In [1]:
% load_ext autoreload
% autoreload 2
In [10]:
import numpy as np
import pandas as pd
import xarray as xr
import datacube
In [2]:
dc = datacube.Datacube()
dc
Out[2]:
Datacube<index=Index<db=PostgresDb<engine=Engine(postgresql://ceholden@:5432/datacube)>>>
In [4]:
obs = dc.product_observations()[0]
In [5]:
dc.list_products()
Out[5]:
name
description
platform
format
instrument
product_type
crs
resolution
tile_size
spatial_dimensions
id
1
ls5_ledaps_scene
Landsat 5 ESPA 30 meter
LANDSAT_5
GeoTiff
TM
ESPA
NaN
NaN
NaN
NaN
2
ls7_ledaps_scene
Landsat 7 ESPA 30 meter
LANDSAT_7
GeoTiff
ETM
ESPA
NaN
NaN
NaN
NaN
3
ls8_ledaps_scene
Landsat 8 ESPA 30 meter
LANDSAT_8
GeoTiff
OLI_TIRS
ESPA
NaN
NaN
NaN
NaN
4
ls8_ledaps_albers
Landsat 8 ESPA products, 5000x5000 pixel 30m t...
LANDSAT_8
NetCDF
OLI_TIRS
ESPA
EPSG:5070
[-30, 30]
[150000.0, 150000.0]
(y, x)
5
ls7_ledaps_albers
Landsat 7 ESPA products, 5000x5000 pixel 30m t...
LANDSAT_7
NetCDF
ETM
ESPA
EPSG:5070
[-30, 30]
[150000.0, 150000.0]
(y, x)
In [89]:
dc.list_measurements()
Out[89]:
aliases
dtype
flags_definition
name
nodata
spectral_definition
units
product
measurement
ls5_ledaps_scene
sr_band1
[band_1, blue]
int16
NaN
sr_band1
-9999
{'wavelength': [410, 411, 412, 413, 414, 415, ...
1
sr_band2
[band_2, green]
int16
NaN
sr_band2
-9999
{'wavelength': [500, 501, 502, 503, 504, 505, ...
1
sr_band3
[band_3, red]
int16
NaN
sr_band3
-9999
{'wavelength': [580, 590, 600, 605, 610, 611, ...
1
sr_band4
[band_4, nir]
int16
NaN
sr_band4
-9999
{'wavelength': [730, 735, 740, 745, 750, 751, ...
1
sr_band5
[band_5, swir1]
int16
NaN
sr_band5
-9999
{'wavelength': [1514, 1515, 1517, 1519, 1521, ...
1
sr_band7
[band_7, swir2]
int16
NaN
sr_band7
-9999
{'wavelength': [2000, 2001, 2003, 2005, 2007, ...
1
cfmask
[mask, CFmask]
uint8
{'cfmask': {'description': 'CFmask', 'values':...
cfmask
255
NaN
1
cfmask_conf
[mask_config]
uint8
{'cfmask_conf': {'description': 'CFmask confid...
cfmask_conf
255
NaN
1
sr_adjacent_cloud_qa
[adjacent_cloud]
uint8
{'sr_adjacent_cloud_qa': {'description': 'Adja...
sr_adjacent_cloud_qa
0
NaN
1
sr_atmos_opacity
[atmospheric_opacity, opacity]
int16
NaN
sr_atmos_opacity
-9999
NaN
1
sr_cloud_qa
[cloud]
uint8
{'sr_cloud_qa': {'description': 'Cloud QA', 'v...
sr_cloud_qa
0
NaN
1
sr_cloud_shadow_qa
[cloud_shadow]
uint8
{'sr_cloud_shadow_qa': {'description': 'Cloud ...
sr_cloud_shadow_qa
0
NaN
1
sr_ddv_qa
[ddv]
uint8
{'sr_ddv_qa': {'description': 'DDV QA', 'value...
sr_ddv_qa
0
NaN
1
sr_fill_qa
[fill]
uint8
{'sr_fill_qa': {'description': 'Fill QA', 'val...
sr_fill_qa
0
NaN
1
sr_land_water_qa
[land_water]
uint8
{'sr_land_water_qa': {'description': 'Land Wat...
sr_land_water_qa
0
NaN
1
sr_snow_qa
[snow]
uint8
{'sr_snow_qa': {'description': 'Snow QA', 'val...
sr_snow_qa
0
NaN
1
ls7_ledaps_scene
sr_band1
[band_1, blue]
int16
NaN
sr_band1
-9999
{'wavelength': [410, 411, 412, 413, 414, 415, ...
1
sr_band2
[band_2, green]
int16
NaN
sr_band2
-9999
{'wavelength': [500, 501, 502, 503, 504, 505, ...
1
sr_band3
[band_3, red]
int16
NaN
sr_band3
-9999
{'wavelength': [580, 590, 600, 605, 610, 611, ...
1
sr_band4
[band_4, nir]
int16
NaN
sr_band4
-9999
{'wavelength': [730, 735, 740, 745, 750, 751, ...
1
sr_band5
[band_5, swir1]
int16
NaN
sr_band5
-9999
{'wavelength': [1514, 1515, 1517, 1519, 1521, ...
1
sr_band7
[band_7, swir2]
int16
NaN
sr_band7
-9999
{'wavelength': [2000, 2001, 2003, 2005, 2007, ...
