Spatial contextual classification and prediction models for mining geospatial data

@article{Shekhar2002SpatialCC,
  title={Spatial contextual classification and prediction models for mining geospatial data},
  author={Shashi Shekhar and Paul R. Schrater and Ranga Raju Vatsavai and Weili Wu and Sanjay Chawla},
  journal={IEEE Trans. Multimedia},
  year={2002},
  volume={4},
  pages={174-188}
}
Modeling spatial context (e.g., autocorrelation) is a key challenge in classification problems that arise in geospatial domains. Markov random fields (MRF) is a popular model for incorporating spatial context into image segmentation and land-use classification problems. The spatial autoregression (SAR) model, which is an extension of the classical regression model for incorporating spatial dependence, is popular for prediction and classification of spatial data in regional economics, natural… CONTINUE READING
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