Guilherme Augusto Zagatti , Miguel Gonzalez , Paolo Avner , Nancy Lozano-Gracia , Christopher J. Brooks , Maximilian Albert , Jonathan Gray , Sarah Elizabeth Antos , Priya Burci , Elisabeth zu Erbach-Schoenberg , Andrew J. Tatem , Erik Wetter , Linus Bengtsson
{"title":"工作之旅:利用CDR估计海地主要大都市地区通勤模式的始发地和目的地","authors":"Guilherme Augusto Zagatti , Miguel Gonzalez , Paolo Avner , Nancy Lozano-Gracia , Christopher J. Brooks , Maximilian Albert , Jonathan Gray , Sarah Elizabeth Antos , Priya Burci , Elisabeth zu Erbach-Schoenberg , Andrew J. Tatem , Erik Wetter , Linus Bengtsson","doi":"10.1016/j.deveng.2018.03.002","DOIUrl":null,"url":null,"abstract":"<div><p>The rapid, unplanned urbanisation in Haiti creates a series of urban mobility challenges which can contribute to job market fragmentation and decrease the quality of life in the city. Data on population and job distributions, and on home-work commuting patterns in major urban centres are scarce. The most recent census took place in 2003 and events such as the 2010 earthquake have caused major redistributions of the population. In this data scarce context, our work takes advantage of nationwide de-identified Call Detail Records (CDR) from the main mobile operator in the country to investigate night and daytime populations densities and commuting patterns. We use a non-supervised learning algorithm to identify meaningful locations for individuals. These locations are then labelled according to a scoring criteria. The labelled locations are distributed in a grid with cells measuring 500 × 500 m in order to aggregate the individual level data and to create origin-destination matrices of weighted connections between home and work locations. The results suggest that labor markets are fragmented in Haiti. The two main urban centres, Port-au-Prince and Cap-Haïtien suffer from low employment accessibility as measured by the percentage of the population that travels beyond their identified home cluster (1 km radius) during the day. The data from the origin-destination matrices suggest that only 42 and 40 percent of the population are considered to be commuters in Port-au-Prince and Cap-Haïtien respectively.</p></div>","PeriodicalId":37901,"journal":{"name":"Development Engineering","volume":"3 ","pages":"Pages 133-165"},"PeriodicalIF":0.0000,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.deveng.2018.03.002","citationCount":"31","resultStr":"{\"title\":\"A trip to work: Estimation of origin and destination of commuting patterns in the main metropolitan regions of Haiti using CDR\",\"authors\":\"Guilherme Augusto Zagatti , Miguel Gonzalez , Paolo Avner , Nancy Lozano-Gracia , Christopher J. Brooks , Maximilian Albert , Jonathan Gray , Sarah Elizabeth Antos , Priya Burci , Elisabeth zu Erbach-Schoenberg , Andrew J. Tatem , Erik Wetter , Linus Bengtsson\",\"doi\":\"10.1016/j.deveng.2018.03.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The rapid, unplanned urbanisation in Haiti creates a series of urban mobility challenges which can contribute to job market fragmentation and decrease the quality of life in the city. Data on population and job distributions, and on home-work commuting patterns in major urban centres are scarce. The most recent census took place in 2003 and events such as the 2010 earthquake have caused major redistributions of the population. In this data scarce context, our work takes advantage of nationwide de-identified Call Detail Records (CDR) from the main mobile operator in the country to investigate night and daytime populations densities and commuting patterns. We use a non-supervised learning algorithm to identify meaningful locations for individuals. These locations are then labelled according to a scoring criteria. The labelled locations are distributed in a grid with cells measuring 500 × 500 m in order to aggregate the individual level data and to create origin-destination matrices of weighted connections between home and work locations. The results suggest that labor markets are fragmented in Haiti. The two main urban centres, Port-au-Prince and Cap-Haïtien suffer from low employment accessibility as measured by the percentage of the population that travels beyond their identified home cluster (1 km radius) during the day. The data from the origin-destination matrices suggest that only 42 and 40 percent of the population are considered to be commuters in Port-au-Prince and Cap-Haïtien respectively.</p></div>\",\"PeriodicalId\":37901,\"journal\":{\"name\":\"Development Engineering\",\"volume\":\"3 \",\"pages\":\"Pages 133-165\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.deveng.2018.03.002\",\"citationCount\":\"31\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Development Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352728517300866\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Economics, Econometrics and Finance\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Development Engineering","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352728517300866","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Economics, Econometrics and Finance","Score":null,"Total":0}
A trip to work: Estimation of origin and destination of commuting patterns in the main metropolitan regions of Haiti using CDR
The rapid, unplanned urbanisation in Haiti creates a series of urban mobility challenges which can contribute to job market fragmentation and decrease the quality of life in the city. Data on population and job distributions, and on home-work commuting patterns in major urban centres are scarce. The most recent census took place in 2003 and events such as the 2010 earthquake have caused major redistributions of the population. In this data scarce context, our work takes advantage of nationwide de-identified Call Detail Records (CDR) from the main mobile operator in the country to investigate night and daytime populations densities and commuting patterns. We use a non-supervised learning algorithm to identify meaningful locations for individuals. These locations are then labelled according to a scoring criteria. The labelled locations are distributed in a grid with cells measuring 500 × 500 m in order to aggregate the individual level data and to create origin-destination matrices of weighted connections between home and work locations. The results suggest that labor markets are fragmented in Haiti. The two main urban centres, Port-au-Prince and Cap-Haïtien suffer from low employment accessibility as measured by the percentage of the population that travels beyond their identified home cluster (1 km radius) during the day. The data from the origin-destination matrices suggest that only 42 and 40 percent of the population are considered to be commuters in Port-au-Prince and Cap-Haïtien respectively.
Development EngineeringEconomics, Econometrics and Finance-Economics, Econometrics and Finance (all)
CiteScore
4.90
自引率
0.00%
发文量
11
审稿时长
31 weeks
期刊介绍:
Development Engineering: The Journal of Engineering in Economic Development (Dev Eng) is an open access, interdisciplinary journal applying engineering and economic research to the problems of poverty. Published studies must present novel research motivated by a specific global development problem. The journal serves as a bridge between engineers, economists, and other scientists involved in research on human, social, and economic development. Specific topics include: • Engineering research in response to unique constraints imposed by poverty. • Assessment of pro-poor technology solutions, including field performance, consumer adoption, and end-user impacts. • Novel technologies or tools for measuring behavioral, economic, and social outcomes in low-resource settings. • Hypothesis-generating research that explores technology markets and the role of innovation in economic development. • Lessons from the field, especially null results from field trials and technical failure analyses. • Rigorous analysis of existing development "solutions" through an engineering or economic lens. Although the journal focuses on quantitative, scientific approaches, it is intended to be suitable for a wider audience of development practitioners and policy makers, with evidence that can be used to improve decision-making. It also will be useful for engineering and applied economics faculty who conduct research or teach in "technology for development."