Elijah Knaap

San Diego State University, Geography, Associate Director, Center for Open Geographical Science

University of California, Riverside, Public Policy, Post-Doc

University of California, Riverside, Center for Geospatial Sciences, Associate Director

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Noel B. Salazar

KU Leuven

Muqtedar Khan

University of Delaware

Mariya Ivancheva

University of Strathclyde, Glasgow

Julita Vassileva

University of Saskatchewan

Alexey Belousov

Russian State University for the Humanities

Naim Kapucu

University of Central Florida

Bob Jessop

Lancaster University

Jon Beasley-Murray

University of British Columbia

Zrinka Mileusnić

University of Primorska

David Seamon

Kansas State University

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Papers by Elijah Knaap

The Legacy of Redlining: A Spatial Dynamics Perspective

International Regional Science Review, Aug 7, 2022

This paper investigates the long-term impacts of the federal Home Owners’ Loan Corporation (HOLC)... more This paper investigates the long-term impacts of the federal Home Owners’ Loan Corporation (HOLC) mortgage risk assessment maps on the spatial dynamics of recent income and racial distributions in California metropolitan areas over the 1990-2010 period. We combine historical HOLC boundaries with modern Census tract data and apply recently developed methods of spatial distribution dynamics to examine if legacy impacts are reflected in recent urban dynamics. Cities with HOLC assessments are found to have higher levels of isolation segregation than the non-HOLC group, but no difference in unevenness segregation between the two groups of cities are found. We find no difference in income or racial and ethnic distributional dynamics between the two groups of cities over the period. At the intra-urban scale, we find that the intersectionality of residing in a C or D graded tract that is also a low-income tract falls predominately upon the minority populations in these eight HOLC cities. Our findings indicate that neighborhoods with poor housing markets and high minority concentrations rarely experience a dramatic change in either their racial and ethnic or socioeconomic compositions—and that negative externalities (e.g. lower home prices and greater segregation levels) emanate from these neighborhoods, with inertia spilling over into nearby zones.

American Community Survey (ACS) Data Uncertainty and the Analysis of Segregation Dynamics

Population Research and Policy Review, Jan 28, 2023

American Community Survey (ACS) data have become the workhorse for the empirical analysis of segr... more American Community Survey (ACS) data have become the workhorse for the empirical analysis of segregation in the U.S.A. during the past decade. The increased frequency the ACS offers over the 10-year Census, which is the main reason for its popularity, comes with an increased level of uncertainty in the published estimates due to the reduced sampling ratio of ACS (1:40 households) relative to the Census (1:6 households). This paper introduces a new approach to integrate ACS data uncertainty into the analysis of segregation. Our method relies on variance replicate estimates for the 5-year ACS and advances over existing approaches by explicitly taking into account the covariance between ACS estimates when developing sampling distributions for segregation indices. We illustrate our approach with a study of comparative segregation dynamics for 29 metropolitan statistical areas in California, using the 2010-2014 and 2015-2019. Our methods yield different results than the simulation technique described by Napierala and Denton (Demography 54(1):285-309, 2017). Taking the ACS estimate covariance into account yields larger error margins than those generated with the simulated approach when the number of census tracts is large and minority percentage is low, and the converse is true when the number of census tracts is small and minority percentage is high.

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Reducing racial segregation of public school districts

Socio-economic Planning Sciences, Dec 1, 2022

geosnap: The Geospatial Neighborhood Analysis Package

this is a quick release to generate a zenodo DOI

spopt: a python package for solving spatial optimization problems in PySAL

Journal of open source software, Jun 14, 2022

Spatial optimization is a major spatial analytical tool in management and planning, the significa... more Spatial optimization is a major spatial analytical tool in management and planning, the significance of which cannot be overstated. Spatial optimization models play an important role in designing and managing effective and efficient service systems such as transportation, education, public health, environmental protection, and commercial investment among others. To this end, spopt (spatial optimization) is under active development for the inclusion of newly proposed models and methods for regionalization, facility location, and transportation-oriented solutions (Feng et al., 2021). Spopt is a submodule in the open-source spatial analysis library PySAL (Python Spatial Analysis Library) founded by Dr.

