Dear R-SIG-GEO members For those of you that are interested on satellite image time series analysis, we would like to announce the availability of the beta version of the R SITS package, which can be obtained from github: > devtools::install_github("e-sensing/sits").
The SITS package is a set of tools for working with satellite image time series. Includes data retrieval from a WTSS (web time series service), different visualisation methods for image time series, smoothing methods for noisy time series, different clustering methods including dendrograms and SOM. Matches noiseless patterns with noisy time series using the TWDTW method for shape recognition. Provides machine learning methods for time series classification, including SVM, LDA, QDA, GLM, Lasso, Random Forests and Deep Learning. The main purpose of SITS is to perform land use and land cover classification using time series derived from satellites such as MODIS, LANDSAT, and SENTINEL-2. It has been finetuned to deliver reasonable performance for raster data sets in the GeoTIFF format. The package has been developed by the team of the "e-sensing" project at INPE (Brazil's National Institute for Space Research), supported by FAPESP (Sao Paulo Research Foundation). We also received support from International Climate Initiative of the Germany Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety. We welcome comments, suggestions and bug reports on the package. We suggest that those who are interested take a look at the vignette, that can be built using the command: > devtools::build_vignettes() Best regards Gilberto -- Prof. Dr. Dr. h.c. Gilberto Camara National Institute for Space Research, INPE, Brazil http://www.dpi.inpe.br/gilberto [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo