The effects of the Maputo ring road on the quantity and quality of nearby housing

Research output: Working paperResearch

Standard

The effects of the Maputo ring road on the quantity and quality of nearby housing. / Fisker, Peter Kielberg; Malmgren-Hansen, David; Sohnesen, Thomas Pave.

2019.

Research output: Working paperResearch

Harvard

Fisker, PK, Malmgren-Hansen, D & Sohnesen, TP 2019 'The effects of the Maputo ring road on the quantity and quality of nearby housing'. https://doi.org/10.35188/UNU-WIDER/2019/747-7

APA

Fisker, P. K., Malmgren-Hansen, D., & Sohnesen, T. P. (2019). The effects of the Maputo ring road on the quantity and quality of nearby housing. W I D E R. Working Papers No. 2019/111 https://doi.org/10.35188/UNU-WIDER/2019/747-7

Vancouver

Fisker PK, Malmgren-Hansen D, Sohnesen TP. The effects of the Maputo ring road on the quantity and quality of nearby housing. 2019. https://doi.org/10.35188/UNU-WIDER/2019/747-7

Author

Fisker, Peter Kielberg ; Malmgren-Hansen, David ; Sohnesen, Thomas Pave. / The effects of the Maputo ring road on the quantity and quality of nearby housing. 2019. (W I D E R. Working Papers; No. 2019/111).

Bibtex

@techreport{3f7c0c8697df4a85aa0f0e29cf7f1c8d,
title = "The effects of the Maputo ring road on the quantity and quality of nearby housing",
abstract = "Using convolutional neural networks applied to satellite images covering a 25 km x 12 km rectangle on the northern outskirts of Greater Maputo, we detect and classify buildings from 2010 and 2018 in order to compare the development in quantity and quality of buildings from before and after construction of a major section of ring road. In addition, we analyse how the effects vary by distance to the road and conclude that the area has seen large overall growth in both quantity and quality of housing, but it is not possible to distinguish growth close to the road from general urban growth. Finally, the paper contributes methodologically to a growing strand of literature focused on combining machine-learning image recognition and the availability of highresolution satellite images. We examine the extent to which it is possible to exploit these methods to analyse changes over time and thus provide an alternative (or complement) to traditional impact analyses.",
keywords = "Faculty of Social Sciences, Mozambique, infrastructure, housing convolutional neural networks, remote sensing, impact assessment, O18q, R14",
author = "Fisker, {Peter Kielberg} and David Malmgren-Hansen and Sohnesen, {Thomas Pave}",
year = "2019",
doi = "10.35188/UNU-WIDER/2019/747-7",
language = "English",
series = "W I D E R. Working Papers",
number = "2019/111",
type = "WorkingPaper",

}

RIS

TY - UNPB

T1 - The effects of the Maputo ring road on the quantity and quality of nearby housing

AU - Fisker, Peter Kielberg

AU - Malmgren-Hansen, David

AU - Sohnesen, Thomas Pave

PY - 2019

Y1 - 2019

N2 - Using convolutional neural networks applied to satellite images covering a 25 km x 12 km rectangle on the northern outskirts of Greater Maputo, we detect and classify buildings from 2010 and 2018 in order to compare the development in quantity and quality of buildings from before and after construction of a major section of ring road. In addition, we analyse how the effects vary by distance to the road and conclude that the area has seen large overall growth in both quantity and quality of housing, but it is not possible to distinguish growth close to the road from general urban growth. Finally, the paper contributes methodologically to a growing strand of literature focused on combining machine-learning image recognition and the availability of highresolution satellite images. We examine the extent to which it is possible to exploit these methods to analyse changes over time and thus provide an alternative (or complement) to traditional impact analyses.

AB - Using convolutional neural networks applied to satellite images covering a 25 km x 12 km rectangle on the northern outskirts of Greater Maputo, we detect and classify buildings from 2010 and 2018 in order to compare the development in quantity and quality of buildings from before and after construction of a major section of ring road. In addition, we analyse how the effects vary by distance to the road and conclude that the area has seen large overall growth in both quantity and quality of housing, but it is not possible to distinguish growth close to the road from general urban growth. Finally, the paper contributes methodologically to a growing strand of literature focused on combining machine-learning image recognition and the availability of highresolution satellite images. We examine the extent to which it is possible to exploit these methods to analyse changes over time and thus provide an alternative (or complement) to traditional impact analyses.

KW - Faculty of Social Sciences

KW - Mozambique

KW - infrastructure

KW - housing convolutional neural networks

KW - remote sensing

KW - impact assessment

KW - O18q

KW - R14

U2 - 10.35188/UNU-WIDER/2019/747-7

DO - 10.35188/UNU-WIDER/2019/747-7

M3 - Working paper

T3 - W I D E R. Working Papers

BT - The effects of the Maputo ring road on the quantity and quality of nearby housing

ER -

ID: 248555972