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American Community Survey (ACS) Data Uncertainty and the Analysis of Segregation Dynamics

Population Research and Policy Review

American Community Survey (ACS) data have become the workhorse for the empirical analysis of segr... more American Community Survey (ACS) data have become the workhorse for the empirical analysis of segregation in the U.S.A. during the past decade. The increased frequency the ACS offers over the 10-year Census, which is the main reason for its popularity, comes with an increased level of uncertainty in the published estimates due to the reduced sampling ratio of ACS (1:40 households) relative to the Census (1:6 households). This paper introduces a new approach to integrate ACS data uncertainty into the analysis of segregation. Our method relies on variance replicate estimates for the 5-year ACS and advances over existing approaches by explicitly taking into account the covariance between ACS estimates when developing sampling distributions for segregation indices. We illustrate our approach with a study of comparative segregation dynamics for 29 metropolitan statistical areas in California, using the 2010–2014 and 2015–2019. Our methods yield different results than the simulation techni...

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Comparative Spatial Segregation Analytics

Spatial Demography

All of the segregation indexes have in common the assumption that segregation can be measured wit... more

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Reducing racial segregation of public school districts

Socio-Economic Planning Sciences

The Legacy of Redlining: A Spatial Dynamics Perspective

International Regional Science Review

spopt: a python package for solving spatial optimization problems in PySAL

Journal of Open Source Software

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ThePySALEcosystem: Philosophy and Implementation

Geographical Analysis, 2021

PySAL is a library for geocomputation and spatial data science. Written in Python, the library ha... more PySAL is a library for geocomputation and spatial data science. Written in Python, the library has a long history of supporting novel scholarship and broadening methodological impacts far afield of academic work. Recently, many new techniques, methods of analyses, and development modes have been implemented, making the library much larger and more encompassing than that previously discussed in the literature. As such, we provide an introduction to the library as it stands now, as well as the scientific and conceptual underpinnings of its core set of components. Finally, we provide a prospective look at the library's future evolution.

pysal/segregation: Segregation Analysis, Inference, and Decomposition

This is a minor release, although some important bugs were fixed and closed. We think that this i... more This is a minor release, although some important bugs were fixed and closed. We think that this is a better suit for the PySAL release of July, 2019. Changes Version 1.1.1 (2019-07-19) We closed a total of 56 issues (enhancements and bug fixes) through 22 pull requests, since our last release on 2019-07-01. Issues Closed absolute concentration values not matching with other open-source options? (#43) Concentration indexes rank fix (#118) remove W from importings in spatial_indexes (#117) consider surface based S (#102) Adds SpatialMinMax index based on Sullivan and Wong (2007) (#116) add robust and informative condition for large magnitude projections (tests only off-diagonal) (#113) MinMaxS (#115) spelling (#114) consider tqdm instead of print statements for simulations (#99) add DOI (#32) Building Error (after tqdm inclusion?) (#110) [WIP] add libcfitsio-dev in travis.yml (#112) enh: add libcfitsio.so.5 in travis.yml following https://github.com/cypress-io/cypress/issues/4069#issu...

geosnap: The Geospatial Neighborhood Analysis Package

this is a quick release to generate a zenodo DOI

Driving to Opportunities: Voucher Users, Cars, and Movement to Sustainable Neighborhoods

AbstractTenant-based rental vouchers have expanded housing choice for millions of low-income hous... more AbstractTenant-based rental vouchers have expanded housing choice for millions of low-income households, yet assisted households still face hurdles when trying to secure housing in high-opportunity neighborhoods with desirable economic, social, and environmental characteristics. Although inadequate transportation is arguably one of the most important hurdles to securing housing in high-opportunity neighborhoods, existing studies of voucher users' location choices have not yet explored the connections between transportation access and residential location outcomes. This article discusses the results from a recent study that attempts to close that gap. Our study draws on data from the Moving to Opportunity for Fair Housing demonstration program and the Welfare-to-Work Voucher Program, two residential mobility initiatives that randomly assigned rental vouchers to low-income households seeking housing assistance. Using a variety of approaches-including cluster analysis, bivariate co...

