CLI Reference
This page provides documentation for our command line tools.
fordead
fordead - Remote sensing time series processing to detect forest anomalies
The usual workflow is : masked_vi --> train_model --> dieback_detection --> forest_mask --> export_results
Usage:
fordead [OPTIONS] COMMAND [ARGS]...
Options:
--version Show the version and exit.
--help Show this message and exit.
fordead calval_dieback_detection
Updates of the csv file containing periods, so for each pixel, the whole time series is covered with the first and last unmasked Sentinel-2 acquisition date of each period, and its associated state. The 'state' column can now hold the following values :
- Training : Period used in training the harmonic model
- Healthy : Period detected as healthy, with no stress, dieback or bare ground detected
- Stress : Period beginning with 3 successive anomalies, ending with the last anomaly before three successive non-anomalies of the beginning of a 'Healthy' period.
- Dieback : Period beginning with 3 successive anomalies, ending with the last available acquisition, or the beggining of a Bare ground period.
- Invalid : The pixel is invalid, there were not enough valid acquisitions to compute a harmonic model
A new column 'anomaly_intensity' is also added, it is a weighted mean of the difference between the calculated vegetation indices and their predicted value for the period. The weight is the number of the date within that period (1+2+3+...+ nb_dates). It is only calculated for 'Healthy', 'Stress' and 'Dieback' periods
if 'update_masked_vi' is True, this function also updates the csv at 'masked_vi_path' with the following columns:
- period_id : id of the period the acquisition is associated with
- state : Status of of the associated period, can be 'Training', 'Healthy', 'Stress', 'Dieback' or 'Invalid'.
- predicted_vi : The prediction of the vegetation index using the harmonic model
- diff_vi : Difference between the vegetation and its prediction, in the expected direction of anomalies for the vegetation index
- anomaly : True if 'diff_vi' exceeds 'threshold_anomaly', else False
See additional information here
Usage:
fordead calval_dieback_detection [OPTIONS]
Options:
--masked_vi_path TEXT Path of the csv containing the vegetation
index for each pixel of each observation, for
each valid Sentinel-2 acquisition.
--pixel_info_path TEXT Path used to write the csv containing pixel
info such as the validity of the model and
its coefficients.
--periods_path TEXT Path of the csv containing pixel periods
--name_column TEXT Name of the ID column [default: id]
--update_masked_vi If True, updates the csv at masked_vi_path
with the columns 'period_id', 'state',
'predicted_vi', 'diff_vi' and 'anomaly'
-s, --threshold_anomaly FLOAT Minimum threshold for anomaly detection
[default: 0.16]
--stress_index_mode TEXT Chosen stress index, if 'mean', the index is
the mean of the difference between the
vegetation index and the predicted vegetation
index for all unmasked dates after the first
anomaly subsequently confirmed. If
'weighted_mean', the index is a weighted
mean, where for each date used, the weight
corresponds to the number of the date (1, 2,
3, etc...) from the first anomaly. If None,
no stress period index is computed.
--vi TEXT Chosen vegetation index [default: CRSWIR]
--path_dict_vi TEXT Path to a text file used to add potential
vegetation indices. If not filled in, only
the indices provided in the package can be
used (CRSWIR, NDVI, NDWI). The file [ex_dict_
vi.txt](https://gitlab.com/fordead/fordead_pa
ckage/-/blob/master/docs/examples/ex_dict_vi.
txt) gives an example for how to format this
file. One must fill the index's name,
formula, and '+' or '-' according to whether
the index increases or decreases when
anomalies occur.
--help Show this message and exit.
fordead calval_masked_vi
Computes the vegetation index for each pixel of each observation, for each valid Sentinel-2 acquisition. Filters out data by applying the fordead mask (if soil_detection is True) or a user mask defined by the user. (optional) Filters out acquisition by applying a limit on the percentage of cloud cover as calculated by the extract_cloudiness function Writes the results in a csv file, as well as the first date of the training period for each pixel and, if soil_detection is True, the first date of detected bare ground.
