Ju, J., Gopal, S., and Kolaczyk, E. D. 2005. On the choice of spatial and categorical scale in
remote sensing land cover classification. Remote Sensing of Environment 96:62–77.
Krönert, R., Steinhardt, U., and Volk, M. 2001. Landscape Balance and Landscape Assessment. New York: Springer.
Lam, N. S.-N., and Quattrochi, D. A. 1992. On the issues of scale, resolution, and fractal
analysis in the mapping sciences. Professional Geographer 44(1):88–98.
Li, G., and Weng, Q. 2005. Using Landsat ETM+ imagery to measure population density in
Indianapolis, Indiana, USA. Photogrammetric Engineering & Remote Sensing 71(8):947–
958.
Liang, B., and Weng, Q. 2008. A multi-scale analysis of census-based land surface temperature
variations and determinants in Indianapolis, United States. Journal of Urban Planning and
Development 134(3):129–139.
Liang, B., Weng, Q., and Lu, D. 2007. Census-based multiple scale residential population
modeling with impervious surface data. In Q. Weng (Ed.), Remote Sensing of Impervious
Surfaces. Boca Raton, FL: CRC/Taylor & Francis, pp. 409–430.
Liu, H., and Weng, Q. 2009. Scaling-up effect on the relationship between landscape
pattern and land surface temperature. Photogrammetric Engineering & Remote Sensing
75(3):291–304.
Lo, C. P., 1986. Applied Remote Sensing. New York: Longman.
Lo, C. P., 2001. Modeling the population of China using DMSP operational linescan system
nighttime data. Photogrammetric Engineering & Remote Sensing 67(9):1037–1047.
Lo, C. P., Quattrochi, D. A., and Luvall, J. C. 1997. Application of high-resolution thermal
infrared remote sensing and GIS to assess the urban heat island effect. International Journal
of Remote Sensing 18:287–304.
Lo, C. P., and Welch, R. 1977. Chinese urban population estimates. Annals of the Association of
American Geographers 67(2):246–253.
Lo, C. P., and Yeung, A. K. W. 2002. Concepts and Techniques of Geographic Information
Systems. Upper Saddle River, NJ: Prentice Hall, pp 351–353.
Lu, D., Tian, H., Zhou, G., and Ge, H. 2008. Regional mapping of human settlements in
southeastern China with multisensor remotely sensed data. Remote Sensing of Environment
112(9):3668–3679.
Lu, D., and Weng, Q. 2007. A survey of image classification methods and techniques for
improving classification performance. International Journal of Remote Sensing 28(5):
823–870.
Lu, D., and Weng, Q. 2009. Extraction of urban impervious surfaces from IKONOS imagery.
International Journal of Remote Sensing 30(5):1297–1311.
Lu, D., Weng, Q., and Li, G. 2006. Residential population estimation using a remote
sensing derived impervious surface approach. International Journal of Remote Sensing
27(16):3553–3570.
Madhavan, B. B., Kubo, S., Kurisaki, N., and Sivakumar, T. V. L. N. 2001. Appraising the
anatomy and spatial growth of the Bangkok Metropolitan area using a vegetationimpervious-soil model through remote sensing. International Journal of Remote Sensing
22:789–806.
Mannan, B., and Ray, A. K. 2003. Crisp and fuzzy competitive learning networks for
supervised classification of multispectral IRS scenes. International Journal of Remote
Sensing 24:3491–3502.
76
ON THE ISSUE OF SCALE IN URBAN REMOTE SENSING
remote sensing land cover classification. Remote Sensing of Environment 96:62–77.
Krönert, R., Steinhardt, U., and Volk, M. 2001. Landscape Balance and Landscape Assessment. New York: Springer.
Lam, N. S.-N., and Quattrochi, D. A. 1992. On the issues of scale, resolution, and fractal
analysis in the mapping sciences. Professional Geographer 44(1):88–98.
Li, G., and Weng, Q. 2005. Using Landsat ETM+ imagery to measure population density in
Indianapolis, Indiana, USA. Photogrammetric Engineering & Remote Sensing 71(8):947–
958.
Liang, B., and Weng, Q. 2008. A multi-scale analysis of census-based land surface temperature
variations and determinants in Indianapolis, United States. Journal of Urban Planning and
Development 134(3):129–139.
Liang, B., Weng, Q., and Lu, D. 2007. Census-based multiple scale residential population
modeling with impervious surface data. In Q. Weng (Ed.), Remote Sensing of Impervious
Surfaces. Boca Raton, FL: CRC/Taylor & Francis, pp. 409–430.
Liu, H., and Weng, Q. 2009. Scaling-up effect on the relationship between landscape
pattern and land surface temperature. Photogrammetric Engineering & Remote Sensing
75(3):291–304.
Lo, C. P., 1986. Applied Remote Sensing. New York: Longman.
Lo, C. P., 2001. Modeling the population of China using DMSP operational linescan system
nighttime data. Photogrammetric Engineering & Remote Sensing 67(9):1037–1047.
Lo, C. P., Quattrochi, D. A., and Luvall, J. C. 1997. Application of high-resolution thermal
infrared remote sensing and GIS to assess the urban heat island effect. International Journal
of Remote Sensing 18:287–304.
Lo, C. P., and Welch, R. 1977. Chinese urban population estimates. Annals of the Association of
American Geographers 67(2):246–253.
Lo, C. P., and Yeung, A. K. W. 2002. Concepts and Techniques of Geographic Information
Systems. Upper Saddle River, NJ: Prentice Hall, pp 351–353.
Lu, D., Tian, H., Zhou, G., and Ge, H. 2008. Regional mapping of human settlements in
southeastern China with multisensor remotely sensed data. Remote Sensing of Environment
112(9):3668–3679.
Lu, D., and Weng, Q. 2007. A survey of image classification methods and techniques for
improving classification performance. International Journal of Remote Sensing 28(5):
823–870.
Lu, D., and Weng, Q. 2009. Extraction of urban impervious surfaces from IKONOS imagery.
International Journal of Remote Sensing 30(5):1297–1311.
Lu, D., Weng, Q., and Li, G. 2006. Residential population estimation using a remote
sensing derived impervious surface approach. International Journal of Remote Sensing
27(16):3553–3570.
Madhavan, B. B., Kubo, S., Kurisaki, N., and Sivakumar, T. V. L. N. 2001. Appraising the
anatomy and spatial growth of the Bangkok Metropolitan area using a vegetationimpervious-soil model through remote sensing. International Journal of Remote Sensing
22:789–806.
Mannan, B., and Ray, A. K. 2003. Crisp and fuzzy competitive learning networks for
supervised classification of multispectral IRS scenes. International Journal of Remote
Sensing 24:3491–3502.
76
ON THE ISSUE OF SCALE IN URBAN REMOTE SENSING