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Driving to Opportunity: Understanding the Links among Transportation Access, Residential Outcomes, and Economic Opportunity for Housing Voucher Recipients

In the 1990s and early 2000s, the Department of Housing and Urban Development sponsored two major... more In the 1990s and early 2000s, the Department of Housing and Urban Development sponsored two major experiments to test whether housing choice vouchers propelled low-income households into greater economic security, the Moving to Opportunity for Fair Housing program (MTO) and the Welfare to Work Voucher program (WTW). Using data from these programs, this study examines differences in residential location and employment outcomes between voucher recipients with access to automobiles and those without. Overall, the findings underscore the positive role of automobiles in outcomes for housing voucher participants.

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Metropolitan planning in a vacuum: Lessons on regional equity planning from Baltimore’s Sustainable Communities Initiative

Journal of Urban Affairs, 2019

The following characterization is obtained: THEOREM. Let G be a finite group generated by a conju... more The following characterization is obtained: THEOREM. Let G be a finite group generated by a conjugacy class D of subgroups of prime order p ^ 5, such that for any choice of distinct A and B in D, the subgroup generated by A and B is isomorphic to Z p x Z p , L 2 (p m) or SL 2 (p m), where m depends on A and B. Assume G has no nontrivial solvable normal subgroup. Then G is isomorphic to Sp n (q) or U n (q) for some power q of p.

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Opportunity for Whom? The Diverse Definitions of Neighborhood Opportunity in Baltimore

City & Community, 2018

Across the United States, communities are increasingly interested in the spatial structure of opp... more Across the United States, communities are increasingly interested in the spatial structure of opportunity. Recently, several federal programs have promulgated opportunity mapping as a tool to help increase disadvantaged communities’ access to neighborhood opportunity. The increasing institutionalization of opportunity mapping raises questions about how opportunity is defined and by whom. This paper analyzes data from community engagement events held for a regional planning process throughout the Baltimore metropolitan area. During these events, over 100 residents were asked what it means to live in neighborhoods that provide opportunity. The results showed similarities as well as remarkable differences in residents’ definitions of opportunity across race, income, and geography. Racial and ethnic minorities, low–income groups, and those living in distressed neighborhoods were more likely to identify job accessibility, employment, and job training as key components of and pathways to ...

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Strategic Planning for GIS Design

Geographic Information Science & Technology Body of Knowledge, 2018

Spatio-temporal analysis of socioeconomic neighborhoods: The Open Source Longitudinal Neighborhood Analysis Package (OSLNAP)

Proceedings of the Python in Science Conference, 2018

The neighborhood effects literature represents a wide span of the social sciences broadly concern... more The neighborhood effects literature represents a wide span of the social sciences broadly concerned with the influence of spatial context on social processes. From the study of segregation dynamics, the relationships between the built environment and health outcomes, to the impact of concentrated poverty on social efficacy, neighborhoods are a central construct in empirical work. From a dynamic lens, neighborhoods experience changes not only in their socioeconomic composition, but also in spatial extent; however, the literature has ignored the latter source of change. In this paper, we discuss the development of a novel, spatially explicit tool: the Open Source Longitudinal Neighborhood Analysis Package (OSLNAP) using the scientific Python ecosystem.

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How Do Cities Flow in an Emergency? Tracing Human Mobility Patterns during a Natural Disaster with Big Data and Geospatial Data Science

Urban Science, 2019

Understanding human movements in the face of natural disasters is critical for disaster evacuatio... more Understanding human movements in the face of natural disasters is critical for disaster evacuation planning, management, and relief. Despite the clear need for such work, these studies are rare in the literature due to the lack of available data measuring spatiotemporal mobility patterns during actual disasters. This study explores the spatiotemporal patterns of evacuation travels by leveraging users’ location information from millions of tweets posted in the hours prior and concurrent to Hurricane Matthew. Our analysis yields several practical insights, including the following: (1) We identified trajectories of Twitter users moving out of evacuation zones once the evacuation was ordered and then returning home after the hurricane passed. (2) Evacuation zone residents produced an unusually large number of tweets outside evacuation zones during the evacuation order period. (3) It took several days for the evacuees in both South Carolina and Georgia to leave their residential areas af...

