needed medians, and traffic signs for
preventing motorists from making U-turns while students cross the street…………….. 17
Figure 4-3:Lomita Street without sidewalks or one narrow sidewalk………………….. 17
Figure 4-4:City of Lomita residential streets near schools without sidewalks ……….... 18
Figure 4-5:City of Lomita’s Street a cross street from Eshelman Elementary school
without sidewalks………………………………………………………………………. 18
Figure 4-6:Streets by Eshelman Elementary school in the City of Lomita without
sidewalk………………………………………………………………………………… 19
Figure 4-7:Students dropped off in the middle of the street in front of Narbonne High
School…………………………………………………………………………………... 19
Figure 4-8:Students walk in street to get where sidewalks are missing………………... 20
Figure 4-9:No sidewalks encourage students to ride scooters in streets ………………. 20
Figure 4-10:Narbonne High students walk in the middle of a street without sidewalks.. 21
Figure 4-11:Students walk in a street where sidewalks are narrow ……………………. 21
Figure 4-12:Unsafe and blocked sidewalks near a school in Lomita ………………….. 22
Figure 4-13:A damaged sidewalk near Eshelman Elementary School ………………… 22
Figure 4-14:Map of Lomita by Sidewalk Availability ……………………………..…. 26
v
Figure 4-15: Map of Lomita by Crime per 1,000 Persons ……………………………. 28
Figure 4-16: Map of Traffic Accidents per Square Mile, Lomita, California…………. 30
Figure 4-17: Walkability Index Scores for Lomita by Census Block Group………….. 32
vi
ABSTRACT
A GIS-BASED ANALYSIS OF WHY CHILDREN DO NOT WALK TO SCHOOL IN
LOMITA, CALIFORNIA
By
Afsaneh Rafii
Master of Arts in Geography
Substantial evidence points to a great decline in the number of American children who
walk or bike to school since 1970. In addition, a number of studies point to the great
benefit of physical exercise, like walking, on a host of physical and mental health issues,
such as obesity, cardio-vascular health and attention deficit disorders. These health
issues have reached epidemic proportions in the United States in recent years, but still
children continue to ride in vehicles to school. A significant literature suggests that
increased walking distances and families’ safety concerns are the major reasons
discouraging students from walking to school. In order to investigate these assertions,
several GIS based analyses of school walkability are undertaken. An analysis of the
temporal changes in distance between school aged children and schools in Los Angeles
finds no significant change over the past few decades in distance metrics affecting the
likelihood of walking to school. A follow-up case study of walkability in Lomita,
California finds that several schools in that part of Los Angeles are located in
neighborhoods with poor walkability characteristics, indicating that school site locations
vii
may be partially to blame for the low number of students who walk to school in urban
settings. Policy recommendations are offered.
viii
Chapter 1: Introduction
The trip to and from school has changed dramatically in the past 40 years. Today instead
of walking or bicycling to and from school, children use private cars or school buses.
Today approximately 45 percent of children are driven to school by their parents and
about 39 percent ride in school buses (McDonald et al. 2011). This leaves about 15
percent of children aged 5 to 14 in the United States who walk or bike to and from
school, a significant decrease from the nearly 50 percent that walked or biked in 1969
(McMillan 2003; Serdula et al.1993). There are a number of reasons preventing students
from walking or riding bikes to school nowadays, including fear of crime and injury,
laziness, and school closures. In addition to the social and personal costs in terms of
taxes and pollution, there is a variety of personal and social health costs associated with
this sea change in school transportation. This thesis examines how school closures in Los
Angeles County have altered the landscape of elementary school distribution in an
attempt to evaluate the effect of school policies on the ability of school aged children to
walk to school. A case study, conducted in the city of Lomita, California, considers
multiple factors affecting walkability in that locale in an attempt to further shed light on
the problem. The benefits of this walking and biking to school, as well as the programs
designed to promote walking as an alternative for students are discussed.
1.1 Background
Substantially fewer students walk or ride their bicycles to school today, and increasingly
students are using private transportation (Beck & Greenspan 2008). In 1960,
approximately 50 percent of children walked or rode their bicycle to school (Amram et
al. 2011). In 1969, 48 percent of children 5 to 14 years of age usually walked or bicycled
1
to school (Lee & Moudon 2004; The National Center for Safe Routes to School 2011). In
addition, approximately 87 percent of children living within one mile of school walked or
rode their bicycle during the 1960s (Epstein et al. 1997). By 2009, a mere 13 percent of
children aged 5 to 14 years walked or bicycled to school (Serdula et al. 1994).
This illustrates that only 40 years ago children were routinely moving around their
neighborhood by foot or by bicycle, without parental supervision, mainly traveling to and
from school (Clifton et al. 2007). Today over 85% of children are not walking or biking
to get to school, which has serious implications for the future in terms of physical activity
and health for children (Frank & Engelke 2001). This change has had many effects,
including undermining children’s’ health and increased air pollution (Zuurbier et al.
2010). This study began as an attempt to understand why these changes have occurred.
1.2 Significance of the Study
Walking to school is an affordable and environmentally clean mode of transportation that
may increase physical activity, sense of well-being, and reduce or decrease health
problems in children such as obesity, diabetes, hypertension, colon cancer, and heart
disease (Liu, & Hannon 2005). Significant links exist between the levels of walking and
cycling and health (Keppel et al. 2005). Studies have also shown that more than half of
the differences in obesity and asthma rates among countries are related to walking and
cycling alone (Ogden et al. 2000). Approximately 30 percent of the differences in obesity
rates among states and cities across the U.S. are related to walking and bicycling rates
(Berrigan & Troiano 2002; Atkinson et al. 2005). One of the important benefits of
walking is to prevent of the risk of obesity in children (Berrigan & Troiano, 2002).