See additional information here
Usage:
fordead calval_masked_vi [OPTIONS]
Options:
--reflectance_path TEXT Path of the csv file with extracted reflectance.
--masked_vi_path TEXT Path used to write the csv containing the
vegetation index for each pixel of each
observation, for each valid Sentinel-2
acquisition.
--periods_path TEXT Path used to write the csv containing the first
date of the training periods for each pixel and,
if soil_detection is True, the first date of
detected bare ground.
--name_column TEXT Name of the ID column [default: id]
--cloudiness_path TEXT Path of a csv with the columns
'area_name','Date' and 'cloudiness' used to
filter acquisitions, can be calculated by the
[extract_cloudiness function](https://fordead.gi
tlab.io/fordead_package/docs/Tutorials/Validatio
n/03_extract_cloudiness/). Not used if not
given.
--vi TEXT Chosen vegetation index [default: CRSWIR]
-n, --lim_perc_cloud FLOAT Maximum cloudiness at the tile scale, used to
filter used SENTINEL dates. Set parameter as -1
to not filter based on cloudiness [default:
0.4]
--soil_detection If True, bare ground is detected and used as
mask, but the process has not been tested on
other data than THEIA data in France (see https:
//fordead.gitlab.io/fordead_package/docs/user_gu
ides/english/01_compute_masked_vegetationindex/)
. If False, mask from formula_mask is applied.
--formula_mask TEXT formula whose result would be binary, as
described here https://fordead.gitlab.io/fordead
_package/reference/fordead/masking_vi/#compute_v
egetation_index. Is only used if soil_detection
is False. [default: (B2 >= 700)]
--path_dict_vi TEXT Path of text file to add vegetation index
formula, if None, only built-in vegetation
indices can be used (CRSWIR, NDVI)
-b, --list_bands TEXT Bands to import and use ex : -b B2 -b B3 -b B11
[default: B2, B3, B4, B8, B8A, B11, B12]
--apply_source_mask If True, applies the mask from SENTINEL-data
supplier
--sentinel_source TEXT Source of data, can be 'THEIA' et 'Scihub' et
'PEPS' [default: THEIA]
--ignored_period TEXT Period whose Sentinel dates to ignore (format
'MM-DD', ex : --ignored_period 11-01
--ignored_period 05-01
--help Show this message and exit.
fordead calval_train_model
Adjusts an harmonic model to predict the temporal periodicity of the vegetation index, based on the acquisitions of a specified training period.
See additional information here
Usage:
fordead calval_train_model [OPTIONS]
Options:
--masked_vi_path TEXT Path of the csv containing the vegetation
index for each pixel of each observation, for
each valid Sentinel-2 acquisition.
--pixel_info_path TEXT Path used to write the csv containing pixel
info such as the validity of the model and
its coefficients.
--periods_path TEXT Path of the csv containing pixel periods, it
will be updated with the last_date of the
training.
--name_column TEXT Name of the ID column [default: id]
--min_last_date_training TEXT The date in YYYY-MM-DD format after which
SENTINEL dates are no longer used for
training, as long as there are at least
nb_min_date dates valid for the pixel
[default: 2018-01-01]
--max_last_date_training TEXT Date in YYYY-MM-DD format until which
SENTINEL dates can be used for training to
reach the number of nb_min_date valid dates
[default: 2018-06-01]
--nb_min_date INTEGER Minimum number of valid dates to calculate a
model. [default: 10]
--help Show this message and exit.
