Satellite Image Time Series Analysis for Earth Observation Data Cubes

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Documentation for package ‘sits’ version 1.1.0

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C P S misc

sits-package sits

-- C --

cerrado_2classes Samples of classes Cerrado and Pasture

-- P --

plot Plot time series
plot.classified_image Plot classified images
plot.geo_distances Make a kernel density plot of samples distances.
plot.patterns Plot patterns that describe classes
plot.predicted Plot time series predictions
plot.probs_cube Plot probability cubes
plot.raster_cube Plot RGB data cubes
plot.rfor_model Plot Random Forest model
plot.sits Plot time series
plot.som_evaluate_cluster Plot confusion between clusters
plot.som_map Plot a SOM map
plot.torch_model Plot Torch (deep learning) model
plot.uncertainty_cube Plot uncertainty cubes
plot.xgb_model Plot XGB model
point_mt_6bands A time series sample with data from 2000 to 2016

-- S --

samples_l8_rondonia_2bands Samples of Amazon tropical forest biome for deforestation analysis
samples_modis_4bands Samples of nine classes for the state of Mato Grosso
sits sits
sits_accuracy Assess classification accuracy (area-weighted method)
sits_accuracy.classified_image Assess classification accuracy (area-weighted method)
sits_accuracy.sits Assess classification accuracy (area-weighted method)
sits_apply Apply a function on a set of time series
sits_apply.raster_cube Apply a function on a set of time series
sits_apply.sits Apply a function on a set of time series
sits_as_sf Return a sits_tibble or sits_cube as an sf object.
sits_as_sf.raster_cube Return a sits_tibble or sits_cube as an sf object.
sits_as_sf.sits Return a sits_tibble or sits_cube as an sf object.
sits_bands Get the names of the bands
sits_bands.patterns Get the names of the bands
sits_bands.sits Get the names of the bands
sits_bands.sits_cube Get the names of the bands
sits_bands.sits_model Get the names of the bands
sits_bbox Get the bounding box of the data
sits_bbox.sits Get the bounding box of the data
sits_bbox.sits_cube Get the bounding box of the data
sits_classify Classify time series or data cubes
sits_classify.raster_cube Classify time series or data cubes
sits_classify.sits Classify time series or data cubes
sits_clustering Find clusters in time series samples
sits_cluster_clean Removes labels that are minority in each cluster.
sits_cluster_dendro Find clusters in time series samples
sits_cluster_frequency Show label frequency in each cluster produced by dendrogram analysis
sits_confidence_sampling Suggest high confidence samples to increase the training set.
sits_config Configure parameters for sits package
sits_configuration Configure parameters for sits package
sits_config_show Configure parameters for sits package
sits_cube Create data cubes from image collections
sits_cube.local_cube Create data cubes from image collections
sits_cube.stac_cube Create data cubes from image collections
sits_filter Filter time series and data cubes
sits_filters Filter time series and data cubes
sits_formula_linear Define a linear formula for classification models
sits_formula_logref Define a loglinear formula for classification models
sits_geo_dist Compute the minimum distances among samples and prediction points.
sits_get_data Get time series from data cubes and cloud services
sits_get_data.csv Get time series from data cubes and cloud services
sits_get_data.data.frame Get time series from data cubes and cloud services
sits_get_data.default Get time series from data cubes and cloud services
sits_get_data.sf Get time series from data cubes and cloud services
sits_get_data.shp Get time series from data cubes and cloud services
sits_get_data.sits Get time series from data cubes and cloud services
sits_impute_linear Replace NA values with linear interpolation
sits_kfold_validate Cross-validate time series samples
sits_labels Get labels associated to a data set
sits_labels.patterns Get labels associated to a data set
sits_labels.sits Get labels associated to a data set
sits_labels.sits_cube Get labels associated to a data set
sits_labels.sits_model Get labels associated to a data set
sits_labels<- Change the labels of a set of time series
sits_labels<-.probs_cube Change the labels of a set of time series
sits_labels<-.sits Change the labels of a set of time series
sits_labels_summary Inform label distribution of a set of time series
sits_labels_summary.sits Inform label distribution of a set of time series
sits_label_classification Build a labelled image from a probability cube
sits_lighttae Train a model using Lightweight Temporal Self-Attention Encoder
sits_list_collections Configure parameters for sits package
sits_merge Merge two data sets (time series or cubes)
sits_merge.raster_cube Merge two data sets (time series or cubes)
sits_merge.sits Merge two data sets (time series or cubes)
sits_mixture_model Multiple endmember spectral mixture analysis
sits_mlp Train multi-layer perceptron models using torch
sits_patterns Find temporal patterns associated to a set of time series
sits_reduce_imbalance Reduce imbalance in a set of samples
sits_regularize Build a regular data cube from an irregular one
sits_resnet Train ResNet classification models
sits_rfor Train random forest models
sits_run_examples Informs if sits examples should run
sits_run_tests Informs if sits tests should run
sits_sample Sample a percentage of a time series
sits_select Filter bands on a data set (tibble or cube)
sits_select.patterns Filter bands on a data set (tibble or cube)
sits_select.sits Filter bands on a data set (tibble or cube)
sits_select.sits_cube Filter bands on a data set (tibble or cube)
sits_sgolay Filter time series and data cubes
sits_smooth Smooth probability cubes with spatial predictors
sits_smooth.bayes Smooth probability cubes with spatial predictors
sits_smooth.bilateral Smooth probability cubes with spatial predictors
sits_som Use SOM for quality analysis of time series samples
sits_som_clean_samples Use SOM for quality analysis of time series samples
sits_som_evaluate_cluster Use SOM for quality analysis of time series samples
sits_som_map Use SOM for quality analysis of time series samples
sits_svm Train support vector machine models
sits_tae Train a model using Temporal Self-Attention Encoder
sits_tempcnn Train temporal convolutional neural network models
sits_timeline Get timeline of a cube or a set of time series
sits_time_series Get the time series for a row of a sits tibble
sits_to_csv Export a sits tibble metadata to the CSV format
sits_to_xlsx Save accuracy assessments as Excel files
sits_train Train classification models
sits_tuning Tuning machine learning models hyper-parameters
sits_tuning_hparams Tuning machine learning models hyper-parameters
sits_twdtw_classify Find matches between patterns and time series using TWDTW
sits_uncertainty Estimate classification uncertainty based on probs cube
sits_uncertainty.entropy Estimate classification uncertainty based on probs cube
sits_uncertainty.least Estimate classification uncertainty based on probs cube
sits_uncertainty.margin Estimate classification uncertainty based on probs cube
sits_uncertainty.ratio Estimate classification uncertainty based on probs cube
sits_uncertainty_sampling Suggest samples for enhancing classification accuracy
sits_validate Validate time series samples
sits_values Return the values of a set of time series
sits_view View data cubes and samples in leaflet
sits_view.classified_image View data cubes and samples in leaflet
sits_view.default View data cubes and samples in leaflet
sits_view.probs_cube View data cubes and samples in leaflet
sits_view.raster_cube View data cubes and samples in leaflet
sits_view.sits View data cubes and samples in leaflet
sits_view.som_map View data cubes and samples in leaflet
sits_whittaker Filter time series and data cubes
sits_xgboost Train extreme gradient boosting models

-- misc --

%>% Pipe
.sits_get_top_values Get top values of a raster.
:= Set by reference in data.table
_PACKAGE sits
`sits_labels<-` Change the labels of a set of time series