Classification of Large-Scale Remote Sensing Images for Automatic Identification of Health Hazards

@inproceedings{Wolters2017ClassificationOL,
  title={Classification of Large-Scale Remote Sensing Images for Automatic Identification of Health Hazards},
  author={Mark A. Wolters and C. B. Dean},
  booktitle={Statistics in biosciences},
  year={2017}
}
Remote sensing images from Earth-orbiting satellites are a potentially rich data source for monitoring and cataloguing atmospheric health hazards that cover large geographic regions. A method is proposed for classifying such images into hazard and nonhazard regions using the autologistic regression model, which may be viewed as a spatial extension of logistic regression. The method includes a novel and simple approach to parameter estimation that makes it well suited to handling the large and… CONTINUE READING