AN ANALYSIS OF URBAN AMENITY CLUSTERS IN LOS ANGELES by Samuel Glendening Krueger

179 Pages·2012·6.14 MB·English

DELIMITING THE POSTMODERN URBAN CENTER:
AN ANALYSIS OF URBAN AMENITY CLUSTERS IN LOS ANGELES

by

Samuel Glendening Krueger

________________________________________________________________________

A Thesis Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
(GEOGRAPHIC INFORMATION SCIENCE AND TECHNOLOGY)

August 2012

Copyright 2012 Samuel Glendening Krueger
TABLE OF CONTENTS

List of Tables iii

List of Figures iv

Abbreviations ix

Abstract x

Chapter 1: Introduction 1
1.1 A New Method for Delimiting City Centers 1
1.2 Delimiting the Center of Los Angeles 2

Chapter 2: Context 3
2.1 Existing methods for delimiting city centers 3
2.2 New ways of seeing centrality 15
2.3 A new concept for delimiting city centers 23
2.4 Popular concepts regarding the center of Los Angeles 29
2.5 Research into the center of Los Angeles 32
2.6 The Wilshire/Santa Monica Corridor: a hypothesis 42

Chapter 3: Data 48
3.1 Esri Business Analyst 48
3.2 North American Industry Classification System (NAICS) 50
3.3 Directory of Major Malls (DMM) 57

Chapter 4: Methodology 60
4.1 Methodological Considerations 60
4.2 Analysis Process 78

Chapter 5: Discussion 107
5.1 Results 107
5.2 Questions of precision 115
5.3 A more detailed analysis of the central areas 120
5.4 Implications for delimiting city centers 124
5.5 Implications for Los Angeles 128
5.6 The Wilshire/Santa Monica Corridor 131
5.7 Further research 157

References 165

ii
LIST OF TABLES

Table 1: Amenity categories with NAICS codes and descriptions. 55

Table 2: Attributes of each analysis array. 76

Table 3: Attributes of the union array. 77

Table 4: Hierarchy of central neighborhoods in the Wilshire/Santa 143
Monica Corridor.

Table 5: Hierarchy of central nodes in the Wilshire/Santa Monica 149
Corridor.

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LIST OF FIGURES

Figure 1: Giuliano & Redfearn’s (2007, p.2946, fig. 3c) map of ranked 8
‘10-10’ employment centers in Los Angeles.

Figure 2: Redfearn’s (2007, p.533, fig.9) map of employment centers in 8
Los Angeles.

Figure 3: Greene’s (2008, p.141, fig. 1) map of ranked employment 9
centers in Los Angeles.

Figure 4: Author’s photograph of the cityscape along the base of the 14
Santa Monica Mountains from the Pacific Ocean to
Downtown Los Angeles; photographed from the Kenneth
Hahn State Recreation Area in the Baldwin Hills, February
20, 2011.

Figure 5: Greene’s (2008, p.152, fig. 5) map of the Los Angeles HAZ. 20

Figure 6: The popularly-conceived essential places of Los Angeles in 31
mutual proximity along the base of the Santa Monica
Mountains.

Figure 7: Greene’s (2008, p.144, fig. 2) map of the Los Angeles CBD. 34

Figure 8: Giuliano & Small’s (1991, p.167, fig. 1) map of ranked ‘10- 36
10’ employment centers in Los Angeles.

Figure 9: Giuliano & Redfearn’s (2007, p.2951, fig. 4c) map of ranked 36
‘20-20’ employment centers in Los Angeles.

Figure 10: Redfearn’s (2007, p.526, fig. 2) employment density map of 37
Los Angeles.

Figure 11: Gordon & Richardson’s (1996, p.292, fig. 1) map of Los 40
Angles activity centers.

Figure 12: Garreau’s (1991, p.262) map of Los Angeles area Edge 41
Cities.

Figure 13: Hypothetical location of the center of Los Angeles. 43

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Figure 14: Detailed extents of the hypothetical center of Los Angeles. 44

Figure 15: Expected center of Chicago. 62

Figure 16: Expected center of New York. 62

Figure 17: Varied cell sizes for capturing processes operating at 71
multiple scales.

Figure 18: Offset pairs of cell arrays to aggregate the underlying data in 73
different ways.

Figure 19: All six analysis arrays, intersected. 74

Figure 20: The union array, made from the intersected analysis arrays. 75

Figure 21: Urban areas in San Bernardino and Riverside counties. 84

Figure 22: Study area and analysis area creation process. 84

Figure 23: Chicago initial study area and analysis area. 84

Figure 24: New York initial study area and analysis area. 85

Figure 25: Los Angeles initial study area and analysis area. 86

Figure 26: Analysis array creation process. 88

Figure 27: Example cell arrays over Los Angeles. 88

Figure 28: Amenity point collection process. 89

Figure 29: Full-Service restaurants in central Los Angeles. 90

Figure 30: Amenity point aggregation process. 92

Figure 31: Los Angeles restaurants aggregated into the 2km analysis 92
array A with resulting cluster delineation.

Figure 32: Los Angeles restaurants aggregated into the 2km analysis 93
array B with resulting cluster delineation.