Moreover, obesity has increased in the United States over the last thirty years (Tremblay
2
& Willms 2000). The percentage of overweight children between the ages of 6 to 11 in
the United States has grown from 4% in 1965 to 13% in 1999. Moreover the rate of
overweight adolescents age 12 to 19 increased from 5 percent in 1970 to 14% in 1999
(Ogden et al. 2002). Some researchers believe that active travel, like walking and biking,
has significant health benefits (Lee & Moudon 2004). Bassett (2000) showed that the
relationship between active travel and health was discernible at three different geographic
levels: international, state and city. His study also emphasized that the United States
government needs to encourage physical activity by creating a safe and welcoming
atmosphere with a reasonable infrastructure (Edwing et al. 2005). Even light or moderate
physical activity, such as walking or cycling, can reduce the risk of heart disease and
early death (Tudor-Locke et al. 2002). Not only can light physical activity reduce the risk
of cardiovascular disease, but it also can promote mental health and prevent asthma.
Researchers like Rupert (2012), an obstetrician and gynecologist, who practices at Kaiser
Permanente in North Portland, found that children who are more physically active have
better academic performance. Rupert (2012) also found that the more exposure to nature
and free outdoor play and outdoor activities children get, the greater the reduction in the
stress levels, and ADHD symptoms. When parents use cars less, and walk or bike to
school with their kids, or let their children walk or bike to school, there is an
improvement in air quality and less impact on limited energy resources (Gehring et al.
2010).
Despite the substantial logic behind walking or biking to school, it appears there has been
little improvement on this front in recent years. A review of the literature (below)
suggests strongly that increased walking distances and families’ safety concerns are the
3
major reasons discouraging students from walking to school. In order to investigate these
assertions, several GIS based analyses of school walkability are undertaken. An analysis
of the temporal changes in distance between school aged children and schools in Los
Angeles finds no significant change over the past few decades in distance metrics. A
follow-up case study of walkability in Lomita, California finds that several schools are
located in neighborhoods with poor walkability characteristics.
4
Chapter 2: Walkability Literature
It is assumed that most families and even children understand that walking is a beneficial
activity. The question then becomes why children don’t walk more. A number of studies
have already sought answers to this question and many related ones (Allison & Ludwig
2005). However, one area that these studies usually do not gathering a lot of focus on is
the dynamics of transportation: like walking and biking, child safety, and driving
awareness around school zones, as well as around school buses, and child care centers
(Kerr et al. 2006). As it turns out, walkability or perceptions of walkability figure
prominently among the reasons children don’t walk. This study examines those fears
against the reality on-the-ground using GIS.
2.1 Walkability
Walkability has become a buzzword in planning circles and among academics in recent
years. The decrease in walking and biking to school has been the focus of much research
(Kerr et al. 2006). Some researchers are interested in the association between the built
environment and physical activity (walking and biking) and have focused attention on
children between the ages 5 and 17 (Atkinson et al. 2005). At least a few studies (e.g.,
Hossain et al. 2009) examine how GIS can be used to understand the relationship
between physical activity and the built environment for a group of children. Norman &
Nutter (2006) focused a similar study on the walking behaviors of low-income children
Walkable communities are livable places which give their residents safe and trusty
transportation choices and could improve the quality of life of the residents (Frank &
Engelke 2001). Walkable communities improve transportation efficiency and create
5
healthier and happier lives for their residents. Overall, increased walkability also could
help improve safety, as well as health and social collaboration (Serdula et al. 1993).
2.2 Barriers to Walkability
The most basic barrier to walkability is the friction of distance. When destinations, like
schools, malls or markets are too far from residences, people are simply unable to choose
to walk. Time constraints overwhelm the positive benefits associated with walking. This
fact has not escaped study.
Researchers are strongly concerned that children do not walk or bike to school as much
as in the past and they are working hard to understand what reasons are behind this
problem (Martin & Carlson 2004). Research has shown that kids live further from school
than they did in the 1960s. In fact, in 1969, 41 percent of children from kindergarten to
8th grade lived within one mile of school, and almost 89 percent of those children usually
walked or bicycled to school (CDC 2004). Only 31 percent of children in kindergarten
through 8th grade, in 2009, were living at least within one mile of school, and out of
those only a mere 35 percent of them usually walked or biked to school (Morris, 2001).
Between 1968 and 2001, the number of schools decreased by about 1,000 while the
number of students increased by over 2 million (NCES, 2003). However, fewer students
live within a mile of their school as compared to earlier times. Nowadays, kids go to
larger schools located further from home than they did two generations ago.
One of the main reasons for the decrease of walkability to schools is lack of
neighborhood schools. Today in twenty first century, there are not many neighborhoods
schools in comparison to the past, and many neighborhood schools were eliminated
6
during the 1980s. Moreover, President Regan cut the budgets of non-military programs,
including Federal Education Program in what was pitched as an effort to reduce the
deficit (Rosenbaum, David E, 1986), and because of this law, the government closed
down these schools. No replacements were built. The result of this policy gradually
decreased the number of walking of children and increased carpooling and machinery
transportation to these schools based on distance (Rosenbaum & David, 1986). As a
result of these observations, the first objective of this study is the examine changes in
distance school-aged children must travel in Los Angeles since the 1980s.
2.2.1 Safety
A number of researchers point to both real and perceived safety issues as the key element
determining the walkability of a town or neighborhood. In fact, one researcher claims
that the main reason why fewer children are walking or biking to school is because of
safety and street construction conditions (Kerr et al. 2006).
A lot of the focus seems to be on the built environment; the manner in which the
pathways to and from school are constructed and how poor design increases the risk of
injury. Ewing et al. (2004) also note that parents have cited street conditions, safety, and
crime as leading reasons for not letting or not making students walk to school. Safety
concerns raised when vehicles are parked along walkways contributing to potential
pedestrian vehicle contact and traffic collisions in the vicinity of schools (Ewing, et al.