1
cfmask
[mask, CFmask]
uint8
{'cfmask': {'description': 'CFmask', 'values':...
cfmask
255
NaN
1
cfmask_conf
[mask_config]
uint8
{'cfmask_conf': {'description': 'CFmask confid...
cfmask_conf
255
NaN
1
sr_adjacent_cloud_qa
[adjacent_cloud]
uint8
{'sr_adjacent_cloud_qa': {'description': 'Adja...
sr_adjacent_cloud_qa
0
NaN
1
sr_atmos_opacity
[atmospheric_opacity, opacity]
int16
NaN
sr_atmos_opacity
-9999
NaN
1
sr_cloud_qa
[cloud]
uint8
{'sr_cloud_qa': {'description': 'Cloud QA', 'v...
sr_cloud_qa
0
NaN
1
sr_cloud_shadow_qa
[cloud_shadow]
uint8
{'sr_cloud_shadow_qa': {'description': 'Cloud ...
sr_cloud_shadow_qa
0
NaN
1
sr_ddv_qa
[ddv]
uint8
{'sr_ddv_qa': {'description': 'DDV QA', 'value...
sr_ddv_qa
0
NaN
1
sr_fill_qa
[fill]
uint8
{'sr_fill_qa': {'description': 'Fill QA', 'val...
sr_fill_qa
0
NaN
1
...
...
...
...
...
...
...
...
...
ls8_ledaps_scene
sr_band7
[band_7, swir2]
int16
NaN
sr_band7
-9999
{'wavelength': [2037, 2038, 2039, 2040, 2041, ...
1
cfmask
[mask, CFmask]
uint8
{'cfmask': {'description': 'CFmask', 'values':...
cfmask
255
NaN
1
cfmask_conf
[mask_config]
uint8
{'cfmask_conf': {'description': 'CFmask confid...
cfmask_conf
255
NaN
1
sr_cloud
[cloud]
uint8
{'cirrus_cloud': {'description': 'Cloud', 'val...
sr_cloud
0
NaN
1
ls8_ledaps_albers
coastal_aerosol
[band_1, coastal_aerosol]
int16
NaN
coastal_aerosol
-9999
{'wavelength': [427, 428, 429, 430, 431, 432, ...
1
blue
[band_2, blue]
int16
NaN
blue
-9999
{'wavelength': [436, 437, 438, 439, 440, 441, ...
1
green
[band_3, green]
int16
NaN
green
-9999
{'wavelength': [512, 513, 514, 515, 516, 517, ...
1
red
[band_4, red]
int16
NaN
red
-9999
{'wavelength': [625, 626, 627, 628, 629, 630, ...
1
nir
[band_5, nir]
int16
NaN
nir
-9999
{'wavelength': [829, 830, 831, 832, 833, 834, ...
1
swir1
[band_6, swir1]
int16
NaN
swir1
-9999
{'wavelength': [1515, 1516, 1517, 1518, 1519, ...
1
swir2
[band_7, swir2]
int16
NaN
swir2
-9999
{'wavelength': [2037, 2038, 2039, 2040, 2041, ...
1
cf_mask
[mask, CFmask]
int16
{'cfmask': {'description': 'CFmask', 'values':...
cf_mask
255
NaN
1
cf_mask_conf
[mask_config]
int16
{'cfmask_conf': {'description': 'CFmask confid...
cf_mask_conf
255
NaN
1
cloud
[cloud]
int16
{'cirrus_cloud': {'description': 'Cloud', 'val...
cloud
0
NaN
1
ls7_ledaps_albers
blue
[band_1, blue]
int16
NaN
blue
-9999
{'wavelength': [410, 411, 412, 413, 414, 415, ...
1
green
[band_2, green]
int16
NaN
green
-9999
{'wavelength': [500, 501, 502, 503, 504, 505, ...
1
red
[band_3, red]
int16
NaN
red
-9999
{'wavelength': [580, 590, 600, 605, 610, 611, ...
1
nir
[band_4, nir]
int16
NaN
nir
-9999
{'wavelength': [730, 735, 740, 745, 750, 751, ...
1
swir1
[band_5, swir1]
int16
NaN
swir1
-9999
{'wavelength': [1514, 1515, 1517, 1519, 1521, ...
1
swir2
[band_7, swir2]
int16
NaN
swir2
-9999
{'wavelength': [2000, 2001, 2003, 2005, 2007, ...
1
cf_mask
[mask, CFmask]
int16
{'cfmask': {'description': 'CFmask', 'values':...
cf_mask
255
NaN
1
cf_mask_conf
[mask_config]
int16
{'cfmask_conf': {'description': 'CFmask confid...
cf_mask_conf
255
NaN
1
adjacent_cloud_qa
[adjacent_cloud]
int16
{'sr_adjacent_cloud_qa': {'description': 'Adja...
adjacent_cloud_qa
255
NaN
1
atmos_opacity
[atmospheric_opacity, opacity]
int16
NaN
atmos_opacity
-9999
NaN
1
cloud_qa
[cloud]
int16
{'sr_cloud_qa': {'description': 'Cloud QA', 'v...
cloud_qa
0
NaN
1
cloud_shadow_qa
[cloud_shadow]
int16
{'sr_cloud_shadow_qa': {'description': 'Cloud ...
cloud_shadow_qa
0
NaN
1
ddv_qa
[ddv]
int16
{'sr_ddv_qa': {'description': 'DDV QA', 'value...
ddv_qa
0
NaN
1
fill_qa
[fill]
int16
{'sr_fill_qa': {'description': 'Fill QA', 'val...
