Ehsan Momeni, PhD - Academia.edu (original) (raw)

Books by Ehsan Momeni, PhD

Taylor & Francis Group CRC Press, 2022

Urban sprawl is known as an unsustainable process and outcome of urban growth. This chapter defin... more Urban sprawl is known as an unsustainable process and outcome of urban growth. This chapter defines urban sprawl and discusses ways to measure sprawl, including various indices that quantify the magnitude and the extent of this unsustainable development. As a case study, this chapter discusses the measurement of the spatial structure of urban and suburban neighborhood sprawl using Memphis, Tennessee, located in the southeastern United States. Specifically, it applies the GIS-based analysis and uses the Shannon entropy measure. The Shannon entropy's common application is the metropolitan regional scale allowing for comparisons across different regions. Urban sprawl and blight both plague the metropolitan areas, and sprawl correlates with spatial inequality of various types, including income, also referred to as “twin problems” of the metropolitan region. Accordingly, this chapter's case study analyzes the link between urban sprawl and blight, testing a hypothesis that these key indicators are correlated with blight. The chapter adds to literature on GIS applications in urban sprawl analysis.

Taylor & Francis Group CRC Press, 2022

Urban sprawl is a global phenomenon commonly known for its wide-ranging negative consequences for... more Urban sprawl is a global phenomenon commonly known for its wide-ranging negative consequences for urban sustainability. In this chapter, we identify drivers of sprawl, provide examples, and distinguish sprawl from urban growth. We discuss how sprawl is countered by smarter alternatives to urban growth. Among the consequences, we highlight the connections of urban blight and sprawl, which are given little attention, particularly in the urban studies literature on sprawl. Finally, we discuss the vulnerability and resiliency of the urban form in the face of an infectious COVID-19 pandemic.

Papers by Ehsan Momeni, PhD

GeoScape, 2022

Historically, industry shaped the space-economy of the American city, a major source of employmen... more Historically, industry shaped the space-economy of the American city, a major source of employment opportunity for residents that selected housing nearby or within a convenient or affordable commuting distance. However, the contemporary American city is structurally characterized by abandoned, blighted, vacant industrial properties due to urban expansion, deindustrialization and the suburbanization of both jobs and population. The urban studies literature rarely documents the neighborhood impact of industrial blight akin to studies of residential blight. We determine the proximity-effect of industrial blight on the neighborhood thought of not as an isolated and closed entity, but as a connected and open entity within the city and the region. Unlike studies confined to the property value impact, we determine Pearson correlations of industrial blight and vacancy expansively with the socioeconomic and physical characteristics of neighborhoods. We use path analysis to determine direct, indirect, and total neighborhood impact of industrial blight and vacancy. The census block group and parcel-level geographic information system (GIS) provide our principal sources of data. The block group geography contains the neighborhood as a fundamental spatial unit. We determine how the neighborhood impact varies with distance from the blighted, vacant industrial property. Highlights for public administration, management and planning: • The neighborhood, a fundamental spatial unit of the block-group geography of the metropolitan region, is highlighted in various proximities to the industrial blight and vacant sites. • We show how neighborhood viability, measured by block group median income, is impacted by industrial blight in proximity. • We determine correlations with socioeconomic characteristics of the neighborhood in various distances to the blighted and vacant properties. • Planning and policy alternatives to address industrial blight and vacancy are suggested.

Applied Geography, 2022

This study explores the association between urban form, socio-demographics, and travel behavior f... more This study explores the association between urban form, socio-demographics, and travel behavior for 1990, 2000, and 2010 in Shelby County, Tennessee, at a micro-level using U.S. Census tracts capturing active and passive transportation modes. We used bivariate correlations between land use and land cover mix (estimated separately by Simpson's index), population, race, age, education, and commuting modes. Major findings indicate that land use mix is positively related to public transportation use while the land cover mix is negatively related; the opposite is found for both diversity measures and working from home. Greater land cover diversity discourages walking and biking and encourages car commuting; Blacks are the majority who use public transportation; older travelers are more likely to use transportation alternatives; higher-educated people tend to work from home or commute by bike. This study helps city planners in designing sustainable cities and increasing active modes use. Understanding travel patterns may help policymakers to control local/regional problems like increasing traffic congestions and emissions due to a modal shift in commuting to a private car during a COVID-19 pandemic, as well as develop strategies for encouraging active modes and public transport use in the post-COVID-19 world.

