GIS: Stressing the geographical

Progress in Physical Geography

Volumn 28, Issue 1, 2004, Pages 152-158

  Foody, Giles M ^a  

^a UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84990370512     PISSN: 03091333     EISSN: None     Source Type: Journal    
DOI: 10.1191/0309133304pp407pr     Document Type: Review

References (46)

1. Arita, H. and Rodriguez, P. 2002: Geographic range, turnover rate and the scaling of species diversity. Ecography 25, 541-550.
2. Atkinson, P. M., German, S. E., Sear, D. A. and Clark, M. J. 2003: Exploring the relations between riverbank erosion and geomorphological controls using geographically weighted logistic regression. Geographical Analysis 35, 58-82.
3. Austin, M. P. 2002: Spatial prediction of species distribution: an interface between ecological theory and statistical modelling. Ecological Modelling 157, 101-118.
4. Brunsdon, C., McClatchey, J. and Unwin, D. J. 2001: Spatial variations in the average rainfall-altitude relationship in Great Britain: an approach using geographically weighted regression. International Journal of Climatology 21, 455-466.
5. Cohen, W. B., Maiersperger, T. K., Gower, S. T. and Turner, D. P. 2003. An improved strategy for regression of biophysical variables and Landsat ETM+ data. Remote Sensing of Environment 84, 561-571.
6. Eastman, J. R., and Laney, R. M. 2002: Bayesian soft classification for sub-pixel analysis: a critical evaluation. Photogrammetric Engineering and Remote Sensing 68, 1149-1154.
7. Foody, G. M. 2002: The role of soft classification techniques in the refinement of estimates of ground control point location. Photogrammetric Engineering and Remote Sensing 68, 897-903.
8. Fotheringham, A. S., Charlton, M. E. and Brunsdon, C. 2001: Spatial variations in school performance: a local analysis using geographically weighted regression. Geographical and Environmental Modelling 5, 43-66.
9. Fotheringham, A. S., Brunsdon, C. and Charlton, M. 2002: Geographically weighted regression: the analysis of spatially varying relationships. Chichester: Wiley.
10. Gahegan, M. 2003: Is inductive machine learning just another wild goose (or might it lay the golden egg)? International Journal of Geographical Information Science 17, 69-92.
11. Goodin, D. G. and Henebry, G. M. 2002: The effect of rescaling on fine spatial resolution NDVI data: a test using multi-resolution aircraft sensor data. International Journal of Remote Sensing 23, 3865-3871.
12. Guisan, A., Edwards, T. C. and Hastie, T. 2002: Generalised linear and generalised additive models in studies of species distributions: Setting the scene. Ecological Modelling 157, 89-100.
13. Heegaard, E. 2002: The outer border and central border for species-environmental relationships estimated by nonparametric generalised additive models. Ecological Modelling 157, 131-139.
14. Hirzel, A. and Guisan, A. 2002: Which is the optimal sampling strategy for habitat suitability modelling. Ecological Modelling 157, 331-341.
15. Hlavka, C. A. and Dungan, J. L. 2002: Areal estimates of fragmented land cover: effects of pixel size and model-based corrections. International Journal of Remote Sensing 23, 711-724.
16. Jakomulska, A. M. and Radomski, J. P. 2002: Uncertainty in land cover mapping from remotely sensed data using textural algorithm and artificial neural networks, In Foody, G. M. and Atkinson, P. M., editors, Uncertainty in remote sensing and GIS. Chichester: Wiley, 99-118.
17. Ju, J., Kolaczyk, E. D. and Gopal, S. 2003: Gaussian mixture discriminant analysis and sub-pixel land cover characterization in remote sensing. Remote Sensing of Environment 84, 550-560.
18. Lehmann, A., Overton, J. McC. and Leathwick, J. R. 2003: GRASP: generalised regression analysis and spatial prediction. Ecological Modelling 160, 165-183.
19. Leung, Y., Mei, C-L. and Zhang, W-X. 2000a, Statistical test for spatial nonstationarity based on the geographically weighted regression model. Environment and Planning A 32, 9-32.
20. Leung, Y., Mei, C-L. and Zhang, W-X. 2000b, Testing for spatial autocorrelation among the residuals of he geographically weighted regression. Environment and Planning A 32, 871-890.
21. Liebhold, A. M. and Gurevitch, J. 2002: Integrating the statistical analysis of spatial data in ecology. Ecography 25, 553-557.
22. Miller, J. and Franklin, J. 2002: Modelling the distribution of four vegetation alliances using generalised linear models and classification tress with spatial dependence. Ecological Modelling 157, 227-247.