fill_qa
0
NaN
1
land_water_qa
[land_water]
int16
{'sr_land_water_qa': {'description': 'Land Wat...
land_water_qa
0
NaN
1
snow_qa
[snow]
int16
{'sr_snow_qa': {'description': 'Snow QA', 'val...
snow_qa
0
NaN
1
68 rows × 7 columns
In [30]:
?xr.concat
In [15]:
?xr.merge
In [11]:
datasets = [
dc.load(product=prod,
product_type='ESPA',
platform=['LANDSAT_5', 'LANDSAT_7', 'LANDSAT_8'],
x=(-72, -71.90), y=(41., 41.10))
for prod in ['ls7_ledaps_albers', 'ls8_ledaps_albers']
]
In [33]:
products = ['ls7_ledaps_albers', 'ls8_ledaps_albers']
# Find measurements common to all products
measurements = dc.list_measurements().reset_index()
measurements.index = measurements['product']
data_vars = set(measurements.loc[products[0], 'measurement'])
for prod in products[1:]:
data_vars.intersection_update(measurements.loc[prod, 'measurement'])
# Read each product individually
datasets = []
for prod in products:
ds = dc.load(product=prod,
product_type='ESPA',
platform=['LANDSAT_5', 'LANDSAT_7', 'LANDSAT_8'],
measurements=data_vars,
x=(-72, -71.90), y=(41., 41.10))
ds['platform'] = ('time', np.repeat(prod, ds.time.size))
datasets.append(ds)
# Concat along time
combined = xr.concat(datasets, dim='time')
# Sort by time
sorted_time = np.sort(combined.time)
combined.loc[dict(time=sorted_time)]
Out[33]:
<xarray.Dataset>
Dimensions: (time: 61, x: 364, y: 432)
Coordinates:
* y (y) float64 2.263e+06 2.263e+06 2.263e+06 2.263e+06 ...
* x (x) float64 1.979e+06 1.979e+06 1.979e+06 1.979e+06 ...
* time (time) datetime64[ns] 2013-04-16T15:28:55 ...
Data variables:
red (time, y, x) int16 115 107 106 102 106 111 112 112 108 107 ...
swir1 (time, y, x) int16 116 100 98 100 99 98 103 107 105 107 ...
swir2 (time, y, x) int16 107 100 93 93 98 99 103 104 105 103 104 ...
nir (time, y, x) int16 87 79 71 74 76 75 79 82 76 75 75 74 78 ...
cf_mask_conf (time, y, x) int16 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 ...
green (time, y, x) int16 246 235 236 239 235 231 237 245 238 237 ...
blue (time, y, x) int16 207 202 194 213 197 200 202 209 197 205 ...
platform (time) <U17 'ls8_ledaps_albers' 'ls8_ledaps_albers' ...
cf_mask (time, y, x) int16 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 ...
Attributes:
crs: EPSG:5070
In [34]:
combined
Out[34]:
<xarray.Dataset>
Dimensions: (time: 61, x: 364, y: 432)
Coordinates:
* y (y) float64 2.263e+06 2.263e+06 2.263e+06 2.263e+06 ...
* x (x) float64 1.979e+06 1.979e+06 1.979e+06 1.979e+06 ...
* time (time) datetime64[ns] 2013-10-01T15:22:55 ...
Data variables:
red (time, y, x) int16 20 -2 20 64 43 43 20 64 -9999 -2 87 20 ...
swir1 (time, y, x) int16 8 8 8 -20 -20 8 8 8 -9999 8 8 8 -9999 ...
swir2 (time, y, x) int16 50 50 -10 -10 19 80 19 -10 -9999 19 19 ...
nir (time, y, x) int16 -10 -42 23 23 -10 -42 -10 -10 -9999 23 ...
cf_mask_conf (time, y, x) int16 1 1 1 1 1 1 1 1 255 1 1 1 255 255 1 255 ...
green (time, y, x) int16 187 160 134 187 134 187 134 187 -9999 ...
blue (time, y, x) int16 235 186 186 211 186 235 211 161 -9999 ...
platform (time) <U17 'ls7_ledaps_albers' 'ls8_ledaps_albers' ...
cf_mask (time, y, x) int16 1 1 1 1 1 1 1 1 255 1 1 1 255 255 1 255 ...
Attributes:
crs: EPSG:5070
In [9]:
query = {
}
obs = []
for prod in products:
obs.extend(
dc.product_observations(product=prod, )
)
group_by = datacube.api.query.group_by()
sources = dc.product_sources(sources, )
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-9-0f2a55cceaec> in <module>()
8 )
9
---> 10 sources = dc.product_sources(sources)
TypeError: product_sources() missing 3 required positional arguments: 'group_func', 'dimension', and 'units'
In [ ]:
In [7]:
ds = dc.load(product='ls8_ledaps_albers', x=(-72, -71.90), y=(41., 41.10))
In [9]:
%matplotlib nbagg
ds['swir1'].isel(x=0, y=0).plot.line('ro')
Out[9]:
[<matplotlib.lines.Line2D at 0x7f3b2a9fbdd8>]
In [10]:
from datacube.storage import masking
masking.get_flags_def(ds)
# pandas.DataFrame.from_dict(masking.get_flags_def(ds), orient='index')
clr = masking.make_mask(ds, cfmask='clear')
In [28]:
ds.x.size
Out[28]:
364
In [40]:
%matplotlib nbagg
ds.where(clr)['swir1'].notnull().sum(dim='time')
Out[40]:
<xarray.DataArray 'swir1' (y: 432, x: 364)>
array([[0, 0, 0, ..., 2, 3, 1],
[0, 0, 0, ..., 2, 2, 2],
[0, 0, 1, ..., 2, 2, 2],
...,
[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0],
[0, 0, 1, ..., 1, 0, 0]])
Coordinates:
* x (x) float64 1.979e+06 1.979e+06 1.979e+06 1.979e+06 1.979e+06 ...