fordead dieback_detection
Detects anomalies by comparing the vegetation index and its prediction from the model. Detects pixels suffering from dieback when there are 3 successive anomalies. If pixels detected as suffering from dieback have 3 successive dates without anomalies, they are considered healthy again. If stress_index_mode parameter is given, Those periods between detection and return to normal are saved, with the date of first anomaly, date of return to normal, number of dates, and an associated stress index. Anomalies and dieback data are written in the data_directory See details here : https://fordead.gitlab.io/fordead_package/docs/user_guides/english/03_dieback_detection/
Usage:
fordead dieback_detection [OPTIONS]
Options:
-o, --data_directory TEXT Path of the output directory
-s, --threshold_anomaly FLOAT Minimum threshold for anomaly detection
[default: 0.16]
--max_nb_stress_periods INTEGER
Maximum number of stress periods [default:
5]
--stress_index_mode TEXT Chosen stress index, if 'mean', the index is
the mean of the difference between the
vegetation index and the predicted
vegetation index for all unmasked dates
after the first anomaly subsequently
confirmed. If 'weighted_mean', the index is
a weighted mean, where for each date used,
the weight corresponds to the number of the
date (1, 2, 3, etc...) from the first
anomaly. If None, the stress periods are not
detected, and no informations on stress
periods are saved.
--vi TEXT Chosen vegetation index, only useful if
step1 was skipped
--path_dict_vi TEXT Path of text file to add vegetation index
formula, only useful if step1 was skipped
--help Show this message and exit.
fordead export_results
Export results to a vectorized shapefile format.
Usage:
fordead export_results [OPTIONS]
Options:
-o, --data_directory TEXT Path of the output directory
--start_date TEXT Start date for exporting results [default:
2015-06-23]
--end_date TEXT End date for exporting results [default:
2030-01-02]
--frequency TEXT Frequency used to aggregate results, if
value is 'sentinel', then periods correspond
to the period between sentinel dates used in
the detection, or it can be the frequency as
used in pandas.date_range. e.g. 'M'
(monthly), '3M' (three months), '15D'
(fifteen days) [default: M]
--multiple_files If True, one shapefile is exported for each
period containing the areas in dieback at
the end of the period. Else, a single
shapefile is exported containing diebackd
areas associated with the period of dieback
-t, --conf_threshold_list FLOAT
List of thresholds used as bins to
discretize the confidence index into several
classes
-c, --conf_classes_list TEXT List of classes names, if
conf_threshold_list has n values,
conf_classes_list must have n+1 values
--help Show this message and exit.
fordead extract_cloudiness
Usage:
fordead extract_cloudiness [OPTIONS]
Options:
--sentinel_dir TEXT Path of the directory containing Sentinel-2 data.
--export_path TEXT Path to write csv file with extracted cloudiness
-t, --tile_selection TEXT List of tiles from which to extract reflectance
(ex : -t T31UFQ -t T31UGQ). If None, all tiles
are extracted.
--sentinel_source TEXT Source of data, can be 'THEIA' et 'Scihub' et
'PEPS' [default: THEIA]
--help Show this message and exit.
fordead extract_reflectance
Extracts reflectance from Sentinel-2 data using a vector file containing points, exports the data to a csv file. If new acquisitions are added to the Sentinel-2 directory, new data is extracted and added to the existing csv file.
Usage:
fordead extract_reflectance [OPTIONS]
Options:
--obs_path TEXT Path to a vector file containing observation
points, must have an ID column corresponding to
name_column parameter, an 'area_name' column
with the name of the Sentinel-2 tile from which
to extract reflectance, and a 'espg' column
containing the espg integer corresponding to
the CRS of the Sentinel-2 tile.
--sentinel_source TEXT Can be either 'Planetary', in which case data
is downloaded from Microsoft Planetary Computer
stac catalogs, or the path of the directory
containing Sentinel-2 data.
--export_path TEXT Path to write csv file with extracted
reflectance
--cloudiness_path TEXT Path of a csv with the columns
'area_name','Date' and 'cloudiness', can be
calculated by the [extract_cloudiness function]
(https://fordead.gitlab.io/fordead_package/docs
/Tutorials/Validation/03_extract_cloudiness/).