Frontiers in Sustainable Cities, 2021

Urban studies related to previous pandemics and impacts on cities focused on vulnerable categorie... more Urban studies related to previous pandemics and impacts on cities focused on vulnerable categories including poor and marginalized groups. We continue this tradition and analyze unemployment outcomes in a context of a multi-dimensional social disadvantage that is unfolding during the ongoing public health crisis. For this, we first propose an approach to identify communities by social disadvantage status captured by several key metrics. Second, we apply this methodology in the study of the effect of social disadvantage on unemployment during the COVID-19 and measure the COVID-19-related economic impact using the most recent data on unemployment. The study focuses upon vulnerable communities in in the southeastern US (Tennessee) with a concentration of high social vulnerability and rural communities. While all communities initially experienced the impact that was both sudden and severe, communities that had lower social disadvantage pre-COVID were much more likely to start resuming economic activities earlier than communities that were already vulnerable pre-COVID due to high social disadvantage with further implications upon community well-being. The impact of social disadvantage grew stronger post-COVID compared with the pre-pandemic period. In addition, we investigate worker characteristics associated with adverse labor market outcomes during the later stage of the current economic recession. We show that some socio-demographic groups have a systematically higher likelihood of being unemployed. Compared with the earlier stages, racial membership, poverty and loss of employment go hand in hand, while ethnic membership (Hispanics) and younger male workers are not associated with higher unemployment. Overall, the study contributes to a growing contemporaneous research on the consequences of the Covid-19 recession. Motivated by the lack of the research on the spatial aspect of the COVID-19-caused economic recession and its economic impacts upon the vulnerable communities during the later stages, we further contribute to the research gap.

GeoScape, Jul 2, 2021

The urban expansion from the city center to the suburb and beyond is indicated by Shannon entropy... more The urban expansion from the city center to the suburb and beyond is indicated by Shannon entropy, a robust and versatile measure of sprawl. However, the metropolitan regionwide entropy masks the morphology of land cover and land use consequential to urban expansion within the city-region. To surmount the limitation, we focus on the block-group, which is a US census defined socio-spatial unit that identifies the metropolitan region's development pattern structurally, forming tracts that comprise neighborhoods. The concentration and dispersion of land use and land cover by block-group reveals a North American metropolitan region's commonly known but rarely measured spatial structure of its urban and suburban sprawl. We use parcel data from county assessor of property (GIS) and land cover pixel data from the National Land Cover Data (NLCD) to compute block-group landuse and land-cover entropy. The change in block group entropy over a decade indicates whether the city-region's land use and land cover transition to a concentrated or dispersed pattern. Furthermore, we test a hypothesis that blight correlates with sprawl. Blight and sprawl are among the key factors that plague the metropolitan region. We determine the correlations with household income as well as (block group) distance from the city center. It turns out, blight is among the universally held distance-decay phenomena. The share of the block group's blighted properties decays (nonlinearly) with distance from the city center. Highlights for public administration, management and planning: • The metropolitan region's outward growth is highlighted by mapping the changing morphology of the block group within the city-region. • The block group entropy is computed with land use (parcel) and land cover (pixel) data. • The block group entropy change indicates the pattern of the land use and land cover transition with concentration or dispersion. • We test the hypothesis that blight correlates with sprawl with statistical models. • The block group's blighted properties decrease (nonlinearly) with distance from the city center.

Transactions in GIS - Wiley, Jun 9, 2020

While cellular automata (CA) are considered an effective algorithm to model urban growth, their p... more While cellular automata (CA) are considered an effective algorithm to model urban growth, their precise calibration can be challenging. The Shannon relative index (SRI) is an indicator of urban sprawl accounting for dispersion or concentration of built‐up/non‐built‐up areas. This study uses SRIs directly in the calibration of CA as patterns, applying a genetic algorithm (GA). Moreover, the kappa coefficient is used in the calibration process. CA was calibrated using data for 2001 and 2006 and validated using 2011 data to model urban growth in Shelby County, TN. Results indicate that the kappa coefficient achieves the highest value using the proposed method (89.48%) compared with a GA without patterns (86.15%, which underestimates 32.22 km2) or logistic regression (85.83%, which underestimates 36.76 km2). A more precise calibration of urban growth using the proposed method helps city planners to provide more realistic models for the future of the region.