* y (y) float64 2.263e+06 2.263e+06 2.263e+06 2.263e+06 2.263e+06 ...
In [81]:
%matplotlib nbagg
clr.cf_mask.loc['2016-1':'2016-3'].plot(col='time', col_wrap=3)
Out[81]:
<xarray.plot.facetgrid.FacetGrid at 0x7fc9f5746b70>
In [67]:
gw = datacube.api.GridWorkflow(dc.index, product='ls8_ledaps_albers')
gw.list_tiles(product='ls8_ledaps_albers')
# gw.list_cells(product_type='ESPA', product='ls8_ledaps_albers')
Out[67]:
defaultdict(dict,
{(12,
14,
numpy.datetime64('2013-07-05T15:29:05.000000000')): {'geobox': GeoBox(5000, 5000, Affine(30.0, 0.0, 1800000.0,
0.0, -30.0, 2250000.0), EPSG:5070), 'sources': <xarray.DataArray (time: 1)>
array([ (Dataset <id=67ce3c1e-0ffc-4f06-ae5d-4e5a1154c4ab type=ls8_ledaps_albers location=/projectnb/landsat/datasets/AGDC/TILES/LS8_OLI_LEDAPS/LS8_OLI_LEDAPS_3577_12_14_20130705152905000000.nc>,)], dtype=object)
Coordinates:
* time (time) datetime64[ns] 2013-07-05T15:29:05},
(12,
14,
numpy.datetime64('2013-07-21T15:29:03.000000000')): {'geobox': GeoBox(5000, 5000, Affine(30.0, 0.0, 1800000.0,
0.0, -30.0, 2250000.0), EPSG:5070), 'sources': <xarray.DataArray (time: 1)>
array([ (Dataset <id=7e5ed3c4-86eb-415d-91a7-a9715b34089d type=ls8_ledaps_albers location=/projectnb/landsat/datasets/AGDC/TILES/LS8_OLI_LEDAPS/LS8_OLI_LEDAPS_3577_12_14_20130721152903000000.nc>,)], dtype=object)
Coordinates:
* time (time) datetime64[ns] 2013-07-21T15:29:03},
(12,
14,
numpy.datetime64('2013-08-06T15:29:07.000000000')): {'geobox': GeoBox(5000, 5000, Affine(30.0, 0.0, 1800000.0,
0.0, -30.0, 2250000.0), EPSG:5070), 'sources': <xarray.DataArray (time: 1)>
array([ (Dataset <id=205cfb62-f9fa-4293-a29c-2b6e1c0194ef type=ls8_ledaps_albers location=/projectnb/landsat/datasets/AGDC/TILES/LS8_OLI_LEDAPS/LS8_OLI_LEDAPS_3577_12_14_20130806152907000000.nc>,)], dtype=object)
Coordinates:
* time (time) datetime64[ns] 2013-08-06T15:29:07},
(12,
14,
numpy.datetime64('2013-08-22T15:29:09.000000000')): {'geobox': GeoBox(5000, 5000, Affine(30.0, 0.0, 1800000.0,
0.0, -30.0, 2250000.0), EPSG:5070), 'sources': <xarray.DataArray (time: 1)>
array([ (Dataset <id=30fadee2-f88b-4f5d-8eaf-41188d4d7163 type=ls8_ledaps_albers location=/projectnb/landsat/datasets/AGDC/TILES/LS8_OLI_LEDAPS/LS8_OLI_LEDAPS_3577_12_14_20130822152909000000.nc>,)], dtype=object)
Coordinates:
* time (time) datetime64[ns] 2013-08-22T15:29:09},
(12,
14,
numpy.datetime64('2013-09-07T15:29:08.000000000')): {'geobox': GeoBox(5000, 5000, Affine(30.0, 0.0, 1800000.0,
0.0, -30.0, 2250000.0), EPSG:5070), 'sources': <xarray.DataArray (time: 1)>
array([ (Dataset <id=0e3c200b-75f2-4fab-aed0-bc806e1cc593 type=ls8_ledaps_albers location=/projectnb/landsat/datasets/AGDC/TILES/LS8_OLI_LEDAPS/LS8_OLI_LEDAPS_3577_12_14_20130907152908000000.nc>,)], dtype=object)
Coordinates:
* time (time) datetime64[ns] 2013-09-07T15:29:08},
(12,
14,
numpy.datetime64('2013-09-23T15:29:00.000000000')): {'geobox': GeoBox(5000, 5000, Affine(30.0, 0.0, 1800000.0,
0.0, -30.0, 2250000.0), EPSG:5070), 'sources': <xarray.DataArray (time: 1)>
array([ (Dataset <id=b5970e5e-429f-400c-8f7d-9a8201538a20 type=ls8_ledaps_albers location=/projectnb/landsat/datasets/AGDC/TILES/LS8_OLI_LEDAPS/LS8_OLI_LEDAPS_3577_12_14_20130923152900000000.nc>,)], dtype=object)
Coordinates:
* time (time) datetime64[ns] 2013-09-23T15:29:00},
(12,
14,
numpy.datetime64('2013-11-10T15:28:51.000000000')): {'geobox': GeoBox(5000, 5000, Affine(30.0, 0.0, 1800000.0,
0.0, -30.0, 2250000.0), EPSG:5070), 'sources': <xarray.DataArray (time: 1)>
array([ (Dataset <id=b50ab46c-c7c8-4472-b1f5-49a78794e5bc type=ls8_ledaps_albers location=/projectnb/landsat/datasets/AGDC/TILES/LS8_OLI_LEDAPS/LS8_OLI_LEDAPS_3577_12_14_20131110152851000000.nc>,)], dtype=object)
Coordinates:
* time (time) datetime64[ns] 2013-11-10T15:28:51},
(12,
14,
numpy.datetime64('2013-11-26T15:28:43.000000000')): {'geobox': GeoBox(5000, 5000, Affine(30.0, 0.0, 1800000.0,
0.0, -30.0, 2250000.0), EPSG:5070), 'sources': <xarray.DataArray (time: 1)>
array([ (Dataset <id=5868c880-815b-4d74-95c7-d5ca2da58e3c type=ls8_ledaps_albers location=/projectnb/landsat/datasets/AGDC/TILES/LS8_OLI_LEDAPS/LS8_OLI_LEDAPS_3577_12_14_20131126152843000000.nc>,)], dtype=object)
Coordinates:
* time (time) datetime64[ns] 2013-11-26T15:28:43},
