Changes in version 1.5 New features in SITS version 1.5.4 - Fix bug in sits_summary() in obtaining the variance summary with multiple tiles - Add new plot type in sits_accuracy() function ("confusion_matrix") - Add new type parameter in sits_accuracy() function for selecting plot type - Improve plot.som_evaluate_cluster function to include a legend parameter - Add new sits_snic segmentation function based on the snic package - Add pkgdown documentation website for the sits package - Add new imputation functions: impute_mean(), impute_median(), and impute_mean_window() - Improve validation messages in the sits_accuracy() function - Add sits_labels<- support for probs_vector_cube and probs_class_cube - Extend the sits_colors_qgis() function to export sits color palettes to QGIS for vector cubes - Fix area calculations in sits_summary() - Add res parameter to the sits_mosaic() function to allow generating mosaics at different resolutions Hotfix version 1.5.3-1 - Replace arma::is_finite with std::isfinite Hotfix version 1.5.3-1 - Improve documentation for sits_labels - Improve documentation for sits_train - Improve documentation of roi parameter in sits_mosaic and sits_plot - Improve sits_accuracy messages when results are empty - Update TAE implementation to make better use of embeddings - Fix MPC token management in sits_cube_copy - Fix error in message for missing colors - Fix division by zero error in sits_texture - Add res parameter in sits_mosaic New features in SITS version 1.5.3 - Introduce a Python API for SITS (pysits) - New version of the documentation on code and sitsbook - Implement SAR texture measures based on co-occurrence matrices - Refactor MPC token generation - Introduce sits_roi_to_tiles function - Add support for HLS collection from MPC - Support for TERRASCOPE products WORLD COVER and WORLD CEREAL - Support for Open Geo Hub Harmonized Landsat collection - Review sits_get_data() implementation - Improvements in sits_mosaic() - Fix sits_clean() multicores operations - Add WebGL as default engine in sits_view() using leafgl - Review CDSE implementation to support OpenSearch and STAC endpoints - Improve speed in sits_summary() and sits_stratified sampling - Fix problems in sits_regularize() - Include label parameter on sits_select() - General bug fixes New features in SITS version 1.5.2 - Include exclusion_mask parameter in sits_classify() and sits_smooth() - Support classification data cubes with NA values - Support for multiple tiling system in sits_regularize(), including MGRS and Brazil Data Cube grids - Review sits_merge() implementation to better handle multiple scenario cases - Support roi when plotting data cubes - Refactor sits_cube_copy() to improve timeout handling and efficiency - Include filtering by tiles in regularization operation - Include start and end dates for each collection in sits_list_collections() - Add support to SpatExtent object from terra as roi in sits_cube() - Update crs usage in sits_get_data() to support WKT - Implement Sakoe-Chiba approximation for DTW algorithm - Support for tmap version 4.0 - Enhance performance and usability in visualization functions - Enhance sits_classify() performance with segments classification - Support for interactive visualization with SOM samples - General bug fixes New features in SITS version 1.5.1 - Support for ESA World Cover map - Support for Digital Earth Australia products - Support for Digital Earth Africa geomedian products - Support for PLANET Mosaic products - Improve .netrc access to Harmonized Landsat-Sentinel cubes - Use ROI to cut data cube after mosaic operation - Support for raster and vector classification using DEM as base cubes - Convert from 'httr' package to 'httr2' package - Remove deprecated class to purrr::map_dfc, purrr::map_dfr and similar - Fix tuning for torch models - Add geometry validation when extracting time series - Add multicores processing support for active learning sampling methods - Remove tapply from .reg_cube_split_assets() for R 4.X compatibility - Fix sits_merge() function that was not merging SAR and OPTICAL cubes - Rename n_input_pixels back to input_pixels for compatibility with models trained in old versions of the package - Fix torch usage in Apple M3 - Fix date parameter usage in sits_view() - Improve plot() performance using raster overviews New features in SITS version 1.5.0 - Support for SENTINEL-1-RTC and SENTINEL-2-L2A in CDSE - Include support for DEA products SENTINEL-1-RTC, LS5-SR, LS7-SR, LS9-SR, ALOS-PALSAR-MOSAIC, NDVI ANOMALY, DAILY CHIRPS, MONTHLY CHIRPS and DEM-30 - Support for Sentinel-1 GRD and RTC collections from Planetary Computer - Include parameter tile to select data from Sentinel-1 (MPC) - Include parameter tile to select data from Sentinel-1 and Sentinel-2 (DEAFRICA) - Include parameter tile to select data from HLS collections - Improved