{"title":"按机型划分的通用航空流动业务空间分布模型","authors":"Tao Li, A. Trani","doi":"10.1109/ICNSURV.2018.8384877","DOIUrl":null,"url":null,"abstract":"A two-level model is developed to estimate the spatial distribution of itinerant General Aviation (GA) operations by four aircraft engine types (single-engine piston, piston, turboprop, and jet). In the first level, a logit model is used to model the state-choice behaviors, that is, how the GA operations at an origin airport distribute among neighboring states. The impact of social-economic factors on the spatial distribution is considered in the first-level model. A gravity-based model is used as the second-level model to assign the projected operations to a state among the airports within the state. We applied the model to estimate the spatial distribution of GA operations among TAF airports in 2008, and compared the estimation results with the observed statistics. The comparison shows that the model estimates are generally consistent with the observations.","PeriodicalId":112779,"journal":{"name":"2018 Integrated Communications, Navigation, Surveillance Conference (ICNS)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Modeling spatial distribution of itinerant General Aviation operations by aircraft type\",\"authors\":\"Tao Li, A. Trani\",\"doi\":\"10.1109/ICNSURV.2018.8384877\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A two-level model is developed to estimate the spatial distribution of itinerant General Aviation (GA) operations by four aircraft engine types (single-engine piston, piston, turboprop, and jet). In the first level, a logit model is used to model the state-choice behaviors, that is, how the GA operations at an origin airport distribute among neighboring states. The impact of social-economic factors on the spatial distribution is considered in the first-level model. A gravity-based model is used as the second-level model to assign the projected operations to a state among the airports within the state. We applied the model to estimate the spatial distribution of GA operations among TAF airports in 2008, and compared the estimation results with the observed statistics. The comparison shows that the model estimates are generally consistent with the observations.\",\"PeriodicalId\":112779,\"journal\":{\"name\":\"2018 Integrated Communications, Navigation, Surveillance Conference (ICNS)\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 Integrated Communications, Navigation, Surveillance Conference (ICNS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNSURV.2018.8384877\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Integrated Communications, Navigation, Surveillance Conference (ICNS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNSURV.2018.8384877","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modeling spatial distribution of itinerant General Aviation operations by aircraft type
A two-level model is developed to estimate the spatial distribution of itinerant General Aviation (GA) operations by four aircraft engine types (single-engine piston, piston, turboprop, and jet). In the first level, a logit model is used to model the state-choice behaviors, that is, how the GA operations at an origin airport distribute among neighboring states. The impact of social-economic factors on the spatial distribution is considered in the first-level model. A gravity-based model is used as the second-level model to assign the projected operations to a state among the airports within the state. We applied the model to estimate the spatial distribution of GA operations among TAF airports in 2008, and compared the estimation results with the observed statistics. The comparison shows that the model estimates are generally consistent with the observations.