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
2022-01-29 09:23:49	ga_ls8c_ard_3-2-1_091077_2022-01-28_final
2022-01-31 10:47:33	ga_ls8c_ard_3-2-1_105070_2022-01-31_final
2022-02-13 10:19:47	ga_ls8c_ard_3-2-1_100078_2022-02-13_final
2022-02-19 11:24:20	ga_ls8c_ard_3-2-1_110085_2022-02-19_final
2022-02-20 10:23:07	ga_ls8c_ard_3-2-1_101071_2022-02-20_final
2022-03-04 09:16:31	ga_ls8c_ard_3-2-1_089090_2022-03-03_final
2022-03-09 09:34:14	ga_ls8c_ard_3-2-1_092088_2022-03-09_final
2022-03-10 10:14:18	ga_ls8c_ard_3-2-1_099080_2022-03-10_final
2022-03-12 10:01:07	ga_ls8c_ard_3-2-1_097078_2022-03-12_final
2022-03-14 11:30:01	ga_ls8c_ard_3-2-1_111084_2022-03-14_final
2022-03-15 10:28:00	ga_ls8c_ard_3-2-1_102068_2022-03-15_final
2022-03-20 10:49:17	ga_ls8c_ard_3-2-1_105075_2022-03-20_final
2022-03-21 09:51:39	ga_ls8c_ard_3-2-1_096070_2022-03-21_final
2022-04-17 11:13:57	ga_ls8c_ard_3-2-1_109075_2022-04-17_final
2022-04-24 11:17:42	ga_ls8c_ard_3-2-1_110069_2022-04-24_final
2022-04-27 10:09:18	ga_ls8c_ard_3-2-1_099068_2022-04-27_final
2022-04-27 10:13:41	ga_ls8c_ard_3-2-1_099079_2022-04-27_final
2022-04-27 11:50:58	ga_ls8c_ard_3-2-1_115075_2022-04-27_final
2022-04-27 11:51:46	ga_ls8c_ard_3-2-1_115077_2022-04-27_final
2022-06-02 09:52:24	ga_ls8c_ard_3-2-1_095087_2022-06-02_final
2022-06-08 09:12:12	ga_ls8c_ard_3-2-1_089079_2022-06-07_final
2022-06-08 10:49:06	ga_ls8c_ard_3-2-1_105074_2022-06-08_final
2022-06-16 11:38:38	ga_ls8c_ard_3-2-1_113074_2022-06-16_final
2022-06-19 10:28:16	ga_ls8c_ard_3-2-1_102068_2022-06-19_final
2022-06-20 11:14:44	ga_ls8c_ard_3-2-1_109076_2022-06-20_final
2022-06-23 10:07:58	ga_ls8c_ard_3-2-1_098079_2022-06-23_final
2022-06-24 09:16:44	ga_ls8c_ard_3-2-1_089090_2022-06-23_final
2022-07-15 09:33:40	ga_ls8c_ard_3-2-1_092086_2022-07-15_final
2022-07-18 11:42:17	ga_ls8c_ard_3-2-1_113083_2022-07-18_final
2022-07-24 11:04:30	ga_ls8c_ard_3-2-1_107081_2022-07-24_final
2022-07-29 11:19:30	ga_ls8c_ard_3-2-1_110072_2022-07-29_final
2022-08-02 09:17:08	ga_ls8c_ard_3-2-1_090075_2022-08-01_final
2022-08-12 11:32:46	ga_ls8c_ard_3-2-1_112074_2022-08-12_final
2022-08-22 10:28:36	ga_ls8c_ard_3-2-1_102068_2022-08-22_final
2022-09-03 10:53:19	ga_ls8c_ard_3-2-1_106068_2022-09-03_final
2022-09-04 10:01:42	ga_ls8c_ard_3-2-1_097078_2022-09-04_final
2022-09-08 09:34:37	ga_ls8c_ard_3-2-1_093072_2022-09-08_final
2022-09-13 09:58:47	ga_ls8c_ard_3-2-1_096086_2022-09-13_final
2022-09-15 11:19:44	ga_ls8c_ard_3-2-1_110072_2022-09-15_final
2022-09-19 09:21:20	ga_ls8c_ard_3-2-1_090085_2022-09-18_final
2022-09-22 11:30:44	ga_ls8c_ard_3-2-1_111084_2022-09-22_final
2022-09-24 09:35:06	ga_ls8c_ard_3-2-1_093073_2022-09-24_final
2022-10-01 11:20:08	ga_ls8c_ard_3-2-1_110073_2022-10-01_final
2022-10-03 09:34:04	ga_ls8c_ard_3-2-1_092086_2022-10-03_final
2022-10-06 09:57:46	ga_ls8c_ard_3-2-1_097068_2022-10-06_final
2022-10-11 10:17:26	ga_ls8c_ard_3-2-1_100071_2022-10-11_final
2022-10-11 11:58:43	ga_ls8c_ard_3-2-1_116077_2022-10-11_final
2022-10-12 11:00:17	ga_ls8c_ard_3-2-1_107070_2022-10-12_final
2022-10-12 11:05:28	ga_ls8c_ard_3-2-1_107083_2022-10-12_final
2022-10-14 09:16:36	ga_ls8c_ard_3-2-1_089089_2022-10-13_final
