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
2018-06-16 11:16:01	ga_ls8c_ard_3-0-0_110067_2018-06-16_final
2018-06-17 10:20:24	ga_ls8c_ard_3-0-0_101067_2018-06-17_final
2018-06-18 09:24:47	ga_ls8c_ard_3-0-0_092067_2018-06-17_final
2018-06-30 09:49:38	ga_ls8c_ard_3-0-0_096067_2018-06-30_final
2018-06-30 11:28:31	ga_ls8c_ard_3-0-0_112067_2018-06-30_final
2018-07-01 10:32:54	ga_ls8c_ard_3-0-0_103067_2018-07-01_final
2018-07-02 09:37:17	ga_ls8c_ard_3-0-0_094067_2018-07-02_final
2018-07-02 11:16:11	ga_ls8c_ard_3-0-0_110067_2018-07-02_final
2018-07-03 10:20:34	ga_ls8c_ard_3-0-0_101067_2018-07-03_final
2018-07-04 09:24:57	ga_ls8c_ard_3-0-0_092067_2018-07-03_final
2018-08-19 09:37:41	ga_ls8c_ard_3-0-0_094067_2018-08-19_final
2018-08-19 11:16:35	ga_ls8c_ard_3-0-0_110067_2018-08-19_final
2018-08-19 11:16:58	ga_ls8c_ard_3-0-0_110068_2018-08-19_final
2018-08-20 10:20:58	ga_ls8c_ard_3-0-0_101067_2018-08-20_final
2018-08-21 09:25:21	ga_ls8c_ard_3-0-0_092067_2018-08-20_final
2018-09-16 10:02:34	ga_ls8c_ard_3-0-0_098067_2018-09-16_final
2018-09-16 11:41:28	ga_ls8c_ard_3-0-0_114067_2018-09-16_final
2018-09-17 10:45:50	ga_ls8c_ard_3-0-0_105067_2018-09-17_final
2018-09-18 09:50:13	ga_ls8c_ard_3-0-0_096067_2018-09-18_final
2018-09-18 11:29:06	ga_ls8c_ard_3-0-0_112067_2018-09-18_final
2018-09-19 10:33:29	ga_ls8c_ard_3-0-0_103067_2018-09-19_final
2018-09-19 10:33:53	ga_ls8c_ard_3-0-0_103068_2018-09-19_final
2018-09-20 09:37:52	ga_ls8c_ard_3-0-0_094067_2018-09-20_final
2018-09-20 11:16:45	ga_ls8c_ard_3-0-0_110067_2018-09-20_final
2018-09-21 10:21:08	ga_ls8c_ard_3-0-0_101067_2018-09-21_final
2018-09-22 09:25:31	ga_ls8c_ard_3-0-0_092067_2018-09-21_final
2018-11-21 09:50:31	ga_ls8c_ard_3-0-0_096067_2018-11-21_final
2018-11-21 11:29:24	ga_ls8c_ard_3-0-0_112067_2018-11-21_final
2018-11-22 10:33:47	ga_ls8c_ard_3-0-0_103067_2018-11-22_final
2018-11-22 10:34:11	ga_ls8c_ard_3-0-0_103068_2018-11-22_final
2018-11-23 09:38:10	ga_ls8c_ard_3-0-0_094067_2018-11-23_final
2018-11-23 11:17:03	ga_ls8c_ard_3-0-0_110067_2018-11-23_final
2018-11-24 10:21:25	ga_ls8c_ard_3-0-0_101067_2018-11-24_final
2018-11-25 09:25:48	ga_ls8c_ard_3-0-0_092067_2018-11-24_final
2018-12-07 09:50:29	ga_ls8c_ard_3-0-0_096067_2018-12-07_final
2018-12-07 11:29:22	ga_ls8c_ard_3-0-0_112067_2018-12-07_final
2018-12-08 10:33:45	ga_ls8c_ard_3-0-0_103067_2018-12-08_final
2018-12-09 09:38:07	ga_ls8c_ard_3-0-0_094067_2018-12-09_final
2018-12-09 11:17:00	ga_ls8c_ard_3-0-0_110067_2018-12-09_final
2018-12-10 10:21:22	ga_ls8c_ard_3-0-0_101067_2018-12-10_final
2018-12-11 09:25:45	ga_ls8c_ard_3-0-0_092067_2018-12-10_final
2018-12-16 09:44:17	ga_ls8c_ard_3-0-0_095067_2018-12-16_final
2018-12-16 11:23:10	ga_ls8c_ard_3-0-0_111067_2018-12-16_final
2018-12-17 10:27:32	ga_ls8c_ard_3-0-0_102067_2018-12-17_final
2018-12-18 09:31:55	ga_ls8c_ard_3-0-0_093067_2018-12-18_final
2018-12-18 11:10:48	ga_ls8c_ard_3-0-0_109067_2018-12-18_final
2018-12-19 10:15:11	ga_ls8c_ard_3-0-0_100067_2018-12-19_final
2018-12-23 09:50:28	ga_ls8c_ard_3-0-0_096067_2018-12-23_final
2018-12-23 11:29:21	ga_ls8c_ard_3-0-0_112067_2018-12-23_final
2018-12-24 10:33:44	ga_ls8c_ard_3-0-0_103067_2018-12-24_final