Can be ignored if sentinel_source is
'Planetary'
-n, --lim_perc_cloud FLOAT Maximum cloudiness at the tile scale, used to
filter used SENTINEL dates. Set parameter as -1
to not filter based on cloudiness [default:
0.4]
--name_column TEXT Name of the ID column [default: id]
-b, --bands_to_extract TEXT Bands to extract ex : -b B2 -b B3 -b B11
[default: B2, B3, B4, B5, B6, B7, B8, B8A, B11,
B12, Mask]
-t, --tile_selection TEXT List of tiles from which to extract reflectance
(ex : -t T31UFQ -t T31UGQ). If None, all tiles
are extracted.
--start_date TEXT First date of the period from which to extract
reflectance. [default: 2015-01-01]
--end_date TEXT Last date of the period from which to extract
reflectance. [default: 2030-01-01]
--help Show this message and exit.
fordead forest_mask
Compute forest mask from IGN's BDFORET or CESBIO's OSO map See details here : https://fordead.gitlab.io/fordead_package/docs/user_guides/english/04_compute_forest_mask/
Usage:
fordead forest_mask [OPTIONS]
Options:
-o, --data_directory TEXT Path of the output directory
-f, --forest_mask_source TEXT Source of the forest mask, can be 'vector' to
use a vector file at vector_path, or the path
to a binary raster of 10m resolution with the
value 1 on the pixels of interest, 'BDFORET'
to use the BD Foret of the IGN, 'OSO' to use
the CESBIO's land use map, or None to not use
a forest mask and to extend the area of
interest to all pixels
--dep_path TEXT Path to shapefile containg departements with
code insee. Optionnal, only used if
forest_mask_source equals 'BDFORET'
--bdforet_dirpath TEXT Path to directory containing BD FORET.
Optionnal, only used if forest_mask_source
equals 'BDFORET'
--list_forest_type TEXT List of forest types to be kept in the forest
mask, corresponds to the CODE_TFV of the BD
FORET. Optionnal, only used if
forest_mask_source equals 'BDFORET'
[default: FF2-00-00, FF2-90-90, FF2-91-91,
FF2G61-61]
--path_oso TEXT Path to soil occupation raster, only used if
forest_mask_source = 'OSO'
--list_code_oso INTEGER List of values used to filter the soil
occupation raster. Only used if
forest_mask_source = 'OSO' [default: 17]
--vector_path TEXT path of shapefile whose polygons will be
rasterized as a binary raster with
resolution, extent and crs of the raster at
path_example_raster. Only used if
forest_mask_source = 'vector'
--path_example_raster TEXT Path to raster from which to copy the extent,
resolution, CRS...
--help Show this message and exit.
fordead graph_series
Export graphs of the time series of the vegetation index for each dates, the model and the detection, for a specific pixel, or a region of interest.
By specifying 'shape_path' and 'name_column' parameters, it can be used with a shapefile containing points with a column containing a unique ID used to name the exported image.
By specifying 'x' and 'y' parameters, it can be used with coordinates in the Sentinel-2 data CRS. If neither shape_path or x and y parameters are specified, the user will be prompted to give coordinates in the system of projection of the tile.
Graphs can also be plotted for random pixels inside the forest mask. The user can also choose to specify pixels by their indices from the top left hand corner of the computed area.
If only a small region of interest was computed (for example by using extent_shape_path parameter in the step 01_compute_masked_vegetationindex), then it creates a timelapse on this region of interest.
The graphs are exported in the data_directory/TimeSeries directory as png files.
See details here : https://fordead.gitlab.io/fordead_package/docs/user_guides/english/Results_visualization
Usage:
fordead graph_series [OPTIONS]
Options:
-o, --data_directory TEXT Path of the directory containing results from the
region of interest
-x FLOAT x coordinate in the Sentinel-2 data CRS of the
pixel of interest. Not used if shape_path
parameter is used.
-y FLOAT y coordinate in the Sentinel-2 data CRS of the
pixel of interest. Not used if shape_path
parameter is used.
