Chen, G., Hay, G. J., and St-Onge, B. 2011. A GEOBIA framework to estimate forest
parameters from lidar transects, Quickbird imagery and machine learning: A case study in
Quebec, Canada. International Journal of Applied Earth Observation and Geoinformation
15:28–37.
Cousins, S. H. 1993. Hierarchy in ecology: Its relevance to landscape ecology and geographic
information systems. In R. H. Young, D. R. Green, and S. H. Cousins (Eds.), Landscape
Ecology and GIS. New York: Taylor & Francis, pp. 75–86.
Daubechies, I. 1988. Orthonormal bases of compactly supported wavelets. Communications on
Pure and Applied Mathematics 41:906–966.
Dey, V., Zhang, Y., and Zhong, M. 2010. A review on image segmentation techniques with
remote sensing perspective. ISPRS TC VII Symposium Vienna, Austria, July 5, Vol.
XXXVIII, Part 7A, pp. 31–42.
Doxani, G., Karantzalos, K., and Tsakiri-Strati, A. 2012. Monitoring urban changes based on
scale space filtering and object-oriented classification. International Journal of Applied
Earth Observations and Geoinformation 15:38–48.
Drǎ gut ̧ , L., Tiede, D., and Levick, S. R. 2010. ESP: A tool to estimate scale parameter for
multiresolution image segmentation of remotely sensed data. International Journal of
Geographical Information Science 24(6):859–871.
Foody, G. 1999. Image classification with a neural network: From completely-crisp to fullyfuzzy situations. In P. M. Atkinson and N. J. Tate (Eds.), Advances in Remote Sensing and
GIS Analysis. Chichester: Wiley, pp. 17–37.
Forman, R. T. T. 1995. Land Mosaics: The Ecology of Landscapes and Regions. Cambridge,
UK: Cambridge University Press.
Gibson, C. C., Ostrom, E., and Ahn, T. K. 2000. The concept of scale and the human
dimensions of global change: A survey. Ecological Economics 32:217–239.
Graham, I. 2001. Object-Oriented Methods. Principles and Practices, 3rd ed. Reading, MA:
Addison-Wesley.
Hall, O., Hay, G. J., Bouchard, A., and Marceau, D. J. 2004. Detecting dominant landscape
objects through multiple scales: An integration of object-specific methods and watershed
segmentation. Landscape Ecology 19(1):59–76.
Haralick, R. M., Sternberg, S. R., and Zhuang, X. 1987. Image analysis using mathematical
morphology. IEEE Transactions on Pattern Analysis and Machine Intelligence 9(4):532–550.
Haury, L. R., McGowan, J. A., and Wiebe, P. H. 1978. Patters and processes in the time-space
scales of plankton distributons. In J. H. Steele (Ed.), Spatial Pattern in Plankton Communities. New York: Plenum, pp. 277–327.
Hay, G. J., and Blaschke, T. 2010. Forward: Special issue on geographic object-based
image analysis (GEOBIA). Photogrammetric Engineering and Remote Sensing 76(2):
121–122.
Hay, G. J., Blaschke, T., Marceau, D. J., and Bouchard, A. 2003. A comparison of three imageobject methods for the multiscale analysis of landscape structure. ISPRS Journal of
Photogrammetry and Remote Sensing 57(5–6):327–345.
Hay, G. J., and Castilla, G. 2008. Geographic Object-Based Image Analysis (GEOBIA): A new
name for a new discipline. In T. Blaschke, S. Lang, and G. J. Hay (Eds.), Object-Based
Image Analysis. Spatial Concepts for Knowledge-Driven Remote Sensing Applications.
Berlin: Springer, pp. 75–89.
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parameters from lidar transects, Quickbird imagery and machine learning: A case study in
Quebec, Canada. International Journal of Applied Earth Observation and Geoinformation
15:28–37.
Cousins, S. H. 1993. Hierarchy in ecology: Its relevance to landscape ecology and geographic
information systems. In R. H. Young, D. R. Green, and S. H. Cousins (Eds.), Landscape
Ecology and GIS. New York: Taylor & Francis, pp. 75–86.
Daubechies, I. 1988. Orthonormal bases of compactly supported wavelets. Communications on
Pure and Applied Mathematics 41:906–966.
Dey, V., Zhang, Y., and Zhong, M. 2010. A review on image segmentation techniques with
remote sensing perspective. ISPRS TC VII Symposium Vienna, Austria, July 5, Vol.
XXXVIII, Part 7A, pp. 31–42.
Doxani, G., Karantzalos, K., and Tsakiri-Strati, A. 2012. Monitoring urban changes based on
scale space filtering and object-oriented classification. International Journal of Applied
Earth Observations and Geoinformation 15:38–48.
Drǎ gut ̧ , L., Tiede, D., and Levick, S. R. 2010. ESP: A tool to estimate scale parameter for
multiresolution image segmentation of remotely sensed data. International Journal of
Geographical Information Science 24(6):859–871.
Foody, G. 1999. Image classification with a neural network: From completely-crisp to fullyfuzzy situations. In P. M. Atkinson and N. J. Tate (Eds.), Advances in Remote Sensing and
GIS Analysis. Chichester: Wiley, pp. 17–37.
Forman, R. T. T. 1995. Land Mosaics: The Ecology of Landscapes and Regions. Cambridge,
UK: Cambridge University Press.
Gibson, C. C., Ostrom, E., and Ahn, T. K. 2000. The concept of scale and the human
dimensions of global change: A survey. Ecological Economics 32:217–239.
Graham, I. 2001. Object-Oriented Methods. Principles and Practices, 3rd ed. Reading, MA:
Addison-Wesley.
Hall, O., Hay, G. J., Bouchard, A., and Marceau, D. J. 2004. Detecting dominant landscape
objects through multiple scales: An integration of object-specific methods and watershed
segmentation. Landscape Ecology 19(1):59–76.
Haralick, R. M., Sternberg, S. R., and Zhuang, X. 1987. Image analysis using mathematical
morphology. IEEE Transactions on Pattern Analysis and Machine Intelligence 9(4):532–550.
Haury, L. R., McGowan, J. A., and Wiebe, P. H. 1978. Patters and processes in the time-space
scales of plankton distributons. In J. H. Steele (Ed.), Spatial Pattern in Plankton Communities. New York: Plenum, pp. 277–327.
Hay, G. J., and Blaschke, T. 2010. Forward: Special issue on geographic object-based
image analysis (GEOBIA). Photogrammetric Engineering and Remote Sensing 76(2):
121–122.
Hay, G. J., Blaschke, T., Marceau, D. J., and Bouchard, A. 2003. A comparison of three imageobject methods for the multiscale analysis of landscape structure. ISPRS Journal of
Photogrammetry and Remote Sensing 57(5–6):327–345.
Hay, G. J., and Castilla, G. 2008. Geographic Object-Based Image Analysis (GEOBIA): A new
name for a new discipline. In T. Blaschke, S. Lang, and G. J. Hay (Eds.), Object-Based
Image Analysis. Spatial Concepts for Knowledge-Driven Remote Sensing Applications.
Berlin: Springer, pp. 75–89.
REFERENCES
165