Satellite Image Time Series Analysis for Earth Observation Data Cubes

Documentation for package ‘sits’ version 1.5.2

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C H I P S misc

sits-package

sits

-- C --

cerrado_2classes

Samples of classes Cerrado and Pasture

-- H --

hist.probs_cube	histogram of prob cubes
hist.raster_cube	histogram of data cubes
hist.sits	Histogram
hist.uncertainty_cube	Histogram uncertainty cubes

-- I --

impute_linear

Replace NA values by linear interpolation

-- P --

plot	Plot time series
plot.class_cube	Plot classified images
plot.class_vector_cube	Plot Segments
plot.dem_cube	Plot DEM cubes
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.probs_vector_cube	Plot probability vector cubes
plot.raster_cube	Plot RGB data cubes
plot.rfor_model	Plot Random Forest model
plot.sar_cube	Plot SAR data cubes
plot.sits	Plot time series
plot.sits_accuracy	Plot confusion matrix
plot.sits_cluster	Plot a dendrogram cluster
plot.som_clean_samples	Plot SOM samples evaluated
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.uncertainty_vector_cube	Plot uncertainty vector cubes
plot.variance_cube	Plot variance cubes
plot.vector_cube	Plot RGB vector data 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_ndvi	Samples of nine classes for the state of Mato Grosso
sits	sits
sits_accuracy	Assess classification accuracy (area-weighted method)
sits_accuracy.class_cube	Assess classification accuracy (area-weighted method)
sits_accuracy.default	Assess classification accuracy (area-weighted method)
sits_accuracy.derived_cube	Assess classification accuracy (area-weighted method)
sits_accuracy.raster_cube	Assess classification accuracy (area-weighted method)
sits_accuracy.sits	Assess classification accuracy (area-weighted method)
sits_accuracy.tbl_df	Assess classification accuracy (area-weighted method)
sits_add_base_cube	Add base maps to a time series data cube
sits_apply	Apply a function on a set of time series
sits_apply.default	Apply a function on a set of time series
sits_apply.derived_cube	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 raster_cube as an sf object.
sits_as_sf.raster_cube	Return a sits_tibble or raster_cube as an sf object.
sits_as_sf.sits	Return a sits_tibble or raster_cube as an sf object.
sits_bands	Get the names of the bands
sits_bands.default	Get the names of the bands
sits_bands.patterns	Get the names of the bands
sits_bands.raster_cube	Get the names of the bands
sits_bands.sits	Get the names of the bands
sits_bands.sits_model	Get the names of the bands
sits_bands<-	Get the names of the bands
sits_bands<-.default	Get the names of the bands
sits_bands<-.raster_cube	Get the names of the bands
sits_bands<-.sits	Get the names of the bands
sits_bbox	Get the bounding box of the data
sits_bbox.default	Get the bounding box of the data
sits_bbox.raster_cube	Get the bounding box of the data
sits_bbox.sits	Get the bounding box of the data
sits_bbox.tbl_df	Get the bounding box of the data
sits_classify	Classify time series or data cubes
sits_classify.default	Classify time series or data cubes
sits_classify.derived_cube	Classify time series or data cubes
sits_classify.raster_cube	Classify time series or data cubes
sits_classify.segs_cube	Classify time series or data cubes
sits_classify.sits	Classify time series or data cubes
sits_classify.tbl_df	Classify time series or data cubes
sits_clean	Cleans a classified map using a local window
sits_clean.class_cube	Cleans a classified map using a local window
sits_clean.default	Cleans a classified map using a local window
sits_clean.derived_cube	Cleans a classified map using a local window
sits_clean.raster_cube	Cleans a classified map using a local window
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_colors	Function to retrieve sits color table
sits_colors_qgis	Function to save color table as QML style for data cube
sits_colors_reset	Function to reset sits color table
sits_colors_set	Function to set sits color table
sits_colors_show	Function to show colors in SITS
sits_combine_predictions	Estimate ensemble prediction based on list of probs cubes
sits_combine_predictions.average	Estimate ensemble prediction based on list of probs cubes
sits_combine_predictions.default	Estimate ensemble prediction based on list of probs cubes
sits_combine_predictions.uncertainty	Estimate ensemble prediction based on list of probs cubes
sits_confidence_sampling	Suggest high confidence samples to increase the training set.
sits_config	Configure parameters for sits package
