Population Estimation Using a 3D City Model: A Multi-Scale Country-Wide Study in the Netherlands

Biljecki, Filip; Ohori, Ken Arroyo; Ledoux, Hugo; Peters, Ravi; Stoter, J.E.

doi:10.1371/journal.pone.0156808

Cited by 61 publications

(62 citation statements)

References 119 publications

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“…Similar accuracy limitations have been reported in the production of the GHS-POP and the HRSL population datasets [10,17]. Even when several local studies have demonstrated that information on the building use has the potential to improve population distribution results [61,62], this remains a major source of limitation in the production of global population datasets, as it is not possible to derive detailed semantic information on the building use through remote sensing methodologies. Population datasets such as LandScan and WorldPop integrate land use and land cover covariates to improve their results; however, as mentioned above, this introduces global transferability limitations and applicability restrictions.…”

Section: Discussionmentioning

confidence: 54%

New Perspectives for Mapping Global Population Distribution Using World Settlement Footprint Products

et al. 2019

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In the production of gridded population maps, remotely sensed, human settlement datasets rank among the most important geographical factors to estimate population densities and distributions at regional and global scales. Within this context, the German Aerospace Centre (DLR) has developed a new suite of global layers, which accurately describe the built-up environment and its characteristics at high spatial resolution: (i) the World Settlement Footprint 2015 layer (WSF-2015), a binary settlement mask; and (ii) the experimental World Settlement Footprint Density 2015 layer (WSF-2015-Density), representing the percentage of impervious surface. This research systematically compares the effectiveness of both layers for producing population distribution maps through a dasymetric mapping approach in nine low-, middle-, and highly urbanised countries. Results indicate that the WSF-2015-Density layer can produce population distribution maps with higher qualitative and quantitative accuracies in comparison to the already established binary approach, especially in those countries where a good percentage of building structures have been identified within the rural areas. Moreover, our results suggest that population distribution accuracies could substantially improve through the dynamic preselection of the input layers and the correct parameterisation of the Settlement Size Complexity (SSC) index.

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Section: Discussionmentioning

confidence: 54%

New Perspectives for Mapping Global Population Distribution Using World Settlement Footprint Products

et al. 2019

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“…Three-dimensional information from buildings (e.g., area and height of a building) is conducive to population estimation on a fine scale [43,44]. Building height could not objectively reflect the distribution of the population because of the influence of building types and building characteristics.…”

Section: Establishment Of Population Disaggregation Modelmentioning

confidence: 99%

Geospatial Disaggregation of Population Data in Supporting SDG Assessments: A Case Study from Deqing County, China

Qiu

Zhao

Fan

et al. 2019

IJGI

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Quantitative assessments and dynamic monitoring of indicators based on fine-scale population data are necessary to support the implementation of the United Nations (UN) 2030 Agenda and to comprehensively achieve its 17 Sustainable Development Goals (SDGs). However, most population data are collected by administrative units, and it is difficult to reflect true distribution and uniformity in space. To solve this problem, based on fine building information, a geospatial disaggregation method of population data for supporting SDG assessments is presented in this paper. First, Deqing County in China, which was divided into residential areas and nonresidential areas according to the idea of dasymetric mapping, was selected as the study area. Then, the town administrative areas were taken as control units, building area and number of floors were used as weighting factors to establish the disaggregation model, and population data with a resolution of 30 m in Deqing County in 2016 were obtained. After analyzing the statistical population of 160 villages and the disaggregation results, we found that the global average accuracy was 87.08%. Finally, by using the disaggregation population data, indicators 3.8.1, 4.a.1, and 9.1.1 were selected to conduct an accessibility analysis and a buffer analysis in a quantitative assessment of the SDGs. The results showed that the SDG measurement and assessment results based on the disaggregated population data were more accurate and effective than the results obtained using the traditional method.

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“…The research results from the regression analysis of Lwin and Murayama [47] and Biljecki et al [48] suggested that building floor space has a strong, positive, and linear correlation with population. This study found that the total building floor space within a particular geographic area has a meaningful association with the number of the population in the area.…”

Section: Introductionmentioning

confidence: 99%

Using Building Floor Space for Station Area Population and Employment Estimation

et al. 2019

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Analyzing population and employment sizes at the local finer geographic scale of transit station areas offers valuable insights for cities in terms of developing better decision-making skills to support transit-oriented development. Commonly, the station area population and employment have been derived from census tract or even block data. Unfortunately, such detailed census data are hardly available and difficult to access in cities of developing countries. To address this problem, this paper explores an alternative technique in remote estimation of population and employment by using building floor space derived from an official administrative geographic information system (GIS) dataset. Based on the assumption that building floor space is a proxy to a number of residents and workers, we investigate to what extent they can be used for estimating the station area population and employment. To assess the model, we employ five station areas with heterogeneous environments in Tokyo as our empirical case study. The estimated population and employment are validated with the actual population and employment as reported in the census. The results indicate that building floor space, together with the city level aggregate information of building morphology, the density coefficient, demographic attributes, and real estate statistics, are able to generate a reasonable estimation.

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Population Estimation Using a 3D City Model: A Multi-Scale Country-Wide Study in the Netherlands

Cited by 61 publications

References 119 publications

New Perspectives for Mapping Global Population Distribution Using World Settlement Footprint Products

New Perspectives for Mapping Global Population Distribution Using World Settlement Footprint Products

Geospatial Disaggregation of Population Data in Supporting SDG Assessments: A Case Study from Deqing County, China

Using Building Floor Space for Station Area Population and Employment Estimation

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