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.
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.
Minimum recommended requirements: 16 GB RAM and 4 CPU dual-core.
Version: |
1.5.2 |
Depends: |
R (≥ 4.1.0) |
Imports: |
yaml (≥ 2.3.0), dplyr (≥ 1.1.0), grDevices, graphics, leaflet (≥ 2.2.2), lubridate, luz (≥ 0.4.0), parallel, purrr (≥ 1.0.2), randomForest, Rcpp (≥ 1.0.13), rstac (≥ 1.0.1), sf (≥ 1.0-19), slider (≥ 0.2.0), stats, terra (≥ 1.8-5), tibble (≥ 3.1), tidyr (≥ 1.3.0), tmap (≥ 4.0), torch (≥
0.14.0), 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), methods, mgcv, nnet, openxlsx, proxy, randomForestExplainer, RColorBrewer, RcppArmadillo (≥
0.12), scales, spdep, stringr, supercells (≥ 1.0.0), testthat (≥ 3.1.3), tools, xgboost |
Published: |
2025-02-12 |
DOI: |
10.32614/CRAN.package.sits |
Author: |
Rolf Simoes [aut],
Gilberto Camara [aut, cre, ths],
Felipe Souza [aut],
Felipe Carlos [aut],
Lorena Santos [ctb],
Karine Ferreira [ctb, ths],
Charlotte Pelletier [ctb],
Pedro Andrade [ctb],
Alber Sanchez [ctb],
Estefania Pizarro [ctb],
Gilberto Queiroz [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 |