2005; Fabbri et al. 2008). Another study suggested that children do not walk to school is
because they have to negotiate pedestrian paths that are often blocked by parked vehicles
(Zucca et al. 2008). Another study notes that street condition concerns are strongly
linked or related to the kind of physical environment and landscape architecture (Cervero
7
& Duncan 2003). Poor street conditions may influence not only children's school travels
but also bring their play activity and their overall physical activity down (Boarnet &
Anderson, 2005). The lack of sidewalks, green routes, and poor street conditions could be
the reasons for decreasing for walking and biking to school anymore (Fulton, et at. 2005).
Clearly in many instances parental fears are well founded. School zones are dangerous
and appear to perhaps be getting more dangerous. Approximately 250 children annually
are killed near schools, and approximately 23,000 are injured while walking and
bicycling to and from school (TSA 2009). Traffic-related crashes are the leading cause of
death and the major cause of injury among children aged one to seventeen (Ewing et al.
2004). These deaths and/or injuries cost hundreds of millions of dollars annually in
medical costs and work-loss costs (Lawrence, et al. 2009).
Parents themselves appear to be part of the problem. Parents often will drive quickly and
without precision to and from school grounds creating a potentially hazardous
environment for children (Schlossberg & Greene 2006). Fear drives the danger. Data has
shown how traffic volume around schools and distance to school has increased
dramatically and therefore because of this reason active transport like walking to school
decreased (Strauss & Pollack, 2001). It is a self-reinforcing loop that shows few signs of
abating.
In addition to fears about traffic related injury or death, several studies have pointed to
fears of criminal activity, including drug trafficking and kidnapping as a reason for a
decrease in walkability (Day, 2006; Martin, & Carlson, 2005).
8
Chapter 3: Distance and Walkability - Los Angeles County
In order to investigate the level of school walkability, a multi-pronged methodology was
devised based on the literature presented above. The first component of this study’s
methodology was designed to analyze the most fundamental component of walkability:
distance. As detailed below, distance proved to be an unlikely cause in the declining
prevalence of school children walking in Los Angeles in general. Therefore, a case-study
approach was implemented that focused on the neighborhood of Lomita, California sub
region of Greater Los Angeles in which a more in-depth understanding of walkability
could be gained.
The primary aim of this project is to determine why children are not walking and/or
biking to school compared to years past. A preliminary examination of the western
reaches of Los Angeles’ San Fernando Valley district and the city of Lomita, California
suggested that one of the reasons children walk to school less frequently is the greater
distance between home and school in 2014 than it was in the late 1960s, which is the
common era by which modern walking studies are compared.
Cuts in school funding and attempts at creating various “school of choice” programs,
often called “magnet” schools have resulted in a new public school landscape. A number
of neighborhood schools in the western San Fernando Valley, including Osco Avenue,
Collins Street, and Platt Ranch, Highlander Road elementary schools were closed in the
1980s as children of the baby-boom generation filtered out of the region. It is clear that
children living near these schools today have to commute longer distances than did their
counterparts during the 1960s. If this pattern is repeated frequently around the Los
9
Angeles, or the nation, then it suggests a large number of students are riding to school
because too many schools are beyond easy walking distance.
In Lomita, one of the three regional neighborhood schools closed. In the West Valley,
only one of the closed elementary schools has re-opened, so children that once lived in
close proximity to the closed schools must travel further to attend elementary school.
The neighborhood school once known as Lomita Elementary was renamed “Lomita
Math/Science Magnet” and students from the neighborhood, if they are not admitted, may
not attend this school – even if they live across the street. Instead, they are forced to go
to elementary school in neighboring communities, sometimes at significant distances to
their home. In addition, children from distant neighborhoods accepted into the
math/science magnet school may travel many miles to attend. It is unlikely that many of
the children affected by these changes are likely to walk to school.
From these observations, it was determined that shifting school policies adopted in the
wake of budget cuts and equitability efforts since the 1970s may have had a negative
effect on the ability of children in Los Angeles County to walk to school. It is plausible
to believe that similar policy changes elsewhere in the United States have had similar
effects on children nationwide.
In order to analyze the likelihood such observations are true, a test was created designed
to evaluate the effect of distance on changing walking habits of schoolchildren. It is
hypothesized that if more students are prohibited from walking to school by changes in
the policies of local districts, then there will be a statistically significant increase in the
percentage of school-aged children that live in a census tract/block group whose centroid
10
point is greater than one-half mile from a neighborhood school in 2014, than there were
in 1980.
In order to test the hypothesis, all elementary schools in Los Angeles County were
mapped at two time intervals. The first map plotted each elementary school’s location in
1980. The second map plotted each elementary school’s location in 2010. High schools,
junior high schools and middle schools were excluded from consideration because
student attending such schools are drawn from greater distances and therefore are less
likely to walk anyway. Magnet schools and other schools of choice were also excluded
from consideration in both periods. It should be noted that no magnet school or school of
choice existed in 1980. These years were chosen because they were the best years for
which data was available. Though much of the research reviewed above compares data
from the 1960s to more recent years, school address data was not available for 1960s.
Moreover, many schools were still being constructed in the 1960s, which would make
comparisons difficult. The mid-1980s, however appear to be when the first major wave
of school closures began, so that year presents itself as a logical proxy for this
measurement.
Once the schools were plotted as points on the map, a series of buffers were generated
around each school at both .05 mile and 1-mile intervals. Both open and schools closed
since 1980 were included in the map. Rather than use standard Euclidean Distance, the
street distance, or “Drive Time” distance was used. This distance measurement tool more
faithfully replicates the actual walking distance encountered by pedestrians and/or
automobile drivers. It must be admitted that in a few locations, students may have access
11
to “short cuts” or other pedestrian-only pathways that would not be represented in the
Drive-Time buffer tool. This concern is unlikely however to affect the overall analysis.
The next step in the process was to calculate the number of school aged children
who lived within each of the buffered regions adjacent to both open and closed schools.
A count of persons aged 5 to 18 was selected as the proxy for “school-aged children”
because it best served as a proxy for the number of students who attended elementary
school.