23. Moisen, G. G. and Frescino, T. S. 2002: Comparing five modelling techniques for predicting forest characteristics. Ecological Modelling 157, 209-225.
24. Nakaya, T. 2003: Local spatial interaction modelling based on the geographically weighted regression approach. In Thomas, R., Boots, B. and Okabe, A., editors, Modelling geographical systems: Statistical and computational applications. Dordrecht: Kluwer, 45-69.
25. Narayannan, R. M. and Desetty, M. K. 2002: Effect of spatial resolution on information content characterization in remote sensing imagery based on classification accuracy. International Journal of Remote Sensing 23, 537-553.
26. Oksanen, J. and Minchin, P. R. 2002: Continuum theory revisited: what shape are species responses along ecological gradients? Ecological Modelling 157, 119-129.
27. Osborne, P. E. and Suarez-Seoane, S. 2002: Should data be partitioned spatially before building large-scale distribution models? Ecological Modelling 157, 249-259.
28. Paez, A., Uchida, T. and Miyamoto, K. 2002a, A general framework for estimation and inference of geographically weighted regression models: 1. Location-specific kernel bandwidths and a test for local heterogeneity. Environment and Planning A 34, 733-754.
29. Paez, A., Uchida, T. and Miyamoto, K. 2002b, A general framework for estimation and inference of geographically weighted regression models: 2. Spatial association and model spefication tests. Environment and Planning A 34, 883-904.
30. Phillips, J. D. 2002: Global and local factors in earth surface systems. Ecological Modelling 149, 257-272.
31. Read, J. M. and Lam, N. S. N. 2002: Spatial methods for characterizing land cover and detecting land-cover changes for the tropics. International Journal of Remote Sensing 23, 2457-2474.
32. Recknagel, F., editor 2003: Ecological informatics: understanding ecological by biologically-inspired computation. Berlin: Springer.
33. Rosin, P. L. 2001: Robust pixel unmixing. IEEE Transactions on Geoscience and Remote Sensing 39, 1978-1983.
34. Saura, S. 2002: Effects of minimum mapping unit on land cover data spatial configuration and composition. International Journal of Remote Sensing 23, 4853-4880.
35. Schmidt, H. and Karnieli, A. 2002: Analysis of the temporal and spatial vegetation patterns in a semi-arid environment observed by NOAA AVHRR imagery and spectral ground measurements. International Journal of Remote Sensing 23, 3971-4000.
36. Tatem, A. J., Lewis, H. G., Atkinson, P. M. and Nixon, M. S. 2002a, Super-resolution land cover mapping from remotely sensed imagery using a Hopfield neural network. In Foody, G. M. and Atkinson, P, M., editors, Uncertainty in remote sensing and GIS. Chichester: Wiley, 77-98
37. Tatem, A. J., Lewis, H. G., Atkinson, P. M. and Nixon, M. S. 2002b, Super-resolution land cover pattern prediction using a Hopfield neural network. Remote Sensing of Environment 79, 1-14.
38. Treitz, P. 2001: Variogram analysis of high spatial resolution remote sensing data: an examination of boreal forest ecosystems. International Journal of Remote Sensing 22, 3895-3900.
39. Van Meirvenne, M. and Goovaerts, P. 2002: Accounting for spatial dependence in the processing of multi-temporal SAR images using factorial kriging. International Journal of Remote Sensing 23, 371-387.
40. Verhoeye, J. and DeWulf, R. 2001: Land cover mapping at the sub-pixel scale using linear optimisation techniques. Remote Sensing of Environment 79, 96-104.
41. Wang, J., Price, K. P. and Rich, P. M. 2001: Spatial patterns of NDVI in response to precipitation and temperature in the central Great Plains. International Journal of Remote Sensing 22, 3827-3844.
42. Wang, J., Liu, J., Zhuan, D., Li, L. and Ge, Y. 2002: Spatial sampling design for monitoring the area of cultivated land. International Journal of Remote Sensing 23, 263-284.
43. Wood, S. N. and Augustin, N. H. 2002: GAMs with integrated model selection using penalized regression splines and applications to environmental modelling. Ecological Modelling 157, 157-177.
44. Wu, C. and Murray, A. T. 2003: Estimating impervious surface distribution by spectral mixture analysis. Remote Sensing of Environment 84, 493-505.
45. Zaniewski, A. E., Lehmann, A. and Overton, J. McC. 2002: Predicting species spatial distributions using presence-only data: a case study of native New Zealand ferns. Ecological Modelling 157, 261-280.
46. Zhan, Q., Molenaar, M. and Lucieer, A. 2002: Pixel unmixing at the sub-pixel scale based on land cover class probabilities: application to urban areas. In Foody, G. M. and Atkinson, P. M., editors, Uncertainty in remote sensing and GIS. Chichester: Wiley, 59-76.