(12,
14,
numpy.datetime64('2013-12-12T15:28:41.000000000')): {'geobox': GeoBox(5000, 5000, Affine(30.0, 0.0, 1800000.0,
0.0, -30.0, 2250000.0), EPSG:5070), 'sources': <xarray.DataArray (time: 1)>
array([ (Dataset <id=1a3dc709-b94e-41aa-be50-26374b5ca6e5 type=ls8_ledaps_albers location=/projectnb/landsat/datasets/AGDC/TILES/LS8_OLI_LEDAPS/LS8_OLI_LEDAPS_3577_12_14_20131212152841000000.nc>,)], dtype=object)
Coordinates:
* time (time) datetime64[ns] 2013-12-12T15:28:41},
(12,
14,
numpy.datetime64('2013-12-28T15:28:32.000000000')): {'geobox': GeoBox(5000, 5000, Affine(30.0, 0.0, 1800000.0,
0.0, -30.0, 2250000.0), EPSG:5070), 'sources': <xarray.DataArray (time: 1)>
array([ (Dataset <id=e238584f-19aa-4401-a1a3-abebd088a871 type=ls8_ledaps_albers location=/projectnb/landsat/datasets/AGDC/TILES/LS8_OLI_LEDAPS/LS8_OLI_LEDAPS_3577_12_14_20131228152832000000.nc>,)], dtype=object)
Coordinates:
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* time (time) datetime64[ns] 2016-06-11T15:26:48}})
In [68]:
?gw.load
In [93]:
gw.list_tiles(product_type='ESPA', product='ls8_ledaps_albers', platform=['LANDSAT_5', 'LANDSAT_7', 'LANDSAT_8'])
Out[93]:
defaultdict(dict,
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Coordinates:
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Coordinates:
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Coordinates:
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Coordinates:
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Coordinates:
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Coordinates:
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Coordinates:
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Coordinates:
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Coordinates:
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Coordinates:
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Coordinates:
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Coordinates:
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Coordinates:
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Coordinates:
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Coordinates:
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array([ (Dataset <id=ef12b487-e1a9-47c0-88ed-d166fde7a19c type=ls8_ledaps_albers location=/projectnb/landsat/datasets/AGDC/TILES/LS8_OLI_LEDAPS/LS8_OLI_LEDAPS_3577_14_16_20151015152706000000.nc>,)], dtype=object)
Coordinates:
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Coordinates:
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Coordinates:
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Coordinates:
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Coordinates:
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Coordinates:
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array([ (Dataset <id=66262491-4f64-45e9-9678-e6c94096f394 type=ls8_ledaps_albers location=/projectnb/landsat/datasets/AGDC/TILES/LS8_OLI_LEDAPS/LS8_OLI_LEDAPS_3577_14_16_20160323152651000000.nc>,)], dtype=object)
Coordinates:
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Coordinates:
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Coordinates:
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Coordinates:
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Coordinates:
* time (time) datetime64[ns] 2016-05-26T15:26:44},
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numpy.datetime64('2016-06-11T15:26:48.000000000')): {'geobox': GeoBox(5000, 5000, Affine(30.0, 0.0, 2100000.0,
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array([ (Dataset <id=58d95a95-b2ec-4d89-8099-f5d655472c28 type=ls8_ledaps_albers location=/projectnb/landsat/datasets/AGDC/TILES/LS8_OLI_LEDAPS/LS8_OLI_LEDAPS_3577_14_16_20160611152648000000.nc>,)], dtype=object)
Coordinates:
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In [87]:
dataset.metadata_doc['platform']
Out[87]:
{'code': 'LANDSAT_8'}
In [58]:
TILE = (14, 14)
cell_obs = gw.cell_observations(product='ls8_ledaps_albers')
datasets = cell_obs[TILE]['datasets']
# Sort by center time
datasets = sorted(datasets, key=lambda d: d.center_time)
In [65]:
from osgeo import gdal
p = str(dataset.local_path)
for name, md in dataset.measurements.items():
