Mapping Urban Areas by Fusing Multiple Sources of Coarse Resolution Remotely Sensed Data

Photogrammetric Engineering and Remote Sensing

Volumn 69, Issue 12, 2003, Pages 1377-1386

  Schneider, Annemarie ^a   Friedl, Mark A ^a   McIver, Douglas K ^a   Woodcock, Curtls E ^a  

^a BOSTON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AGRICULTURE; DATA REDUCTION; ECOSYSTEMS; MAPPING; POPULATION STATISTICS; URBAN PLANNING;

URBAN LAND COVER;

REMOTE SENSING;

ACCURACY ASSESSMENT; DATA ASSIMILATION; IMAGE CLASSIFICATION; MAPPING METHOD; REMOTE SENSING; SPATIAL RESOLUTION; URBAN AREA; URBANIZATION;

NORTH AMERICA;

EID: 0345359173     PISSN: 00991112     EISSN: None     Source Type: Journal    
DOI: 10.14358/PERS.69.12.1377     Document Type: Review

References (53)

1. Alzola, C., and F. Harrell, 2003. An Introduction to Splus and the Hmisc and Design Libraries, University of Virginia, Department of Biostatistics and Epidemiology, Charlottesville, Virginia, http://hesweb1.med.virginia.edu/ biostat/s/splus.html (software), last accessed 18 July 2003.
2. Belward, A.S., and T. Loveland, 1997. The IGBP-DIS global 1 km land cover data set, DISCover: First results, International Journal of Remote Sensing, 18:3291-3295.
3. Benediktsson, J.A., and J.R. Sveinsson, 2000. Consensus based classification of multisource remote sensing data, Multiple Classifier Systems: Lecture Notes in Computer Science, 1857:280-289.
4. Card, D.H., 1982. Using known map category marginal frequencies to improve estimates of thematic map accuracy, Photogrammetric Engineering & Remote Sensing, 48:431-439.
5. Cihlar, J., R. Latifovic, J. Chen, J. Beaubien, Z. Li, and S. Magnussen, 2000. Selecting representative high resolution sample images of land cover studies, Part 2: Application to estimating land cover composition, Remote Sensing of Environment, 72:127-138.
6. Collins, M., R.E. Schapire, and Y. Singer, 2002. Logistic regression, Adaboost, and Bregman distances, Machine Learning, 48:253-285.
7. Congalton, R.G., 1991. A review of assessing the accuracy of classifications of remotely sensed data, Remote Sensing of Environment, 37:35-46.
8. CORINE, 1994. CORINE Land Cover Technical Guide, Commission of the European Communities Office for Official Publications, Copenhagen, Denmark, 168 p.
9. Curran, P.J., and H.D. Williamson, 1985. The accuracy of ground data used in remote sensing, International Journal of Remote Sensing, 6:1637-1651.
10. Danko, D.M., 1992. The Digital Chart of the World project, Photogrammetric Engineering & Remote Sensing, 58:1125-1128.
11. Deichmann, U., D. Balk, and G. Yetman, 2001. Transforming Population Data for Interdisciplinary Usages: From Census to Grid, Socioeconomic Data and Applications Center, CIESIN, Columbia University, New York, N.Y., http://sedac.ciesin.org/plue/gpw, last accessed 18 July 2003.
12. Doll, C.N.H., J.P. Muller, and C.D. Elvidge, 2000. Nighttime imagery as a tool for global mapping of socioeconomic parameters and greenhouse gas emissions, Ambio, 29:157-162.
13. Douglas, I., 1994. Human settlements, Changes in Land Use and Land Cover: A Global Perspective (W.B. Meyer and B.L. Turner, editors), Cambridge University Press, Cambridge, United Kingdom, pp. 149-169.
14. Elvidge, C.D., K.E. Baugh, E.A. Kihn, and E.R. Davis, 1996. Mapping city lights with nighttime data from the DMSP operational linescan system, Photogrammetric Engineering & Remote Sensing, 63:727-734.
