This Package is adapted from Victor Maus's R package dtwSat.
Dynamic Time Warping and Time-Weighted Dynamic Time Warping (TWDTW) for satellite image time series analysis. pyDtwSat provides visulisation to land use land cover classification of the time series of satellite images.
Maus, Victor, Gilberto Camara, Marius Appel, and Edzer Pebesma. 2019. “dtwSat: Time-Weighted Dynamic Time Warping for Satellite Image Time Series Analysis in R.” Journal of Statistical Software 88 (5): 1–31. https://doi.org/10.18637/jss.v088.i05.
Maus, Victor, Gilberto Camara, Ricardo Cartaxo, Alber Sanchez, Fernando M. Ramos, and Gilberto R. de Queiroz. 2016. “A Time-Weighted Dynamic Time Warping Method for Land-Use and Land-Cover Mapping.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 9 (8): 3729–39. https://doi.org/10.1109/JSTARS.2016.2517118.