All configuration parameters ############################ .. list-table:: :widths: auto :header-rows: 1 * - Name - Default Value - Description - Type - Name * - a_crop_label_replacement - ['10', 'annual_crop'] - Replace a label by a string, ie ['10', 'annual_crop'] - list - a_crop_label_replacement * - account - None - Feed the sbatch parameter 'account' - str - account * - acor_feat - False - Apply atmospherically corrected features - bool - acor_feat * - additional_features - - OTB's bandmath expressions, separated by comma - str - additional_features * - allowed_retry - 0 - allow dask to retry a failed job N times - int - allowed_retry * - angle - True - if True, smoothing corners of pixels (45°) - bool - angle * - annual_classes_extraction_source - None - - str - annual_classes_extraction_source * - annual_crop - ['11', '12'] - The list of classes to be replaced by previous data - list - annual_crop * - arbo - /* - input folder hierarchy - str - arbo * - auto_date - True - Enable the use of `start_date` and `end_date` - bool - auto_date * - autocontext_iterations - 3 - Number of iterations in auto-context - int - autocontext_iterations * - band_ref - 1 - Date `YYYYMMDD` of the reference image - int - band_ref * - band_src - 3 - Number of the band of the VHR image to use for coregistration - int - band_src * - bingdal - None - path to GDAL binaries - str - bingdal * - blocksize - 2000 - block size to split raster to prevent Numpy memory error - str - blocksize * - boundary_comparison_mode - False - Enable classification comparison - bool - boundary_comparison_mode * - boundary_exterior_buffer_size - 0 - Buffer size outside the region - int - boundary_exterior_buffer_size * - boundary_fusion_epsilon - 0.0 - Threshold to avoid weights equals to zero - float - boundary_fusion_epsilon * - boundary_interior_buffer_size - 0 - Buffer size inside the region - int - boundary_interior_buffer_size * - buffer_size - None - define the working size batch in number of pixels - int - buffer_size * - builders_class_name - ['i2_classification'] - The name of the class defining the builder - list - builders_class_name * - builders_paths - /path/to/iota2/sources - The path to user builders - str - builders_paths * - check_inputs - True - Enable the inputs verification - bool - check_inputs * - chunk - 10 - number of chunks for statistics computing - int - chunk * - chunk_size_mode - split_number - The chunk split mode, currently the choice is 'split_number' - str - chunk_size_mode * - chunk_size_x - 50 - number of cols for one chunk - int - chunk_size_x * - chunk_size_y - 50 - number of rows for one chunk - int - chunk_size_y * - classif_mode - separate - 'separate' or 'fusion' - str - classif_mode * - classification - None - Input raster of classification - str - classification * - classifier - None - otb classification algorithm - str - classifier * - clipfield - None - field to identify distinct areas - str - clipfield * - clipfile - None - vector-based file to clip output vector-based classification - str - clipfile * - clipvalue - None - value of field which identify distinct areas - int - clipvalue * - cloud_threshold - 0 - Threshold to consider that a pixel is valid - int - cloud_threshold * - color_table - None - Absolute path to the file that links the classes and their colours - str - color_table * - compression_algorithm - ZSTD - Set the gdal compression algorithm to use: NONE, LZW, ZSTD (default).All rasters write with OTB will be compress with the chosen algorithm. - str - compression_algorithm * - compression_predictor - 2 - Set the predictor for LZW and ZSTD compression: 1 (no predictor), 2 (horizontal differencing, default) - int - compression_predictor * - concat_mode - True - enable the use of all features - bool - concat_mode * - confidence - None - Input raster of confidence - str - confidence * - copy_input - True - use spectral bands as features - bool - copy_input * - crop_mix - False - Enable crop mix workflow - bool - crop_mix * - cross_validation_folds - 5 - the number of k-folds - int - cross_validation_folds * - cross_validation_grouped - False - - bool - cross_validation_grouped * - cross_validation_parameters - {} - - dict - cross_validation_parameters * - data_field - None - Field name indicating classes labels in `ground_thruth` - str - data_field * - data_mode_access - gapfilled - choose which data can be accessed in custom features - str - data_mode_access * - date_src - None - Date `YYYYMMDD` of the reference image - str - date_src * - date_vhr - None - Date `YYYYMMDD` of the VHR image - str - date_vhr * - deep_learning_parameters - {} - deep learning parameter description is available :doc:`here ` - dict - deep_learning_parameters * - dempster_shafer_sar_opt_fusion - False - Enable the use of both SAR and optical data to train a model. - bool - dempster_shafer_sar_opt_fusion * - dempstershafer_mob - precision - Choose the dempster shafer mass of belief estimation method - str - dempstershafer_mob * - dim_red - False - Enable the dimensionality reduction mode - bool - dim_red * - douglas - 10 - Douglas-Peucker tolerance for vector-based generalization - int - douglas * - dozip - True - Zip output vector-based classification (OSO-like production) - bool - dozip * - enable_autocontext - False - Enable the auto-context processing - bool - enable_autocontext * - enable_boundary_fusion - False - Enable the boundary fusion - bool - enable_boundary_fusion * - enable_probability_map - False - Produce the probability map - bool - enable_probability_map * - enable_sensor_gapfilling - False - Enable or disable gapfilling for landsat 8 and 9 IR data - bool - enable_sensor_gapfilling * - end_date - - The last date of interpolated image time series : YYYYMMDD format - str - end_date * - exogeneous_data - None - Path to a Geotiff file containing additional data to be used in external features - str - exogeneous_data * - external_features_flag - False - enable the external features mode - bool - external_features_flag * - extract_bands - False - - bool - extract_bands * - features - ['NDVI', 'NDWI', 'Brightness'] - List of additional features computed - list - features * - features_from_raw_dates - False - learn model from raw sensor's date (no interpolations) - bool - features_from_raw_dates * - features_path - None - input directory containing features as rasters - str - features_path * - fill_missing_dates - False - fill raw data with no data if dates are missing - bool - fill_missing_dates * - first_step - None - The step group name indicating where the chain start - str - first_step * - force_standard_labels - False - Standardize labels for feature extraction - bool - force_standard_labels * - from_rasterdb_resampling_method - nn - output features type choice among `gdalwarp.html#cmdoption-gdalwarp-r `_. Enabled if chain.rasters_grid_path is set - str - from_rasterdb_resampling_method * - from_vectordb_resampling_method - near - output features type choice among `gdalwarp.html#cmdoption-gdalwarp-r `_. Enabled if chain.grid is set - str - from_vectordb_resampling_method * - full_learn_segment - False - enable the use of entire segment for learning - bool - full_learn_segment * - functions - None - function list to be used to compute features - str/list - functions * - fusion_options - -nodatalabel 0 -method majorityvoting - OTB FusionOfClassification options for voting method involved if classif_mode is set to 'fusion' - str - fusion_options * - fusionof_all_samples_validation - False - Enable the use of all reference data to evaluate the fusion raster - bool - fusionof_all_samples_validation * - fusionofclassification_all_samples_validation - False - Enable the use of all reference data to validate the classification merge - bool - fusionofclassification_all_samples_validation * - generate_final_probability_map - False - Enable the mosaicing of probabilities maps. - bool - generate_final_probability_map * - grasslib - None - path to grasslib - str - grasslib * - grid - None - input grid to fit - str - grid * - gridsize - None - number of lines and columns of the serialization process - int - gridsize * - ground_truth - None - Absolute path to reference data - str - ground_truth * - hermite - 10 - Hermite Interpolation threshold for vector-based smoothing - int - hermite * - higher_stats - False - If True, compute more complexe statistics (Shanon, majority order and difference, etc.) - bool - higher_stats * - inland - None - inland water limit shapefile - str - inland * - iterate - True - Minimal number of SIFT points to find to create the new RPC model - bool - iterate * - keep_bands - ['B1', 'B2', 'B3', 'B4', 'B5', 'B6', 'B7'] - The list of spectral bands used for classification - list - keep_bands * - keep_duplicates - True - use 'rel_refl' can generate duplicated feature (ie: NDVI), set to False remove these duplicated features - bool - keep_duplicates * - keep_runs_results - True - - bool - keep_runs_results * - keyword_arguments - {} - keyword arguments to be passed to model - dict - keyword_arguments * - l5_path_old - None - Absolute path to Landsat-5 images coming from old THEIA format (D*H*) - str - l5_path_old * - l8_path - None - Absolute path to Landsat-8 images comingfrom new tiled THEIA data - str - l8_path * - l8_path_old - None - Absolute path to Landsat-8 images coming from old THEIA format (D*H*) - str - l8_path_old * - l8_usgs_infrared_path - None - Absolute path to :doc:`Landsat-8 images coming from USGS data ` - str - l8_usgs_infrared_path * - l8_usgs_optical_path - None - Absolute path to :doc:`Landsat-8 images coming from USGS data ` - str - l8_usgs_optical_path * - l8_usgs_path - None - Absolute path to :doc:`Landsat-8 images coming from USGS data ` - str - l8_usgs_path * - l8_usgs_thermal_path - None - Absolute path to :doc:`Landsat-8 images coming from USGS data ` - str - l8_usgs_thermal_path * - last_step - None - The step group name indicating where the chain ends - str - last_step * - lcfield - Class - Name of the field to store landcover class in vector-based