A probabilistic graphical model approach in 30 m land cover mapping with multiple data sources

@article{Wang2016APG,
  title={A probabilistic graphical model approach in 30 m land cover mapping with multiple data sources},
  author={Jie Wang and Luyan Ji and Xiaomeng Huang and Haohuan Fu and Shiming Xu and Congcong Li},
  journal={CoRR},
  year={2016},
  volume={abs/1612.03373}
}
There is a trend to acquire high accuracy land-cover maps using multi-source classification methods, most of which are based on data fusion, especially pixel-or feature-level fusions. A probabilistic graphical model (PGM) approach is proposed in this research for 30 m resolution land-cover mapping with multi-temporal Landsat and MODerate Resolution Imaging Spectroradiometer (MODIS) data. Independent classifiers were applied to two single-date Landsat 8 scenes and the MODIS time-series data… CONTINUE READING