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sits
View on CRAN: Click
here
Download and install sits package within the R console
Install from CRAN:
install.packages("sits")
Install from Github:
library("remotes")
install_github("cran/sits")
Install by package version:
library("remotes")
install_version("sits", "1.5.2")
Attach the package and use:
library("sits")
Maintained by
Gilberto Camara
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.sits . https://github.com/e-sensing/sits/issues . https://github.com/e-sensing/sits/ . https://e-sensing.github.io/sitsbook/ . sits citation info . sits results . sits.pdf . sits_1.5.2.tar.gz . sits_1.5.2.zip . sits_1.5.2.zip . sits_1.5.2.zip . sits_1.5.2.tgz . sits_1.5.2.tgz . sits_1.5.2.tgz . sits_1.5.2.tgz . sits archive . https://CRAN.R-project.org/package=sits .
First Published: 2022-05-19
Latest Update: 2023-11-02
Description:
An end-to-end toolkit for land use and land cover classification using big Earth observation data, based on machine learning methods applied to satellite image data cubes, as described in Simoes et al (2021) <doi:10.3390/rs13132428>. Builds regular data cubes from collections in AWS, Microsoft Planetary Computer, Brazil Data Cube, and Digital Earth Africa using the Spatio-temporal Asset Catalog (STAC) protocol (<https://stacspec.org/> and the 'gdalcubes' R package developed by Appel and Pebesma (2019) <doi:10.3390/data4030092>. 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 as presented by Santos et al (2021) <doi:10.1016/j.isprsjprs.2021.04.014>. Provides machine learning methods including support vector machines, random forests, extreme gradient boosting, multi-layer perceptrons, temporal convolutional neural networks proposed by Pelletier et al (2019) <doi:10.3390/rs11050523>, residual networks by Fawaz et al (2019) <doi:10.1007/s10618-019-00619-1>, and temporal attention encoders by Garnot and Landrieu (2020) <doi:10.48550/arXiv.2007.00586>. Performs efficient classification of big Earth observation data cubes and includes functions for post-classification smoothing based on Bayesian inference, and methods for uncertainty assessment. Enables best practices for estimating area and assessing accuracy of land change as recommended by Olofsson et al (2014) <doi:10.1016/j.rse.2014.02.015>. Minimum recommended requirements: 16 GB RAM and 4 CPU dual-core.
How to cite:
Gilberto Camara (2022). sits: Satellite Image Time Series Analysis for Earth Observation Data Cubes. R package version 1.5.2, https://cran.r-project.org/web/packages/sits. Accessed 28 Apr. 2025.
Previous versions and publish date:
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View sits citation profile
Other R packages that sits depends,
imports, suggests or enhances
Complete documentation for sits
Functions, R codes and Examples using
the sits R package
Some associated functions: cerrado_2classes . dot-check_date_parameter . plot.class_cube . plot.class_vector_cube . plot.geo_distances . plot . plot.patterns . plot.predicted . plot.probs_cube . plot.probs_vector_cube . plot.raster_cube . plot.rfor_model . plot.sits_accuracy . plot.sits_cluster . plot.som_evaluate_cluster . plot.som_map . plot.torch_model . plot.uncertainty_cube . plot.variance_cube . plot.vector_cube . plot.xgb_model . point_mt_6bands . print.sits_accuracy . print.sits_area_accuracy . samples_l8_rondonia_2bands . samples_modis_ndvi . sits-package . sits_accuracy . sits_accuracy_summary . sits_apply . sits_as_sf . sits_bands . sits_bbox . sits_classify . sits_cluster_clean . sits_cluster_dendro . sits_cluster_frequency . sits_colors . sits_colors_qgis . sits_colors_reset . sits_colors_set . sits_colors_show . sits_combine_predictions . sits_confidence_sampling . sits_config . sits_config_show . sits_cube . sits_cube_copy . sits_factory_function . sits_filter . sits_formula_linear . sits_formula_logref . sits_geo_dist . sits_get_data . sits_kfold_validate . sits_label_classification . sits_labels . sits_labels_summary . sits_lighttae . sits_list_collections . sits_merge . sits_mixture_model . sits_mlp . sits_model_export . sits_mosaic . sits_patterns . sits_pred_features . sits_pred_normalize . sits_pred_reference . sits_pred_sample . sits_predictors . sits_reclassify . sits_reduce_imbalance . sits_regularize . sits_resnet . sits_rfor . sits_run_examples . sits_run_tests . sits_sample . sits_segment . sits_select . sits_sgolay . sits_show_prediction . sits_slic . sits_smooth . sits_som . sits_som_clean_samples . sits_som_evaluate_cluster . sits_stats . sits_svm . sits_tae . sits_tempcnn . sits_timeline . sits_to_csv . sits_to_xlsx . sits_train . sits_tuning . sits_tuning_hparams . sits_uncertainty . sits_uncertainty_sampling . sits_validate . sits_variance . sits_view . sits_whittaker . sits_xgboost . summary.class_cube . summary.raster_cube . summary.sits . summary.sits_accuracy . summary.sits_area_accuracy . tick-sits_labels-set-tick .