classification - str - lcfield * - lib64bit - None - Path of BandMath and Concatenate OTB executables returning 64-bits float pixel values - str - lib64bit * - list_tile - None - List of tile to process, separated by space - str - list_tile * - logger_level - INFO - Set the logger level: NOTSET, DEBUG, INFO, WARNING, ERROR, CRITICAL - str - logger_level * - max_nn_inference_size - None - maximum batch inference size - int - max_nn_inference_size * - maximum_cpu - 4 - the maximum number of CPU available - int - maximum_cpu * - maximum_ram - 16.0 - the maximum amount of RAM available. (gB) - float - maximum_ram * - merge_final_classifications - False - Enable the fusion of classifications mode, merging all run in a unique result. - bool - merge_final_classifications * - merge_final_classifications_method - majorityvoting - Indicate the fusion of classification method: 'majorityvoting' or 'dempstershafer' - str - merge_final_classifications_method * - merge_final_classifications_ratio - 0.1 - Percentage of samples to use in order to evaluate the fusion raster - float - merge_final_classifications_ratio * - merge_final_classifications_undecidedlabel - 255 - Indicate the label for undecision case during fusion - int - merge_final_classifications_undecidedlabel * - merge_run - False - Enable the fusion of regression mode, merging all run in a unique result. - bool - merge_run * - merge_run_method - mean - Indicate the fusion of regression method: 'mean' or 'median' - str - merge_run_method * - merge_run_ratio - 0.1 - Percentage of samples to use in order to evaluate the fusion raster - float - merge_run_ratio * - minimum_required_dates - 2 - required minimum number of available dates for each sensor - int - minimum_required_dates * - minsiftpoints - 40 - Minimal number of SIFT points to find to create the new RPC model - int - minsiftpoints * - minstep - 16 - Minimal size of steps between bins in pixels - int - minstep * - mmu - 1000 - MMU of output vector-based classification (projection unit),(Default : 0.1 ha) - int - mmu * - mode - 2 - Coregistration mode of the time series - int - mode * - mode_outside_regionsplit - 0.1 - Set the threshold for split huge model - float - mode_outside_regionsplit * - model_type - None - machine learning algorthm’s name - str - model_type * - module - /path/to/iota2/sources - absolute path for user source code - str - module * - no_data_value - -10000 - value considered as no_data in features map mosaic ('i2_features_map' builder name) - int - no_data_value * - no_label_management - maxConfidence - Method for choosing a label in case of fusion - str - no_label_management * - nomenclature - None - configuration file which describe nomenclature - configuration file which describe nomenclature - nomenclature * - nomenclature_path - None - Absolute path to the nomenclature description file - str - nomenclature_path * - number_of_chunks - 50 - the expected number of chunks - int - number_of_chunks * - obia_segmentation_path - None - filename for input segmentation - str - obia_segmentation_path * - otb_classifier_options - None - OTB option for classifier.If None, the OTB default values are used - dict - otb_classifier_options * - out_worldclim_dtype - float32 - output worlclim data type, ie : 'uint16', 'float32'. - np.dtype - out_worldclim_dtype * - out_worldclim_rescale_range - None - rescale worldclim data between 0 and max(np.dtype) at run time for RAM usage purpose. - np.dtype - out_worldclim_rescale_range * - outprefix - dept - Prefix to use for naming of vector-based classifications - str - outprefix * - output_features_pix_type - float - output features type choice among uint8/uint16/int16/uint32/int32/float/double. - str - output_features_pix_type * - output_name - None - temporary chunks are written using this name as prefix - str - output_name * - output_path - None - Absolute path to the output directory - str - output_path * - output_prev_features - None - Path to previous features for crop mix - str - output_prev_features * - output_statistics - True - output_statistics - bool - output_statistics * - padding_size_x - 0 - The padding for chunk - int - padding_size_x * - padding_size_y - 0 - The padding for chunk - int - padding_size_y * - pattern - None - Pattern of the time series files to coregister - str - pattern * - patterns - ALT,ASP,SLP - key name for detect the input images - str - patterns * - prec - 3 - Estimated shift between source and reference raster in pixel (source raster resolution) - int - prec * - prev_features - None - Path to a configuration file used to produce previous features - str - prev_features * - prod - None - OSO-like output vector (aliases) is produced. Other possible value : carhab - str - prod * - proj - None - The projection wanted. Format EPSG:XXXX is mandatory - str - proj * - random_seed - None - Fix the random seed for random split of reference data - int - random_seed * - rasters_grid_path - None - input grid to fit - str - rasters_grid_path * - ratio - 0.5 - Should be between 0.0 