sds_file = 'NETCDF:"{file}":{measurement}'.format(file=p, measurement=md['layer'])
_sds = gdal.Open(sds_file)
print(_sds.GetMetadata_Dict())
{'NC_GLOBAL#history': "NetCDF-CF file created by datacube version '1.1.4' at 20160714.", 'time#calendar': 'standard', 'NC_GLOBAL#title': 'Boston University Data Cube Landsat Surface Reflectance', 'crs#false_easting': '0', 'crs#standard_parallel': '{29.5,45.5}', 'time#long_name': 'Time, unix time-stamp', 'NC_GLOBAL#keywords_vocabulary': 'GCMD', 'NC_GLOBAL#institution': 'Boston University', 'y#standard_name': 'projection_y_coordinate', 'NETCDF_DIM_time_VALUES': '1461511597', 'NC_GLOBAL#product_version': '2.0.0', 'y#long_name': 'y coordinate of projection', 'NC_GLOBAL#project': 'BU', 'crs#crs_wkt': 'PROJCS["NAD83 / Conus Albers",GEOGCS["NAD83",DATUM["North_American_Datum_1983",SPHEROID["GRS 1980",6378137,298.257222101,AUTHORITY["EPSG","7019"]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY["EPSG","6269"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4269"]],PROJECTION["Albers_Conic_Equal_Area"],PARAMETER["standard_parallel_1",29.5],PARAMETER["standard_parallel_2",45.5],PARAMETER["latitude_of_center",23],PARAMETER["longitude_of_center",-96],PARAMETER["false_easting",0],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["X",EAST],AXIS["Y",NORTH],AUTHORITY["EPSG","5070"]]', 'nir#units': '1', 'NC_GLOBAL#instrument': 'TM', 'time#standard_name': 'time', 'crs#semi_minor_axis': '6356752.314140356', 'NC_GLOBAL#Conventions': 'CF-1.6, ACDD-1.3', 'NC_GLOBAL#source': 'Surface reflectance from LEDAPS', 'NC_GLOBAL#references': 'http://dx.doi.org/10.3334/ORNLDAAC/1146', 'NETCDF_DIM_EXTRA': '{time}', 'crs#semi_major_axis': '6378137', 'NC_GLOBAL#keywords': 'AU/GA,NASA/GSFC/SED/ESD/LANDSAT,REFLECTANCE,ETM+,TM,OLI,EARTH SCIENCE', 'y#units': 'metre', 'time#axis': 'T', 'NC_GLOBAL#acknowledgment': 'Landsat data is provided by the United States Geological Survey (USGS).', 'NC_GLOBAL#geospatial_lat_max': '40.72351010483209', 'NC_GLOBAL#geospatial_bounds_crs': 'EPSG:4326', 'nir#alias': 'band_5', 'crs#inverse_flattening': '298.257222101', 'crs#latitude_of_projection_origin': '23', 'x#long_name': 'x coordinate of projection', 'NETCDF_DIM_time_DEF': '{1,6}', 'NC_GLOBAL#geospatial_lon_max': '-68.9125882946302', 'NC_GLOBAL#date_created': '2016-07-13T22:24:12.505047', 'NC_GLOBAL#geospatial_lon_units': 'degrees_east', 'NC_GLOBAL#platform': 'LANDSAT-5', 'crs#grid_mapping_name': 'albers_conical_equal_area', 'NC_GLOBAL#summary': 'Landsat 8 Operational Land Imager Analysis Ready data prepared by USGS', 'crs#false_northing': '0', 'time#units': 'seconds since 1970-01-01 00:00:00', 'crs#longitude_of_central_meridian': '-96', 'NC_GLOBAL#coverage_content_type': 'physicalMeasurement', 'crs#GeoTransform': '{2100000,30,0,2250000,0,-30}', 'NC_GLOBAL#geospatial_lat_min': '39.07301919071188', 'NC_GLOBAL#processing_level': 'L2', 'NC_GLOBAL#license': 'https://creativecommons.org/licenses/by/4.0/', 'x#units': 'metre', 'crs#spatial_ref': 'PROJCS["NAD83 / Conus Albers",GEOGCS["NAD83",DATUM["North_American_Datum_1983",SPHEROID["GRS 1980",6378137,298.257222101,AUTHORITY["EPSG","7019"]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY["EPSG","6269"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4269"]],PROJECTION["Albers_Conic_Equal_Area"],PARAMETER["standard_parallel_1",29.5],PARAMETER["standard_parallel_2",45.5],PARAMETER["latitude_of_center",23],PARAMETER["longitude_of_center",-96],PARAMETER["false_easting",0],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["X",EAST],AXIS["Y",NORTH],AUTHORITY["EPSG","5070"]]', 'NC_GLOBAL#geospatial_lat_units': 'degrees_north', 'NC_GLOBAL#geospatial_bounds': 'POLYGON((-70.63105771584051 40.72351010483209, -71.09496888808575 39.431257108692336, -69.40465970697232 39.073019190711875, -68.9125882946302 40.35857900913365, -70.63105771584051 40.72351010483209))', 'NC_GLOBAL#geospatial_lon_min': '-71.09496888808575', 'NC_GLOBAL#cdm_data_type': 'Grid', 'x#standard_name': 'projection_x_coordinate', 'nir#grid_mapping': 'crs', 'nir#_FillValue': '-9999', 'NC_GLOBAL#naming_authority': 'gov.usgs', 'crs#long_name': 'NAD83 / Conus Albers', 'NC_GLOBAL#product_suite': 'USGS Landsat', 'nir#long_name': 'Surface Reflectance 0.85-0.88 microns (Near Infrared)'}