2022-10-15 11:32:46	ga_ls8c_ard_3-2-1_112074_2022-10-15_final
2022-10-28 09:25:30	ga_ls8c_ard_3-2-1_091080_2022-10-27_final
2022-10-29 10:10:22	ga_ls8c_ard_3-2-1_098084_2022-10-29_final
2022-11-15 10:49:57	ga_ls8c_ard_3-2-1_105075_2022-11-15_final
2022-11-16 11:36:47	ga_ls8c_ard_3-2-1_112084_2022-11-16_final
2022-11-18 09:41:08	ga_ls8c_ard_3-2-1_094073_2022-11-18_final
2022-11-20 11:08:04	ga_ls8c_ard_3-2-1_108074_2022-11-20_final
2022-12-01 09:15:04	ga_ls8c_ard_3-2-1_089085_2022-11-30_final
2022-12-11 11:25:25	ga_ls8c_ard_3-2-1_111071_2022-12-11_final
2022-12-14 10:22:11	ga_ls8c_ard_3-2-1_100083_2022-12-14_final
2022-12-18 11:31:55	ga_ls8c_ard_3-2-1_112072_2022-12-18_final
2022-12-19 10:36:17	ga_ls8c_ard_3-2-1_103072_2022-12-19_final
2022-12-20 09:41:02	ga_ls8c_ard_3-2-1_094073_2022-12-20_final
2022-12-21 10:25:53	ga_ls8c_ard_3-2-1_101077_2022-12-21_final
2022-12-24 10:59:09	ga_ls8c_ard_3-2-1_106083_2022-12-24_final
2022-12-27 11:25:17	ga_ls8c_ard_3-2-1_111071_2022-12-27_final
2022-12-30 10:18:07	ga_ls8c_ard_3-2-1_100073_2022-12-30_final
2023-01-07 09:31:04	ga_ls8c_ard_3-2-1_092079_2023-01-07_final
2023-01-10 09:57:33	ga_ls8c_ard_3-2-1_097068_2023-01-10_final
2023-01-14 11:14:27	ga_ls8c_ard_3-2-1_109075_2023-01-14_final
2023-01-18 10:47:41	ga_ls8c_ard_3-2-1_105070_2023-01-18_final
2023-01-20 10:36:09	ga_ls8c_ard_3-2-1_103072_2023-01-20_final
2023-01-25 09:17:28	ga_ls8c_ard_3-2-1_090076_2023-01-24_final
2023-01-25 10:55:09	ga_ls8c_ard_3-2-1_106073_2023-01-25_final
2023-01-26 09:58:20	ga_ls8c_ard_3-2-1_097070_2023-01-26_final
2023-01-29 10:30:03	ga_ls8c_ard_3-2-1_102072_2023-01-29_final
2023-02-09 11:52:45	ga_ls8c_ard_3-2-1_115078_2023-02-09_final
2023-02-11 11:38:46	ga_ls8c_ard_3-2-1_113074_2023-02-11_final
2023-02-15 09:39:30	ga_ls8c_ard_3-2-1_093085_2023-02-15_final
2023-02-20 09:52:45	ga_ls8c_ard_3-2-1_096072_2023-02-20_final
2023-02-24 11:08:01	ga_ls8c_ard_3-2-1_108075_2023-02-24_final
2023-02-25 10:14:22	ga_ls8c_ard_3-2-1_099080_2023-02-25_final
2023-03-01 09:46:51	ga_ls8c_ard_3-2-1_095073_2023-03-01_final
2023-03-07 09:10:07	ga_ls8c_ard_3-2-1_089074_2023-03-06_final
2023-03-07 09:11:43	ga_ls8c_ard_3-2-1_089078_2023-03-06_final
2023-03-11 10:25:51	ga_ls8c_ard_3-2-1_101078_2023-03-11_final
2023-03-11 10:27:27	ga_ls8c_ard_3-2-1_101082_2023-03-11_final
2023-03-13 11:51:11	ga_ls8c_ard_3-2-1_115075_2023-03-13_final
2023-03-14 10:55:33	ga_ls8c_ard_3-2-1_106075_2023-03-14_final
2023-03-16 09:07:05	ga_ls8c_ard_3-2-1_088082_2023-03-15_final
2023-03-22 10:03:37	ga_ls8c_ard_3-2-1_098069_2023-03-22_final
2023-03-26 09:40:51	ga_ls8c_ard_3-2-1_094074_2023-03-26_final
2023-03-31 09:56:57	ga_ls8c_ard_3-2-1_097068_2023-03-31_final
2023-04-17 10:39:58	ga_ls8c_ard_3-2-1_104068_2023-04-17_final
2023-04-18 11:24:49	ga_ls8c_ard_3-2-1_111072_2023-04-18_final
2023-04-25 11:31:47	ga_ls8c_ard_3-2-1_112074_2023-04-25_final
2023-04-29 09:32:57	ga_ls8c_ard_3-2-1_092086_2023-04-29_final
2023-05-01 10:55:03	ga_ls8c_ard_3-2-1_106075_2023-05-01_final
2023-05-06 09:39:50	ga_ls8c_ard_3-2-1_093088_2023-05-06_final
2023-05-09 10:02:42	ga_ls8c_ard_3-2-1_098068_2023-05-09_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