Malaysian Journal of Geosciences (MJG), 2020

In this paper, DTFL an image classifier based on Decision Tree and Fuzzy Logics is proposed. At t... more In this paper, DTFL an image classifier based on Decision Tree and Fuzzy Logics is proposed. At the beginning of classification using DTFL, each pixel is located at the highest level of a decision tree where it belongs to the combination of all classes. DTFL transfers a pixel to a lower level of the decision tree where the pixel belongs to a combination of fewer classes. Decision-making about transfers is based on fuzzy logic with seven different membership functions including triangular-shaped, trapezoidal-shaped, π-shaped, bell-shaped, Gaussian, differential S-shaped and multiplicative S-shaped. Eventually, pixels will reach the lowest level of the decision tree where it belongs to only one class. For accuracy assessment, DTFL was used to classify a GeoEye-1 image. The overall accuracy of 96.14% and a kappa coefficient of 96.06% were reached by DTFL. In comparison, the overall accuracy of 89.91% and a kappa coefficient of 89.77% were reached by a Maximum Likelihood Classifier, MLC. In the case of applying a threshold in MLC to reach the same accuracy as DTFL, 8.73% of pixels take the non-classified label while using DTFL all the pixels get a proper label. The results indicate that the proposed classifier extracts more information from images.

Journal of Geography & Natural Disasters , 2018

Urban planners and decision-makers always demand the most updated maps in order to model urban dy... more Urban planners and decision-makers always demand the most updated maps in order to model urban dynamics and make an optimized plan for the city. Conventional mapping techniques in Iran are still based on the use of traditional panchromatic aerial photos. Keeping maps up-to-date is a challenge for National Cartographic Center, as the main producer of maps in Iran. This paper examines the ability of GeoEye-1 high-resolution satellite images to update large-scale topographic maps of Iran considering Iranian national mapping standards. Extractable urban features from GeoEye-1 images and their geometric accuracy were studied and compared with aerial photos. The study found GeoEye-1 images as a practical alternative for aerial photogrammetry for updating large-scale topographic maps in Iran. Maps at a scale of 1:3,000 with 1 m contour interval can be extracted from GeoEye-1 images based on Iranian standards. Also, the study found that cost of map updating using GeoEye-1 images is less than the cost of map updating using conventional aerial photogrammetry.

Geomatics 93, 21th National Conference and Exhibition, 2014

National Cartographic Center, 2012

Shahrnegar, 2011

S h a h r n e g a r No.55 -55 ‫ش��ماره‬ ‫یادداشت‬ 3 ‫نوشت:‬ ‫پی‬ 1 . Result-based Budgeting

Geomatics 90, 18th National Conference and Exhibition, 2011

International Society for Photogrammetry and Remote Sensing, 2011

Geomatics 89, 17th National Conference and Exhibition, 2010

American Society for Photogrammetry and Remote Sensing, San Diego, CA, 2010

7th International Symposium on Digital Earth, Perth Convention and Exhibition Centre, 2011

A map scale of 1:25,000 satisfies the needs for a wide range of map users including ur... more A map scale of 1:25,000 satisfies the needs for a wide range of map users including urban city planners, as well as several GIS applications. Nowadays because of high potential of satellite images, maps production procedure and their updating increasingly go towards using satellite photogrammetry. The advantages of using satellite images show the necessity of more evaluation and studying on satellite images more than ever. This study includes a comprehensive comparison of geometric accuracy and information content between two most commonly used imageries, IRS-P5 and ALOS-PRISM for updating of 1:25,000 -scale maps. Information content of imageries was evaluated based on object identification and extraction for all features of 1:25,000- scale maps. Accuracy in the vertical direction was calculated by comparing the spot height values of more than 170 points with elevation values measured on aerial photographs. More than 150 points extracted from planimetric features were used for accuracy assessment in planimetric direction. The results of these evaluations show that IRS-P5 stereo images, from the point of geometric accuracy, have the capability of 1:25,000- scale maps revision, also, from the point of information content, have the capability of revision for most objects in 1:25,000- scale maps. The planimetric accuracy of ALOS-PRISM satisfies needed accuracy for 1:25,000- scale maps, but some block noises that adversely affect the legibility of image, reduce the altimetric accuracy. Values of accuracy statistics show that ALOS-PRISM stereo images are not suitable to acquire heights of features by stereo plotting.