--shape_path TEXT Path to shapefile containing points whose data
will be plotted. If None, indexes or coordinates
for x and y can be given
--name_column TEXT Name of the column containing the name of the
point, used to name the exported image. Not used
if pixel is selected from indexes or coordinates
--ymin FLOAT ymin limit of graph
--ymax FLOAT ymax limit of graph
--chunks INTEGER Chunk length to import data as dask arrays and
save RAM, advised if computed area in
data_directory is large
--help Show this message and exit.
fordead masked_vi
Computes masks and masked vegetation index for each SENTINEL date under a cloudiness threshold. The mask includes pixels ouside satellite swath, some shadows, and the mask from SENTINEL data provider if the option is chosen. Also, if soil detection is activated, the mask includes bare ground detection and cloud detection, but the process might only be adapted to THEIA data in France's coniferous forests. If it is not activated, then the user can choose a mask of his own using the formula_mask parameter. Results are written in the chosen directory. See details here : https://fordead.gitlab.io/fordead_package/docs/user_guides/english/01_compute_masked_vegetationindex/
Usage:
fordead masked_vi [OPTIONS]
Options:
-i, --input_directory TEXT Path of the directory with Sentinel dates
-o, --data_directory TEXT Path of the output directory
-n, --lim_perc_cloud FLOAT Maximum cloudiness at the tile scale, used to
filter used SENTINEL dates. Set parameter as
-1 to not filter based on cloudiness
[default: 0.4]
--interpolation_order INTEGER interpolation order for bands at 20m
resolution : 0 = nearest neighbour, 1 =
linear, 2 = bilinéaire, 3 = cubique
[default: 0]
--sentinel_source TEXT Source of data, can be 'THEIA' et 'Scihub' et
'PEPS' [default: THEIA]
--apply_source_mask If True, applies the mask from SENTINEL-data
supplier
--soil_detection If True, bare ground is detected and used as
mask, but the process has not been tested on
other data than THEIA data in France (see htt
ps://fordead.gitlab.io/fordead_package/docs/u
ser_guides/english/01_compute_masked_vegetati
onindex/). If False, mask from formula_mask
is applied.
--formula_mask TEXT formula whose result would be binary, as
described here https://fordead.gitlab.io/ford
ead_package/reference/fordead/masking_vi/#com
pute_vegetation_index. Is only used if
soil_detection is False. [default: (B2 >=
700)]
--vi TEXT Chosen vegetation index [default: CRSWIR]
--compress_vi Stores the vegetation index as low-resolution
floating-point data as small integers in a
netCDF file. Uses less disk space but can
lead to very small difference in results as
the vegetation is rounded to three decimal
places
--ignored_period TEXT Period whose Sentinel dates to ignore (format
'MM-DD', ex : --ignored_period 11-01
--ignored_period 05-01
--extent_shape_path TEXT Path of shapefile used as extent of
detection, if None, the whole tile is used
--path_dict_vi TEXT Path of text file to add vegetation index
formula, if None, only built-in vegetation
indices can be used (CRSWIR, NDVI)
--help Show this message and exit.
fordead obs_to_s2_grid
Attributes intersecting Sentinel-2 tiles to observation points or polygons, adding their epsg and name. If polygons are used, they are converted to grid points located at the centroid of Sentinel-2 pixels. If points or polygons intersect several Sentinel-2 tiles, they are duplicated for each of them. If some intersect no Sentinel-2 tiles, they are removed and their IDs are printed.
Usage:
fordead obs_to_s2_grid [OPTIONS]
Options:
--obs_path TEXT Path to a vector file containing observation
points or polygons, must have an ID column
corresponding to name_column parameter
--sentinel_source TEXT Can be either 'Planetary', in which case the
Sentinel-2 grid is infered from Microsoft
Planetary Computer stac catalogs, or the path of
the directory containing Sentinel-2 data.
--export_path TEXT Path used to write resulting vector file, with
added 'epsg','area_name' and 'id_pixel' columns
--name_column TEXT Name of the ID column [default: id]
-t, --tile_selection TEXT A list of names of Sentinel-2 directories. (ex :
-t T31UFQ -t T31UGQ). If None, all tiles are
used.