15. Elvidge, C.D., K.E. Baugh, J.B. Dietz, P.C. Sutton, and H.W. Kroehl, 1999. Radiance calibration of DMSP-OLS low light imaging data of human settlements, Remote Sensing of Environment, 68:77-88.
16. Estrella, A., 1998. A new measure of fit for equations with dichotomous dependent variables, Journal of Business and Economic Statistics, 16:198-205.
17. Fayyad, U.M., and K.B. Irani, 1992. On the handling of continuous-valued attributes in decision tree generation, Machine Learning, 8:87-102.
18. Fitzpatrick-Lins, K., 1981. Comparison of sampling procedures and data analysis for a land-use and land-cover map, Photogrammetric Engineering & Remote Sensing, 47:343-351.
19. Friedl, M.A., and C.E. Brodley, 1997. Decision tree classification of land cover from remotely sensed data, Remote Sensing of Environment, 61:399-409.
20. Friedl, M.A., C.E. Brodley, and A.H. Strahler, 1999. Maximizing the land cover classification accuracies produced by decision trees at continental to global scales, IEEE Transactions on Geoscience and Remote Sensing, 27:969-977.
21. Friedl, M.A., D.K. McIver, F. Gao, J.C.F. Hodges, and A.H., Strahler, 2000. Characterization of North American land cover from NOAA-AVHRR data using the EOS MODIS land cover classification algorithm, Geophysical Research Letters, 27:977-980.
22. Friedl, M.A., D.K. McIver, J.C.F. Hodges, Y. Zhang, D. Muchoney, A.H. Strahler, C.E. Woodcock, S. Gopal, A. Schneider, A. Cooper, A. Baccini, F. Gao, and C.B. Schaaf, 2002. Global land cover mapping from MODIS: Algorithms and early results, Remote Sensing of Environment, 83:287-302.
23. Friedman, J., T. Hastie, and R. Tibshirani, 2000. Additive logistic regression, Annals of Statistics, 28:337-374.
24. Hansen, M., R.S. DeFries, .G. Townshend, and R. Sohlberg, 2000. Global land cover classification at 1 km spatial resolution using a classification tree, International Journal of Remote Sensing, 21:1331-1364.
25. Hastie, T.J., and R.J. Tibshirani, 1990. Generalized Additive Models, Chapman and Hall, New York, N.Y., 335 p.
26. Hosmer, D.W., and S. Lemeshow, 2000. Applied Logistic Regression, John Wiley and Sons, New York, N.Y., 307 p.
27. Imhoff, M.L., W.T. Lawrence, D.C. Stutzer, and C.D. Elvidge, 1997. A technique for using composite DMSP-OLS "city lights" satellite data to map urban areas, Remote Sensing of Environment, 61: 361-370.
28. Jensen, J.R., and D.L. Toll, 1982. Detecting residential land use development at the urban fringe, Photogrammetric Engineering & Remote Sensing, 48:629-643.
29. Loveland, T., Z. Zhu, D. Ohlen, J. Brown, B. Reed, and L. Yang, 1999. An analysis of the IGBP global land cover characterization process, Photogrammetric Engineering & Remote Sensing, 65: 1021-1031.
30. Lucht, W., C.B. Schaaf, and A.H. Strahler, 2000. An algorithm for the retrieval of albedo from space using semiempirical BRDF models, IEEE Transactions on Geoscience and Remote Sensing, 38:977-998.
31. McIver, D.K., and M.A. Friedl, 2001. Estimating pixel-scale land cover classification confidence using non-parametric machine learning methods, IEEE Transactions on Geoscience and Remote Sensing, 39:1959-1968.
32. _, 2002. Using prior probabilities in decision-tree classification of remotely-sensed data, Remote Sensing of Environment, 81: 253-261.
33. Miller, G., 1988. Living in the Environment, Wadsworth, Belmont, California, 379 p.
34. Mingers, J. 1989. An empirical comparison of pruning methods for decision tree induction, Machine Learning, 4:227-243.
