def landsat_clean_mask_invalid(dataset):
"""
Masks out invalid data according to the LANDSAT
surface reflectance specifications. See this document:
https://landsat.usgs.gov/sites/default/files/documents/ledaps_product_guide.pdf pages 19-20.
Parameters
----------
dataset: xarray.Dataset
An xarray `Dataset` containing bands such as 'red', 'green', or 'blue'.
Returns
-------
invalid_mask: xarray.DataArray
An xarray DataArray with the same number and order of coordinates as in `dataset`.
"""
invalid_mask = None
data_arr_names = [
arr_name for arr_name in list(dataset.data_vars)
if arr_name not in ['pixel_qa', 'radsat_qa', 'cloud_qa']
]
# Only keep data where all bands are in the valid range.
for i, data_arr_name in enumerate(data_arr_names):
invalid_mask_arr = xr_and(0 < dataset[data_arr_name],
dataset[data_arr_name] < 10000)
invalid_mask = invalid_mask_arr if i == 0 else xr_and(
invalid_mask, invalid_mask_arr)
return invalid_mask
def load_simple(dc,
platform,
product,
frac_res=None,
abs_res=None,
load_params={},
masking_params={},
indiv_masks=None):
"""
Simplifies loading from the Data Cube by retrieving a dataset along
with its mask.
Parameters
----------
dc: datacube.api.core.Datacube
The Datacube instance to load data with.
platform, product: str
Strings denoting the platform and product to retrieve data for.
frac_res: float
The fraction of the original resolution to scale to. Must be postive.
Note that this can be greater than 1.0, in which case the resolution
is upsampled.
abs_res: list-like
A list-like of the number of pixels for the x and y axes, respectively.
Overrides `frac_res` if specified.
load_params: dict, optional
A dictionary of parameters for `dc.load()`.
Here are some common load parameters:
*lat, lon: list-like 2-tuples of minimum and maximum values for
latitude and longitude, respectively.*
*time: list-like A 2-tuple of the minimum and maximum times
for acquisitions.*
*measurements: list-like The list of measurements to retrieve
from the Datacube.*
masking_params: dict, optional
A dictionary of keyword arguments for corresponding masking functions.
For example: {'cover_types':['cloud']} would retain only clouds for Landsat products,
because `landsat_qa_clean_mask()` is used for the Landsat family of platforms.
indiv_masks: list
A list of masks to return (e.g. ['water']).
These do not have to be the same used to create `clean_mask`.
Returns
-------
dataset: xarray.Dataset
The raw data requested. Can be cleaned with `dataset.where(clean_mask)`.
clean_mask: xarray.DataArray
The clean mask, formed as a logical AND of all masks used.
masks: list of xarray.DataArray
A list of the masks requested by `indiv_masks`,
or `None` if `indiv_masks` is not specified.
Raises
------
AssertionError: If no data is retrieved for any platform query.
:Authors:
John Rattz ([email protected])
"""
current_load_params = dict(platform=platform, product=product)
current_load_params.update(load_params)
dataset = dc.load(**current_load_params)
assert len(dataset.dims) > 0, "No data was retrieved."
# Scale resolution if specified.
if frac_res is not None or abs_res is not None:
dataset = xr_scale_res(dataset, frac_res=frac_res, abs_res=abs_res)
# Get the clean mask for the appropriate LANDSAT satellite platform.
clean_mask = landsat_qa_clean_mask(dataset, platform, **masking_params)
# Get the mask for removing data ouside the accepted range of LANDSAT 7 and 8.
clean_mask = xr_and(clean_mask, landsat_clean_mask_invalid(dataset))
# Retrieve individual masks.
if indiv_masks is None:
masks = None
else:
masks = []
for mask in indiv_masks:
masks.append(
landsat_qa_clean_mask(dataset, platform, cover_types=[mask]))
return dataset, clean_mask, masks