and 1.0 and represent the proportion of the dataset to include in the train split. - float - ratio * - reduction_mode - global - The reduction mode - str - reduction_mode * - region_field - region - The column name for region indicator in`region_path` file - str - region_field * - region_path - None - Absolute path to a region vector file - str - region_path * - region_priority - None - define an order for region intersection - list - region_priority * - rel_refl - False - compute relative reflectances by the red band - bool - rel_refl * - remove_output_path - True - Before the launch of iota2, remove the content of `output_path` - bool - remove_output_path * - resample - True - Resample the reference and the source rasterto the same resolution to find SIFT points - bool - resample * - resampling_bco_radius - 2 - otb radius for bicubic interpolation. - int - resampling_bco_radius * - rssize - 20 - Resampling size of input classification raster (projection unit) - int - rssize * - runs - 1 - Number of independant runs processed - int - runs * - s1_dir - None - Sentinel1 data directory - str - s1_dir * - s1_path - None - Absolute path to Sentinel-1 configuration file - str - s1_path * - s2_l3a_output_path - None - Absolute path to store preprocessed data in a dedicated directory - str - s2_l3a_output_path * - s2_l3a_path - None - Absolute path to Sentinel-2 L3A images (THEIA format) - str - s2_l3a_path * - s2_output_path - None - Absolute path to store preprocessed data in a dedicated directory - str - s2_output_path * - s2_path - None - Absolute path to Sentinel-2 images (THEIA format) - str - s2_path * - s2_s2c_output_path - None - Absolute path to store preprocessed data in a dedicated directory - str - s2_s2c_output_path * - s2_s2c_path - None - Absolute path to Sentinel-2 images (Sen2Cor format) - str - s2_s2c_path * - sample_augmentation - {'activate': False, 'bins': 10} - OTB parameters for sample augmentation - dict - sample_augmentation * - sample_management - None - Absolute path to a CSV file containing samples transfert strategies - str - sample_management * - sample_selection - {'sampler': 'random', 'strategy': 'all'} - OTB parameters for sampling the validation set - dict - sample_selection * - sample_validation - {'sampler': 'random', 'strategy': 'all'} - OTB parameters for sampling the validation set - dict - sample_validation * - samples_classif_mix - False - Enable the second step of crop mix - bool - samples_classif_mix * - sampling_validation - False - Enable sampling validation - bool - sampling_validation * - seed - 1 - seed of input raster classification - int - seed * - spatial_resolution - [] - Output spatial resolution - list or scalar - spatial_resolution * - split_ground_truth - True - Enable the split of reference data - bool - split_ground_truth * - srtm_path - None - Path to a directory containing srtm data - str - srtm_path * - standardization - True - - bool - standardization * - start_date - - The first date of interpolated image time series : YYYYMMDD format - str - start_date * - stats_used - ['mean'] - list of stats used for train and classification - list - stats_used * - statslist - {1: 'rate', 2: 'statsmaj', 3: 'statsmaj'} - dictionnary of requested landcover statistics - dict - statslist * - step - 256 - Initial size of steps between bins in pixels - int - step * - systemcall - False - If True, use yours gdal lib (cf. bingdal) - bool - systemcall * - target_dimension - 4 - The number of dimension required, according to `reduction_mode` - int - target_dimension * - temporal_resolution - 10 - The temporal gap between two interpolations - int - temporal_resolution * - tile_field - None - column name in 'grid' containing tile's name. - str - tile_field * - umc1 - None - MMU for the first regularization - int - umc1 * - umc2 - None - MMU for the second regularization - int - umc2 * - use_additional_features - False - enable the use of additional features - bool - use_additional_features * - use_gapfilling - True - enable the use of gapfilling (clouds/temporal interpolation) - bool - use_gapfilling * - user_feat_path - None - Absolute path to the user's features path - str - user_feat_path * - validity - None - Input raster of validity - str - validity * - validity_threshold - 1 - threshold above which a training pixel is considered valid - int - validity_threshold * - vectorize_fusion_of_classifications - False - flag to inform iota2 to vectorize the fusion of classifications - bool - vectorize_fusion_of_classifications * - vhr_path - None - Absolute path to the VHR file - str - vhr_path * - worldclim_path - None - Path to a directory containing world clim data - str - worldclim_path * - write_outputs - False - write temporary files - bool - write_outputs * - write_reproject_resampled_input_dates_stack - True - flag to write of resampled stack image for each date - bool - write_reproject_resampled_input_dates_stack * - zonal_vector - None - vector file to compute zonal statistics of classification - str - zonal_vector