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Measuring the quality of life in city of Indianapolis by integration of remote sensing and census data
9 references·9 citing·42 second hop
Measuring the quality of life in city of Indianapolis by integration of remote sensing and census data (2007)Measuring the quality of life in city of …A First Course in Factor Analysis (2013)A First Course in Factor Anal…Urban environmental quality and human wellbeing—a social geographical perspective (2003)Urban environmental quality a…Urban environmental quality and human well-being (2003)Urban environmental quality a…Indexes of perceived residential environment quality and neighbourhood attachment in urban environments: a confirmation study on the city of Rome (2002)Indexes of perceived resident…A First Course in Factor Analysis (1993)A First Course in Factor Anal…Social Indicators of Well-Being (1976)Social Indicators of Well-Bei…THE GEOGRAPHY OF SOCIAL WELL-BEING (1974)THE GEOGRAPHY OF SOCIAL WELL-…A First Course in Factor Analysis 2nd Ed (1973)A First Course in Factor Anal…The Application of Electronic Computers to Factor Analysis (1960)The Application of Electronic…Urban Livability in a Rapidly Urbanizing Mid-Size City: Lessons for Planning in the Global South (2025)Urban Livability in a Rapidly…Predicting the liveability of Dutch cities with aerial images and semantic intermediate concepts (2023)Predicting the liveability of…A methodology for identifying typologies to improve innovation district outcomes: The case of South East Queensland (2023)A methodology for identifying…Urban Disparities and Quality of Life Among Afghan Refugees Living in Informal Settlements in Mashhad, Iran (2022)Urban Disparities and Quality…Predicting housing deprivation from space in the slums of Dhaka (2022)Predicting housing deprivatio…How can innovation district performance be assessed? Insights from South East Queensland, Australia (2022)How can innovation district p…Neighbourhood-level housing quality indices for health assessment in Dakar, Senegal (2021)Neighbourhood-level housing q…Comparison between Multi-Criteria Decision-Making Methods and Evaluating the Quality of Life at Different Spatial Levels (2021)Comparison between Multi-Crit…A review of quality of life (QOL) assessments and indicators: Towards a “QOL-Climate” assessment framework (2018)A review of quality of life (…Structural Equations with Latent Variables (1989)Structural Equations with Latent Variables. 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this work references cited by second hop

References

  • 1960The Application of Electronic Computers to Factor Analysis12,390 cited
  • 2013A First Course in Factor Analysis4,527 cited
  • 1976Social Indicators of Well-Being3,679 cited
  • 1993A First Course in Factor Analysis3,512 cited
  • 1973A First Course in Factor Analysis 2nd Ed1,364 cited
  • 2003Urban environmental quality and human well-being797 cited
  • 2003Urban environmental quality and human wellbeing—a social geographical perspective637 cited
  • 2002Indexes of perceived residential environment quality and neighbourhood attachment in urban environments: a confirmation study on the city of Rome429 cited
  • 1974THE GEOGRAPHY OF SOCIAL WELL-BEING37 cited

Cited by

  • 2018A review of quality of life (QOL) assessments and indicators: Towards a “QOL-Climate” assessment framework133 cited
  • 2021Comparison between Multi-Criteria Decision-Making Methods and Evaluating the Quality of Life at Different Spatial Levels63 cited
  • 2025Urban Livability in a Rapidly Urbanizing Mid-Size City: Lessons for Planning in the Global South16 cited
  • 2023Predicting the liveability of Dutch cities with aerial images and semantic intermediate concepts12 cited
  • 2022Urban Disparities and Quality of Life Among Afghan Refugees Living in Informal Settlements in Mashhad, Iran

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8 cited
  • 2022How can innovation district performance be assessed? Insights from South East Queensland, Australia6 cited
  • 2021Neighbourhood-level housing quality indices for health assessment in Dakar, Senegal5 cited
  • 2022Predicting housing deprivation from space in the slums of Dhaka4 cited
  • 2023A methodology for identifying typologies to improve innovation district outcomes: The case of South East Queensland1 cited