K. N. Toosi University of Technology, 2010

µ|»Ê] ¾ÌÌ eÉZÅ ªZÀ» ¶ÌiY{ÉAEË~a\ÌM ®¼¯Ä] ¾ § ÉÁM ÉZÅ ÁÁ{YnÀ,Éf»Y³Âf § GIS Z¼ÀÅY|ÌeZY Ê ·Z|¼v»f¯{ ... more µ|»Ê] ¾ÌÌ eÉZÅ ªZÀ» ¶ÌiY{ÉAEË~a\ÌM ®¼¯Ä] ¾ § ÉÁM ÉZÅ ÁÁ{YnÀ,Éf»Y³Âf § GIS Z¼ÀÅY|ÌeZY Ê ·Z|¼v»f¯{ kÁ½Y|·Á{YÂm|¼v»f¯{ Ân¿Y{ ÊÀ»Â»½ZuY ÊËÂn¿Y{ÃZ¼ ÃZ»É{ |YÊZÀZ¯ZÀÌ¼ ZÀÌ¼½YÂÀ µ|»Ê] ¾ÌÌ eÉZÅ ½Z°» ÉZÅ ¶ÌiY{ÉAEË~a\ÌM ®¼¯Ä] ¾ § ÉÁM ÉZÅ ÁÁ{YnÀ,Éf»Y³Âf § GIS Z¼ÀÅY|ÌeZY Ê ·Z|¼v»f¯{ kÁ½Y|·Á{YÂm|¼v»f¯{ Ân¿Y{ ÊÀ»Â»½ZuY ÊËÂn¿Y{ÃZ¼ É{ ÃZ» Ã{YÂ¿ZyÄ]ºË|¬e ¹Ë Ã{Â]¾»½Z^ÌfaÁZËÊ¿Z³|¿ ¶uY»Ê»Z¼e{Ä |¿Y ¾Áºq Z ÄË|¿YY ZÅ ZAEf¿YZeY|f]Y¾Ì]ZÅZ mÊ¸«Z Ìa ÊÀÌ] dÌ¿Ì] dÌ¿Ë|¿Yd^«ZÂ¯½MÉYÁ ÉÂ·Â» Ã|Ì°q \ÌAE»Ä¸¼mY ¶Ì Ä]YÊ¿YÁY §Ê·Z»ÁÊ¿ZmcYZyÄ¿ÓZÄ¯dY½ZAEm{Ê Ì^ÉZËÔ]¾Ëe d·Á{ d¸» Á ZÅ Ê» ¶Ì¼ve ¦¸fz» ÉZÅ |À ¾»Y ªZÀ» Ze Ã| hZ] dÌ ¼m ½Á §Y Á ËY §Y Y |ÀÀË³ÊÀ°Ë~a\ÌMÊ¬ZÀ»{¹{»YÊy]ÁÃ|Z^Y¾ÌÀ¯Z ,ÊZ¼fmYËY¾ÌÀr¼Å cmZAE»ËY §Y,É{Zf«Y Êf¼«dYÃ|hZ],Ê Ì^[Y~mªZÀ»{½Z°YÄ]¹{» ¶ËZ¼eÁZÅ ¶Ì| f»ªZÀ»{»YÂmdÌ ¼mY |ÀÀ¯d»Z«Y {½Mc|«ËY §YÁ ¶Ìg{YÂu{Y| eËY §Y ÄÅ{Á{Ê Ä»Z¿]¹|ÁÄf~³É ÉË Ä Âe{Ê·ÂYÉZÅ AEÉ YÊZ¿Ê·Z»ÁÊ¿ZmcYZy,ZÅ Ã{Y{ËY §Yc|Ä]Y ¶Ì dY ®¼¯|À»ZÌ¿,Ã|Ë{Äi{ZuªZÀ»j¯YÄ¯ÉÂÄ] Ä¬À»Y §ÉZÅ ÉY Ê»Ê¸¸¼·Y¾Ì]Á |¿Â ÃZÌ£Z°ÅY®Ë½YÂÀÄ]ÉAEË~a\ÌMªZÀ»¾ÌÌ eÁÊËZZÀZ] ÉY ¶Ì ½Yv] dËË|» Ê¿Zm cYZy ÅZ¯ ] ÃÁÔ, ½Z°»Y,cZi|vf» ÉZ ¹ÁZ¬» ªË Y Ê·Z» Á ÄËZ» ÂÀ» Ä] ¾»Y ªZÀ» ÊËZZÀ dyZ Ë ÉY] ÉY~³ ºÅY § Ì¿ Ä¬À» ®Ë ÊZY ÉZÅ Ê» {{³ ®ÌÀ°e ½YÂÀ Ä] Á{ Y nÀ Á Éf»Y³Âf § ,ZAE¿M ÊmÁy cZÔY ºY z] Ä¯ ÊËZÅ dYÊ¿Z°»ÊeZÔY Ä¨ÌÁ ¼mÉ Ã{Y{ÉÁM ÓÉZÅ Áµ|»½ÂÌY^Ì·Z¯, ¶ÌÉZ·|»¹Zn¿YÉY]¹ |¿Y{ Ã|AE ] Y ÉZ·|» d«{ Ê]ZËY Á GIS Ê» Ä¯ ÉY]Y ½YÂÀ Ä] ¶Ì¸ve Á ÄËne { |¿YÂe Á ZÅ ½Z¿Y Ä] Ê¿Z°» Ì£ Á Ê¿Z°» cZÔY ªÌ¨¸e ,|À¯ ®¼¯ ZÅ ÊmÁy {Â» Y ÉZ·|» Y ¶Zu ÉZÅ Ê»Y« ¶Ì¸veÁÄËne ZÀ»Ze|Å{ |À¯ÊËZZÀY ¶Ì ¶]Z¬»{Ë~a\ÌMª YaÂÀ»¾Ë|] ¶ÌÉZ·|» Ã{Y{YÃ{Z¨fYZ] Å{,Ê·Z¼fuY ¶ÌdÁª¼,Á{YnÀÁÉf»Y³Âf §ÉZÅ Ê»d|]ÉZ·|»cÓ{Z » ¶uªËYÄ¬¿ |ËM ºfÌÄ]Ä¨·Â»Á{¾ËY{ÁÁZ] Ê¿Z°»cZÔYÉZÅ cZ^Zv»¹Zn¿YÁ ºfÌ¾ËY{ÊËZÅÌ·Z¿MÁ Ä^Zv»Ya,ZÅ Ä]½YÌ»É É¿Y,Ä¬¿ÅÄ] ¶ÌÉ ½Z»c|»,Ä¬¿ÅÄ] ¶Ì½|Ì½Z»,Ä¬¿Å{[MtËY §Yw¿,Ä¬¿Å{ ¶ÌÊ^Àm Ë~a\ÌMªZÀ»,Ä¬¿Å{Ê·Z¼fuY ¶ÌYÃ|¿Z»ÉZn][Â½YÌ»ÁÄ¬¿Å½|¿Z» ¶ÌË ¬»{ Ê»ÊËZZÀ ¶Ì ¶]Z ÉËÄ»Z¿]¾Ìu{Ze|¿Â ÄÀÌAE]É|À]dËÂ·ÁYZÅ {Ë~acÂÉY O