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The Legacy of Redlining: A Spatial Dynamics Perspective

International Regional Science Review, Aug 7, 2022

American Community Survey (ACS) Data Uncertainty and the Analysis of Segregation Dynamics

Population Research and Policy Review, Jan 28, 2023

Download

Reducing racial segregation of public school districts

Socio-economic Planning Sciences, Dec 1, 2022

geosnap: The Geospatial Neighborhood Analysis Package

this is a quick release to generate a zenodo DOI

spopt: a python package for solving spatial optimization problems in PySAL

Journal of open source software, Jun 14, 2022

Download

American Community Survey (ACS) Data Uncertainty and the Analysis of Segregation Dynamics

Population Research and Policy Review

American Community Survey (ACS) data have become the workhorse for the empirical analysis of segr... more American Community Survey (ACS) data have become the workhorse for the empirical analysis of segregation in the U.S.A. during the past decade. The increased frequency the ACS offers over the 10-year Census, which is the main reason for its popularity, comes with an increased level of uncertainty in the published estimates due to the reduced sampling ratio of ACS (1:40 households) relative to the Census (1:6 households). This paper introduces a new approach to integrate ACS data uncertainty into the analysis of segregation. Our method relies on variance replicate estimates for the 5-year ACS and advances over existing approaches by explicitly taking into account the covariance between ACS estimates when developing sampling distributions for segregation indices. We illustrate our approach with a study of comparative segregation dynamics for 29 metropolitan statistical areas in California, using the 2010–2014 and 2015–2019. Our methods yield different results than the simulation techni...

Download

Comparative Spatial Segregation Analytics

Spatial Demography

All of the segregation indexes have in common the assumption that segregation can be measured wit... more

Download

Reducing racial segregation of public school districts

Socio-Economic Planning Sciences

The Legacy of Redlining: A Spatial Dynamics Perspective

International Regional Science Review

spopt: a python package for solving spatial optimization problems in PySAL

Journal of Open Source Software

Download

ThePySALEcosystem: Philosophy and Implementation

Geographical Analysis, 2021

pysal/segregation: Segregation Analysis, Inference, and Decomposition

geosnap: The Geospatial Neighborhood Analysis Package

this is a quick release to generate a zenodo DOI

Driving to Opportunities: Voucher Users, Cars, and Movement to Sustainable Neighborhoods

Download

Driving to Opportunity: Understanding the Links among Transportation Access, Residential Outcomes, and Economic Opportunity for Housing Voucher Recipients

Download

Metropolitan planning in a vacuum: Lessons on regional equity planning from Baltimore’s Sustainable Communities Initiative

Journal of Urban Affairs, 2019

Download

Opportunity for Whom? The Diverse Definitions of Neighborhood Opportunity in Baltimore

City & Community, 2018

Download

Strategic Planning for GIS Design

Geographic Information Science & Technology Body of Knowledge, 2018

Spatio-temporal analysis of socioeconomic neighborhoods: The Open Source Longitudinal Neighborhood Analysis Package (OSLNAP)

Proceedings of the Python in Science Conference, 2018

Download

How Do Cities Flow in an Emergency? Tracing Human Mobility Patterns during a Natural Disaster with Big Data and Geospatial Data Science

Urban Science, 2019

Download

Opportunity for Whom? The Diverse Definitions of Neighborhood Opportunity in Baltimore

Strategic Planning for GIS Design

How Do Cities Flow in an Emergency? Tracing Human Mobility Patterns during a Natural Disaster with Big Data and Geospatial Data Science

Understanding human movements in the face of natural disasters is critical for disaster evacuatio... more Understanding human movements in the face of natural disasters is critical for disaster evacuation planning, management, and relief. Despite the clear need for such work, these studies are rare in the literature due to the lack of available data measuring spatiotemporal mobility patterns during actual disasters. This study explores the spatiotemporal patterns of evacuation travels by leveraging users' location information from millions of tweets posted in the hours prior and concurrent to Hurricane Matthew. Our analysis yields several practical insights, including the following: (1) We identified trajectories of Twitter users moving out of evacuation zones once the evacuation was ordered and then returning home after the hurricane passed. (2) Evacuation zone residents produced an unusually large number of tweets outside evacuation zones during the evacuation order period. (3) It took several days for the evacuees in both South Carolina and Georgia to leave their residential areas after the mandatory evacuation was ordered, but Georgia residents typically took more time to return home. (4) Evacuees are more likely to choose larger cities farther away as their destinations for safety instead of nearby small cities. (5) Human movements during the evacuation follow a log-normal distribution.

