{"title":"在微观层面人口普查分解中使用基于地址的非对称映射的好处","authors":"Denis Reiter, Mathias Jehling, R. Hecht","doi":"10.5194/agile-giss-4-38-2023","DOIUrl":null,"url":null,"abstract":"Abstract. Dasymetric mapping is a well-known technique when attempting to refine census data spatially and/or temporally. Existing approaches in micro-level census disaggregation make use of building areas or volumes in the mapping process. In an empirical error comparison it is shown that using additional address data rather than only building footprints or 3D models can substantially reduce dislocation of residential population. We propose the use of address points as a geometric representation unit for a more refined census disaggregation method in the future.\n","PeriodicalId":116168,"journal":{"name":"AGILE: GIScience Series","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Benefits of using address-based dasymetric mapping in micro-level census disaggregation\",\"authors\":\"Denis Reiter, Mathias Jehling, R. Hecht\",\"doi\":\"10.5194/agile-giss-4-38-2023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract. Dasymetric mapping is a well-known technique when attempting to refine census data spatially and/or temporally. Existing approaches in micro-level census disaggregation make use of building areas or volumes in the mapping process. In an empirical error comparison it is shown that using additional address data rather than only building footprints or 3D models can substantially reduce dislocation of residential population. We propose the use of address points as a geometric representation unit for a more refined census disaggregation method in the future.\\n\",\"PeriodicalId\":116168,\"journal\":{\"name\":\"AGILE: GIScience Series\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"AGILE: GIScience Series\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5194/agile-giss-4-38-2023\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"AGILE: GIScience Series","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5194/agile-giss-4-38-2023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Benefits of using address-based dasymetric mapping in micro-level census disaggregation
Abstract. Dasymetric mapping is a well-known technique when attempting to refine census data spatially and/or temporally. Existing approaches in micro-level census disaggregation make use of building areas or volumes in the mapping process. In an empirical error comparison it is shown that using additional address data rather than only building footprints or 3D models can substantially reduce dislocation of residential population. We propose the use of address points as a geometric representation unit for a more refined census disaggregation method in the future.