sits_config_show	Show current sits configuration
sits_config_user_file	List the cloud collections supported by sits
sits_cube	Create data cubes from image collections
sits_cube.local_cube	Create data cubes from image collections
sits_cube.sar_cube	Create data cubes from image collections
sits_cube.stac_cube	Create data cubes from image collections
sits_cube_copy	Copy the images of a cube to a local directory
sits_factory_function	Create a closure for calling functions with and without data
sits_filter	Filter time series with smoothing filter
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_class	Get values from classified maps
sits_get_class.csv	Get values from classified maps
sits_get_class.data.frame	Get values from classified maps
sits_get_class.default	Get values from classified maps
sits_get_class.sf	Get values from classified maps
sits_get_class.shp	Get values from classified maps
sits_get_class.sits	Get values from classified maps
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_get_probs	Get values from probability maps
sits_get_probs.csv	Get values from probability maps
sits_get_probs.data.frame	Get values from probability maps
sits_get_probs.default	Get values from probability maps
sits_get_probs.sf	Get values from probability maps
sits_get_probs.shp	Get values from probability maps
sits_get_probs.sits	Get values from probability maps
sits_impute	Replace NA values in time series with imputation function
sits_kfold_validate	Cross-validate time series samples
sits_labels	Get labels associated to a data set
sits_labels.default	Get labels associated to a data set
sits_labels.derived_cube	Get labels associated to a data set
sits_labels.derived_vector_cube	Get labels associated to a data set
sits_labels.patterns	Get labels associated to a data set
sits_labels.raster_cube	Get labels associated to a data set
sits_labels.sits	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<-.class_cube	Change the labels of a set of time series
sits_labels<-.default	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_label_classification.default	Build a labelled image from a probability cube
sits_label_classification.derived_cube	Build a labelled image from a probability cube
sits_label_classification.probs_cube	Build a labelled image from a probability cube
sits_label_classification.probs_vector_cube	Build a labelled image from a probability cube
sits_label_classification.raster_cube	Build a labelled image from a probability cube
sits_lighttae	Train a model using Lightweight Temporal Self-Attention Encoder
sits_list_collections	List the cloud collections supported by sits
sits_merge	Merge two data sets (time series or cubes)
sits_merge.default	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_mgrs_to_roi	Convert MGRS tile information to ROI in WGS84
sits_mixture_model	Multiple endmember spectral mixture analysis
sits_mixture_model.default	Multiple endmember spectral mixture analysis
sits_mixture_model.derived_cube	Multiple endmember spectral mixture analysis
sits_mixture_model.raster_cube	Multiple endmember spectral mixture analysis
sits_mixture_model.sits	Multiple endmember spectral mixture analysis
sits_mixture_model.tbl_df	Multiple endmember spectral mixture analysis
sits_mlp	Train multi-layer perceptron models using torch
sits_model_export	Export classification models
sits_model_export.sits_model	Export classification models
sits_mosaic	Mosaic classified cubes
sits_patterns	Find temporal patterns associated to a set of time series
sits_predictors	Obtain predictors for time series samples
sits_pred_features	Obtain numerical values of predictors for time series samples
sits_pred_normalize	Normalize predictor values
sits_pred_reference	Obtain categorical id and predictor labels for time series samples
sits_pred_references	Obtain categorical id and predictor labels for time series samples
sits_pred_sample	Obtain a fraction of the predictors data frame
sits_reclassify	Reclassify a classified cube
sits_reclassify.class_cube	Reclassify a classified cube
sits_reclassify.default	Reclassify a classified cube
sits_reduce	Reduces a cube or samples from a summarization function
sits_reduce.raster_cube	Reduces a cube or samples from a summarization function
sits_reduce.sits	Reduces a cube or samples from a summarization function
sits_reduce_imbalance	Reduce imbalance in a set of samples
sits_regularize	Build a regular data cube from an irregular one
sits_regularize.combined_cube	Build a regular data cube from an irregular one
