An end-to-end toolkit for land use and land cover classification
using big Earth observation data. Builds satellite image data cubes from cloud collections.
Supports visualization methods for images and time series and
smoothing filters for dealing with noisy time series.
Enables merging of multi-source imagery (SAR, optical, DEM).
Includes functions for quality assessment of training samples using self-organized maps and
to reduce training samples imbalance. Provides machine learning algorithms including support vector machines,
random forests, extreme gradient boosting, multi-layer perceptrons,
temporal convolution neural networks, and temporal attention encoders.
Performs efficient classification of big Earth observation data cubes and includes
functions for post-classification smoothing based on Bayesian inference.
Enables best practices for estimating area and assessing accuracy of land change.
Includes object-based spatio-temporal segmentation for space-time OBIA.
Minimum recommended requirements: 16 GB RAM and 4 CPU dual-core.
| Version: |
1.5.3 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
yaml (≥ 2.3.0), dplyr (≥ 1.1.0), grDevices, graphics, leafgl, leaflet (≥ 2.2.2), lubridate, luz (≥ 0.4.0), parallel, purrr (≥ 1.0.2), randomForest, Rcpp (≥ 1.1.0), rstac (≥ 1.0.1), sf (≥ 1.0-19), slider (≥ 0.2.0), stats, terra (≥ 1.8-54), tibble (≥ 3.3.0), tidyr (≥ 1.3.0), tmap (≥ 4.1), torch (≥ 0.15.0), units, utils |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
aws.s3, caret, cli, cols4all (≥ 0.8.0), covr, dendextend, dtwclust, DiagrammeR, digest, e1071, exactextractr, FNN, gdalcubes (≥ 0.7.0), geojsonsf, ggplot2, httr2 (≥ 1.1.0), jsonlite, kohonen (≥ 3.0.11), lightgbm, methods, mgcv, nnet, openxlsx, proxy, randomForestExplainer, RColorBrewer, RcppArmadillo (≥ 14.0.0), scales, spdep, stars, stringr, supercells (≥ 1.0.0), testthat (≥ 3.1.3), tools, xgboost |
| Published: |
2025-07-23 |
| DOI: |
10.32614/CRAN.package.sits |
| Author: |
Rolf Simoes [aut],
Gilberto Camara [aut, cre, ths],
Felipe Souza [aut],
Felipe Carlos [aut],
Lorena Santos [ctb],
Charlotte Pelletier [ctb],
Estefania Pizarro [ctb],
Karine Ferreira [ctb, ths],
Alber Sanchez [ctb],
Alexandre Assuncao [ctb],
Daniel Falbel [ctb],
Gilberto Queiroz [ctb],
Johannes Reiche [ctb],
Pedro Andrade [ctb],
Pedro Brito [ctb],
Renato Assuncao [ctb],
Ricardo Cartaxo [ctb] |
| Maintainer: |
Gilberto Camara <gilberto.camara.inpe at gmail.com> |
| BugReports: |
https://github.com/e-sensing/sits/issues |
| License: |
GPL-2 |
| URL: |
https://github.com/e-sensing/sits/,
https://e-sensing.github.io/sitsbook/ |
| NeedsCompilation: |
yes |
| Language: |
en-US |
| Citation: |
sits citation info |
| Materials: |
NEWS |
| In views: |
Spatial |
| CRAN checks: |
sits results |