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
2018-05-24 11:09:50	ga_ls8c_ard_3-0-0_109067_2018-05-24_final
2018-05-25 10:14:12	ga_ls8c_ard_3-0-0_100067_2018-05-25_final
2018-05-31 09:37:02	ga_ls8c_ard_3-0-0_094067_2018-05-31_final
2018-05-31 11:15:55	ga_ls8c_ard_3-0-0_110067_2018-05-31_final
2018-06-01 10:20:17	ga_ls8c_ard_3-0-0_101067_2018-06-01_final
2018-06-01 10:20:41	ga_ls8c_ard_3-0-0_101068_2018-06-01_final
2018-06-02 09:24:39	ga_ls8c_ard_3-0-0_092067_2018-06-01_final
2018-06-02 09:25:03	ga_ls8c_ard_3-0-0_092068_2018-06-01_final
2018-06-07 09:43:12	ga_ls8c_ard_3-0-0_095067_2018-06-07_final
2018-06-07 11:22:05	ga_ls8c_ard_3-0-0_111067_2018-06-07_final
2018-06-08 10:26:28	ga_ls8c_ard_3-0-0_102067_2018-06-08_final
2018-06-09 09:30:52	ga_ls8c_ard_3-0-0_093067_2018-06-09_final
2018-06-09 09:31:16	ga_ls8c_ard_3-0-0_093068_2018-06-09_final
2018-06-09 11:09:45	ga_ls8c_ard_3-0-0_109067_2018-06-09_final
2018-06-10 10:14:08	ga_ls8c_ard_3-0-0_100067_2018-06-10_final
2018-06-23 09:43:23	ga_ls8c_ard_3-0-0_095067_2018-06-23_final
2018-06-23 11:22:16	ga_ls8c_ard_3-0-0_111067_2018-06-23_final
2018-06-24 10:26:39	ga_ls8c_ard_3-0-0_102067_2018-06-24_final
2018-06-24 10:27:03	ga_ls8c_ard_3-0-0_102068_2018-06-24_final
2018-06-25 09:31:03	ga_ls8c_ard_3-0-0_093067_2018-06-25_final
2018-06-25 09:31:27	ga_ls8c_ard_3-0-0_093068_2018-06-25_final
2018-06-25 11:09:56	ga_ls8c_ard_3-0-0_109067_2018-06-25_final
2018-06-26 10:14:19	ga_ls8c_ard_3-0-0_100067_2018-06-26_final
2018-06-26 10:14:43	ga_ls8c_ard_3-0-0_100068_2018-06-26_final
2018-07-12 10:14:27	ga_ls8c_ard_3-0-0_100067_2018-07-12_final
2018-07-16 09:49:46	ga_ls8c_ard_3-0-0_096067_2018-07-16_final
2018-07-16 09:50:10	ga_ls8c_ard_3-0-0_096068_2018-07-16_final
2018-07-16 11:28:39	ga_ls8c_ard_3-0-0_112067_2018-07-16_final
2018-07-17 10:33:02	ga_ls8c_ard_3-0-0_103067_2018-07-17_final
2018-07-17 10:33:26	ga_ls8c_ard_3-0-0_103068_2018-07-17_final
2018-07-18 09:37:25	ga_ls8c_ard_3-0-0_094067_2018-07-18_final
2018-07-18 11:16:18	ga_ls8c_ard_3-0-0_110067_2018-07-18_final
2018-07-19 10:20:41	ga_ls8c_ard_3-0-0_101067_2018-07-19_final
2018-07-19 10:21:05	ga_ls8c_ard_3-0-0_101068_2018-07-19_final
2018-07-20 09:25:04	ga_ls8c_ard_3-0-0_092067_2018-07-19_final
2018-07-25 09:43:38	ga_ls8c_ard_3-0-0_095067_2018-07-25_final
2018-07-25 11:22:31	ga_ls8c_ard_3-0-0_111067_2018-07-25_final
2018-07-25 11:22:55	ga_ls8c_ard_3-0-0_111068_2018-07-25_final
2018-07-26 10:26:54	ga_ls8c_ard_3-0-0_102067_2018-07-26_final
2018-07-26 10:27:18	ga_ls8c_ard_3-0-0_102068_2018-07-26_final
2018-07-27 09:31:17	ga_ls8c_ard_3-0-0_093067_2018-07-27_final
2018-07-27 11:10:10	ga_ls8c_ard_3-0-0_109067_2018-07-27_final
2018-07-28 10:14:34	ga_ls8c_ard_3-0-0_100067_2018-07-28_final
2018-08-01 09:49:53	ga_ls8c_ard_3-0-0_096067_2018-08-01_final
2018-08-01 09:50:17	ga_ls8c_ard_3-0-0_096068_2018-08-01_final
2018-08-01 11:28:46	ga_ls8c_ard_3-0-0_112067_2018-08-01_final
2018-08-02 10:33:09	ga_ls8c_ard_3-0-0_103067_2018-08-02_final
2018-08-02 10:33:33	ga_ls8c_ard_3-0-0_103068_2018-08-02_final
