Robust Geographically Weighted Regression: A Technique for Quantifying Spatial Relationships Between Freshwater Acidification Critical Loads and Catchment Attributes

Annals of the Association of American Geographers

Volumn 100, Issue 2, 2010, Pages 286-306

  Harris, Paul ^a   Fotheringham, A Stewart ^a   Juggins, Steve ^b  

^a NATIONAL UNIVERSITY OF IRELAND   (Ireland)

^b NEWCASTLE UNIVERSITY   (United Kingdom)

Author keywords

Acidified surface waters; Catchment characteristics; Relationship nonstationarity; Robust; Spatial heterogeneity

Indexed keywords

ACIDIFICATION; CALIBRATION; CATCHMENT; CRITICAL LOAD; FRESHWATER; HETEROGENEITY; QUANTITATIVE ANALYSIS; REGRESSION ANALYSIS; SPATIAL ANALYSIS; SURFACE WATER; WATER FLOW; WATER QUALITY;

UNITED KINGDOM;

EID: 77951287343     PISSN: 00045608     EISSN: 14678306     Source Type: Journal    
DOI: 10.1080/00045600903550378     Document Type: Article

References (29)

1. Atkinson, P. M., S. E. German, D. A. Sear, and M. J. Clark. 2003. Exploring the relations between riverbank erosion and geomorphological controls using geographically weighted logistic regression. Geographical Analysis 35:58-82.
2. Blanco-Moreno, J. M., L. Chamorro, J. Izquierdo, R. M. Masalles, and F. X. Sans. 2008. Modeling within-field spatial variability of crop biomass-Weed density relationships using geographically weighted regression. Weed Research 48:512-22.
3. Bowman, A. W., and A. Azzalini. 1997. Applied smoothing techniques for data analysis-The kernel approach with S-plus illustrations. New York: Oxford University Press.
4. Brunsdon, C., A. S. Fotheringham, and M. E. Charlton. 1998. Spatial nonstationarity and autoregressive models. Environment and Planning A 30:957-73.
5. Brunsdon, C., A. S. Fotheringham, and M. E. Charlton. 1999. Some notes on parametric significant tests for geographically weighted regression. Journal of Regional Science 39:497-524.
6. CLAG Freshwaters. 1995. Critical loads of acid deposition for United Kingdom freshwaters. Penicuik, UK: Critical Loads Advisory Group.
7. Curtis, C. J., T. E. H. Allott, R. W. Battarbee, and R. Harri-man. 1995. Validation of the UK critical loads for fresh-waters: Site selection & sensitivity. Water, Air, and Soil Pollution 85:2467-72.
8. Farber, S., and A. Páez. 2007. A systematic investigation of cross-validation in GWR model estimation: Empirical analysis and Monte Carlo simulations. Journal of Geographical Systems 9:371-96.
9. Fotheringham, A. S., C. Brunsdon, and M. E. Charlton. 2002. Geographically weighted regression-The analysis of spatially varying relationships. Chichester, UK: Wiley.
10. Fox, J. 2002. An R and S-plus companion to applied regression. London: Sage.
11. Gotway-Crawford, C. A., and G. W. Hergert. 1997. Incorporating spatial trends and anisotropy in geostatistical mapping of soil properties. Soil Science Society of America Journal 61:298-309.
12. Hall, J. R., S. M. Wright, T. H. Sparks, J. Ullyett, T. E. H. Allott, and M. Hornung. 1995. Predicting freshwater critical loads from national data on geology, soils and land use. Water, Air, and Soil Pollution 85:2443-48.
13. Hengl, T., G. B. M. Heuvelink, and A. Stein. 2004. A generic framework for spatial prediction of soil variables based on regression-kriging. Geoderma 120:75-93.
14. Henriksen, A., J. Kämäri, M. Posch, and A. Wilander. 1992. Critical loads of acidity: Nordic surface waters. Ambio 21:356-63.
15. Hobert, J. P., N. S. Altman, and C. L. Schofield. 1997. Analyses of fish species richness with spatial covari-ate. Journal of the American Statistical Association 92:846-54.
16. Hornung, M., K. Bull, M. Cresser, J. Ullyett, J. R. Hall, S. Langan, P. J. Loveland, and M. J. Wilson. 1995. The sensitivity of surface waters of Great Britain to acidification predicted from catchment characteristics. Environmental Pollution 87:204-14.
17. Kernan, M. R., T. E. H. Allott, and R. W. Battarbee. 1998. Predicting freshwater critical loads of acidification at the catchment scale: An empirical model. Water, Air, and Soil Pollution 185:31-41.
18. Kernan, M. R., R. C. Helliwell, and M. J. Hughes. 2001. Predicting freshwater critical loads from catchment characteristics using national datasets. Water, Air, and Soil Pollution: Focus 1:415-35.
19. Leung, Y., C.-L. Mei, and W.-X. Zhang. 2000a. Statistical tests for spatial nonstationarity based on the geographically weighted regression model. Environment and Planning A 32:9-32.
20. Leung, Y., C.-L. Mei, and W.-X. Zhang. 2000b. Testing for spatial autocorrelation among the residuals of geographically weighted regression. Environment and Planning A 32:871-90.
21. Lloyd, C., and I. Shuttleworth. 2005. Analyzing commuting using local regression techniques: Scale, sensitivity, and geographical patterning. Environment and Planning A 37:81-103.
22. Mei, C.-L., N. Wang, and W.-X. Zhang. 2006. Testing the importance of the explanatory variables in a mixed geographically weighted regression model. Environment and Planning A 38:587-98.
23. Nilsson, J., and P. Grennfelt, eds. 1988. Critical loads for sulphur and nitrogen. Copenhagen, Denmark: Nordic Council of Ministers.
24. Páez, A. 2004. Anisotropic variance functions in geographically weighted regression models. Geographical Analysis 36:299-314.
25. Páez, A., T. Uchida, and K. Miyamoto. 2002. A general framework for estimation and inference of geographically weighted regression models: 2. Spatial association and model specification tests. Environment and Planning A 34:883-904.
26. Wheeler, D. 2007. Diagnostic tools and a remedial method for collinearity in geographically weighted regression. Environment and Planning A 39:2464-81.
27. Wheeler, D., and C. A. Calder. 2007. An assessment of coefficient accuracy in linear regression models with spatially varying coefficients. Journal of Geographical Systems 9:145-66.
28. Wheeler, D., and M. Tiefelsdorf. 2005. Multicollinearity and correlation among local regression coefficients in geographically weighted regression. Journal of Geographical Systems 7:161-87.
29. Zhang, L., H. Bi, P. Cheng, and C. J. Davis. 2004. Modeling spatial variation in tree diameter-height relationships. Forest Ecology and Management 189:317-29.