support for GPU-based classification of deep learning models - Support for non-normalized derived indexes - Support for shapefiles as ROI in sits_cube() - Fix inconsistencies in HLS scale factors - New function to obtain ROI based on MGRS tiles - Add support for uncertainty cubes in sits_mosaic() - Improve performance of sits_segment() using chunk parallelization - Include uncertainty measures for vector probability cubes - New sits_clean() function to improve classified maps - New functions sits_sampling_design() and sits_stratified_sampling() - New sits_reduce() function - Include dtw distance when building SOM maps Changes in version 1.4 Hotfix version 1.4.2-3 - Fix font download in package initialization Hotfix version 1.4.2-2 - Fix integer overflow bug in sits_classify() segments Hotfix version 1.4.2-1 - Fix crs bug in sits_apply() - Update file name in clean feature - Fix time series extraction bug with segments - Fix examples New features in SITS version 1.4.2 - Support for vector data cubes, including visualisation - Object-based time series analysis using spatio-temporal segmentation - Improved support for GPU usage when running deep learning algorithms - New function to clean values by modal filter in classified images - Added experimental support for Sentinel-1 images available on MPC - Summary function now includes cloud cover information - General bug fixes New features in SITS version 1.4.1 - Updated access to collections in Brazil Data Cube, HLS, and AWS - Corrected errors in labelling of classified cubes - Created a factory of functions for segmentation New features in SITS version 1.4.0 - New function for image segmentation based on supercells package - New version of sits_get_data() to extract average values of time series based on segments - Support for Harmonized Landsat Sentinel (HLS) collections from NASA - Support for probability cubes and uncertainty cubes in sits_view() - New summary() function to show details of data cubes and time series tibbles - General big fixes Changes in version 1.3 New features in SITS version 1.3.0 - Remove NOTES and WARNINGS pointed out by CRAN - New sits_mosaic() function for improving visualization of large data sets - Add support to cubes with no cloud coverage information in sits_regularize() - Improve sits_cube_copy() for downloading data from the internet - Tested and validated GPU support for deep learning models in sits - Added multithread support for deep learning models in sits_train() - Improve sits_combine_predictions() - Remove dependencies on data.table package - Organize and clean internal APIs - General bug fixes Changes in version 1.2 Hotfix version 1.2.0-4 - Fix .raster_file_blocksize.terra() bug (issue #918) Hotfix version 1.2.0-3 - Fix stars proxy bug (issue #902) - Fix purrr cross deprecation - Fix ggplot2 aes_string deprecation Hotfix version 1.2.0-2 - Fix tibble subsetting bug (issue #893) Hotfix version 1.2.0-1 - Fix sits_som_clean_samples() bug (issue #890) New features in SITS version 1.2.0 - sits_get_data() can be used to retrieve samples in classified cube - Support for mixture models (sits_mixture_model()) - Joining cubes in a mosaic (sits_mosaic_cubes()) - Extract the trained ML model (sits_model()) - Downloading and copying data cubes (sits_cube_copy()) - Combine prediction by average and entropy (sits_combine_predictions()) - Significant performance improvement when working with COG files - Allow plot of confusion matrix (sits_plot) - Support for operations on CLOUD band in sits_apply() - Bug fixes and internal re-engineering for better code maintenance Changes in version 1.1 Hotfix version 1.1.0-8 - Fix support to BDC cubes in sits_regularize() (issue #848) - Fix support to classified_image cubes in sits_labels()<- (issue #846) Hotfix version 1.1.0-7 - Fix out of memory error in sits_label_classification() and sits_smooth() (issue #850) Hotfix version 1.1.0-6 - Fix resume feature in sits_classify() on BDC cubes (issue #844) Hotfix version 1.1.0-5 - Fix bound box issue in image blocks produced by sits_apply() Hotfix version 1.1.0-4 - Fix MPC cube time expiration bug Hotfix version 1.1.0-3 - Fix bound box issue in image blocks produced by sits_apply() Hotfix version 1.1.0-2 - Improve sits_values() function (issue #810) - Fix sits_reduce_imbalance() function (issue #809) Hotfix version 1.1.0-1 - Fix sits_accuracy() function (issue #807) New features in SITS version 1.1.0 - Introduced support to kernel functions in sits_apply - Introduced new function sits_mixture_model for spectral mixture analysis - Support for the Swiss Data Cube (swissdatacube.org) - Support for mosaic visualization in sits_view - Introduced new function sits_as_sf to convert sits objects to sf - Export images as COG in sits_regularize - Add roi parameter in sits_regularize function - Add crs parameter in sits_get_data - Change