# Process Profiles

The following image provides an overview of the openEO Processes profiles. The minimal profile that allows an openEO implementation to be called "openEO-compliant" is L1 Minimal.

The hierarchy of openEO Processes profiles: L1 Minimal -> L2 Recommended (with sub-profiles) -> L2A/B Raster/Vector -> L3 Advanced (with sub-profiles) -> L4 Above and Beyond — An overview of the openEO Processes profiles.

L1 Minimal ensures that the openEO implementation has a minimal set of functionality which allow users to execute basic use-cases.
L2 Recommended add functionality that we recommend to be available so that users can more effectively make use of the openEO implementation.
L3 Advanced allows users to execute more advanced use cases.
L4 Above and Beyond adds very specific and complex requirements for very specific and highly advanced use cases.

There are various sub-profiles in L2 (e.g., L2-Date) and L3 (e.g., L3-ML) that add a specific set of functionalities centered around specific needs such as date/time manipulation or execution of machine learning workflows.

In the following chapter you can find a list of requirements per profile.

# Requirements per Profile

Note

Missing experimental processes should (by default) lead to a "warning", but not lead to a rejection of that level in openEO.

# L1: Minimal

absolute
add
and
apply
apply_dimension
- All dimensions that your datacubes can include are supported - x and y can usually be excluded
arccos
arcsin
arctan
array_concat
array_create
array_element
between
ceil
clip
constant
cos
divide
e
eq
exp
first
floor
gt
gte
int
last
ln
load_collection
- Parameter temporal_extent: All temporal formats are supported (date-time and date)
log
lt
lte
max
mean
median
min
mod
multiply
neq
not
or
pi
power
product
quantiles
reduce_dimension
- Parameter reducer: At least all processes (up to L1) in the category reducer that accept an array as input and return a single value as output can be used (also in a chain of processes).
- Parameter dimension: All dimensions that your datacubes can include are supported - x and y are excluded as they are handled with reduce_spatial
round
save_result
sd
sgn
sin
sqrt
subtract
sum
tan
variance

# L2: Recommended

add_dimension
- Parameter name: All suitable dimensions are supported
aggregate_temporal
- Parameter reducer: At least all processes (up to the level of this requirement) in the category reducer that accept an array as input and return a single value as output can be used (also in a chain of processes).
- Parameter reducer: Supports access to labels in the callback
- Parameter dimension: All suitable dimensions are supported
aggregate_temporal_period
- Parameter reducer: At least all processes (up to the level of this requirement) in the category reducer that accept an array as input and return a single value as output can be used (also in a chain of processes).
- Parameter reducer: Supports access to labels in the callback
- Parameter dimension: All suitable dimensions are supported
- Parameter period: enum reflects implemention (all values are supported)
all
any
apply_dimension
- Parameter process: Supports access to labels in the callback
arcosh
arctan2
array_element
- Supports labeled arrays
array_find
arsinh
artanh
cosh
count
dimension_labels
- Parameter dimension: All suitable dimensions are supported
drop_dimension
- Parameter name: All suitable dimensions are supported
extrema
filter_bbox
filter_temporal
- Parameter dimension: All suitable dimensions are supported
- All temporal formats are supported (date-time and date)
if
inspect (experimental)
- Parameter level: enum reflects implemention (all values are supported)
is_nan
is_nodata
is_valid
linear_scale_range
nan (experimental)
normalized_difference
reduce_dimension
- Parameter reducer: At least all processes (up to L2) in the category reducer that accept an array as input and return a single value as output can be used (also in a chain of processes).
- Parameter reducer: Supports access to labels in the callback
rename_dimension
rename_labels
- Parameter dimension: All dimensions that your datacubes can include are supported - x and y can usually be excluded
sinh
sort
tanh
xor

# L2A: Recommended Raster

aggregate_spatial
- Parameter reducer: At least all processes (up to the level of this requirement) in the category reducer that accept an array as input and return a single value as output can be used (also in a chain of processes).
apply_kernel
- Parameter border: enum reflects implemention (all values are supported)
filter_bands
- Supports filtering by band name
filter_spatial
load_collection
- Parameter bands: Supports filtering by band name and common name
mask
mask_polygon
resample_spatial
- Parameter method: enum reflects implemention (all values are supported)

# L2B: Recommended Vector

filter_vector (experimental)
vector_buffer (experimental)
vector_reproject (experimental)

# L2-Date: Date & Time manipulation

date_between (experimental)
date_difference (experimental)
date_shift (experimental)