The map below features the drive-time buffers around neighborhood elementary schools
in the San Fernando Valley as they appeared in 1980 (stars), as well as the elementary
schools that closed after 1980 as black dots. The closed schools have an additional 1mile buffer (pink) around them. Block populations appear as pale pink circles on the map
in the background layer. The core of this analysis involved summing the count of schoolaged children living in each census block within one-half or one mile of both open and
closed schools. The results of the analysis are listed below.
The result of this statistical query showed that 48,248 children aged 5-17 years old lived
in a census block with a centroid point was less than one-half mile from a school that in
1980 that has subsequently been closed or turned into a magnet school since. Since there
were 1,476,542 school aged children in Los Angeles County in 1980, which represents
approximately 3.3% of children who would have perhaps been forced to ride to school
based on 1980 figures. Approximately 1,260,000 school-aged children lived within one
half mile of an open neighborhood school in Los Angeles County in 1980. That
represents roughly 76.25% of all school-aged children in the county at that time. By
12
2010, there were 1,929,615 school-aged children living in Los Angeles County.
1,476,951 of those children lived within a half mile of an open neighborhood school,
representing roughly 76.54% of all schoolchildren in Los Angeles County. Statistically,
this represents no statistical difference in the number of children living within a walkable
distance of an open, neighborhood public school in 2010 than there were in 1980 before
the program of school closings began. Distance does not appear to be an important
causal factor. Additional analysis is clearly necessary to understand why students are not
walking to school, at least in Los Angeles County.
Figure 3-0-1: Map of School Closures in the Western San Fernando Valley with Drive Time Buffers.
13
Chapter 4: Lomita, California as Case Study
Because the initial GIS based analysis did not suggest that distance was a significant
factor in the declining rates of walking to school, additional analysis was deemed
necessary. A case-study site in Lomita, California was chosen because of the availability
of data suggested this location as an ideal site for additional study. Lomita had also been
recently awarded a “Safe Routes to School” grant in order to develop safer and cleaner
environment around the schools to encourage children to start walking and biking, rather
than using personal or public transportation. A review of the grant revealed that one of
the reasons for the award was the lack of sidewalks and bike lanes schools. There were
also reported a number of missing traffic lights and poorly placed / insufficient traffic
signage, especially near intersections close to schools. The traffic volume and lack of
green routes, and medians were also noted in the grant award.
Lomita is located between West Carson (2.6 miles) and South Bay Cities (7.4 Miles) with
the longitude and latitude of (LONG: -118.316110 W) / (LAT: 33.793384 N). The City
of Lomita covers about1.911 square miles, and its elevation averages 29 M (95 feet).
According to the 2010 census, Lomita had a population of 20,256 with Whites and
Hispanics or Latinos having the highest numbers, respectively at 11,987 (59.2%) percent,
and 6,652 persons (32.8%). Other races included Native American, 2,923 (14.4%)
percent, and Pacific Islander, 2,680 (13.2%) percent. The socioeconomic divisions are
low-income students in the eastern district (Harbor and Lomita Blvd), while mid to highincome students lived in the western area (Palos Verdes). Furthermore, the 2010 census
stated that out of the 8,068 households, 2,479 (30.7%) have children under the age of 18.
14
Lomita schools are part of the Los Angeles Unified School District within Board District
Seven. Of the six schools in the City of Lomita, four of them are public schools, and the
rest of them are private schools or secondary schools. The primary schools are: Eshelman
Avenue Elementary school, and Lomita Math/Science Magnet (Kindergarten zoned only
1-5 magnet only). This study area focuses on the public schools within the City of
Lomita. All residents are zoned to Fleming Middle School as well as Narbonne High
School (in Los Angeles). The maps below display important landmarks within Lomita.
Figure 4-0-1: Map of Lomita's Census Block Group Boundaries and Schools
15
4.1 Lomita Field Observations
A common and useful part of many geographically informed analyses is field
observation. To help bolster understanding of the conditions shaping students’ and
parents’ decision regarding school transportation, it made sense to observe automotive
and pedestrian traffic near schools. In addition, it is important to observe the built
environment in order to make informed decisions about how to best measure walkability
in Lomita. To that end, several field excursions were made in 2014 during the hours
when students were in transit to and from school to observe automobile and pedestrian
traffic, as well as the condition of pedestrian pathways. A photographic record was made
of the site visits, and observations were recorded.
It was clear from site observations that areas near Lomita schools were not pedestrian
friendly. Many of the streets lacked sidewalks on one side or both sides of the streets
near schools. Even streets immediately adjacent to elementary schools were observed to
have poor sidewalk access for pedestrians. Children were repeatedly observed walking,
biking or riding scooters and skateboards in the middle of streets. Cars used to transport
children to school were repeatedly observed making U-turns in close proximity to student
pedestrians. These observations supported the data contained in the Safe Routes to
School grant award. Photos supporting these observations are included in the pages that
follow.
16
Figure 4-2: Major street in front of Lomita’s School needed medians, and traffic signs for preventing motorists from
making U-turns while students cross the street.
Figure 4-3: Lomita Street without sidewalks or one narrow sidewalk.
17
Figure 4-4: City of Lomita residential streets near schools without sidewalks
Figure 4-5: City of Lomita’s Street a cross street from Eshelman Elementary school without sidewalks
18
Figure 4-6: Streets by Eshelman Elementary school in the City of Lomita without sidewalk.
Figure 4-7: Students dropped off in the middle of the street in front of Narbonne High School
19
Figure 4-8: Students walk in street to get where sidewalks are missing.
Figure 4-9: No sidewalks encourage students to ride scooters in streets.
20
Figure 4-10: Narbonne High students walk in the middle of a street without sidewalks.
Figure 4-11: Students walk in a street where sidewalks are narrow
21
Figure 4-12: Unsafe and blocked sidewalks near a school in Lomita
Figure 4-13: A damaged sidewalk near Eshelman Elementary School.
