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The modifiable areal unit problem (MAUP) in physical geography
Abstract
Of particular importance to the study of large-scale phenomena in physical geography is the modifiable areal unit problem ( MAUP). While often viewed as only a problem in human geography (particularly demographic studies), the MAUP is an issue for all quantitative studies in geography of spatial phenomena (Openshaw and Taylor, 1979). Increasingly, remote sensing and Geographic Information Systems ( GIS) are being used to assess the distribution of phenomena from a large scale. These phenomena are modelled using areal units that can take any shape or size resulting in complications with statistical analysis related to both the scale and method used to create the areal units. In this paper, we define the modifiable areal unit problem, present examples of when it is a problem in physical geography studies, and review some potential solutions to the problem. Our aim is to increase awareness of this complicated issue and to promote further discussion and interest in this topic.
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Remote Sensing and Image Interpretation
Wright, J., Lillesand, T. M., & Kiefer, R. W. (1980) · The Geographical Journal · doi:10.2307/634969 · Cited by 7,238
Journal of The American Statistical Association
Fienberg, S. E. (2005) · Encyclopedia of Statistical Sciences · doi:10.1002/0471667196.ess1317 · Cited by 6,125
Remote Sensing And Image Interpretation
LILLESAND, T. M., Kiefer, R. W., & Chipman, J. (1979) · HAL · Cited by 4,463
Wiens, J. A. (1989) · Functional Ecology · doi:10.2307/2389612 · Cited by 3,689
The Ecology of Interfaces: Riparian Zones
Naiman, R. J., & Décamps, H. (1997) · Annual Review of Ecology and Systematics · doi:10.1146/annurev.ecolsys.28.1.621 · Cited by 2,791
A hierarchical concept of ecosystems
O’Neill, R. V. (1986) · Cited by 1,598
Causal Inferences in Nonexperimental Research
Blalock, H. M. (1964) · Medical Entomology and Zoology · Cited by 1,276
A hierarchical concept of ecosystems
Maurer, B. A. (1987) · Trends in Ecology & Evolution · doi:10.1016/0169-5347(87)90199-6 · Cited by 1,216
(2021) · Journal of Remote Sensing · doi:10.34133/remotesensing · Cited by 1,047
The modifiable areal unit problem and implications for landscape ecology
Jelinski, D. E., & Wu, J. (1996) · Landscape Ecology · doi:10.1007/bf02447512 · Cited by 865
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Metadata
- Authors
- Dark, S. J., & Bram, D.
- Venue
- Progress in Physical Geography: Earth and Environment
- Publisher
- SAGE Publications
- Published
- 2007-10
- Volume
- 31
- Issue
- 5
- Pages
- 471-479
- ISSN
- 0309-1333 (ISSN-L)
- 1477-0296
- OpenAlex
- W2132545125
- Cited by
- 398
- References
- 26
- FWCI
- 11.43
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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