{'NC_GLOBAL#history': "NetCDF-CF file created by datacube version '1.1.4' at 20160714.", 'time#calendar': 'standard', 'green#units': '1', 'green#_FillValue': '-9999', 'crs#false_easting': '0', 'crs#standard_parallel': '{29.5,45.5}', 'time#standard_name': 'time', 'NC_GLOBAL#keywords_vocabulary': 'GCMD', 'NC_GLOBAL#institution': 'Boston University', 'y#standard_name': 'projection_y_coordinate', 'NETCDF_DIM_time_VALUES': '1461511597', 'NC_GLOBAL#product_version': '2.0.0', 'y#long_name': 'y coordinate of projection', 'NC_GLOBAL#project': 'BU', 'crs#crs_wkt': 'PROJCS["NAD83 / Conus Albers",GEOGCS["NAD83",DATUM["North_American_Datum_1983",SPHEROID["GRS 1980",6378137,298.257222101,AUTHORITY["EPSG","7019"]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY["EPSG","6269"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4269"]],PROJECTION["Albers_Conic_Equal_Area"],PARAMETER["standard_parallel_1",29.5],PARAMETER["standard_parallel_2",45.5],PARAMETER["latitude_of_center",23],PARAMETER["longitude_of_center",-96],PARAMETER["false_easting",0],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["X",EAST],AXIS["Y",NORTH],AUTHORITY["EPSG","5070"]]', 'crs#semi_major_axis': '6378137', 'green#alias': 'band_4', 'NC_GLOBAL#Conventions': 'CF-1.6, ACDD-1.3', 'NC_GLOBAL#source': 'Surface reflectance from LEDAPS', 'NC_GLOBAL#license': 'https://creativecommons.org/licenses/by/4.0/', 'NETCDF_DIM_EXTRA': '{time}', 'crs#long_name': 'NAD83 / Conus Albers', 'NC_GLOBAL#title': 'Boston University Data Cube Landsat Surface Reflectance', 'NC_GLOBAL#keywords': 'AU/GA,NASA/GSFC/SED/ESD/LANDSAT,REFLECTANCE,ETM+,TM,OLI,EARTH SCIENCE', 'y#units': 'metre', 'time#axis': 'T', 'NC_GLOBAL#acknowledgment': 'Landsat data is provided by the United States Geological Survey (USGS).', 'NC_GLOBAL#geospatial_lat_max': '40.72351010483209', 'NC_GLOBAL#geospatial_bounds_crs': 'EPSG:4326', 'NC_GLOBAL#instrument': 'TM', 'time#long_name': 'Time, unix time-stamp', 'crs#inverse_flattening': '298.257222101', 'crs#latitude_of_projection_origin': '23', 'x#long_name': 'x coordinate of projection', 'green#long_name': 'Surface Reflectance 0.53-0.59 microns (Green)', 'NC_GLOBAL#geospatial_lon_max': '-68.9125882946302', 'NC_GLOBAL#date_created': '2016-07-13T22:24:12.505047', 'NC_GLOBAL#geospatial_lon_units': 'degrees_east', 'NC_GLOBAL#platform': 'LANDSAT-5', 'crs#grid_mapping_name': 'albers_conical_equal_area', 'NC_GLOBAL#summary': 'Landsat 8 Operational Land Imager Analysis Ready data prepared by USGS', 'crs#false_northing': '0', 'time#units': 'seconds since 1970-01-01 00:00:00', 'crs#longitude_of_central_meridian': '-96', 'NC_GLOBAL#coverage_content_type': 'physicalMeasurement', 'green#grid_mapping': 'crs', 'crs#GeoTransform': '{2100000,30,0,2250000,0,-30}', 'NC_GLOBAL#geospatial_lat_min': '39.07301919071188', 'NC_GLOBAL#processing_level': 'L2', 'crs#semi_minor_axis': '6356752.314140356', 'x#units': 'metre', 'crs#spatial_ref': 'PROJCS["NAD83 / Conus Albers",GEOGCS["NAD83",DATUM["North_American_Datum_1983",SPHEROID["GRS 1980",6378137,298.257222101,AUTHORITY["EPSG","7019"]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY["EPSG","6269"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4269"]],PROJECTION["Albers_Conic_Equal_Area"],PARAMETER["standard_parallel_1",29.5],PARAMETER["standard_parallel_2",45.5],PARAMETER["latitude_of_center",23],PARAMETER["longitude_of_center",-96],PARAMETER["false_easting",0],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["X",EAST],AXIS["Y",NORTH],AUTHORITY["EPSG","5070"]]', 'NC_GLOBAL#geospatial_lat_units': 'degrees_north', 'NC_GLOBAL#geospatial_bounds': 'POLYGON((-70.63105771584051 40.72351010483209, -71.09496888808575 39.431257108692336, -69.40465970697232 39.073019190711875, -68.9125882946302 40.35857900913365, -70.63105771584051 40.72351010483209))', 'NC_GLOBAL#geospatial_lon_min': '-71.09496888808575', 'NC_GLOBAL#cdm_data_type': 'Grid', 'NC_GLOBAL#references': 'http://dx.doi.org/10.3334/ORNLDAAC/1146', 'x#standard_name': 'projection_x_coordinate', 'NC_GLOBAL#naming_authority': 'gov.usgs', 'NETCDF_DIM_time_DEF': '{1,6}', 'NC_GLOBAL#product_suite': 'USGS Landsat'}