22
4.2: Measuring Walkability in Lomita.
After taking into consideration observations from the field, information from the Lomita
grant and several prior research findings, it was determined that a model of walkability
could be developed for the City of Lomita to help characterize neighborhoods in Lomita
on the basis of their walkability. Such an analysis, conducted with GIS software not only
is capable of identifying areas where children are less likely to walk, but also providing a
map to help local government officials prioritize specific areas in the city for
improvement. Any measure of neighborhood walkability may potentially include a large
number of factors, but for this study, limited data availability suggest that three main
factors are viable considerations: sidewalk availability, traffic accident rate and crime
rates. Fortunately, these factors largely coincide with the research findings discovered in
the review of the literature.
4.2.1 Sidewalk Availability
One of the important factors in walkability is the availability of sidewalks. Under ideal
circumstances, each length of street would have two sidewalks flanking either side of the
street. The ratio would be 2:1. In other words, there should be at least two miles of
sidewalk to each mile of street. Field observations already indicated that some areas near
schools fell short of this ideal. In order to determine where the sidewalk to street ratio
falls short of this ideal, and where these ratios are worst, a GIS based analysis was
conducted.
Digital maps of Lomita’s street and sidewalk networks were obtained from the City of
Lomita. Each file was overlaid with a series of polygons to analyze the relative
abundance of streets in Lomita, especially near schools. In order to establish a baseline
23
measure, the entire length of Lomita’s sidewalk network was summed to get a total
length of 372, 866.63 feet. The entire street network was found to be 225,303.69 feet
long, which means the entire city has a sidewalk-to-street ratio of 1.655. This figure falls
well short of 2/1 or 2.0 ratio ideal. To provide context, a one mile Euclidean buffer was
placed around each school and the sidewalk and street networks ratios were recalculated.
Near the three schools under consideration, the ratio fell to 1.22, indicating that for every
feet of street, there was only 1.22 feet of sidewalk within one mile of the Lomita schools.
In other words, most streets had only one or no sidewalks in those areas around Lomita’s
schools. The process was repeated using a half-mile buffer zone. At this distance, the
ratio fell slightly to 1.2 sidewalk feet per street mile. For the sake of comparison, a few
other areas were analyzed. The ratio of the sidewalks to streets for the boundary region
with Palos Verdes located at south of city of Lomita was found to be 1.5. The ratio at
boundary with the City of Torrance was also found to be 1.5; for the boundary cities of
Carson and Harbor City were found to have ratios of 1.58 and 1.7 respectively.
The most important of the sidewalk availability calculations was made with respect to
census block groups. These polygons are small enough to represents neighborhoods and
have adequate data (unlike blocks) to create meaningful rate measurements. This final
component of the sidewalk availability measurement repeated the measuring process, and
the calculation of the sidewalk to street ratio, but within each block group. Rather than
clipping the sidewalk and street line files, a new shape file was created using a technique
called spatial join. Essentially the GIS software counted each line segment in both the
sidewalk and street layers, and summed the length in feet of each segment within the
boundaries of each census block group. The new shapefile map contained several new
24
columns, two of which contained the summed lengths of both sidewalks streets. An
additional column was created in which the ratio of sidewalks to street lengths was
calculated. From that column, a thematic map was created showing the variation of
sidewalk-to-street ratios across Lomita. The ratio of the block group with best sidewalkto-street ratio is 2.53; the worst area of town was under well under .05, meaning there
were hardly any sidewalks at all in these block groups.
25
Figure 4-14: Map of Lomita by Sidewalk Availability. Data Source: City of Lomita
26
4.2.2 Measuring Crime Rates
Fear of crime was another factor noted in previous research on school transportation
concerns, so it was determined that crime rates in Lomita would be included in an index
of walkability. Crime data for Lomita from the Los Angeles County Sherriff’s
Department for 2013 was downloaded from the Sherriff Departments’ website. Each
crime was reported with an identifying address which was geocoded with the address
mapping tool in ArcMap 10.x. A variety of crimes were eliminated from consideration,
including bad check writing, domestic violence disputes, most misdemeanors and other
items in the database that were considered unlikely to raise concern among parents of
school children enough to impact their school transportation decisions. Included in the
database were robbery, rape, burglary, aggravated assault, graffiti, and motor-vehicle
theft. Once the individual crime points were placed on the map, a count of crimes per
census block group was derived using the spatial join tool in the GIS software. The
crime rate per block group was calculated by dividing the number of persons per block by
the number of crimes. The ratio was multiplied by 10,000 to get a crime per 10,000
persons crime rate. A thematic map of this rate was made and appears below.
27
Figure 4-15: Map of Lomita by Crimes per 1,000 Persons. Source: LA County Sherriff.
28
4.2.3 Measuring Traffic Accident Density
Because prior research indicated that traffic accidents and pedestrian safety issues were
an important factor undermining the walkability for school children, a traffic accident
measure was included in the walkability metric developed for this study. Using the same
database provided by the Los County Sherriff’s Department website, a map of accident
locations was created. The point map of accidents was joined to the census blockgroup
polygon map of Lomita to calculate the number of accidents per block group. The total
number of accidents was then divided by the total area in square miles to get a ratio of
accidents per unit of area measured. A thematic map of this accident density appears
below.
29
Figure 4-16: Map of Traffic Accidents per Square Mile, Lomita, California. Source: LA County Sherriff
30
4.2.4 Walkability Index
In order to get a better picture of the overall walkability of neighborhoods in Lomita, the
maps indicating sidewalk availability, crime rate and accident density were combined
into a single map displaying a walkability index for the City of Lomita.
The walkability index was created by assigning a rank from one to five for each of the
three metrics. In each instance, a value of one (1) was assigned to block groups in the
lowest quintile of each map. For example, the block groups with the poorest sidewalk
availability were assigned a value of one. High crime and dense accident areas were
likewise assigned a value of one. Block groups with relatively good sidewalk access, low
crime rates and low accident densities were assigned a value of five (5) to indicate good,
or at least better, walkability. Finally, the ranking scores from each of the three
walkability measures were summed to generate a walkability index score. The minimum
score was three (3) and the maximum score was 15.
