预测小区域人口和土地利用变化的开源模型

IF 3.3 3区 地球科学 Q1 GEOGRAPHY
Nik Lomax, Andrew P. Smith, Luke Archer, Alistair Ford, James Virgo
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引用次数: 7

摘要

人口和家庭的规模、组成和空间分布对支持人口所需的基础设施的需求、发展和交付产生重大影响。基础设施涵盖了广泛的领域,包括能源、交通和水,每个领域都有自己的一套不同规模的空间集水区。需要进行人口预测,以评估未来的潜在需求;然而,官方预测通常没有提供基础设施规划所需的高水平空间分辨率。此外,编制定制的人口预测,通常包括未来可能的人口变化的一系列情景,是一项专业的、资源密集的工作,因此在基础设施发展项目中经常缺失。在本文中,我们提出这样的人口预测应该是基础设施规划的核心,并提出了一套可用于进行人口预测工作的开源模型,从而提供了填补已确定差距所需的工具。我们利用英国的一个案例研究来举例说明如何使用我们的模型评估一系列情景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

An Open-Source Model for Projecting Small Area Demographic and Land-Use Change

An Open-Source Model for Projecting Small Area Demographic and Land-Use Change

The size, composition, and spatial distribution of both people and households have a substantial impact on the demand for and development and delivery of infrastructure required to support the population. Infrastructure encompasses a wide range of domains including energy, transport, and water, each of which has its own set of spatial catchments at differing scales. Demographic projections are required to assess potential future demand; however, official projections are usually not provided at a high level of spatial resolution required for infrastructure planning. Furthermore, generating bespoke demographic projections, often incorporating a range of scenarios of possible future demographic change is a specialist, resource intensive job and as such is often missing from infrastructure development projects. In this paper we make the case that such demographic projections should be at the heart of infrastructure planning and present a set of open-source models which can be used to undertake this demographic projection work, thus providing the tools needed to fill the identified gap. We make use of a case study for the United Kingdom to exemplify how a range of scenarios can be assessed using our model.

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来源期刊
CiteScore
8.70
自引率
5.60%
发文量
40
期刊介绍: First in its specialty area and one of the most frequently cited publications in geography, Geographical Analysis has, since 1969, presented significant advances in geographical theory, model building, and quantitative methods to geographers and scholars in a wide spectrum of related fields. Traditionally, mathematical and nonmathematical articulations of geographical theory, and statements and discussions of the analytic paradigm are published in the journal. Spatial data analyses and spatial econometrics and statistics are strongly represented.
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