Search ga_ls8c_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm to (exclusive):

File format (GeoTiff, NetCDF):

GQA Circular error probable (90%) from:

GQA Circular error probable (90%) to (exclusive):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

A Landsat Collection 1 Level-1 product identifier including the Collection processing levels, processing date, collection number, and collection tier category (e.g. ‘LE07_L1TP_098084_20210307_20210308_02_RT’) :

A Landsat scene ID including WRS path and row, year and day, ground station identifier and archive version number (e.g. ‘LC80900852021066LGN00’) :

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider. For Landsat region_code is a scene path row: '{:03d}{:03d}.format(path,row)' For Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share. :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2017-03-22 09:15:21	ga_ls8c_ard_3-0-0_089088_2017-03-21_final
2017-03-22 09:15:45	ga_ls8c_ard_3-0-0_089089_2017-03-21_final
2017-03-27 09:33:51	ga_ls8c_ard_3-0-0_092088_2017-03-27_final
2017-03-27 09:34:15	ga_ls8c_ard_3-0-0_092089_2017-03-27_final
2017-03-29 09:21:29	ga_ls8c_ard_3-0-0_090088_2017-03-28_final
2017-03-29 09:21:53	ga_ls8c_ard_3-0-0_090089_2017-03-28_final
2017-04-07 09:15:14	ga_ls8c_ard_3-0-0_089088_2017-04-06_final
2017-04-07 09:15:38	ga_ls8c_ard_3-0-0_089089_2017-04-06_final
2017-04-23 09:15:29	ga_ls8c_ard_3-0-0_089089_2017-04-22_final
2017-05-25 09:15:15	ga_ls8c_ard_3-0-0_089088_2017-05-24_final
2017-05-25 09:15:39	ga_ls8c_ard_3-0-0_089089_2017-05-24_final
2017-05-30 09:33:50	ga_ls8c_ard_3-0-0_092088_2017-05-30_final
2017-05-30 09:34:14	ga_ls8c_ard_3-0-0_092089_2017-05-30_final
2017-06-01 09:21:29	ga_ls8c_ard_3-0-0_090088_2017-05-31_final
2017-06-01 09:21:53	ga_ls8c_ard_3-0-0_090089_2017-05-31_final
2017-06-26 09:15:28	ga_ls8c_ard_3-0-0_089088_2017-06-25_final
2017-06-26 09:15:52	ga_ls8c_ard_3-0-0_089089_2017-06-25_final
2018-01-30 09:52:42	ga_ls8c_ard_3-0-0_095088_2018-01-30_final
2018-02-01 09:40:19	ga_ls8c_ard_3-0-0_093088_2018-02-01_final
2018-02-03 09:27:56	ga_ls8c_ard_3-0-0_091088_2018-02-02_final
2018-02-03 09:28:20	ga_ls8c_ard_3-0-0_091089_2018-02-02_final
2018-02-08 09:46:27	ga_ls8c_ard_3-0-0_094088_2018-02-08_final
2018-02-19 09:27:51	ga_ls8c_ard_3-0-0_091088_2018-02-18_final
2018-02-19 09:28:15	ga_ls8c_ard_3-0-0_091089_2018-02-18_final
2018-03-07 09:28:07	ga_ls8c_ard_3-1-0_091089_2018-03-06_final
2018-03-21 09:39:57	ga_ls8c_ard_3-0-0_093088_2018-03-21_final
2018-04-04 09:52:13	ga_ls8c_ard_3-0-0_095088_2018-04-04_final
2018-04-08 09:27:51	ga_ls8c_ard_3-0-0_091089_2018-04-07_final
2018-05-01 09:33:49	ga_ls8c_ard_3-0-0_092089_2018-05-01_final
2018-10-03 09:15:28	ga_ls8c_ard_3-0-0_089088_2018-10-02_final
2018-10-03 09:15:52	ga_ls8c_ard_3-0-0_089089_2018-10-02_final
2018-10-24 09:34:08	ga_ls8c_ard_3-0-0_092088_2018-10-24_final
2018-10-24 09:34:32	ga_ls8c_ard_3-0-0_092089_2018-10-24_final
2018-10-26 09:21:47	ga_ls8c_ard_3-0-0_090088_2018-10-25_final
2018-10-26 09:22:11	ga_ls8c_ard_3-0-0_090089_2018-10-25_final
2019-02-11 09:46:22	ga_ls8c_ard_3-0-0_094088_2019-02-11_final
2019-02-13 09:34:00	ga_ls8c_ard_3-0-0_092088_2019-02-13_final
2019-02-13 09:34:24	ga_ls8c_ard_3-0-0_092089_2019-02-13_final
2019-02-27 09:46:18	ga_ls8c_ard_3-0-0_094088_2019-02-27_final
2019-03-15 09:46:12	ga_ls8c_ard_3-1-0_094088_2019-03-15_final
2019-03-17 09:34:14	ga_ls8c_ard_3-1-0_092089_2019-03-17_final
2019-03-26 09:28:02	ga_ls8c_ard_3-1-0_091089_2019-03-25_final
2019-03-28 09:15:16	ga_ls8c_ard_3-1-0_089088_2019-03-27_final
2019-03-28 09:15:40	ga_ls8c_ard_3-1-0_089089_2019-03-27_final