Several block groups scored well on the index, getting a maximum score of five (5) on
each metric and therefore an overall score of 15. Unfortunately, for students and parents
living in Lomita, each of the schools was located in, or on the border of a block group
with a walkability index of seven (7) or less. Lomita Elementary was in the block group
with the overall worst walkability score. Fleming Middle and Eshelman Elementary
were in neighborhoods with scores of six and seven respectively. No schools were in a
neighborhood that had ideal walkability characteristics.
31
Figure 4-17: Walkability Index Scores for Lomita by Census Block Group
32
Chapter 5: Conclusions
This study has uncovered a number of useful findings. First, it appears that although
there have been a number of close closings since the early 1980s nationwide, it may not
be affecting the rate at which schoolchildren walk to school. In Los Angeles County over
40,000 students live in a short distance of a closed school, but the overall percentage of
school-aged children living within one-half mile of an open neighborhood school has
actually increased since 1980. This suggests that distance may not be an important factor
in the sharp decline in the percentage of children who walk to school nationwide. There
may be locations or school districts where distance may be a significant factor, but in Los
Angeles County this would not seem to be the case.
Second, this study found that at least in Lomita, California, poor walkability
characteristics of neighborhoods hosting a public, neighborhood school may be
responsible for the low percentage of children who walk to school. This study found that
each public school in Lomita, including the magnet school was located in a neighborhood
that had poor walkability characteristics. In particular, these neighborhoods had sidewalk
accessibility well below the city wide average, and far below the ideal metric parents
presumably consider when deciding to allow their children to walk to school. Crime
rates and traffic accident densities were also generally above the citywide averages, and
are likely to contribute to Lomita parents’ decision to not allow students to walk to
school.
A number of limitations undermine the effectiveness of this study. The obvious
limitations are typical for any study; the scope of the data included only a two locations,
33
Los Angeles County and the City of Lomita. Neither location may be typical of
conditions that exist elsewhere. There is an unknown chance that the impact of school
closures on the number of children living within a walkable distance in Los Angeles
County is unusual. Lomita may very well not be typical of other cities even in Los
Angeles, let alone other parts of the United States. There was some reason to believe that
at least in terms of sidewalk accessibility, Lomita is substandard as a whole. Perhaps it is
deserving of the grant it was awarded to improve walkability problems.
Perhaps more importantly is that the metrics used to measure walkability in Lomita do
not truly figure into the decisions parents make regarding school transportation. Though
sidewalk access is clearly a problem, the overall crime and accident rates have dropped in
the United States. It is assumed, since these trends have been widely reported in the news
media, that parents are aware that streets are safer in the last few years than they have
been in several decades. Rather than measuring actual crime and accident rates, future
studies should focus on perceptions of danger. It is very well possible that parents simply
report fear of crime and pedestrian accidents as reasons for driving their student to
school, rather than admitting that they prefer taking their kids to school for other reasons.
5.1 Policy Implications and Recommendations
What is quite clear is that walking and biking, even if it is only to school and back is a
healthy alternative to riding in a car or bus. It would also appear, according to
conclusions made by other researchers that the built environment has a big influence on
physical activity, which in turn has a protective effect against obesity and a positive
influence on public health (Berrigan and Troiano, 2002). Researchers who analyzed city
and state level data from United States and from 15 countries to study the relationship
34
between “active travel” bicycling or walking rather than driving and physical activity,
obesity and diabetes (Bauman, et al., 1999). They found that more than half of the
difference in obesity rates, among countries is linked to waking and cycling rates.
Compounding the health risk is the fact that motorized public and private transportation
creates air pollution, which can lead to many health problems such as lung cancer, heart
disease, and asthma (Atkinson et al., 2005). Data also indicates that physical activity
may improve academic routine and awareness in youth (Appatova el at., 2008).
There are a number of steps that can be taken to improve the walkability of school zones
in the United States. Many of the policy recommendations suggested by this study are in
line with the priorities of the Safe Routes to School program. Steps must be taken to
alleviate both the real and perceived pedestrian hazards associated with walking to
school. Reducing the number of speeding cars is a top priority. Enforcing speed limits
and building speed calming devices such as speed humps is a critical first step. Local
governments should also install solar-powered radar systems that display automotive
speeds to remind drivers to slow down. One study concluded that speed humps reduced
by 53-60 percent the number of injuries or deaths among children struck by an
automobile around schools (Tester et al, 2004). During the enforcement, it has been
observed that children’s safety would be enhanced if flashing lights and additional
signage were installed to notify drivers of their speed (Saelens et al. 2003).
For some locations, including Lomita, building more and better sidewalks near schools is
important. Ideally, sidewalks should near schools feature a buffer between traffic and the
sidewalks on which children are traveling (Byoung-Suk Kweon, 2008). Bike paths are
also a recommended feature, especially dedicated bike lanes that separate cyclists safely
35
from motorized traffic. These so-called green streets increase pedestrian safety around
schools for children to walk and bike to and from school (Zucca et al. 2008).
Other efforts are also likely to improve pedestrian safety and encourage students to walk
or bike to school. Pedestrian crossing should be clearly marked, perhaps with broad
stenciled crosswalk marking. Drop off and pick up zones can be designed to reduce the
chance of pedestrian-vehicle interaction. Schools should actively police the behavior of
parents in these zones. Schools should encourage walking. According to a survey in
1999, 7% percent of schools have policies that restrict children from walking or biking to
school (Kerr J, Rosenberg D et al., 2006). In urban areas, these policies should be
seriously examined to ensure that they are serving the long-term interests of students.
Instead, some schools have implemented a program called “Wednesday’s Walk” which is
intended to demonstrate to parents and students that children can walk and bike to school
safely. Policies such as this can be tried at many more schools.
