Quantifying Cities for Sustainable Development: Transforming urban data collection to support research and policy making in developing countries

量化城市促进可持续发展：转变城市数据收集以支持发展中国家的研究和政策制定

• 批准号: ES/R009848/1
• 负责人: Sean Fox
• 金额: $ 27.88万
• 依托单位: University of Bristol
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=ES%2FR009848%2F1
• 关键词: Quantifying; Cities; Sustainable; Development; Transforming

Our project addresses a critical gap in social research methodology that has important implications for combating urban poverty and promoting sustainable development in low and middle-income countries. Simply put, we're creating a low-cost tool for gathering critical information about urban population dynamics in cities experiencing rapid spatial-demographic and socioeconomic change. Such information is vital to the success of urban planning and development initiatives, as well as disaster relief efforts. By improving the information base of the actors involved in such activities we aim to improve the lives of urban dwellers across the developing world, particularly the poorest and most vulnerable. The key output for the project will be a freely available 'City Sampling Toolkit' that provides detailed instructions and opensource software tools for replicating the approach at various spatial scales. Our research is motivated by the growing recognition that cities are critical arenas for action in global efforts to tackle poverty and transition towards more environmentally sustainable economic growth. Between now and 2050 the global urban population is projected to grow by over 2 billion, with the overwhelming majority of this growth taking place in low and middle-income countries in Africa and Asia. Developing evidence-based policies for managing this growth is an urgent task. As UN Secretary General Ban Ki Moon has observed: "Cities are increasingly the home of humanity. They are central to climate action, global prosperity, peace and human rights...To transform our world, we must transform its cities." Unfortunately, even basic data about urban populations are lacking in many of the fastest growing cities of the world. Existing methods for gathering vital information, including censuses and sample surveys, have critical limitations in urban areas experiencing rapid change. And 'big data' approaches are not an adequate substitute for representative population data when it comes to urban planning and policymaking. We will overcome these limitations through a combination of conceptual innovation and creative integration of novel tools and techniques that have been developed for sampling, surveying and estimating the characteristics of populations that are difficult to enumerate. This, in turn, will help us capture the large (and sometimes uniquely vulnerable) 'hidden populations' in cities missed by traditional approaches.By using freely available satellite imagery, we can get an idea of the current shape of a rapidly changing city and create a 'sampling frame' from which we then identify respondents for our survey. Importantly, and in contrast with previous approaches, we aren't simply going to count official city residents. We are interested in understanding the characteristics of the actually present population, including recent migrants, temporary residents, and those living in informal or illegal settlements, who are often not considered formal residents in official enumeration exercises. In other words, our 'inclusion criterion' for the survey exercise is presence not residence. By adopting this approach, we hope to capture a more accurate picture of city populations. We will also limit the length of our survey questionnaire to maximise responses and then use novel statistical techniques to reconstruct a rich statistical portrait that reflects a wide range of demographic and socioeconomic information. We will pilot our methodology in a city in Pakistan, which recently completed a national census exercise that has generated some controversy with regard to the accuracy of urban population counts. To our knowledge this would be the first project ever to pilot and validate a new sampling and survey methodology at the city scale in a developing country.

我们的项目解决了社会研究方法上的一个关键空白，这对中低收入国家消除城市贫困和促进可持续发展具有重要意义。简单地说，我们正在创造一种低成本的工具，用于收集城市人口动态的关键信息，这些城市正在经历快速的空间人口和社会经济变化。这类信息对城市规划和发展倡议以及救灾努力的成功至关重要。通过改善参与此类活动的行动者的信息库，我们的目标是改善整个发展中世界城市居民的生活，特别是最贫穷和最脆弱的城市居民的生活。该项目的主要产出将是一个免费的“城市采样工具包”，该工具包提供了详细的说明和开源软件工具，用于在各种空间尺度上复制该方法。我们研究的动机是越来越多的人认识到，城市是全球努力解决贫困和向环境更可持续的经济增长过渡的关键领域。从现在到2050年，预计全球城市人口将增加20多亿，其中绝大多数将发生在非洲和亚洲的低收入和中等收入国家。制定以证据为基础的政策来管理这种增长是一项紧迫的任务。正如联合国秘书长潘基文所说：“城市日益成为人类的家园。它们是气候行动、全球繁荣、和平与人权的核心……要改变我们的世界，我们必须改变城市。”不幸的是，在世界上许多发展最快的城市中，连关于城市人口的基本数据都缺乏。收集重要资料的现有方法，包括人口普查和抽样调查，在经历迅速变化的城市地区具有严重的局限性。在城市规划和政策制定方面，“大数据”方法并不能充分替代具有代表性的人口数据。我们将通过概念创新和创造性地整合为抽样、调查和估计难以枚举的人口特征而开发的新工具和技术的结合来克服这些限制。反过来，这将帮助我们捕捉到传统方法忽略的城市中大量（有时是特别脆弱的）“隐藏人口”。通过使用免费的卫星图像，我们可以了解一个快速变化的城市的当前形状，并创建一个“采样框架”，然后我们从中确定调查的受访者。重要的是，与之前的方法不同，我们不是简单地统计官方城市居民。我们感兴趣的是了解实际存在的人口的特征，包括最近的移民、临时居民和那些生活在非正式或非法定居点的人，他们在官方的统计工作中往往不被视为正式居民。换句话说，我们调查的“纳入标准”是存在而不是居住地。通过采用这种方法，我们希望能更准确地了解城市人口。我们还将限制调查问卷的长度，以最大限度地提高回应，然后使用新颖的统计技术来重建一个丰富的统计肖像，反映了广泛的人口和社会经济信息。我们将在巴基斯坦的一个城市试用我们的方法，该城市最近完成了一次全国人口普查，在城市人口统计的准确性方面产生了一些争议。据我们所知，这将是有史以来第一个在发展中国家城市规模上试点和验证新的抽样和调查方法的项目。

项目成果

Modelling and simulating 'informal urbanization': An integrated agent-based and cellular automata model of urban residential growth in Ghana

• DOI: 10.1177/23998083211068843
• 发表时间: 2022-01-12
• 期刊: ENVIRONMENT AND PLANNING B-URBAN ANALYTICS AND CITY SCIENCE
• 影响因子: 3.5
• 作者: Agyemang, Felix S. K.;Silva, Elisabete;Fox, Sean
• 通讯作者: Fox, Sean

sj-pdf-1-epb-10.1177_23998083211068843 - Supplemental Material for Modelling and simulating 'informal urbanization': An integrated agent-based and cellular automata model of urban residential growth in Ghana.

sj-pdf-1-epb-10.1177_23998083211068843 - 用于建模和模拟“非正式城市化”的补充材料：加纳城市住宅增长的基于代理和元胞自动机的集成模型。

• DOI: 10.25384/sage.18703336
• 发表时间: 2022
• 作者: Agyemang F

Mapping Urban Living Standards and Economic Activity in Developing Countries with Energy Data

利用能源数据绘制发展中国家的城市生活水平和经济活动图

• DOI: 10.2139/ssrn.4154318
• 发表时间: 2022
• 期刊: SSRN Electronic Journal
• 作者: Fox S

Mapping urban living standards and economic activity in developing countries with energy data.

• DOI: 10.1371/journal.pone.0291824
• 发表时间: 2023
• 期刊: PloS one
• 影响因子: 3.7