Microsoft Planetary Computer source name to "MPC" - Fix several bugs and improve performance Changes in version 1.0 New features in SITS version 1.0.0 - Available on CRAN. - Hotfix to improve sits_whittaker() function to process cube. - Update documentation to match CRAN standards Changes in version 0.17 New features in SITS version 0.17.0 - Introduced new classifier model sits_lighttae() (Lightweight Temporal Self-Attention) - Introduced sits_uncertainty_sampling() for active learning - Introduced sits_confidence_samples() for semi-supervised learning - Introduced sits_geo_dist() to generate samples-samples and samples-predicted plot - Introduced sits_tuning() for random search of machine learning parameters - Introduced sits_reduce_imbalance() function to balance class samples - Introduced sits_as_sf() to convert a sits tibble to a sf object - Support to torchopt deep learning optimizer package - New types of sits_uncertainty(): least confidence and margin of confidence Improvements in SITS version 0.17.0 - Implement parallel processing for sits_kfold_validate() - Change data to samples in sits machine learning classifiers (NOTE: models trained in previous versions is no longer supported) - Change deep learning functions to snake case - Remove file parameter in sits_get_data() function - Update documentation - Improve several internal functions performances - Fix several bugs Changes in version 0.16 New features in SITS version 0.16.3 - reimplemented all deep learning functions using torch package and remove keras dependence - Introduced sits_TAE() classification model - Introduced sits_lightgbm() classification model - Simplified sits_regularize() parameters - Improve sits_regularize() to reach production level quality - Improve sits_regularize() to use C++ internal functions - Include improved version of gdalcubes - Improve sits_cube() to open results cube - Update plot() parameters on raster cubes - Support multi-tile for classified cube in sits_view() New features in SITS version 0.16.2 - Improve sits_get_data() to accept tibbles - Remove multiples progress bar from sits_cube() - Improve sits_regularize() to process in parallel by tiles, bands, and dates - Improve sits_regularize() to check malformed files New features in SITS version 0.16.1 - Update AWS_NO_SIGN_REQUEST environment variable - Solved bug in .gc_get_valid_interval() function. - Now sits_regularize has a fault tolerance system, so that if there is a processing error the function will delete the malformed files and create them again. - sits_regularize function has a new parameter called multithreads. - sits_cube function for local cubes has a new parameter called multicores. - Print F1 score in sits_kfold_validate with more than 2 labels. New features in SITS version 0.16.0-1 - hotfix sits_cube() function to tolerate malformed paths from STAC service; New features in SITS version 0.16.0 - Include sits_apply() function to generate new bands from existing ones; - Improve sits_accuracy() function to work with multiple cubes; - Add band parameter to sits_view() - Introduce sits_uncertainty() function to provide uncertainty measure to probability maps; - Improve sits_regularize() by taking least cloud cover by default method to compose images - Bug fixes; Changes in version 0.15 New features in SITS version 0.15.1-1 - Fix bug in sits_regularize that generated images with artifacts - Fix wrong bbox in sits_cube from STAC AWS Sentinel-2 New features in SITS version 0.15.1 - Update README.Rmd - Support sits_timeline() to sits model objects - Update drone image - Simplify config_colors.yml by removing palette names - Temporary python files are being generated in the check - Organize color handling in SITS - Organize configuration files - Improve preconditions in sits_regularize() - Compress external data with bzip2 - Update gdalcubes format files - Update rstac version - Check provided parameters in sits_regularize function - Use default palette for SOM colors - Remove start_date and end_date from validation csv file - Use a default brewer palette to plot classified cube - Improve package help pages - Remove unused data sets - Remove rarely used functions - sits_regularize() is producing Float64 images as output - Full support for Microsoft Planetary Computing New features in SITS version 0.15.0-4 - Change gdalcubes_chunk_size in "config.yml" to improve sits_regularize(). New features in SITS version 0.15.0-3 - Fix bug in .source_collection_access_test to pass ellipsis to rstac::post_request function. New features in SITS version 0.15.0-2 - Fix bug in .source_collection_access_test to pass ellipsis to rstac::post_request function. - Update drone version New features in SITS version 0.15.0-1 - Fix bug in sits_plot - Fix bug in sits_timeline for cubes that do not have the same temporal extent. New features in SITS version 0.15.0 - Support for regularization of collections in DEAFRICA and USGS improvement - Collection S2_10_16D_STK-1 removed from BDC source in config file - Add a color for NoClass label improvement - Change mapview to leaflet package - Standardize cube creation parameters - Remove CLASSIFIED and PROBS sources from config file - Change minimal version requirement of terra package to 1.4-11 - Update sits_list_collections() to indicate open data collection - Geographical visualization of samples - Remove dependencies on packages ptw, signal and MASS - Add support to open_data collections in config file - Change default output_dir parameter - Remove sits_cube_clone() function - Plot RGB images from raster cubes - Fixed error in sits_select() for bands in raster cube - Update examples in demo - Support open data collections of DEAFRICA and AWS - Support USGS STAC Landsat 8 catalog - User can provide resampling method to sits_regularize() function - Add support to open data collections on 'AWS' source - Remove OPENDATA source - Update documentation - Resolve ambiguity in "bands" parameter for data cubes - Remove "sits_bands" assignment function - Include "labels" information only on probs and labelled data cubes - Remove S2_10-1 BDC collection from config - Other bug fixes Changes in version 0.14 New features in SITS version 0.14.1-1 - Bug in cube generated by sits_regularize() cannot have "CLOUD" band New features in SITS version 0.14.1 - Implement new function sits_list_collections() - Update gdalcubes parameters - Implement .source_bands_resampling() - Remove name from demo file - Improve sits_som_clean_samples() function - Improve sits_bands<-() function - Improve sits_select() function - Error in cloud band of CBERS4 data example - Include a function to list collections available in cloud services - sits_cube_copy() does not include information on the tile - Get spatial resolution from config file - Fix partial merge configuration file - Change bbox to roi in sits New features in SITS version 0.14.0-2 - fix sits_bbox() function New features in SITS version 0.14.0-1 - fix duplicate link in AWS STAC New features in SITS version 0.14.0 - Now the plot of a classified cube requires a legend or a palette if the labels are not in the default sits palette. - Support for S2-SEN2COR_10_16D_STK-1 BDC collection - Remove function name from msg in check function - Add satellite and sensor info in config file - Remove imager, ranger, proto, and future packages from sits - Support for different providers to LOCAL sources - LOCAL source is dynamically built - Remove sits_cube.local_cube() function parameters satellite and sensor - Add parameters origin and collection to sits_cube.local_cube() function - Fix LOCAL source examples and tests Changes in version 0.13 New features in SITS version 0.13.1 - Update and add more tests in CI - Implement new check functions - Change error and warning messages - fix deprecated warnings in keras package - bug fixes New features in SITS version 0.13.0-3 - Update documentation in Machine Learning methods - Hotfix bug in neuron labelling New features in SITS version 0.13.0-2 - Bug fixes in BDC MODIS cube New features in SITS version 0.13.0-1 - Bug fixes in check STAC bands - Change Landsat-8 (LC8_30-1) product metadata for BDC source New features in SITS version 0.13.0 - Create API for source cube - Update auxiliary functions of the config file - Update config file - Add support to others bands values in config file - Add support to bit mask in USGS cube - Support to multiples directories in local cubes - Support for MODIS cloud bands - Dealing with invalid areas in SITS - Support for WTSS Changes in version 0.12 New features in SITS version 0.12.1 - Update README - Change docker image to new sits build - Adjust CMASK bands values in BDC cubes - Support for sits_config_sensor_bands accept more than one sensor - sits cube selection by shapefile - Problem - sits classify New features in SITS version 0.12.0 - Bugs fixed - Documentation updated - Support for multiple tile in local cubes - Improve selection using roi parameter in sits_classify() function Changes in version 0.11 New features in SITS version 0.11.2 - Added keras serialisation to TempCNN and ResNet models New features in SITS version 0.11.1 - Removed LSTM and FCN deep learning models New features in SITS version 0.11.0 - Important improvements in classification performance - Updated version of deep learning methods - Support for STAC access to Brazil Data Cube, AWS and DE Africa - Improved sits validation Changes in version 0.10 New features in SITS version 0.10.0 - Version update 0.10.0 - Continuous Integration (drone.io) - Bayesian smoothing improvement - Introduces Snow multiprocessing architecture - cube plot allow region of interest (roi) - Support for multiple tiles - Update documentation - Bugs fix Changes in version 