Congress provided approximately one billion dollars for Safe Routes to Schools since
2005 (Watson & Dannenberg 2008). This is probably money well spent. Walking can
lead to a reduction in the health care costs associated with obesity and cardiovascular
diseases (Skelton & Rudolph 2007). For school districts and families, there significant
cost savings (Amram et al. 2011). The US government may realize a good return on
investment if the program actually leads to improved health outcomes for children. The
vast majority of this funding was earmarked for infrastructure improvements near
schools, such as making or repairing sidewalks, paths, speed humps, crosswalks, school
zone signage, and for traffic calming. However, the remaining funds were distributed to
programs that focused on teaching children about traffic safety around schools and
36
encouraging them to take part in healthy activities. An example of a project funded by
this program would be the addition of sidewalks where none currently exists, which has
been proven to reduce the risk of pedestrian versus vehicle accidents by 50 percent
(Appatova et al. 2008).
The City of Lomita sought out and was awarded a Safe Route to School grant. The city
of Lomita participated in the Safe Route to School in 2008 and the Federal government
helped the city to fund building new sidewalks, crosswalks, as well as adding many new
signs for the area especially near the schools, as needed. It still has a long way to go.
Other locales would be wise to seek funding from the Safe Routes to School funds in
order to support projects that make walking and biking to schools healthier, safer, and
easier, as well as more enjoyable for all the students and their families (Lee, Burgeson et
al., 2007).
37
References
Amram, Ofer, Rebecca Abernethy, Michael Brauer, Hugh Davies and Ryan W Allen.
“Proximity of Public elementary schools to major roads in Canadian urban areas. “International
Journal of Health Geographics 10, 68 (2011): 1-11. Accessed: February 28, 2011.
Atkinson, J.L., Sallis, J.F., Saelens, B.E., Cain, K.L. and Black, J.B. 2005. The association of
neighborhood design and recreational environments with physical activity. Accessed:
February 28, 2011.
Bassett DR Jr. Validity and reliability issues in objective monitoring of physical activity.Res Q
Exerc Sport 71(2):30-36, 2000. Accessed: March 2, 2011.
Berrigan, D., and Troiano, R.P. 2002. The association between urban form and physical activity
in U.S. adults. American Journal of Preventive Medicine, 23(2), 74-79. Accessed: March
2, 2011.
Boarnet MG, Anderson CL, Day K, McMillan T, Alfonzo M. Evaluation of the California Safe
Routes to School legislation: urban form changes and children’s active transportation to
school. AM J Prev Med 2005; 28:134-40? Accessed: March 5, 2011.
Cervero R., and Duncan M. 2003. Walking, bicycling, and urban landscapes: Evidence from the
San Francisco Bay area. American Journal of Public Health, 93(9): 1478-1483.
Accessed: March 7, 2011.
Clifton KJ, Livi Smith AD, Rodriguez D. The development and Testing of an Audit for the
Pedestrian Environment. Landsc Urban Plan 2007; 80:95-110. Accessed: March 2, 2011.
Day K. Active living and social justice; planning for physical activity in Low-income, black, and
Latino communities. J Am Plann Asso 2006; 72:88 -99. Accessed: March 15, 2011.
Epstein L, Saelens B, Myers M, and Vito D. 1997. Effects of decreasing sedentary behaviors on
activity choice in obese children. Health Psychology. 16(2): 107-113. Accessed: March
20, 2011.
Estabrooks PA, Lee RE, Gyurcsik NC. Resources for physical activity participation: Does
availability and accessibility differ by neighborhood socioeconomic status? Ann Behav
Med 2003; 25:100-4. Accessed: March 20, 2011.
Ewing R, Forinash CV, Schroeer W. Neighborhood schools and sidewalk connections: What are
the impacts on travel mode choice and vehicle emissions? Transport Res News 2005;
237:4-10. Accessed: March 25, 2011.
Ewing R., W. Schroeer, and W. Greene. School location and student travel: Analysis of factors
affecting mode choice. Transportation Research Record 2004; 1895:5-63. Accessed:
March 25, 2011 and Accessed: June 25, 2014.
38
Frank L, and Engelke P. 2001. The built environment and human activity patterns: Exploring the
impacts of urban from on public health. Journal of Planning Literature, 16(2): 202-218.
Accessed: March 25, 2011.
Fulton JE, Shisler JL, Yore MM, Caspersen CJ. Active transportation to school: findings from a
national survey. Res Q Exerc Sport 2005; 76:352-7. Accessed: April 1, 2011.
Gehring, Ulrike, Alet H. Wijga, Michael Brauer, Paul Fischer, Johan C. de Jongste, Marjan
Kerkhof, Marieke Oldenwening, Henriette A. Smit and Bert Brunekreef. “Traffic-related
Air Pollution and the Development of Asthma and Allergies during the first 8 Years of
Life.” American Journal of Respiratory and Critical Care Medicine 181 (2010): 559-603.
Accessed: April 1, 2011.
Keppel K, Pamuk E, Lynch J, et al. Methodological issues in measuring health disparities. Vital
Health Stat 2005; 2:1-16. Accessed: April 5, 2011.
Kerr J, Rosenberg D, and Sallis JF, et al. Active commuting to school: associations with
environment and parental concerns. Med Sci Sports Exerc 2006; 38:787-94. Accessed:
April 5, 2011.
Lawrence, Bruce, Soma Bhattacharya, Eduward Zaloshnja, Paul Jones, Ted Miller, Phaedra
corso and Claudia Steniner. “Medical and Work Loss Cost Estimation Methods for the
WISQUARS Cost of Injury Module.” Calverton, MD: Pacific Institute for Research and
Evaluation (PIRE), September 2009. Accessed: April 8, 2011.
Lee C, Moudon AV. Physical activity and environmental research in health field: Implications
for urban and transportation planning practice and research. J Plann Lit 2004; 19:147-82.
Accessed: April 8, 2011.