Taylor & Francis Group CRC Press, 2022

GeoScape, 2022

Applied Geography, 2022

Frontiers in Sustainable Cities, 2021

GeoScape, Jul 2, 2021

Transactions in GIS - Wiley, Jun 9, 2020

Malaysian Journal of Geosciences (MJG), 2020

Journal of Geography & Natural Disasters , 2018

Geomatics 93, 21th National Conference and Exhibition, 2014

National Cartographic Center, 2012

Shahrnegar, 2011

S h a h r n e g a r No.55 -55 ‫ش��ماره‬ ‫یادداشت‬ 3 ‫نوشت:‬ ‫پی‬ 1 . Result-based Budgeting

Geomatics 90, 18th National Conference and Exhibition, 2011

International Society for Photogrammetry and Remote Sensing, 2011

Geomatics 89, 17th National Conference and Exhibition, 2010

American Society for Photogrammetry and Remote Sensing, San Diego, CA, 2010

7th International Symposium on Digital Earth, Perth Convention and Exhibition Centre, 2011

K. N. Toosi University of Technology, 2010

NCGIS, 2023

This study successfully applied the Imperialistic Competitive Algorithm (ICA) in the field of urb... more This study successfully applied the Imperialistic Competitive Algorithm (ICA) in the field of urban planning to calibrate a cellular automata (CA) model of urban growth/sprawl in Shelby County, TN. The results can help city developers, transportation engineers, tax assessors, and utility providers to make more realistic decisions in Shelby County.