0.9 New features in SITS version 0.9.8 - Access to Sentinel-2 level-2A images in AWS - Access to the Brazil Data Cube using STAC - Improved raster API - Code revision with lintr and good practices packages - Improvement of assertions and code coverage - Examples and tests generate output in tempdir() New features in SITS version 0.9.7 - Image classification using region of interest (ROI) New features in SITS version 0.9.6 - Access and processing of tiles of the Brazil Data Cube - Plotting of data cube and probability images - Examples of using SITS with SENTINEL-2 and CBERS-4 images New features in SITS version 0.9.5 - Time series tibbles and data cube metadata can now be saved and read in SQLite - Code coverage increased to 95% - Vignettes have been moved to "sits-docs" to reduce building time New features in SITS version 0.9.4 - Filtering can be applied to classified images - Band suffix in filtering is now set to "" - Improvement in code coverage: most of the code has more than 90% coverage New features in SITS version 0.9.3 - Improvements in reading shapefiles: using sampling to retrieve time series inside polygons - Improvement is plotting: uses overloading to the "plot" function New features in SITS version 0.9.2 - Raster classification results can now have versions: a new parameter "version" has been included in the sits_classify function. - Corrections to sits_kohonen and to the documentation. New Features in version 0.9.1 - New deep learning models for time series: 1D convolutional neural networks (sits_FCN), combining 1D CNN and multi-layer perceptron networks (sits_TempCNN), 1D version of ResNet (sits_ResNet), and combination of long-short term memory (LSTM) and 1D CNN (sits_LSTM_FCN). - New version of area accuracy measures that include Olofsson metrics () Changes in version 0.8 New Features - From version 0.8 onwards, the package has been designed to work with data cubes. All references to "coverage" have been replaced by references to "cubes". - The classification of raster images using sits_classify now produces images with the information on the probability of each class for each pixel. This allows more flexibility in the options for labeling the resulting probability raster files. - The function sits_label_classification has been introduced to generate a labelled image from the class probability files, with optional smoothing. The choices are smoothing = none (default), smoothing = bayesian (for bayesian smoothing) and smoothing = majority (for majority smoothing). - To better define a cube, the metadata tibble associated to a cube requires four parameters to define the cube: (a) the web service that provides time series or cubes; (b) the URL of the web service; (c) the name of the satellite; (d) the name of the satellite sensor. If not provided, these parameters are inferred for the sits configuration file. - The functions that do data transformations, such as sits_tasseled_cap and sits_savi now require a sensor parameter ("MODIS" is the default) - Functions sits_bands and sits_labels now work for both tibbles with time series and data cubes. Configuration file - The SITS configuration file has been improved to include information about web service providers, satellites and sensor parameters. Please use sits_show_config() to see the default contents. Users can override these parameters or add their own by creating a config.yml file in their home directory. Examples and Demos - Examples and demos that include classification of raster files now use the inSitu R package, available using devtools::install_github(e-sensing/inSitu). - All examples have been tested and checked for correctness. Functions removed - sits_coverage has been replaced by sits_cube. - sits_raster_classification has been removed. Please use sits_classify. - In sits_classify, the parameter out_prefix has been changed to output_dir, to allow better control of the directory on which to write. - sits_bayes_smooth has been removed. Please use sits_label_classification with smoothing = bayesian. - To define a cube based on local files, service = RASTER has been replaced by service = LOCALHOST. Improvements and fixes - For programmers only: The sits_cube.R file now includes many convenience functions to avoid using cumbersome indexes to files and vector: .sits_raster_params, .sits_cube_all_robjs, .sits_class_band_name, .sits_cube_bands, .sits_cube_service, .sits_cube_file, .sits_cube_files, .sits_cube_labels, .sits_cube_timeline, .sits_cube_robj, .sits_cube_all_robjs, .sits_cube_missing_values, .sits_cube_minimum_values, .sits_cube_maximum_values, .sits_cube_scale_factors, .sits_files_robj. Please look at the documentation provided in the sits_cube.R file. - For programmers only: The metadata that describes the data cube no longer stores the raster objects associated to the files associated with the cube.