2019-03-31 09:46:09	ga_ls8c_ard_3-1-0_094088_2019-03-31_final
2019-04-02 09:33:47	ga_ls8c_ard_3-1-0_092088_2019-04-02_final
2019-04-02 09:34:11	ga_ls8c_ard_3-1-0_092089_2019-04-02_final
2019-04-18 09:34:05	ga_ls8c_ard_3-1-0_092089_2019-04-18_final
2019-04-20 09:21:19	ga_ls8c_ard_3-0-0_090088_2019-04-19_final
2019-04-20 09:21:43	ga_ls8c_ard_3-0-0_090089_2019-04-19_final
2019-05-18 09:46:13	ga_ls8c_ard_3-0-0_094088_2019-05-18_final
2019-05-20 09:33:52	ga_ls8c_ard_3-0-0_092088_2019-05-20_final
2019-05-20 09:34:16	ga_ls8c_ard_3-0-0_092089_2019-05-20_final
2019-06-03 09:46:21	ga_ls8c_ard_3-0-0_094088_2019-06-03_final
2019-06-05 09:34:00	ga_ls8c_ard_3-1-0_092088_2019-06-05_final
2019-06-05 09:34:24	ga_ls8c_ard_3-0-0_092089_2019-06-05_final
2019-06-07 09:21:40	ga_ls8c_ard_3-0-0_090088_2019-06-06_final
2019-06-07 09:22:04	ga_ls8c_ard_3-0-0_090089_2019-06-06_final
2019-06-30 09:28:22	ga_ls8c_ard_3-1-0_091089_2019-06-29_final
2019-07-02 09:15:37	ga_ls8c_ard_3-1-0_089088_2019-07-01_final
2019-07-02 09:16:01	ga_ls8c_ard_3-1-0_089089_2019-07-01_final
2019-09-04 09:15:55	ga_ls8c_ard_3-1-0_089088_2019-09-03_final
2019-09-04 09:16:19	ga_ls8c_ard_3-1-0_089089_2019-09-03_final
2019-10-04 09:28:26	ga_ls8c_ard_3-1-0_091088_2019-10-03_final
2019-10-04 09:28:50	ga_ls8c_ard_3-1-0_091089_2019-10-03_final
2019-10-06 09:16:05	ga_ls8c_ard_3-1-0_089088_2019-10-05_final
2019-10-06 09:16:29	ga_ls8c_ard_3-1-0_089089_2019-10-05_final
2021-01-22 09:52:56	ga_ls8c_ard_3-2-0_095088_2021-01-22_final
2021-02-04 09:22:01	ga_ls8c_ard_3-2-0_090088_2021-02-03_final
2021-02-04 09:22:24	ga_ls8c_ard_3-2-0_090089_2021-02-03_final
2021-02-07 09:52:54	ga_ls8c_ard_3-2-0_095088_2021-02-07_final
2021-02-13 09:16:12	ga_ls8c_ard_3-2-0_089089_2021-02-12_final
2021-02-16 09:46:41	ga_ls8c_ard_3-2-0_094088_2021-02-16_final
2021-02-27 09:28:28	ga_ls8c_ard_3-2-0_091089_2021-02-26_final
2021-03-01 09:15:42	ga_ls8c_ard_3-2-0_089088_2021-02-28_final
2021-03-01 09:16:06	ga_ls8c_ard_3-2-0_089089_2021-02-28_final
2021-03-22 09:34:28	ga_ls8c_ard_3-2-0_092089_2021-03-22_final
2021-03-24 09:21:42	ga_ls8c_ard_3-2-0_090088_2021-03-23_final
2021-03-24 09:22:06	ga_ls8c_ard_3-2-0_090089_2021-03-23_final
2021-03-31 09:28:15	ga_ls8c_ard_3-2-0_091089_2021-03-30_final
2021-04-02 09:15:29	ga_ls8c_ard_3-2-0_089088_2021-04-01_final
2021-04-02 09:15:53	ga_ls8c_ard_3-2-0_089089_2021-04-01_final
2021-04-07 09:34:23	ga_ls8c_ard_3-2-0_092089_2021-04-07_final
2021-04-09 09:21:37	ga_ls8c_ard_3-2-0_090088_2021-04-08_final
2021-04-09 09:22:01	ga_ls8c_ard_3-2-0_090089_2021-04-08_final
2021-04-12 09:52:30	ga_ls8c_ard_3-2-0_095088_2021-04-12_final
2021-04-16 09:28:09	ga_ls8c_ard_3-2-0_091089_2021-04-15_final
2021-04-18 09:15:23	ga_ls8c_ard_3-2-0_089088_2021-04-17_final
2021-04-18 09:15:47	ga_ls8c_ard_3-2-0_089089_2021-04-17_final
2021-04-23 09:34:16	ga_ls8c_ard_3-2-0_092089_2021-04-23_final
2021-06-28 09:21:47	ga_ls8c_ard_3-2-0_090088_2021-06-27_final
2021-06-28 09:22:10	ga_ls8c_ard_3-2-0_090089_2021-06-27_final
2021-07-01 09:52:41	ga_ls8c_ard_3-2-0_095088_2021-07-01_final
2021-07-03 09:40:20	ga_ls8c_ard_3-2-0_093088_2021-07-03_final
2021-07-05 09:27:58	ga_ls8c_ard_3-2-0_091088_2021-07-04_final
2021-07-05 09:28:22	ga_ls8c_ard_3-2-0_091089_2021-07-04_final
2021-07-17 09:52:43	ga_ls8c_ard_3-2-0_095088_2021-07-17_final
2021-07-19 09:40:22	ga_ls8c_ard_3-2-0_093088_2021-07-19_final
2021-07-21 09:28:26	ga_ls8c_ard_3-2-0_091089_2021-07-20_final
2021-07-23 09:15:41	ga_ls8c_ard_3-2-0_089088_2021-07-22_final

Return to ga_ls8c_ard_3 whole collection overview

ga_ls8c_ard_3: Geoscience Australia Landsat 8 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years