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Estimating the spatial distribution of the population of Riyadh, Saudi Arabia using remotely sensed built land cover and height data

Estimating the spatial distribution of the population of Riyadh, Saudi Arabia using remotely sensed built land cover and height data
Estimating the spatial distribution of the population of Riyadh, Saudi Arabia using remotely sensed built land cover and height data
This paper investigates the use of Landsat ETM+, remotely sensed height data, ward-level census population, and dwelling units to downscale population in Riyadh, Saudi Arabia. Regression analysis is used to model the relationship between density of dwelling units and built area proportion at the block level and the coefficients used to downscale density of dwelling units to the parcel level. The population distribution is estimated based on average population per dwelling unit. Seven models were fitted and compared. First, a conventional approach, using ISODATA-classified built land cover alone as a covariate, is used as a benchmark against which to evaluate six more sophisticated models. The conventional model results in low accuracy measured by overall relative error (ORE) (+116%). Approaches for potentially increasing accuracy are explored, incorporating above-surface height data into the downscaling process. These include masking out zero and near-zero height areas when estimating built area; using height to estimate the number of floors; replacing the ISODATA model with a support vector machine; estimating volume-adjusted habitable space; stratifying the study area into different building categories; and preservation of the dependent variable for the best model. These approaches result in large increases in accuracy in the density of dwelling unit estimates. However, while the height data accounts for the vertical dimension (primarily through the number of floors), it is not possible to account for variation in dwelling density which arises due to other factors such as living standards, affluence and other spatially varying factors, without further data

0198-9715
167-176
Al-Ahmadi, Mohammed
ff5aca26-d409-49ec-8f7b-cb6af18ba92a
Atkinson, Peter
96e96579-56fe-424d-a21c-17b6eed13b0b
Martin, David
e5c52473-e9f0-4f09-b64c-fa32194b162f
Al-Ahmadi, Mohammed
ff5aca26-d409-49ec-8f7b-cb6af18ba92a
Atkinson, Peter
96e96579-56fe-424d-a21c-17b6eed13b0b
Martin, David
e5c52473-e9f0-4f09-b64c-fa32194b162f

Al-Ahmadi, Mohammed, Atkinson, Peter and Martin, David (2013) Estimating the spatial distribution of the population of Riyadh, Saudi Arabia using remotely sensed built land cover and height data Computers, Environment and Urban Systems, 41, pp. 167-176. (doi:10.1016/j.compenvurbsys.2013.06.002).

Record type: Article

Abstract

This paper investigates the use of Landsat ETM+, remotely sensed height data, ward-level census population, and dwelling units to downscale population in Riyadh, Saudi Arabia. Regression analysis is used to model the relationship between density of dwelling units and built area proportion at the block level and the coefficients used to downscale density of dwelling units to the parcel level. The population distribution is estimated based on average population per dwelling unit. Seven models were fitted and compared. First, a conventional approach, using ISODATA-classified built land cover alone as a covariate, is used as a benchmark against which to evaluate six more sophisticated models. The conventional model results in low accuracy measured by overall relative error (ORE) (+116%). Approaches for potentially increasing accuracy are explored, incorporating above-surface height data into the downscaling process. These include masking out zero and near-zero height areas when estimating built area; using height to estimate the number of floors; replacing the ISODATA model with a support vector machine; estimating volume-adjusted habitable space; stratifying the study area into different building categories; and preservation of the dependent variable for the best model. These approaches result in large increases in accuracy in the density of dwelling unit estimates. However, while the height data accounts for the vertical dimension (primarily through the number of floors), it is not possible to account for variation in dwelling density which arises due to other factors such as living standards, affluence and other spatially varying factors, without further data

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More information

Published date: 2013
Organisations: Geography & Environment, PHEW – S (Spatial analysis and modelling), Population, Health & Wellbeing (PHeW)

Identifiers

Local EPrints ID: 356574
URI: https://eprints.soton.ac.uk/id/eprint/356574
ISSN: 0198-9715
PURE UUID: adc7602c-f680-4b0e-b138-84f348567eb4
ORCID for David Martin: ORCID iD orcid.org/0000-0003-0397-0769

Catalogue record

Date deposited: 16 Sep 2013 13:12
Last modified: 18 Jul 2017 03:38

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