The modifiable areal unit problem (MAUP) in physical geography

Progress in Physical Geography - Tập 31 Số 5 - Trang 471-479 - 2007
Shawna Dark1, D. L. Bram1
1California State University, Northridge, CA 91330, USA

Tóm tắt

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.

Từ khóa


Tài liệu tham khảo

Amrhein, C.G., 1996, Geographical Systems, 3, 143

Arbia, G., 1996, Geographical Systems, 3, 123

Blalock, H., 1964, Causal inferences in non-experimental research

10.1191/0309133305pp432ra

Burke, I.C., 1991, Vegetation, 80, 71

10.1023/A:1007938619068

Clarke, K.C., 2002, Geographic information systems and environmental modeling.UpperSaddleRiver,NJ

Davis, F.W., 1998, The California Gap Analysis Project — Final Report

Evans, B.M., 2002, Hydrology, 2, 1

Fotheringham, A.S. 1989: Scale-independent spatial analysis. In Goodchild, M.F. and Gopal, S., editors, Accuracy of Spatial Databases, London: Taylor and Francis, 221—8.

Fotheringham, A.S., 1991, Statistical geography: problems in analyzing areal data

Gehlke, C.E., 1934, Journal of the American Statistical Association, 169

10.1177/030913330102500303

Goodchild, M.F., 1997, Scale, multiscaling, remote sensing, and GIS

10.1002/hyp.5626

10.1023/A:1013101931793

10.1061/(ASCE)1084-0699(1999)4:1(10)

10.1007/BF02447512

Jelinski, D.E., Goodchild, M.F. and Steyaert, L. 1994: Multiple roles for GIS in global change research: towards a research agenda. In Michener, W.K., Brunt, J.W. and Stafford, S.G., editors, Environmental Information Management and Analysis: Ecosystem to Global Scales, London: Taylor and Francis, 41—58.

10.2307/1931688

10.1016/B978-0-12-233440-5.50007-5

Lillisand, T.M., 2004, Remote sensing and image interpretation

Lu, J.G., Sun, G., McNulty, S.G. and Amaytya, D.M. 2003: Modeling actual evapotranspiration from forested watershed across the southeastern United States. Journal of the American Water Resources Association 39, 886—96.

Maidment, D., 2000, Hydrologic and hydraulic modeling support with geographic information systems

Marceau, D.J. 1992: The problem of scale and spatial aggregation in remote sensing: an empirical investigation using forestry data. Unpublished PhD thesis. Ontario,Canada:DepartmentofGeography, University of Waterloo , 180.

Marceau, D.J., 1999, Journal of Remote Sensing, 25, 357

10.1016/0034-4257(94)90046-9

10.1191/0309133305pp455ra

10.2307/2529650

Murguia, M., 2000, Ann. Bot. Fennici, 37, 289

10.1146/annurev.ecolsys.28.1.621

10.1191/0309133304pp411ra

10.2307/622300

10.1068/a160017

Openshaw, S. and Taylor, P.J. 1979: A million or so correlation coefficients: three experiments on the modifiable areal unit problem. In Wrigley, N., editor, Statistical applications in spatial sciences, London: Pion, 127—44.

O'Neill, R.V., 1986, A hierarchical concept of ecosystems

Rosswell, T., 1991, Ecology, 72, 45

10.1002/1096-9837(200008)25:9<1025::AID-ESP116>3.0.CO;2-Z

10.4324/9780203302217

10.1007/978-94-009-9394-5_18

10.2307/2389612

10.1002/hyp.387

Yule, G., 1950, An introduction to the theory of statistics