2018-12-25 09:38:06	ga_ls8c_ard_3-0-0_094067_2018-12-25_final
2018-12-25 11:16:59	ga_ls8c_ard_3-0-0_110067_2018-12-25_final
2018-12-26 10:21:22	ga_ls8c_ard_3-0-0_101067_2018-12-26_final
2018-12-27 09:25:45	ga_ls8c_ard_3-0-0_092067_2018-12-26_final
2019-01-01 09:44:17	ga_ls8c_ard_3-0-0_095067_2019-01-01_final
2019-01-01 11:23:10	ga_ls8c_ard_3-0-0_111067_2019-01-01_final
2019-01-02 10:27:32	ga_ls8c_ard_3-0-0_102067_2019-01-02_final
2019-01-03 09:31:55	ga_ls8c_ard_3-0-0_093067_2019-01-03_final
2019-01-03 11:10:48	ga_ls8c_ard_3-0-0_109067_2019-01-03_final
2019-01-04 10:15:11	ga_ls8c_ard_3-0-0_100067_2019-01-04_final
2019-01-06 10:02:49	ga_ls8c_ard_3-0-0_098067_2019-01-06_final
2019-01-06 11:41:42	ga_ls8c_ard_3-0-0_114067_2019-01-06_final
2019-01-07 10:46:04	ga_ls8c_ard_3-0-0_105067_2019-01-07_final
2019-01-08 09:50:27	ga_ls8c_ard_3-0-0_096067_2019-01-08_final
2019-01-08 11:29:20	ga_ls8c_ard_3-0-0_112067_2019-01-08_final
2019-01-09 10:33:42	ga_ls8c_ard_3-0-0_103067_2019-01-09_final
2019-01-10 09:38:05	ga_ls8c_ard_3-0-0_094067_2019-01-10_final
2019-01-10 11:16:58	ga_ls8c_ard_3-0-0_110067_2019-01-10_final
2019-01-11 10:21:20	ga_ls8c_ard_3-0-0_101067_2019-01-11_final
2019-01-12 09:25:43	ga_ls8c_ard_3-0-0_092067_2019-01-11_final
2023-07-20 10:52:05	ga_ls8c_ard_3-2-1_106067_2023-07-20_final
2023-07-20 12:30:58	ga_ls8c_ard_3-2-1_122067_2023-07-20_final
2023-07-21 09:56:28	ga_ls8c_ard_3-2-1_097067_2023-07-21_final
2023-07-27 12:37:15	ga_ls8c_ard_3-2-1_123067_2023-07-27_final
2023-07-28 10:02:45	ga_ls8c_ard_3-2-1_098067_2023-07-28_final
2023-07-28 10:03:09	ga_ls8c_ard_3-2-1_098068_2023-07-28_final
2023-08-20 10:09:06	ga_ls8c_ard_3-2-1_099067_2023-08-20_final
2023-08-20 10:09:30	ga_ls8c_ard_3-2-1_099068_2023-08-20_final
2023-08-21 10:52:22	ga_ls8c_ard_3-2-1_106067_2023-08-21_final
2023-08-21 10:52:46	ga_ls8c_ard_3-2-1_106068_2023-08-21_final
2023-08-21 12:31:15	ga_ls8c_ard_3-2-1_122067_2023-08-21_final
2023-08-22 09:56:45	ga_ls8c_ard_3-2-1_097067_2023-08-22_final
2023-08-23 10:40:01	ga_ls8c_ard_3-2-1_104067_2023-08-23_final
2023-08-25 10:27:40	ga_ls8c_ard_3-2-1_102067_2023-08-25_final
2023-08-28 10:58:58	ga_ls8c_ard_3-2-1_107068_2023-08-28_final
2023-08-28 12:37:27	ga_ls8c_ard_3-2-1_123067_2023-08-28_final
2023-08-29 10:02:57	ga_ls8c_ard_3-2-1_098067_2023-08-29_final
2023-08-29 10:03:21	ga_ls8c_ard_3-2-1_098068_2023-08-29_final
2023-08-30 10:46:13	ga_ls8c_ard_3-2-1_105067_2023-08-30_final
2023-09-01 10:34:15	ga_ls8c_ard_3-2-1_103068_2023-09-01_final
2023-09-05 10:09:06	ga_ls8c_ard_3-2-1_099067_2023-09-05_final
2023-09-06 10:52:21	ga_ls8c_ard_3-2-1_106067_2023-09-06_final
2023-09-06 12:31:14	ga_ls8c_ard_3-2-1_122067_2023-09-06_final
2023-09-08 10:40:01	ga_ls8c_ard_3-2-1_104067_2023-09-08_final
2023-09-08 10:40:24	ga_ls8c_ard_3-2-1_104068_2023-09-08_final
2023-09-15 10:46:16	ga_ls8c_ard_3-2-1_105067_2023-09-15_final
2023-09-17 10:34:19	ga_ls8c_ard_3-2-1_103068_2023-09-17_final
2023-09-26 10:27:46	ga_ls8c_ard_3-2-1_102067_2023-09-26_final
2023-09-29 12:37:35	ga_ls8c_ard_3-2-1_123067_2023-09-29_final
2023-09-30 10:03:04	ga_ls8c_ard_3-2-1_098067_2023-09-30_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