2023 North Carolina Geographic Information Systems (2023 NCGIS), 2023

This study successfully applied Imperialistic Competitive Algorithm (ICA) in the field of urban p... more This study successfully applied Imperialistic Competitive Algorithm (ICA) in the field of urban planning to calibrate a cellular automata (CA) model of urban growth/sprawl in Shelby County, TN. The results can help city developers, transportation engineers, tax assessors, and utility providers to make more realistic decisions in Shelby County.

50th Annual Conference on Urban Affairs Association (UAA), 2022

Research Question: How industrial blight correlates with the socio-economic and physical characte... more Research Question: How industrial blight correlates with the socio-economic and physical characteristics of neighborhoods? Purpose: To determine the proximity-effect of industrial blight on the neighborhood, thought of as not an isolated, closed system but a connected entity within the city and the region: • We fill the void in the literature by a gradation of distance from industrial blight, from ¼ to ½ and ¾ mile. As well, we measure the neighborhood impact of blight for the county as a whole. • We determine the direct and indirect impact of the industrial site on the neighborhood with a path analysis by using block-group data.

The 33rd Annual Student Research Forum (SRF), University of Memphis, Memphis, TN., 2021

Obesity and overweight are common and serious chronic diseases in the United States. Obesity/over... more Obesity and overweight are common and serious chronic diseases in the United States. Obesity/overweight puts people at more risk of many other diseases including diabetes, heart diseases, and certain cancers. This study explores the relationship between the percentage of obese/overweight population and COVID-19 confirmed cases/deaths per 100,000 population at a county level over the U.S. Statistical analyses show that counties with more percentage of obese/overweight population significantly experienced more COVID-19 confirmed cases/deaths determined by ANOVA (F(3,3103)) = 77.188, p = .000 and ANOVA (F(3,3103)) = 109.626, p = .000 for cases and deaths, respectively.

75th Annual Conference of the Southeastern Division of the American Association of Geographers (SEDAAG), 2020

The study seeks to explore the impacts of social disadvantage on public health in unprecedented t... more The study seeks to explore the impacts of social disadvantage on public health in unprecedented times of the COVID-19 pandemic. We simultaneously capture multiple risk factors mediating the COVID-19-related outcomes through the concept of a multi-dimensional social disadvantage and map geographical inequalities in coronavirus disease 2019 morbidity and mortality in Tennessee. Disadvantaged communities suffer a greater burden due to being already vulnerable prior to the COVID-19 pandemic and may have higher numbers of confirmed and probable cases and deaths in the community. It is important to identify “high-priority areas” where resources including testing kits and facilities need to be provided in a timely fashion to mitigate community spread. We identified counties in Tennessee with a greater burden of the disease due to a concentration of contributing factors. These include exposure to air pollution, obesity, minorities/Hispanic ethnicity, poverty, and crowded household conditions. The areas with high shares of the above-listed risk factors have been designated as “high social disadvantage”, while areas with low shares have been designated as “low social disadvantage”. We tested the relationship between socio-economic deprivation and the burden from COVID-19- related morbidity and mortality (the primary health outcomes) in Tennessee.

31st Annual Student Research Forum, The University of Memphis, Memphis, TN, USA, 2019

Over the past three decades, more than 91% of work journeys in Shelby County, TN, were made ... more Over the past three decades, more than 91% of work journeys in Shelby County, TN, were made on cars, trucks or vans. While over-reliance on private vehicles is not environment-friendly behavior, researchers document the importance of biking, on both physical and mental health. This study uses demographics in 2010 to identify neighborhoods with the highest demand for biking. The output shows Southeast of Shelby County, including Germantown, with the highest demand for biking based on education, age and ethnicity of residents. Results will help urban planners to make authentic plans for the future of biking in Shelby County.