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{'NC_GLOBAL#history': "NetCDF-CF file created by datacube version '1.1.4' at 20160714.", 'red#_FillValue': '-9999', 'time#calendar': 'standard', 'NC_GLOBAL#title': 'Boston University Data Cube Landsat Surface Reflectance', 'crs#false_easting': '0', 'crs#standard_parallel': '{29.5,45.5}', 'time#standard_name': 'time', 'y#units': 'metre', 'NC_GLOBAL#keywords_vocabulary': 'GCMD', 'NC_GLOBAL#institution': 'Boston University', 'y#standard_name': 'projection_y_coordinate', 'NETCDF_DIM_time_VALUES': '1461511597', 'NC_GLOBAL#product_version': '2.0.0', 'y#long_name': 'y coordinate of projection', 'NC_GLOBAL#project': 'BU', 'crs#crs_wkt': 'PROJCS["NAD83 / Conus Albers",GEOGCS["NAD83",DATUM["North_American_Datum_1983",SPHEROID["GRS 1980",6378137,298.257222101,AUTHORITY["EPSG","7019"]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY["EPSG","6269"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4269"]],PROJECTION["Albers_Conic_Equal_Area"],PARAMETER["standard_parallel_1",29.5],PARAMETER["standard_parallel_2",45.5],PARAMETER["latitude_of_center",23],PARAMETER["longitude_of_center",-96],PARAMETER["false_easting",0],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["X",EAST],AXIS["Y",NORTH],AUTHORITY["EPSG","5070"]]', 'red#grid_mapping': 'crs', 'red#long_name': 'Surface Reflectance 0.64-0.67 microns (Red)', 'NC_GLOBAL#instrument': 'TM', 'crs#semi_minor_axis': '6356752.314140356', 'NC_GLOBAL#Conventions': 'CF-1.6, ACDD-1.3', 'NC_GLOBAL#source': 'Surface reflectance from LEDAPS', 'NC_GLOBAL#references': 'http://dx.doi.org/10.3334/ORNLDAAC/1146', 'NETCDF_DIM_EXTRA': '{time}', 'crs#semi_major_axis': '6378137', 'NC_GLOBAL#keywords': 'AU/GA,NASA/GSFC/SED/ESD/LANDSAT,REFLECTANCE,ETM+,TM,OLI,EARTH SCIENCE', 'red#alias': 'band_4', 'time#axis': 'T', 'NC_GLOBAL#acknowledgment': 'Landsat data is provided by the United States Geological Survey (USGS).', 'NC_GLOBAL#geospatial_lat_max': '40.72351010483209', 'NC_GLOBAL#geospatial_bounds_crs': 'EPSG:4326', 'time#long_name': 'Time, unix time-stamp', 'crs#inverse_flattening': '298.257222101', 'crs#latitude_of_projection_origin': '23', 'x#long_name': 'x coordinate of projection', 'NETCDF_DIM_time_DEF': '{1,6}', 'NC_GLOBAL#geospatial_lon_max': '-68.9125882946302', 'NC_GLOBAL#date_created': '2016-07-13T22:24:12.505047', 'NC_GLOBAL#geospatial_lon_units': 'degrees_east', 'NC_GLOBAL#platform': 'LANDSAT-5', 'crs#grid_mapping_name': 'albers_conical_equal_area', 'NC_GLOBAL#summary': 'Landsat 8 Operational Land Imager Analysis Ready data prepared by USGS', 'crs#false_northing': '0', 'time#units': 'seconds since 1970-01-01 00:00:00', 'crs#longitude_of_central_meridian': '-96', 'NC_GLOBAL#coverage_content_type': 'physicalMeasurement', 'crs#GeoTransform': '{2100000,30,0,2250000,0,-30}', 'NC_GLOBAL#geospatial_lat_min': '39.07301919071188', 'NC_GLOBAL#processing_level': 'L2', 'NC_GLOBAL#license': 'https://creativecommons.org/licenses/by/4.0/', 'x#units': 'metre', 'crs#spatial_ref': 'PROJCS["NAD83 / Conus Albers",GEOGCS["NAD83",DATUM["North_American_Datum_1983",SPHEROID["GRS 1980",6378137,298.257222101,AUTHORITY["EPSG","7019"]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY["EPSG","6269"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4269"]],PROJECTION["Albers_Conic_Equal_Area"],PARAMETER["standard_parallel_1",29.5],PARAMETER["standard_parallel_2",45.5],PARAMETER["latitude_of_center",23],PARAMETER["longitude_of_center",-96],PARAMETER["false_easting",0],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["X",EAST],AXIS["Y",NORTH],AUTHORITY["EPSG","5070"]]', 'NC_GLOBAL#geospatial_lat_units': 'degrees_north', 'NC_GLOBAL#geospatial_bounds': 'POLYGON((-70.63105771584051 40.72351010483209, -71.09496888808575 39.431257108692336, -69.40465970697232 39.073019190711875, -68.9125882946302 40.35857900913365, -70.63105771584051 40.72351010483209))', 'NC_GLOBAL#geospatial_lon_min': '-71.09496888808575', 'NC_GLOBAL#cdm_data_type': 'Grid', 'x#standard_name': 'projection_x_coordinate', 'NC_GLOBAL#naming_authority': 'gov.usgs', 'crs#long_name': 'NAD83 / Conus Albers', 'NC_GLOBAL#product_suite': 'USGS Landsat', 'red#units': '1'}
Content source: ceholden/agdc_config
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