Figure 33: Los Angeles restaurants aggregated into the 5km analysis 94
array A with resulting cluster delineation.
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Figure 34: Los Angeles restaurants aggregated into the 5km analysis 95
array B with resulting cluster delineation.

Figure 35: Los Angeles restaurants aggregated into the 13km analysis 96
array A with resulting cluster delineation.

Figure 36: Los Angeles restaurants aggregated into the 13km analysis 97
array B with resulting cluster delineation.

Figure 37: Amenity category count calculation process. 98

Figure 38: Amenity cluster identification process. 99

Figure 39: The ‘intersect’ and ‘contain’ spatial selection methods. 100

Figure 40: Cluster value assignment process. 101

Figure 41: Cluster value core and fringe assignments. 101

Figure 42: Union array creation process. 102

Figure 43: Cluster score calculation process. 103

Figure 44: Restaurant cluster scores in central Los Angeles. 103

Figure 45: Centrality score calculation process. 104

Figure 46: Cartographic visualization process. 106

Figure 47: Chicago centrality score under the union analysis array 108
across the entire analysis extent.

Figure 48: Chicago centrality score under the union analysis array in 109
the central area.

Figure 49: New York centrality score under the union analysis array 110
across the entire analysis extent.

Figure 50: New York centrality score under the union analysis array in 111
the central area.

Figure 51: Los Angeles centrality score under the union analysis array 112
across the entire analysis extent.
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Figure 52: Los Angeles centrality score under the union analysis array 113
in the central area.

Figure 53: Los Angeles centrality score under the union analysis array 114
in the main region of high scores.

Figure 54: Los Angeles centrality score under the 2km analysis cells in 118
the main region of high scores.

Figure 55: Los Angeles 100% centrality score areas under each of the 120
three analysis cell scales.

Figure 56: Chicago centrality score under the 0.8km analysis cells. 122

Figure 57: New York centrality score under the 0.8km analysis cells. 123

Figure 58: Los Angeles centrality score under the 0.8km analysis cells. 124

Figure 59: Los Angeles centrality score under the 0.8 analysis cells, 132
overlaid on the 100% centrality score areas from each of
the three larger analysis cell scales.

Figure 60: The Wilshire/Santa Monica Corridor: Los Angeles centrality 134
score under the 0.8km analysis cells in the area attaining
100% centrality scores under all three larger-scale
analyses.

Figure 61: The Wilshire/Santa Monica Corridor (cartographic 137
depiction): centrality score classes from Figure 60 buffered
outwards by 0.4km each.

Figure 62: Comparison of the Wilshire/Santa Monica Corridor 139
(cartographic depiction) with Manhattan Island.

Figure 63: Primary Los Angeles tourism destinations in and around the 141
Wilshire/Santa Monica Corridor.

Figure 64: Hierarchy of central neighborhoods in the Wilshire/Santa 145
Monica Corridor.

Figure 65: Hierarchy of central nodes in the Wilshire/Santa Monica 149
Corridor.

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Figure 66: Looking west into the financial district on 7th Street from 153
just east of Broadway, Los Angeles (author’s photograph,
May 13, 2012).

Figure 67: Looking south on Broadway towards 6th and 7th Streets 154
from 5th Street, Los Angeles (author’s photograph, May
13, 2012).

Figure 68: A major break in east-west street grid continuity at Century 156
City.

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ABBREVIATIONS

CBD: Central Business District
CSA: Combined Statistical Area
DMM: Directory of Major Malls
E/R: Employment to Residents ratio
GCS: Geographic Coordinate System
GIS: Geographic Information Science
GLA: Gross Leasable Area
HAZ: High Amenity Zone
ICSC: International Council of Shopping Centers
LISA: Local Indicators of Spatial Association
MAUP: Modifiable Areal Unit Problem
MSA: Metropolitan Statistical Area
NAFTA: North American Free Trade Agreement
NAICS: North American Industry Classification System
OMB: Office of Management and Budget
SIC: Standard Industrial Classification
UA: Urban Area
UC: Urban Cluster
UTM: Universal Transverse Mercator
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ABSTRACT

An analysis of urban morphology in the Los Angeles metropolitan area was
conducted. Specifically, Local Indicators of Spatial Association (LISA) were used to
identify clusters of different types of urban amenities. A centrality score was calculated
for every location based on the number of spatially coincident clusters, which was used to
delimit the central place.
The methodology, which was validated in the Chicago and New York
metropolitan areas, employed multiple regular hexagonal arrays into which amenity
location points were aggregated. These arrays, whose results were combined for a final
analysis output, mitigated against the Modifiable Areal Unit Problem (MAUP) and
revealed urban structures operating at multiple scales.
Prevailing methods for delimiting urban centrality tend to reduce urban place to a
monetary space by focusing on employment centers, commuting patterns, or ‘central’
land uses in order to identify a downtown or a Central Business District (CBD). This
study elevates the experience of place within urban structure to identify an ambiguously
bounded and internally inconsistent central place: a postmodern urban center.
The study reveals both polycentrism and a strong core center in Los Angeles. The
core center, called the Wilshire/Santa Monica Corridor, is delimited in detail.
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