Geosilhouettes: Geographical measures of cluster fit

Regionalization, under various guises and descriptions, is a longstanding and pervasive interest ... more Regionalization, under various guises and descriptions, is a longstanding and pervasive interest of urban studies. With an increasingly large number of studies on urban place detection in language, behavior, pricing, and demography, recent critiques of longstanding regional science perspectives on place detection have focused on the arbitrariness and non-geographical nature of measures of best fit. In this paper, we develop new explicitlygeographical measures of cluster fit. These hybrid spatial-social measures, called geosilhouettes, are demonstrated to capture the “core” of geographical clusters in racial data on census blocks in Brooklyn neighborhoods. These new geosilhouettes are also useful in a variety of boundary analysis and outlier detection uses. These new measures are defined, demonstrated, and new directions are suggested.

Metropolitan planning in a vacuum: Lessons on regional equity planning from Baltimore's Sustainable Communities Initiative

CATSLife: A Study of Lifespan Behavioral Development and Cognitive Functioning

The purpose of this update is to provide the most current information about both the Colorado Ado... more The purpose of this update is to provide the most current information about both the Colorado Adoption Project (CAP) and the Longitudinal Twin Study (LTS) and to introduce the Colorado Adoption/Twin Study of Lifespan behavioral development and cognitive aging (CATSLife), a product of their merger and a unique study of lifespan behavioral development and cognitive aging. The primary objective of CATSLife is to assess the unique saliency of early childhood genetic and environmental factors to adult cognitive maintenance and change, as well as proximal influences and innovations that emerge across development. CATSLife is currently assessing up to 1600 individuals on the cusp of middle age, targeting those between 30 and 40 years of age. The ongoing CATSLife data collection is described as well as the longitudinal data available from the earlier CAP and LTS assessments. We illustrate CATSLife via current projects and publications, highlighting the measurement of genetic, biochemical, social, sociodemographic and environmental indices, including geospatial features, and their impact on cognitive maintenance in middle adulthood. CATSLife provides an unparalleled opportunity to assess prospectively the etiologies of cognitive change and test the saliency of early childhood versus proximal influences on the genesis of cognitive decline.

Driving to Opportunities: Voucher Users, Cars, and Movement to Sustainable Neighborhoods

Tenant-based rental vouchers have expanded housing choice for millions of low-income households, ... more Tenant-based rental vouchers have expanded housing choice for millions of low-income households, yet assisted households still face hurdles when trying to secure housing in high-opportunity neighborhoods with desirable economic, social, and environmental characteristics. Although inadequate transportation is arguably one of the most impor- tant hurdles to securing housing in high-opportunity neighborhoods, existing studies of voucher users' location choices have n ot yet explored the connections between trans- portation access and residential location outcomes. This article discusses the results from a recent study that attempts to close that gap. Our study draws on data from the Moving to Opportunity for Fair Housing demonstration program and the Welfare-to- Work Voucher Program, two residential mobility initiatives that randomly assigned rental vouchers to low-income households seeking housing assistance. Using a variety of approaches—including cluster analysis, bivariate comparisons, and multivariate analysis—we find evidence of important connections between automobile access and improved neighborhood conditions. We also find that neighborhoods with similar levels of poverty exhibit a wide array of other characteristics that matter differently for dif- ferent kinds of households. Our findings suggest a need for more integrated and holistic planning and program development to account for the importance of both cars and transit to low-income households' well-being.

Spatio-temporal analysis of socioeconomic neighborhoods

Locating the Most Connected Transit Stop, Route, and Transfer Center: Tool for Users and Decision Makers

NCHRP 08-36: Sketch Planning Tools for Regional Sustainability

Challenges and Opportunities for Economic Prosperity in the 21st Century: Sustainable and Equitable Economic Development in Maryland

Toward an Equitable Region: Lessons from Baltimore's Sustainable Communities Initiative

Driving to Opportunity : Understanding the links among transportation access, residential outcomes, and economic opportunity for housing voucher recipients

Elijah Knaap

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