Some associated R codes: RcppExports.R . api_accessors.R . api_accuracy.R . api_apply.R . api_band.R . api_bbox.R . api_block.R . api_check.R . api_chunks.R . api_classify.R . api_clean.R . api_cluster.R . api_colors.R . api_combine_predictions.R . api_comp.R . api_conf.R . api_csv.R . api_cube.R . api_data.R . api_debug.R . api_download.R . api_factory.R . api_file.R . api_file_info.R . api_gdal.R . api_gdalcubes.R . api_imputation.R . api_jobs.R . api_label_class.R . api_mixture_model.R . api_ml_model.R . api_mosaic.R . api_parallel.R . api_period.R . api_plot_raster.R . api_plot_time_series.R . api_plot_vector.R . api_point.R . api_predictors.R . api_raster.R . api_raster_sub_image.R . api_raster_terra.R . api_reclassify.R . api_regularize.R . api_roi.R . api_s2tile.R . api_samples.R . api_segments.R . api_sf.R . api_shp.R . api_signal.R . api_smooth.R . api_smote.R . api_som.R . api_source.R . api_source_aws.R . api_source_bdc.R . api_source_deafrica.R . api_source_hls.R . api_source_local.R . api_source_mpc.R . api_source_sdc.R . api_source_stac.R . api_source_usgs.R . api_space_time_operations.R . api_stac.R . api_stats.R . api_summary.R . api_tibble.R . api_tile.R . api_timeline.R . api_torch.R . api_torch_psetae.R . api_ts.R . api_tuning.R . api_uncertainty.R . api_utils.R . api_values.R . api_variance.R . api_vector.R . api_vector_info.R . api_view.R . data.R . sits-package.R . sits_accuracy.R . sits_active_learning.R . sits_apply.R . sits_bands.R . sits_bbox.R . sits_classify.R . sits_cluster.R . sits_colors.R . sits_combine_predictions.R . sits_config.R . sits_csv.R . sits_cube.R . sits_cube_copy.R . sits_factory.R . sits_filters.R . sits_geo_dist.R . sits_get_data.R . sits_label_classification.R . sits_labels.R . sits_lighttae.R . sits_machine_learning.R . sits_merge.R . sits_mixture_model.R . sits_mlp.R . sits_model_export.R . sits_mosaic.R . sits_patterns.R . sits_plot.R . sits_predictors.R . sits_reclassify.R . sits_regularize.R . sits_resnet.R . sits_sample_functions.R . sits_segmentation.R . sits_select.R . sits_sf.R . sits_smooth.R . sits_som.R . sits_summary.R . sits_tae.R . sits_tempcnn.R . sits_timeline.R . sits_train.R . sits_tuning.R . sits_uncertainty.R . sits_utils.R . sits_validate.R . sits_variance.R . sits_view.R . sits_xlsx.R . zzz.R . Full sits package functions and examples
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