--overwrite Overwrites file at obs_path
--help Show this message and exit.
fordead preprocess_obs
Used as a preprocessing function for a vector file containing observation points or polygons. Can add an ID column if one does not already exist, and can also apply a buffer to erode or dilate observations.
Usage:
fordead preprocess_obs [OPTIONS]
Options:
--obs_path TEXT Path of vector file containing observation points or
polygons to preprocess
--export_path TEXT Path used to export the resulting preprocessed
observation points or polygons
--buffer INTEGER Length in meters of the buffer used to dilate (positive
integer) or erode (negative integer) the observations.
If None, no buffer is applied. Some observations may
disappear completely if a negative buffer is applied
--name_column TEXT Name of the column used to identify observations. If the
column doesn't already exists, it is added as an integer
between 1 and the number of observations [default: id]
--help Show this message and exit.
fordead process_tiles
Apply full fordead processing to several tiles: compute_masked_vegetationindex > train_model > dieback_detection > compute_forest_mask > export_results
Usage:
fordead process_tiles [OPTIONS]
Options:
-i, --sentinel_directory PATH Path of the directory with a directory
containing Sentinel data for each tile
[required]
-o, --output_directory PATH Output directory [required]
-t, --tiles TEXT List of tiles to process : -t T31UGP -t
T31UGQ -t study_area [required]
Step 1: compute_masked_vegetationindex arguments:
-c, --lim_perc_cloud FLOAT Maximum cloudiness at the tile or zone
scale, used to filter used SENTINEL dates
--vi TEXT Chosen vegetation index
--sentinel_source [THEIA|Scihub|PEPS]
Source of Sentinel data: 'THEIA', 'Scihub'
or 'PEPS'
--apply_source_mask If activated, applies the mask from
SENTINEL-data provider
--extent_shape_path PATH Path of shapefile used as extent of
detection
--soil_detection If activated, detects bare ground
--ignored_period TEXT Period whose date to ignore (format 'MM-DD',
ex : --ignored_period 11-01 05-01
--compress_vi If activated, stores the vegetation index as
low-resolution floating-point data as small
integers in a netCDF file. Uses less disk
space but can lead to very small difference
in results as the vegetation is rounded to
three decimal places
Step 2: train_model arguments:
--min_last_date_training TEXT
First date that can be used for detection
--max_last_date_training TEXT
Last date that can be used for training
--nb_min_date INTEGER Minimum number of valid dates reqquired for
modelling the vegetation index
--correct_vi If True, corrects vi using large scale
median vi
Step 3: dieback_detection arguments:
-s, --threshold_anomaly FLOAT
Minimum threshold for anomaly detection
--max_nb_stress_periods INTEGER
Maximum number of stress periods. If this
number is reached, the pixel is masked in
the too_many_stress_periods, thus removed
from future exports. Only used if
stress_index_mode is not None.
--stress_index_mode [mean|weighted_mean]
Chosen stress index, if 'mean', the index is
the mean of the difference between the
vegetation index and the predicted
vegetation index for all unmasked dates
after the first anomaly subsequently
confirmed. If 'weighted_mean', the index is
a weighted mean, where for each date used,
the weight corresponds to the number of the
date (1, 2, 3, etc...) from the first
anomaly. If None, the stress periods are not
detected, and no information is saved
Step 4: compute_forest_mask arguments:
-f, --forest_mask_source TEXT
Source of the forest mask, accepts
'BDFORET', 'OSO', the path to a vector file
or a binary raster with the extent and
resolution of the computed area, or None in
which case all pixels will be considered
valid
--dep_path PATH Path to shapefile containg departements with
code insee. Optionnal, only used if
forest_mask_source equals 'BDFORET'
--bdforet_dirpath PATH Path to directory containing BD FORET.