sits_regularize.default	Build a regular data cube from an irregular one
sits_regularize.dem_cube	Build a regular data cube from an irregular one
sits_regularize.derived_cube	Build a regular data cube from an irregular one
sits_regularize.rainfall_cube	Build a regular data cube from an irregular one
sits_regularize.raster_cube	Build a regular data cube from an irregular one
sits_regularize.sar_cube	Build a regular data cube from an irregular one
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_sampling_design	Allocation of sample size to strata
sits_segment	Segment an image
sits_select	Filter bands on a data set (tibble or cube)
sits_select.default	Filter bands on a data set (tibble or cube)
sits_select.raster_cube	Filter bands on a data set (tibble or cube)
sits_select.sits	Filter bands on a data set (tibble or cube)
sits_sgolay	Filter time series with Savitzky-Golay filter
sits_slic	Segment an image using SLIC
sits_smooth	Smooth probability cubes with spatial predictors
sits_smooth.default	Smooth probability cubes with spatial predictors
sits_smooth.derived_cube	Smooth probability cubes with spatial predictors
sits_smooth.probs_cube	Smooth probability cubes with spatial predictors
sits_smooth.probs_vector_cube	Smooth probability cubes with spatial predictors
sits_smooth.raster_cube	Smooth probability cubes with spatial predictors
sits_som	Use SOM for quality analysis of time series samples
sits_som_clean_samples	Cleans the samples based on SOM map information
sits_som_evaluate_cluster	Evaluate cluster
sits_som_map	Use SOM for quality analysis of time series samples
sits_som_remove_samples	Evaluate cluster
sits_stats	Obtain statistics for all sample bands
sits_stratified_sampling	Allocation of sample size to strata
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_tiles_to_roi	Convert MGRS tile information to ROI in WGS84
sits_timeline	Get timeline of a cube or a set of time series
sits_timeline.default	Get timeline of a cube or a set of time series
sits_timeline.derived_cube	Get timeline of a cube or a set of time series
sits_timeline.raster_cube	Get timeline of a cube or a set of time series
sits_timeline.sits	Get timeline of a cube or a set of time series
sits_timeline.sits_model	Get timeline of a cube or a set of time series
sits_timeline.tbl_df	Get timeline of a cube or a set of time series
sits_timeseries_to_csv	Export a a full sits tibble to the CSV format
sits_to_csv	Export a sits tibble metadata to the CSV format
sits_to_csv.default	Export a sits tibble metadata to the CSV format
sits_to_csv.sits	Export a sits tibble metadata to the CSV format
sits_to_csv.tbl_df	Export a sits tibble metadata to the CSV format
sits_to_xlsx	Save accuracy assessments as Excel files
sits_to_xlsx.list	Save accuracy assessments as Excel files
sits_to_xlsx.sits_accuracy	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_uncertainty	Estimate classification uncertainty based on probs cube
sits_uncertainty.default	Estimate classification uncertainty based on probs cube
sits_uncertainty.probs_cube	Estimate classification uncertainty based on probs cube
sits_uncertainty.probs_vector_cube	Estimate classification uncertainty based on probs cube
sits_uncertainty_sampling	Suggest samples for enhancing classification accuracy
sits_validate	Validate time series samples
sits_variance	Calculate the variance of a probability cube
sits_variance.default	Calculate the variance of a probability cube
sits_variance.derived_cube	Calculate the variance of a probability cube
sits_variance.probs_cube	Calculate the variance of a probability cube
sits_variance.raster_cube	Calculate the variance of a probability cube
sits_view	View data cubes and samples in leaflet
sits_view.class_cube	View data cubes and samples in leaflet
sits_view.class_vector_cube	View data cubes and samples in leaflet
sits_view.data.frame	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_view.uncertainty_cube	View data cubes and samples in leaflet
sits_view.vector_cube	View data cubes and samples in leaflet
sits_whittaker	Filter time series with whittaker filter
sits_xgboost	Train extreme gradient boosting models
summary.class_cube	Summarize data cubes
summary.raster_cube	Summarize data cubes
summary.sits	Summarize sits
summary.sits_accuracy	Summarize accuracy matrix for training data
summary.sits_area_accuracy	Summarize accuracy matrix for area data
summary.variance_cube	Summarise variance cubes

-- misc --

`sits_labels<-`

Change the labels of a set of time series