73rd Annual Conference of the Southeastern Division of the AAG (SEDAAG), Johnson City, TN, 2018

The close relationship exists between land use and transportation, with land use configu... more The close relationship exists between land use and transportation, with land use configuration shaping travel patterns over the short term. Respectively, we examined changes in urban form measured by land use/land cover changes and related changes in transportation behavior over the twenty-year period in a large-sized urban area in the southeast USA. In addition, we studied changes in population attributes including age structure and educational achievement as the main drivers of demand for residential and commercial land due to their impact on the distribution of housing and jobs and hence, travel patterns. Specifically, changes in spatial data and socio-demographic characteristics including population, age, race, and education were examined for the 1990s, 2000s, and 2010s. The urban form was examined by studying trends in LC and LU mix by computing a Simpson’s index for both measures for the two decades. In agreement with other metropolitan areas, the share of developed land use has increased (by almost 4% in the study area since the early 1990s) to meet the demand of housing and jobs for the growing population, while planted area and forest decreased significantly due to sprawl and urban development. As expected, lower values of Simpson’s index for land cover is negatively and consistently associated with public transportation for all three periods of examination, while positively related to working at home. Conversely, higher values of Simpson’s index for land use mix is positively and consistently associated with public transportation. Farther, the results indicate that young people today are more using public transportation in comparison with the past. Although Blacks constitute the majority of people who use public transportation, White commuters using public transport increased over the study period. In addition, older travelers are more likely to use alternative transportation modes. Higher educated people are more likely to work at home and use a bike as a commuting mode. The study contributes to urban planning research by identifying the impact of changes in land use, land cover, and socio-demographic characteristics on the use of various transportation including active and passive modes. It further contributes to decision making in planning by describing how priority areas with existing walkability demand can be identified.

30th Annual Student Research Forum, The University of Memphis, Memphis, TN, USA., 2018

In Shelby County, TN, more than 90% of house-to-work journeys between 1990 and 2010 were made on... more In Shelby County, TN, more than 90% of house-to-work journeys between 1990 and 2010 were made on private vehicles which is not an environment-friendly behavior. This study contributes to efforts for improving public transportation by identifying neighborhoods with the highest demand of it. Analyses of Census 2010 data show a significant relationship between the use of public transportation and socio-demographics. This study identified North Memphis, including Frayser, with the highest demand of public transportation based on land-use, age, ethnicity and education. Results will help urban planners to make reliable plans for public transportation in Shelby County.

ProQuest Dissertations and Theses database, 2022

Land use and land cover (LULC) data analyses disclosed large land conversion in Shelby County, TN... more Land use and land cover (LULC) data analyses disclosed large land conversion in Shelby County, TN, between 1990 and 2010. LULC mixtures have significant associations with socio-demographics and travel behavior. Mathematical modeling is used to forecast urban expansion in order to promote sustainable development. Cellular automata (CA) is a popular approach for the simulation of urban growth. Nevertheless, precise calibration of CA is challenging due to uncertainties and its knowledge-intensive process. Shannon relative indices (SRIs) have been used in this study as an indicator of land patterns to calibrate a CA model of urban growth in Shelby County. The results of using a Genetic Algorithm (GA) indicate that including patterns in the calibration improves the simulations’ accuracy (from 93.21% to 94.84%). Furthermore, an Imperialistic Competitive Algorithm (ICA) was implemented for the first time in the field of urban planning to calibrate the CA model of urban growth. Two alternatives including total disagreement and the Kappa coefficient have been separately implemented in the cost function of ICA. The findings indicate that the Kappa coefficient achieves higher overall accuracy in ICA, compared with the total disagreement (93.86% vs 92.37%). Moreover, adding patterns to the Kappa coefficient improves overall accuracy and increases the maximum (from 93.86% to 94.65%), the mean (from 79.76% to 81.11%), and the median (from 79.97% to 82.54%) of simulations’ accuracy. The pattern-based calibration resulted in a more realistic simulation of urban growth of over 9.49 sq. km of land in Shelby County (in comparison with the simulation without adding patterns). The results also demonstrated that ICA surpasses logistic regression (LR). While LR's overall accuracy was 92.98%, ICA's was 94.88% with patterns added, 94.40% using the Kappa coefficient alone, and 94.03% using the total disagreement. Using ICA and including patterns resulted in a correct simulation of urban growth of over 37.56 sq. km of land in Shelby County (in comparison with when an LR is used). Urban planners can utilize these findings to more accurately forecast urban growth while construction companies, transportation engineers, tax assessors, and utility providers will all benefit from accurately modeled urban land.

K. N. Toosi University of Technology, 2011