# L2-Text: Text manipulation

text_begins
text_concat (text_merge)
text_contains
text_ends

# L3: Advanced

add_dimension
- Parameter type: enum reflects implemention (all values are supported)
aggregate_spatial
- Parameter reducer: Supports access to labels in the callback
- Parameter context: is supported and passed to the callback
aggregate_spatial_window (experimental)
aggregate_temporal
- Parameter context: is supported and passed to the callback
- All temporal formats are supported (date-time, date and time)
aggregate_temporal_period
- Parameter context: is supported and passed to the callback
apply
- Parameter process: At least all processes (up to the level of this requirement) in the categories comparison, logic and math can be used (also in a chain of processes).
- Parameter context: is supported and passed to the callback
apply_dimension
- Parameter process: At least all processes (up to the level of this requirement) in the categories array, comparison, logic and math can be used (also in a chain of processes).
- Parameter context: is supported and passed to the callback
apply_neighborhood
- Parameter process: Supports access to labels in the callback
- Parameter context: is supported and passed to the callback
- Parameter data: All listed label types supported.
- Parameter size / overlap: Units m, px and null are supported
array_append
- Supports labeled arrays
array_apply
- Parameter process: Supports access to labels in the callback
- Parameter context: is supported and passed to the callback
- Supports labeled arrays
array_concat
- Supports labeled arrays
array_contains
array_create_labeled (experimental)
array_filter
- Parameter context: is supported and passed to the callback
- Supports labeled arrays
array_find_label (experimental)
array_interpolate_linear
- Supports labeled arrays
array_labels
array_modify (experimental)
- Supports labeled arrays
cloud_detection (experimental)
count
- Parameter context: is supported and passed to the callback
create_data_cube (create_raster_cube)
cummax (experimental)
cummin (experimental)
cumproduct (experimental)
cumsum (experimental)
filter_bands
- Supports filtering by common name
filter_labels (experimental)
- Parameter context: is supported and passed to the callback
- Parameter dimension: All suitable dimensions are supported
flatten_dimensions (experimental)
is_infinite (experimental)
load_collection
- Parameter properties: Supports querying by queryables defined via the API.
load_geojson (experimental)
load_stac (load_result) (experimental)
- Supports loading from STAC API - Features.
- Supports loading from STAC API - Item Search.
- Supports loading from static STAC.
- Parameter temporal_extent: All temporal formats are supported (date-time and date)
- Parameter bands: Supports filtering by band name and common name
merge_cubes
- Parameter context: is supported and passed to the callback
ndvi
- Supports common names as band names
order
rearrange
reduce_dimension
- Parameter context: is supported and passed to the callback
reduce_spatial (experimental)
- Parameter reducer: At least all processes (up to the level of this requirement) in the category reducer that accept an array as input and return a single value as output can be used (also in a chain of processes).
- Parameter reducer: Supports access to labels in the callback
- Parameter context: is supported and passed to the callback
resample_cube_spatial
- Parameter method: enum reflects implemention (all values are supported)
resample_cube_temporal
- Parameter dimension: All suitable dimensions are supported
resample_spatial
- Parameter align: enum reflects implemention (all values are supported)
trim_cube
unflatten_dimensions (experimental)
vector_to_random_points (experimental)
vector_to_regular_points (experimental)

# L3-ML: Machine Learning

fit_curve (experimental)
fit_regr_random_forest
load_ml_model (experimental)
predict_curve (experimental)
save_ml_model (experimental)

# L3-UDF: User-Defined Functions

run_udf
- Parameter context: is supported and passed to the callback
run_udf_externally (experimental)

# L3-Clim: Cimatology

anomaly
climatological_normal

# L3-ARD: Analysis-Ready Data

ard_normalized_radar_backscatter (experimental)
- has been tested on > 100x100km at 10m resolution (or equivalent)
- Custom parameters are provided via the options parameter
ard_surface_reflectance (experimental)
- Parameter atmospheric_correction_method: enum reflects implemention (all values are supported)
- Parameter cloud_detection_method: enum reflects implemention (all values are supported)
- Custom parameters are provided via the atmospheric_correction_options and/or cloud_detection_options parameters

# L4: Above and Beyond

aggregate_spatial
- Parameter reducer: At least all processes (up to the level of this requirement) in the categories array, comparison, logic and math can be used (also in a chain of processes).
aggregate_temporal
- Parameter reducer: At least all processes (up to the level of this requirement) in the categories array, comparison, logic and math can be used (also in a chain of processes).
aggregate_temporal_period
- Parameter reducer: At least all processes (up to the level of this requirement) in the categories array, comparison, logic and math can be used (also in a chain of processes).
apply_neighborhood
- Parameter process: At least all processes (up to the level of this requirement) in the categories array, comparison, logic and math can be used (also in a chain of processes).
apply_polygon (chunk_polygon) (experimental)
array_apply
- Parameter process: At least all processes (up to the level of this requirement) in the categories comparison, logic and math can be used (also in a chain of processes).
atmospheric_correction (experimental)
- Parameter method: enum reflects implemention (all values are supported)
- Custom parameters are provided via the options parameter
filter_bands
- Supports filtering by wavelength
filter_bbox
- Parameter extent: Supports filtering by base/height
load_collection
- Parameter spatial_extent: Supports filtering by base/height
load_stac (load_result) (experimental)
- Parameter spatial_extent: Supports filtering by base/height
load_uploaded_files (experimental)
load_url (experimental)
reduce_dimension
- Parameter reducer: At least all processes (up to the level of this requirement) in the categories array, comparison, logic and math can be used (also in a chain of processes).
reduce_spatial (experimental)
- Parameter reducer: At least all processes (up to the level of this requirement) in the categories array, comparison, logic and math can be used (also in a chain of processes).
sar_backscatter (experimental)
- Parameter coefficient: enum reflects implemention (all values are supported)
- Custom parameters are provided via the options parameter