Optionnal, only used if forest_mask_source
equals 'BDFORET'
--list_forest_type TEXT List of forest types to be kept in the
forest mask, corresponds to the CODE_TFV of
the BD FORET. Optionnal, only used if
forest_mask_source equals 'BDFORET'
--path_oso PATH Path to soil occupation raster, only used if
forest_mask_source = 'OSO'
--list_code_oso TEXT List of values used to filter the soil
occupation raster. Only used if
forest_mask_source = 'OSO'
Step 5: results_export arguments:
--start_date_results TEXT Start date for results export
--end_date_results TEXT End date for results export
--results_frequency TEXT Frequency used to aggregate results, if
value is 'sentinel', then periods correspond
to the period between sentinel dates used in
the detection, or it can be the frequency as
used in pandas.date_range. e.g. 'M'
(monthly), '3M' (three months), '15D'
(fifteen days)
--multiple_files If activated, one shapefile is exported for
each period containing the areas suffering
from dieback at the end of the period. Else,
a single shapefile is exported containing
diebackd areas associated with the period of
dieback
--path_dict_vi PATH Path of text file to add vegetation index
formula, if None, only built-in vegetation
indices can be used
--threshold_list FLOAT List of thresholds used to classify the
levels of dieback by discretising the
confidence index
--classes_list TEXT List of class names for discretising the
confidence index. If threshold_list has
length n, classes_list must have length n+1.
--help Show this message and exit.
fordead read_tileinfo
Prints parameters, all dates used and last anomaly date computed to the console
Usage:
fordead read_tileinfo [OPTIONS]
Options:
-o, --data_directory TEXT Path of the output directory containing the saved
TileInfo object
--help Show this message and exit.
fordead sensitivity_analysis
Allows the testing of many parameter combinations, running three detection steps mask_vi_from_dataframe, train_model_from_dataframe and dieback_detection_from_dataframe using default parameters as well as user defined parameter combinations. A 'test_info.csv' is written in 'testing_directory', where each test_id is associated with the value of all parameters used in the iteration. Each test results can be found in a newly created directory whose name is the test_id.
See additional information here
Usage:
fordead sensitivity_analysis [OPTIONS]
Options:
--testing_directory TEXT Directory where the results will be exported
--reflectance_path TEXT Path of the csv file with extracted reflectance.
--cloudiness_path TEXT Path of a csv with the columns 'area_name','Date'
and 'cloudiness', can be calculated by the
[extract_cloudiness function](https://fordead.gitl
ab.io/fordead_package/docs/Tutorials/Validation/03
_extract_cloudiness/). Not used if not given.
--args_to_test TEXT Path to a text file where each line begins
parameter name, then each value is separated with
a space. All combinations will be tested. See an
example [here](https://gitlab.com/fordead/fordead_
package/-/blob/master/docs/examples/ex_dict_args.t
xt)
--update_masked_vi If True, updates the csv at masked_vi_path with
the columns 'period_id', 'state', 'predicted_vi',
'diff_vi' and 'anomaly'
--name_column TEXT Name of the ID column [default: id]
--help Show this message and exit.
fordead theia_preprocess
Automatically downloads all Sentinel-2 data from THEIA between two dates under a cloudiness threshold. Then this data is unzipped, keeping only chosen bands from Flat REflectance data, and zip files can be emptied as a way to save storage space. Finally, if two Sentinel-2 directories come from the same acquisition date, they are merged by replacing no data pixels from one directory with pixels with data in the other, before removing the latter directory.
Usage:
fordead theia_preprocess [OPTIONS]
Options:
-i, --zipped_directory TEXT Path of the directory with zipped theia data
-o, --unzipped_directory TEXT Path of the output directory
-t, --tiles TEXT Name of the tiles to be downloaded (format :
T31UFQ)
-u, --login_theia TEXT Login of your theia account
-p, --password_theia TEXT Password of your theia account
-l, --level [LEVEL1C|LEVEL2A|LEVEL3A]
Product level for reflectance products
[default: LEVEL2A]
-s, --start_date TEXT start date, fmt('2015-12-22') [default:
2015-06-23]
-e, --end_date TEXT end date, fmt('2015-12-22'). If None, the
current date is used.
