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A pixel level evaluation of five multitemporal global gridded population datasets : a case study in Sweden, 1990–2015

Archila Bustos, Maria Francisca LU ; Hall, Ola LU ; Niedomysl, Thomas LU and Ernstson, Ulf (2020) In Population and Environment 42(2). p.255-277
Abstract

Human activity is a major driver of change and has contributed to many of the challenges we face today. Detailed information about human population distribution is fundamental and use of freely available, high-resolution, gridded datasets on global population as a source of such information is increasing. However, there is little research to guide users in dataset choice. This study evaluates five of the most commonly used global gridded population datasets against a high-resolution Swedish population dataset on a pixel level. We show that datasets which employ more complex modeling techniques exhibit lower errors overall but no one dataset performs best under all situations. Furthermore, differences exist in how unpopulated areas are... (More)

Human activity is a major driver of change and has contributed to many of the challenges we face today. Detailed information about human population distribution is fundamental and use of freely available, high-resolution, gridded datasets on global population as a source of such information is increasing. However, there is little research to guide users in dataset choice. This study evaluates five of the most commonly used global gridded population datasets against a high-resolution Swedish population dataset on a pixel level. We show that datasets which employ more complex modeling techniques exhibit lower errors overall but no one dataset performs best under all situations. Furthermore, differences exist in how unpopulated areas are identified and changes in algorithms over time affect accuracy. Our results provide guidance in navigating the differences between the most commonly used gridded population datasets and will help researchers and policy makers identify the most suitable datasets under varying conditions.

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Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Dasymetric mapping, Gridded population, Human population distribution, Population estimation
in
Population and Environment
volume
42
issue
2
pages
23 pages
publisher
Springer
external identifiers
  • scopus:85090130289
ISSN
0199-0039
DOI
10.1007/s11111-020-00360-8
language
English
LU publication?
yes
id
30729ae7-f2b3-476a-91c4-84330109d136
date added to LUP
2020-09-15 07:35:44
date last changed
2022-04-19 00:39:23
@article{30729ae7-f2b3-476a-91c4-84330109d136,
  abstract     = {{<p>Human activity is a major driver of change and has contributed to many of the challenges we face today. Detailed information about human population distribution is fundamental and use of freely available, high-resolution, gridded datasets on global population as a source of such information is increasing. However, there is little research to guide users in dataset choice. This study evaluates five of the most commonly used global gridded population datasets against a high-resolution Swedish population dataset on a pixel level. We show that datasets which employ more complex modeling techniques exhibit lower errors overall but no one dataset performs best under all situations. Furthermore, differences exist in how unpopulated areas are identified and changes in algorithms over time affect accuracy. Our results provide guidance in navigating the differences between the most commonly used gridded population datasets and will help researchers and policy makers identify the most suitable datasets under varying conditions.</p>}},
  author       = {{Archila Bustos, Maria Francisca and Hall, Ola and Niedomysl, Thomas and Ernstson, Ulf}},
  issn         = {{0199-0039}},
  keywords     = {{Dasymetric mapping; Gridded population; Human population distribution; Population estimation}},
  language     = {{eng}},
  number       = {{2}},
  pages        = {{255--277}},
  publisher    = {{Springer}},
  series       = {{Population and Environment}},
  title        = {{A pixel level evaluation of five multitemporal global gridded population datasets : a case study in Sweden, 1990–2015}},
  url          = {{http://dx.doi.org/10.1007/s11111-020-00360-8}},
  doi          = {{10.1007/s11111-020-00360-8}},
  volume       = {{42}},
  year         = {{2020}},
}