Chen, J., Li, J., Pan, D., Zhu, Q., and Mao, Z. 2012. Edge-guided multiscale segmentation of
satellite multispectral imagery. IEEE Transactions on Geoscience and Remote Sensing
50(11):4513–4520.
Cheng, H., Jiang, X., Sun, Y., and Wang, J. 2001. Color image segmentation: advances and
prospects, Pattern Recognition 34:2259–2281.
Chirici, G., Giuliarelli, D., Biscontini, D., Tonti, D., Mattioli, W., Marchetti, M., and Corona, P.
2011. Large-scale monitoring of coppice forest clearcuts by multitemporal very high
resolution satellite imagery: A case study from central Italy. Remote Sensing of Environment
115:1025–1033.
Clinton, N., Holt, A., Scarborough, J., Yan, L., and Gong, P. 2010. Accuracy assessment
measures for object-based image segmentation goodness. Photogrammetric Engineering &
Remote Sensing 76(3):289–299.
Conchedda, G., Durieux, L., and Mayaux, P. 2008. An object-based method for mapping and
change analysis in mangrove ecosystems. ISPRS Journal of Photogrammetry & Remote
Sensing 63:578–589.
Crevier, D. 2008. Image segmentation algorithm development using ground truth image data
sets. Computer Vision and Image Understanding 112(2):143–159.
de Chant, T., and Kelly, M. 2009. Individual object change detection for monitoring the impact
of a forest pathogen on a hardwood forest. Photogrammetric Engineering & Remote Sensing
75(8):1005–1013.
Definiens Imaging. 2005. eCognition User Guide, Munich: Definiens Imaging.
Doxani, G., Karantzalos, K., and Tsakiri-Strati, M. 2012. Monitoring urban changes based on
scale-space filtering and object-oriented classification. International Journal of Applied
Earth Observation and Geoinformation 15:38–48.
Drǎ gut, L., and Eisank, C. 2011. Object representations at multiple scales from digital elevation
models. Geomorphology 129:183–189.
Drǎ gut, L., Tiede, D., and Levick, R. 2010. ESP: A tool to estimate scale parameter for
multiresolution image segmentation of remotely sensed data. International Journal of
Geographical Information Science 24:859–871.
Dronova, I., Gong, P., Clinton, N., Wang, L., Fu, W., Qi, S., and Liu, Y. 2012. Landscape
analysis of wetland plant functional types: The effects of image segmentation
scale, vegetation classes and classification methods. Remote Sensing of Environment
127:357–369.
Dronova, I., Gong, P., and Wang, L. 2011. Object-based analysis and change detection of major
wetland cover types and their classification uncertainty during the low water period at
Poyang Lake, China. Remote Sensing of Environment 115:3220–3236.
Durieux, L., Lagabrielle, E., and Nelson, A. 2008. A method for monitoring building
construction in urban sprawl areas using object-based analysis of Spot 5 images and
existing GIS data. ISPRS Journal of Photogrammetry & Remote Sensing 63:399–408.
Duro, D., Franklin, S., and Dube, M. 2012. A comparison of pixel-based and object-based
image analysis with selected machine learning algorithms for the classification of
agricultural landscapes using SPOT-5 HRG imagery. Remote Sensing of Environment
118:259–272.
Hall, L., Bensaid, A., Clarke, L., Velthuizen, R., Silbiger, M., and Bezdek, J. 1992. A
comparison of neural network and fuzzy clustering techniques in segmenting magnetic
resonance images of the brain. IEEE Transactions on Neural Networks 3(5):672–681.
208
OPTIMUM SCALE IN OBJECT-BASED IMAGE ANALYSIS
satellite multispectral imagery. IEEE Transactions on Geoscience and Remote Sensing
50(11):4513–4520.
Cheng, H., Jiang, X., Sun, Y., and Wang, J. 2001. Color image segmentation: advances and
prospects, Pattern Recognition 34:2259–2281.
Chirici, G., Giuliarelli, D., Biscontini, D., Tonti, D., Mattioli, W., Marchetti, M., and Corona, P.
2011. Large-scale monitoring of coppice forest clearcuts by multitemporal very high
resolution satellite imagery: A case study from central Italy. Remote Sensing of Environment
115:1025–1033.
Clinton, N., Holt, A., Scarborough, J., Yan, L., and Gong, P. 2010. Accuracy assessment
measures for object-based image segmentation goodness. Photogrammetric Engineering &
Remote Sensing 76(3):289–299.
Conchedda, G., Durieux, L., and Mayaux, P. 2008. An object-based method for mapping and
change analysis in mangrove ecosystems. ISPRS Journal of Photogrammetry & Remote
Sensing 63:578–589.
Crevier, D. 2008. Image segmentation algorithm development using ground truth image data
sets. Computer Vision and Image Understanding 112(2):143–159.
de Chant, T., and Kelly, M. 2009. Individual object change detection for monitoring the impact
of a forest pathogen on a hardwood forest. Photogrammetric Engineering & Remote Sensing
75(8):1005–1013.
Definiens Imaging. 2005. eCognition User Guide, Munich: Definiens Imaging.
Doxani, G., Karantzalos, K., and Tsakiri-Strati, M. 2012. Monitoring urban changes based on
scale-space filtering and object-oriented classification. International Journal of Applied
Earth Observation and Geoinformation 15:38–48.
Drǎ gut, L., and Eisank, C. 2011. Object representations at multiple scales from digital elevation
models. Geomorphology 129:183–189.
Drǎ gut, L., Tiede, D., and Levick, R. 2010. ESP: A tool to estimate scale parameter for
multiresolution image segmentation of remotely sensed data. International Journal of
Geographical Information Science 24:859–871.
Dronova, I., Gong, P., Clinton, N., Wang, L., Fu, W., Qi, S., and Liu, Y. 2012. Landscape
analysis of wetland plant functional types: The effects of image segmentation
scale, vegetation classes and classification methods. Remote Sensing of Environment
127:357–369.
Dronova, I., Gong, P., and Wang, L. 2011. Object-based analysis and change detection of major
wetland cover types and their classification uncertainty during the low water period at
Poyang Lake, China. Remote Sensing of Environment 115:3220–3236.
Durieux, L., Lagabrielle, E., and Nelson, A. 2008. A method for monitoring building
construction in urban sprawl areas using object-based analysis of Spot 5 images and
existing GIS data. ISPRS Journal of Photogrammetry & Remote Sensing 63:399–408.
Duro, D., Franklin, S., and Dube, M. 2012. A comparison of pixel-based and object-based
image analysis with selected machine learning algorithms for the classification of
agricultural landscapes using SPOT-5 HRG imagery. Remote Sensing of Environment
118:259–272.
Hall, L., Bensaid, A., Clarke, L., Velthuizen, R., Silbiger, M., and Bezdek, J. 1992. A
comparison of neural network and fuzzy clustering techniques in segmenting magnetic
resonance images of the brain. IEEE Transactions on Neural Networks 3(5):672–681.
208
OPTIMUM SCALE IN OBJECT-BASED IMAGE ANALYSIS