-n, --lim_perc_cloud INTEGER Maximum cloudiness in SENTINEL dates
downloaded (%) [default: 50]
-b, --bands TEXT List of bands to extracted (B2, B3, B4, B5,
B6, B7, B8, B8A, B11, B12, as well as CLMR2,
CLMR2, EDGR1, EDGR2, SATR1, SATR2 for
LEVEL2A data, and DTS1, DTS2, FLG1, FLG2,
WGT1, WGT2 for LEVEL3A) [default: B2, B3,
B4, B5, B6, B7, B8, B8A, B11, B12, CLMR2]
-c, --correction_type [SRE|FRE|FRC]
Chosen correction type (SRE or FRE for
LEVEL2A data, FRC for LEVEL3A) [default:
FRE]
--empty_zip If True, the zip files are emptied as a way
to save space.
--retry INTEGER Number of retries when downloading data
[default: 3]
--wait INTEGER Wait time between retries in seconds
[default: 300]
--search_timeout INTEGER Search time out in seconds [default: 10]
--help Show this message and exit.
fordead timelapse
Create timelapse allowing navigation through Sentinel-2 dates with detection results superimposed. By specifying 'shape_path' and 'name_column' parameters, it can be used with a shapefile containing one or multiple polygons or points with a column containing a unique ID used to name the export. By specifying 'x' and 'y' parameters, it can be used by specifying coordinates in the system of projection of the tile. The timelapse is exported in the data_directory/Timelapses directory as an html file.
See details https://fordead.gitlab.io/fordead_package/docs/user_guides/english/Results_visualization
Usage:
fordead timelapse [OPTIONS]
Options:
-o, --data_directory TEXT Path of the directory containing results from
the region of interest
--shape_path TEXT Path of the shapefile of the area, or points,
to convert to timelapse. Not used if timelapse
made from x and y coordinates
--name_column TEXT Name of the column containing the name of the
export. Not used if timelapse made from x and
y coordinates [default: id]
-x, --x INTEGER Coordinate x in the crs of the Sentinel-2
tile. Not used if timelapse is made using a
shapefile
-y, --y INTEGER Coordinate y in the crs of the Sentinel-2
tile. Not used if timelapse is made using a
shapefile
--buffer INTEGER Buffer around polygons or points for the
extent of the timelapse [default: 100]
--vector_display_path TEXT Path of the shapefile with ground observations
-d, --hover_column_list TEXT List of columns to display when hovering mouse
over vectors of vector_display_path
--max_date TEXT Last date used in the timelapse
--show_confidence_class If True, detected dieback is shown with the
confidence class at the last date used, as
vectorized in the step [05_export_results](htt
ps://fordead.gitlab.io/fordead_package/docs/us
er_guides/english/05_export_results/)
--zip_results If True, puts timelapses in a zip file
--help Show this message and exit.
fordead train_model
Uses first SENTINEL dates to train a periodic vegetation index model capable of predicting the vegetation index at any date. If there aren't nb_min_date at min_last_date_training, later dates between min_last_date_training and max_last_date_training can be used. See details here : https://fordead.gitlab.io/fordead_package/docs/user_guides/english/02_train_model/
Usage:
fordead train_model [OPTIONS]
Options:
-o, --data_directory TEXT Path of the output directory
--nb_min_date INTEGER Minimum number of valid dates to compute a
vegetation index model for the pixel
[default: 10]
--min_last_date_training TEXT First date that can be used for detection
[default: 2018-01-01]
--max_last_date_training TEXT Last date that can be used for training
[default: 2018-06-01]
--correct_vi If True, corrects vi using large scale median
vi
--path_vi TEXT Path of directory containing vegetation
indices for each date. If None, the
information has to be saved from a previous
step
--path_masks TEXT Path of directory containing masks for each
date. If None, the information has to be
saved from a previous step
--help Show this message and exit.