Lee S, Burgeson C, Fulton J, Spain C, physical Education and Physical Activity: Results from
the School Health Policies and Programs Study 2006. Journal of School Health. 2007
Oct; 77 (8):435-463-304. Available:
http://www.ashaweb.org/files/public/JOSH_1007/josh_77_8_lee_p_435.pdf
Accessed: April 8, 2011.
Liu GC and Hannon T. 2005. Reasons for the prevalence of childhood obesity. Genetic
Predisposition and Environmental Influences. The Endocrinologist, 15(1): 49-55.
Accessed: April 8, 2011.
Martin S, Carison S. Barriers to children walking to or from school United States, 2004.
(Reprinted from MMWR Morb Mortal Wkly Rep 2005; 54:94952). JAMA 2005;
294:2160-2. Accessed: April 10, 2011.
McDonald, Noreen, Austin Brown, Lauren Marchetti and Margo Pedroso. “U.S. School Travel
2009: An Assessment of Trends. “American Journal of Preventive Medicine 41, 2 (2011):
146-151. Accessed: April 10, 2011.
39
McMillan TE. Walking and urban form: modeling and testing parental decisions about children’s
travel. [Dissertation] Irvine (CA): university of California, 2003. Accessed: April 12,
2011.
Morris, J, Wang, F, & Lilja (2001). School Children’s Travel Patterns: A Look Back and a Way
Forward. Transport Engineering in Australia, Vol. 7, No. ½, 2001: 15-25. Available:
http://www.patrec.org/web_docs/atrf/papers/2001/1405_Morris,%20Wang%20&%20Lilj
a%20%282001%29.pdf. Accessed: April 19, 2011.
Norman G, Nutter S, Ryan S, Sallis J, Calfas K and Patrick K. 2006. Community design and
access to recreational facilities as correlates of adolescent physical activity and body
mass index. Journal of Physical Activity and Health, 3(S1): S118 - S128. Accessed: April
18, 2011.
Ogden CL, Flegal KM, Carroll MD, Johnson GL. Prevalence and trends in overweight among
U.S. children and adolescents, 1999-2000, JAMA 2002; 288:1728-32.
Pedestrians: 2009 Data “and “Bicyclists and Other Cyclists: 2009 Data.” Accessed: April
18, 2011.
Washington, DC: National Highway Traffic Safety Administration, 2009. Available at
http://www.nrd.nhtsa.dot.gov/Pubs/811394.pdf . Accessed: April 18, 2011.
Physical Activity for Everyone: Recommendations. Centers for Disease Control and Prevention.
2007. Accessed 2007 May; Available at
http://www.cdc.gov/nccdphp/dnpa/physical/recommendations/index.htm. Accessed:
April 25, 2011.
Pollack, K. M., C. Kercher, et al. 2010. “Toward environments and policies that promote injuryfree active living-it wouldn’t hurt”. Health & Place 18(1): 106-114. Accessed: May 10,
2012. Accessed: April 25, 2011.
Rosenbaum, David (January, 8 1986). Regan insists budget cut are way to reduce deficit. “The
New York Times”. Retrieved August 21, 2008. Accessed: June 26, 2014.
Saelens BE, Sallis JF and Frank LD. 2003. Environmental correlates of walking and cycling:
Findings from the transportation, urban design, and planning literatures. Annals of
Behavioral Medicine, 25(2):80-91. Accessed: April 28, 2011.
Serdula M, Ivery D, Coates R, Freedman D, Williamson D, Byers T. Do obese children become
obese adults? A review of the literature. Preventive Medicine. 1993 March; 22 (2):16777. Accessed: May 2, 2011.
Serdula MK, Williamson DF, Anda RF, Levy A, Heaton A, Byers T. Weight control practices in
adults. Am J Public Health. 1992; 82:1251-1257. Accessed: May 2, 2011.
Schlossberg M, Greene J. Phillips PP, Johnson B. Parker B. School trips: effects of urban form
and distance on travel mode. J Am Plann Assoc 2006; 72:337-46. Accessed: May 2, 2011.
40
Skelton JA C Rudolph. “Overweight and obesity” in RM Kliegman et al., eds., Nelson Textbook
of Pediatrics, 18th ed. Philadelphia: Saunders Elsevier, 2007, p. 232-242: Accessed: May
2, 2011.
The National Center for Safe routes to School (2011). How Children Get to School: School
Travel Pattern from 1962 to 2009.Accessed April 12, 2012. Available:
http://saferoutesinfo.org/sites/default/files/resources/NHTS_school_travel_report_2011_0.pdf.
Accessed: May 2, 2011.
U.S. Centers for Disease control and Prevention. Barriers to Children Walking to or from School
United States 2004, Morbidity and Morbidity Weekly Report September 30, 2005.
Available: http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5438a2.html. Accessed:
March 23, 2011.
U. S. Department of Health and Human Services. Physical activity guidelines advisory
committee report. Washington, DC: U.S. Department of Health and Human Services,
2008. Available: http://www.health.gov/PAGuidelines/Report/. Accessed: February 1,
2011.
Watson M. and Dannenberg A. “Investment in Safe Routes to School Projects: Public Health
Benefits for the Larger Community. “Preventing Chronic Disease, 5(3): A90, July 2008.
Accessed: April 20, 2012.
Zucca, A., Sharifi, A. M., & Fabbri, A. G. Application of spatial multi-criteria analysis to site
selection for a local park: A case study in the Bergamo Province, Italy. Journal of
Environmental Management, 88(4), 752-769 (2008). Accessed: April 20, 2012.
Zuurbier, Moniek, Gerard Hoek, Marieke Oldenwening, Virissa Lenters, Kees Meliefste, Peter
van den hazel and Bert Brunekreef. “Commuters’ Exposure to Particulate Matter Air
Pollution is affected by Transport, Fuel Type, and Route.” Environmental Health
Perspectives 118, 6 (2010): 783-789. Accessed: March 23, 2011.
41