德国正在经历城市增长还是郊区增长?对比长期存在的和新的城市梯度分类

IF 5.4 2区 地球科学 Q1 GEOGRAPHY
Tamilwai J. Kolowa , Matthias Weigand , Ines Standfuß , Sebastian Klüsener , Nik Lomax , Hannes Taubenböck
{"title":"德国正在经历城市增长还是郊区增长?对比长期存在的和新的城市梯度分类","authors":"Tamilwai J. Kolowa ,&nbsp;Matthias Weigand ,&nbsp;Ines Standfuß ,&nbsp;Sebastian Klüsener ,&nbsp;Nik Lomax ,&nbsp;Hannes Taubenböck","doi":"10.1016/j.apgeog.2025.103779","DOIUrl":null,"url":null,"abstract":"<div><div>Understanding population shifts along urban-rural gradients is crucial for informed decision-making in sustainable spatial planning. Empirical accounts of urbanization and suburbanization rely on classification choices, typically derived from administrative units. Recently, novel classification approaches based on remote sensing and high-resolution population data have gained relevance. This trend, driven by methodological advancements, raises the question of whether these new approaches yield similar or different results in comparative analyses along urban-rural gradients. Our paper explores how classification choices affect assessments of population trends along the urban-rural gradient at both the national and subnational regional scales. We contrast three urban gradient classifications to analyze population change in 50 German metropolitan regions from 2011 to 2022. Results indicate that, at the national scale, observed trends in urban, suburban, and peri-urban areas are consistent across all classifications. For Germany, we find that urban areas have registered higher growth rates than suburban and peri-urban areas across all classifications. However, at the regional scale, observed trends partially depend on classification choices, suggesting that regional findings are particularly sensitive to the chosen classification scheme. The methodological framework presented here can also be applied to other geographical contexts for which similar data are available.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"185 ","pages":"Article 103779"},"PeriodicalIF":5.4000,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Is Germany experiencing urban or suburban growth? Contrasting long-standing and novel urban gradient classifications\",\"authors\":\"Tamilwai J. Kolowa ,&nbsp;Matthias Weigand ,&nbsp;Ines Standfuß ,&nbsp;Sebastian Klüsener ,&nbsp;Nik Lomax ,&nbsp;Hannes Taubenböck\",\"doi\":\"10.1016/j.apgeog.2025.103779\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Understanding population shifts along urban-rural gradients is crucial for informed decision-making in sustainable spatial planning. Empirical accounts of urbanization and suburbanization rely on classification choices, typically derived from administrative units. Recently, novel classification approaches based on remote sensing and high-resolution population data have gained relevance. This trend, driven by methodological advancements, raises the question of whether these new approaches yield similar or different results in comparative analyses along urban-rural gradients. Our paper explores how classification choices affect assessments of population trends along the urban-rural gradient at both the national and subnational regional scales. We contrast three urban gradient classifications to analyze population change in 50 German metropolitan regions from 2011 to 2022. Results indicate that, at the national scale, observed trends in urban, suburban, and peri-urban areas are consistent across all classifications. For Germany, we find that urban areas have registered higher growth rates than suburban and peri-urban areas across all classifications. However, at the regional scale, observed trends partially depend on classification choices, suggesting that regional findings are particularly sensitive to the chosen classification scheme. The methodological framework presented here can also be applied to other geographical contexts for which similar data are available.</div></div>\",\"PeriodicalId\":48396,\"journal\":{\"name\":\"Applied Geography\",\"volume\":\"185 \",\"pages\":\"Article 103779\"},\"PeriodicalIF\":5.4000,\"publicationDate\":\"2025-09-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Geography\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0143622825002747\",\"RegionNum\":2,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GEOGRAPHY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Geography","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0143622825002747","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOGRAPHY","Score":null,"Total":0}
引用次数: 0

摘要

了解城乡梯度的人口变化对可持续空间规划的明智决策至关重要。城市化和郊区化的实证研究依赖于分类选择,通常来源于行政单位。近年来,基于遥感和高分辨率人口数据的新型分类方法得到了广泛的应用。这种趋势,由方法的进步驱动,提出了一个问题,即这些新方法在城乡梯度比较分析中是否产生相似或不同的结果。本文探讨了分类选择在国家和次国家区域尺度上如何影响城乡梯度的人口趋势评估。我们对比了三种城市梯度分类,分析了2011年至2022年德国50个大都市区的人口变化。结果表明,在全国范围内,观察到的城市、郊区和城郊地区的趋势在所有分类中都是一致的。就德国而言,我们发现在所有分类中,城市地区的增长率都高于郊区和近郊地区。然而,在区域尺度上,观察到的趋势部分取决于分类选择,这表明区域调查结果对所选择的分类方案特别敏感。这里提出的方法框架也可适用于其他有类似数据的地理环境。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Is Germany experiencing urban or suburban growth? Contrasting long-standing and novel urban gradient classifications
Understanding population shifts along urban-rural gradients is crucial for informed decision-making in sustainable spatial planning. Empirical accounts of urbanization and suburbanization rely on classification choices, typically derived from administrative units. Recently, novel classification approaches based on remote sensing and high-resolution population data have gained relevance. This trend, driven by methodological advancements, raises the question of whether these new approaches yield similar or different results in comparative analyses along urban-rural gradients. Our paper explores how classification choices affect assessments of population trends along the urban-rural gradient at both the national and subnational regional scales. We contrast three urban gradient classifications to analyze population change in 50 German metropolitan regions from 2011 to 2022. Results indicate that, at the national scale, observed trends in urban, suburban, and peri-urban areas are consistent across all classifications. For Germany, we find that urban areas have registered higher growth rates than suburban and peri-urban areas across all classifications. However, at the regional scale, observed trends partially depend on classification choices, suggesting that regional findings are particularly sensitive to the chosen classification scheme. The methodological framework presented here can also be applied to other geographical contexts for which similar data are available.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Applied Geography
Applied Geography GEOGRAPHY-
CiteScore
8.00
自引率
2.00%
发文量
134
期刊介绍: Applied Geography is a journal devoted to the publication of research which utilizes geographic approaches (human, physical, nature-society and GIScience) to resolve human problems that have a spatial dimension. These problems may be related to the assessment, management and allocation of the world physical and/or human resources. The underlying rationale of the journal is that only through a clear understanding of the relevant societal, physical, and coupled natural-humans systems can we resolve such problems. Papers are invited on any theme involving the application of geographical theory and methodology in the resolution of human problems.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信