Published August 31, 2022 | Version v1
Presentation Open

Time series-based machine learning algorithms for mapping dominant tree species in Flanders from Sentinel data

  • 1. ROR icon KU Leuven
  • 2. Research Institute for Nature and Forest

Description

This presentation was given on the ForestSAT 2022 conference. 

It compares three machine learning and deep learning methods for the classification of dominant tree species in forests in Flanders from Sentinel-2 time series: Random Forest, 1D-CNN (Pelletier et al, 2019) and Time Series Forest (Deng et al, 2013). 

References

Deng, H., Runger , G., Tuv , E., & Vladimir, M. (2013). A time series forest for classification and feature extraction. Information Sciences , 239 , 142 153.

Pelletier, C., Webb, G., & Petitjean , F. (2019). Temporal Convolutional Neural Network for the Classification of Satellite Image Time Series. Remote Sensing , 11 (5), 523.

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Additional details

Funding

Research Foundation - Flanders
GEO-INFORMED - Spatio-temporal deep learning workflows for transforming remote sensing data into geo-indicators for environmental policy support SBO project S006421N