35. Owen, T.W., K.P. Gallo, C.E. Elvidge, and K.E. Baugh, 1998. Using DMSP-OLS light frequency data to categorize urban environments associated with US climate observing stations, International Journal of Remote Sensing, 19:3451-3456.
36. Paola, J.D., and R.A. Schowengerdt, 1995. A detailed comparison of backpropagation neural network and maximum likelihood classifiers for urban land use classification, IEEE Transactions on Geoscience and Remote Sensing, 33:981-996.
37. Quinlan, J.R., 1987. Simplifying decision trees, International Journal of Machine Studies, 27:221-234.
38. _, 1993. C4.5: Programs for Machine Learning, Morgan Kauffman, San Mateo, California, 302 p.
39. th National Conference on Artificial Intelligence (AAAI-96), 04-08 August, Portland, Oregon (AAAI Press), pp. 725-730.
40. Ranchin, T., L. Wald, and M. Mangolini, 2001. Improving the spatial resolution of remotely sensed images by means of sensor fusion, Remote Sensing and Urban Analysis (J.P. Donnay, M.J. Barnesley, and P.A. Longley, editors), Taylor and Francis, New York, N.Y., pp. 21-37.
41. Robert, C.P., 1997. The Bayesian Choice: A Decision-Theoretic Motivation, Springer-Verlag, New York, N.Y., 436 p.
42. Seto, K.C., C.E. Woodcock, C. Song, X. Huang, J. Lu, and R.K. Kaufmann, 2002. Monitoring land-use change in the Pearl River Delta using Landsat TM, International Journal of Remote Sensing, 23:1985-2004.
43. Stehman, S.V., 1997. Selecting and interpreting measures of thematic accuracy assessment, Remote Sensing of Environment, 62:77-89.
44. _, 2001. Statistical rigor and practical utility in thematic map accuracy assessment, Photogrammetric Engineering & Remote Sensing, 67:727-734.
45. Stoms, D.M., 1996. Validating large area land cover databases with Maplets, Geocarto International, 11:87-95.
46. Strahler, A.H., D. Muchoney, J. Borak, F. Gao, M.A. Friedl, S. Gopal, J.C.F. Hodges, E. Lambin, O.K. McIver, A. Moody, C.B. Schaaf, and C.E. Woodcock, 1999. MODIS Land Cover/Land Cover Change Algorithm Theoretical Basis Document, Version 5.0, Department of Geography, Boston University, Boston, Massachusetts, http://geography.bu.edu/landcover/index.html, last accessed 18 July 2003.
47. Sutton, P., 1997. Modeling population density with nighttime satellite imagery and GIS. Computers, Environment and Urban Systems, 21:227-244.
48. Tobler, W.R., U. Deichmann, J. Gottsegen, and K. Maloy, 1995. The Global Demography Project, National Center for Geographic Information and Analysis 95-6, University of California, Santa Barbara, California, 75 p.
49. United Nations, 2000. Demographic Yearbook, Department of Economic and Social Affairs, Statistical Office, United Nations, New York, N.Y., 674 p.
50. Vogelmann, J.E., T. Sohl, and S.M. Howard, 1998. Regional characterization of land cover using multiple sources of data, Photogrammetric Engineering & Remote Sensing, 64:45-67.
51. Vogelmann, J.E., S.M. Howard, L. Yang, C.R. Larson, B.K. Wylie, and N. Driel, 2001. Completion of the 1990 National Land Cover Data for the conterminous United States from Landsat Thematic Mapper and ancillary data, Photogrammetric Engineering & Remote Sensing, 67:650-654.
52. Welch, R., 1980. Monitoring urban population and energy utilization patterns from satellite data, Remote Sensing of Environment, 9:1-9.
53. Yang, L., V. Stehman, J.H. Smith, and J.D. Wickham, 2001. Thematic accuracy assessment of MRLC land cover for the eastern United States, Remote Sensing of Environment, 76:418-422.