2018-08-03 09:37:33	ga_ls8c_ard_3-0-0_094067_2018-08-03_final
2018-08-03 11:16:26	ga_ls8c_ard_3-0-0_110067_2018-08-03_final
2018-08-03 11:16:50	ga_ls8c_ard_3-0-0_110068_2018-08-03_final
2018-08-04 10:20:49	ga_ls8c_ard_3-0-0_101067_2018-08-04_final
2018-08-04 10:21:13	ga_ls8c_ard_3-0-0_101068_2018-08-04_final
2018-08-05 09:25:12	ga_ls8c_ard_3-0-0_092067_2018-08-04_final
2018-08-05 09:25:36	ga_ls8c_ard_3-0-0_092068_2018-08-04_final
2018-08-10 09:43:48	ga_ls8c_ard_3-0-0_095067_2018-08-10_final
2018-08-10 11:22:41	ga_ls8c_ard_3-0-0_111067_2018-08-10_final
2018-08-10 11:23:05	ga_ls8c_ard_3-0-0_111068_2018-08-10_final
2018-08-11 10:27:04	ga_ls8c_ard_3-0-0_102067_2018-08-11_final
2018-08-11 10:27:28	ga_ls8c_ard_3-0-0_102068_2018-08-11_final
2018-08-12 09:31:27	ga_ls8c_ard_3-0-0_093067_2018-08-12_final
2018-08-12 09:31:51	ga_ls8c_ard_3-0-0_093068_2018-08-12_final
2018-08-12 11:10:20	ga_ls8c_ard_3-0-0_109067_2018-08-12_final
2018-08-13 10:14:43	ga_ls8c_ard_3-0-0_100067_2018-08-13_final
2018-08-13 10:15:07	ga_ls8c_ard_3-0-0_100068_2018-08-13_final
2018-08-28 11:10:28	ga_ls8c_ard_3-0-0_109067_2018-08-28_final
2018-08-29 10:14:51	ga_ls8c_ard_3-0-0_100067_2018-08-29_final
2018-08-29 10:15:15	ga_ls8c_ard_3-0-0_100068_2018-08-29_final
2018-09-16 10:02:34	ga_ls8c_ard_3-0-0_098067_2018-09-16_final
2018-09-16 10:02:58	ga_ls8c_ard_3-0-0_098068_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
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
2022-08-22 10:28:12	ga_ls8c_ard_3-2-1_102067_2022-08-22_final
2022-08-22 10:28:36	ga_ls8c_ard_3-2-1_102068_2022-08-22_final
2022-10-05 10:53:00	ga_ls8c_ard_3-2-1_106067_2022-10-05_final
2022-10-05 12:31:53	ga_ls8c_ard_3-2-1_122067_2022-10-05_final
2022-10-06 09:57:22	ga_ls8c_ard_3-2-1_097067_2022-10-06_final
2022-10-09 10:28:14	ga_ls8c_ard_3-2-1_102067_2022-10-09_final
2022-10-12 10:59:29	ga_ls8c_ard_3-2-1_107068_2022-10-12_final
2022-10-12 12:37:58	ga_ls8c_ard_3-2-1_123067_2022-10-12_final
2022-10-13 10:03:27	ga_ls8c_ard_3-2-1_098067_2022-10-13_final
2022-10-13 10:03:51	ga_ls8c_ard_3-2-1_098068_2022-10-13_final
2022-10-14 10:46:42	ga_ls8c_ard_3-2-1_105067_2022-10-14_final
2022-10-16 10:34:46	ga_ls8c_ard_3-2-1_103068_2022-10-16_final
2022-10-21 10:52:58	ga_ls8c_ard_3-2-1_106067_2022-10-21_final
2022-10-21 12:31:51	ga_ls8c_ard_3-2-1_122067_2022-10-21_final
2022-10-22 09:57:22	ga_ls8c_ard_3-2-1_097067_2022-10-22_final
2022-10-28 12:38:05	ga_ls8c_ard_3-2-1_123067_2022-10-28_final
2022-10-29 10:03:35	ga_ls8c_ard_3-2-1_098067_2022-10-29_final
2022-10-30 10:46:51	ga_ls8c_ard_3-2-1_105067_2022-10-30_final
2022-10-30 10:47:15	ga_ls8c_ard_3-2-1_105068_2022-10-30_final
2022-11-05 10:09:46	ga_ls8c_ard_3-2-1_099067_2022-11-05_final
2022-11-06 10:53:02	ga_ls8c_ard_3-2-1_106067_2022-11-06_final
2022-11-06 10:53:26	ga_ls8c_ard_3-2-1_106068_2022-11-06_final
2022-11-06 12:31:55	ga_ls8c_ard_3-2-1_122067_2022-11-06_final
2022-11-07 09:57:24	ga_ls8c_ard_3-2-1_097067_2022-11-07_final
2022-11-07 09:57:48	ga_ls8c_ard_3-2-1_097068_2022-11-07_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