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and detecting land-cover changes for the tropics. International Journal of Remote Sensing
12(2):2457–2474.
Ridd, M. K. 1995. Exploring a V-I-S (Vegetation-Impervious Surface-Soil) model for urban
ecosystem analysis through remote sensing: comparative anatomy for cities. International
Journal of Remote Sensing 16(12):2165–2185.
Schmidt, K. S., Skidmore, A. K., Kloosterman, E. H., van Oosten, H., Kumar, L., and Janssen,
J. A. M. 2004. Mapping coastal vegetation using an expert system and hyperspectral
imagery. Photogrammetric Engineering & Remote Sensing 70:703–715.
Schneider, A., Friedl, M. A., and Potere, D. 2010. Mapping global urban areas using MODIS
500-m data: New methods and datasets based on “urban ecoregions.” Remote Sensing of
Environment 114:1733–1746.
Setiawan, H., Mathieu, R., and Thompson-Fawcett, M. 2006. Assessing the applicability of the
V-I-S model to map urban land use in the developing world: Case study of Yogyakarta,
Indonesia. Computers, Environment and Urban Systems 30(4):503–522.
Shaban, M. A., and Dikshit, O. 2001. Improvement of classification in urban areas by the use of
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Remote Sensing 22:565–593.
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Mather, P. M. 1999. Land cover classification revisited. In P. M. Atkinson and N. J. Tate (Eds.),
Advances in Remote Sensing and GIS. New York: Wiley, pp. 7–16.
McGwire, K., Minor, T., and Fenstermaker, L. 2000. Hyperspectral mixture modeling for
quantifying sparse vegetation cover in arid environments. Remote Sensing of Environment
72:360–374.
Moses, W. J., Gitelson, A. A., Berdnikov, S., and Povazhnyy, V. 2009. Satellite estimation of
Chlorophyll-a concentration using the red and NIR bands of MERIS—The Azov Sea case
study. IEEE Geoscience and Remote Sensing Letters 6:845–849.
Myint, S. W. 2001. A robust texture analysis and classification approach for urban land-use and
land-cover feature discrimination. Geocarto International 16:27–38.
Nichol, J. E. 1996. High-resolution surface temperature patterns related to urban morphology in
a tropical city: A satellite-based study. Journal of Applied Meteorology 35(1):135–146.
Platt, R. V., and Goetz, A. F. H. 2004. A comparison of AVIRIS and Landsat for land
use classification at the urban fringe. Photogrammetric Engineering & Remote Sensing
70:813–819.
Pu, R., Kelly, M., Anderson, G. L., and Gong, P. 2008. Using CASI hyperspectral imagery to
detect mortality and vegetation stress associated with a new hardwood forest disease.
Photogrammetric Engineering & Remote Sensing 74(1):65–75.
Qiu, F., Woller, K. L., and Briggs, R. 2003. Modeling urban population growth from remotely
sensed imagery and TIGER GIS road data. Photogrammetric Engineering & Remote
Sensing 69:1031–1042.
Quattrochi, D. A., and Goodchild, M. F. 1997. Scale in Remote Sensing and GIS. New York:
Lewis Publishers.
Raptis, V. S., Vaughan, R. A., and Wright, G. G. 2003. The effect of scaling on land cover
classification from satellite data. Computers & Geosciences 29:705–714.
Read, J. M., and Lam, N. S-.N. 2002. Spatial methods for characterising land cover
and detecting land-cover changes for the tropics. International Journal of Remote Sensing
12(2):2457–2474.
Ridd, M. K. 1995. Exploring a V-I-S (Vegetation-Impervious Surface-Soil) model for urban
ecosystem analysis through remote sensing: comparative anatomy for cities. International
Journal of Remote Sensing 16(12):2165–2185.
Schmidt, K. S., Skidmore, A. K., Kloosterman, E. H., van Oosten, H., Kumar, L., and Janssen,
J. A. M. 2004. Mapping coastal vegetation using an expert system and hyperspectral
imagery. Photogrammetric Engineering & Remote Sensing 70:703–715.
Schneider, A., Friedl, M. A., and Potere, D. 2010. Mapping global urban areas using MODIS
500-m data: New methods and datasets based on “urban ecoregions.” Remote Sensing of
Environment 114:1733–1746.
Setiawan, H., Mathieu, R., and Thompson-Fawcett, M. 2006. Assessing the applicability of the
V-I-S model to map urban land use in the developing world: Case study of Yogyakarta,
Indonesia. Computers, Environment and Urban Systems 30(4):503–522.
Shaban, M. A., and Dikshit, O. 2001. Improvement of classification in urban areas by the use of
textural features: the case study of Lucknow city, Uttar Pradesh. International Journal of
Remote Sensing 22:565–593.
REFERENCES
77