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
2022-01-05 10:13:22	ga_ls8c_ard_3-2-1_099077_2022-01-05_final
2022-01-18 09:40:02	ga_ls8c_ard_3-2-1_094071_2022-01-18_final
2022-01-31 10:47:09	ga_ls8c_ard_3-2-1_105069_2022-01-31_final
2022-02-01 09:58:18	ga_ls8c_ard_3-2-1_096086_2022-02-01_final
2022-02-03 09:40:45	ga_ls8c_ard_3-2-1_094073_2022-02-03_final
2022-02-08 11:38:34	ga_ls8c_ard_3-2-1_113074_2022-02-08_final
2022-02-23 09:21:07	ga_ls8c_ard_3-2-1_090086_2022-02-22_final
2022-03-04 10:49:01	ga_ls8c_ard_3-2-1_105074_2022-03-04_final
2022-03-05 11:31:28	ga_ls8c_ard_3-2-1_112072_2022-03-05_final
2022-03-08 10:22:41	ga_ls8c_ard_3-2-1_101070_2022-03-08_final
2022-03-08 10:27:52	ga_ls8c_ard_3-2-1_101083_2022-03-08_final
2022-03-25 11:07:45	ga_ls8c_ard_3-2-1_108075_2022-03-25_final
2022-04-12 10:52:37	ga_ls8c_ard_3-2-1_106068_2022-04-12_final
2022-04-13 09:57:00	ga_ls8c_ard_3-2-1_097068_2022-04-13_final
2022-04-19 11:05:11	ga_ls8c_ard_3-2-1_107084_2022-04-19_final
2022-04-28 10:55:44	ga_ls8c_ard_3-2-1_106076_2022-04-28_final
2022-04-29 09:56:31	ga_ls8c_ard_3-2-1_097067_2022-04-29_final
2022-05-01 11:25:28	ga_ls8c_ard_3-2-1_111073_2022-05-01_final
2022-05-05 09:21:31	ga_ls8c_ard_3-2-1_091072_2022-05-04_final
2022-05-14 10:56:42	ga_ls8c_ard_3-2-1_106078_2022-05-14_final
2022-06-01 10:46:00	ga_ls8c_ard_3-2-1_104082_2022-06-01_final
2022-06-05 10:16:57	ga_ls8c_ard_3-2-1_100071_2022-06-05_final
2022-06-08 10:49:30	ga_ls8c_ard_3-2-1_105075_2022-06-08_final
2022-06-11 09:40:21	ga_ls8c_ard_3-2-1_094072_2022-06-11_final
2022-06-18 11:29:28	ga_ls8c_ard_3-2-1_111082_2022-06-18_final
2022-06-29 09:34:05	ga_ls8c_ard_3-2-1_092087_2022-06-29_final
2022-07-01 10:54:38	ga_ls8c_ard_3-2-1_106072_2022-07-01_final
2022-07-19 10:46:17	ga_ls8c_ard_3-2-1_104082_2022-07-19_final
2022-07-22 11:18:02	ga_ls8c_ard_3-2-1_109084_2022-07-22_final
2022-08-14 11:20:01	ga_ls8c_ard_3-2-1_110073_2022-08-14_final
2022-08-21 09:46:32	ga_ls8c_ard_3-2-1_095071_2022-08-21_final
2022-08-21 09:52:32	ga_ls8c_ard_3-2-1_095086_2022-08-21_final
2022-08-31 10:28:24	ga_ls8c_ard_3-2-1_101083_2022-08-31_final
2022-09-19 09:17:45	ga_ls8c_ard_3-2-1_090076_2022-09-18_final
2022-09-30 10:36:29	ga_ls8c_ard_3-2-1_103072_2022-09-30_final
2022-10-02 10:23:43	ga_ls8c_ard_3-2-1_101071_2022-10-02_final
2022-10-12 09:27:23	ga_ls8c_ard_3-2-1_091085_2022-10-11_final
2022-10-20 10:10:30	ga_ls8c_ard_3-2-1_099069_2022-10-20_final
2022-10-20 10:10:54	ga_ls8c_ard_3-2-1_099070_2022-10-20_final
2022-10-26 11:15:09	ga_ls8c_ard_3-2-1_109076_2022-10-26_final
2022-11-01 10:40:05	ga_ls8c_ard_3-2-1_103081_2022-11-01_final
2022-11-15 10:49:57	ga_ls8c_ard_3-2-1_105075_2022-11-15_final
2022-11-16 09:58:18	ga_ls8c_ard_3-2-1_096085_2022-11-16_final
2022-11-19 10:23:36	ga_ls8c_ard_3-2-1_101071_2022-11-19_final
2022-12-08 10:53:20	ga_ls8c_ard_3-2-1_106068_2022-12-08_final
2022-12-12 10:33:46	ga_ls8c_ard_3-2-1_102081_2022-12-12_final
2022-12-17 09:14:34	ga_ls8c_ard_3-2-1_089084_2022-12-16_final
2023-01-15 10:22:25	ga_ls8c_ard_3-2-1_100084_2023-01-15_final
2023-01-23 09:34:36	ga_ls8c_ard_3-2-1_092088_2023-01-23_final
2023-01-24 10:10:41	ga_ls8c_ard_3-2-1_099070_2023-01-24_final
2023-01-25 12:31:38	ga_ls8c_ard_3-2-1_122067_2023-01-25_final
2023-02-15 11:14:23	ga_ls8c_ard_3-2-1_109075_2023-02-15_final
2023-02-22 11:19:38	ga_ls8c_ard_3-2-1_110073_2023-02-22_final
2023-02-27 09:58:01	ga_ls8c_ard_3-2-1_097070_2023-02-27_final
2023-03-04 10:19:20	ga_ls8c_ard_3-2-1_100077_2023-03-04_final
2023-03-09 10:35:49	ga_ls8c_ard_3-2-1_103072_2023-03-09_final
2023-03-10 11:18:17	ga_ls8c_ard_3-2-1_110070_2023-03-10_final
2023-03-21 09:21:58	ga_ls8c_ard_3-2-1_091073_2023-03-20_final
2023-03-29 10:12:56	ga_ls8c_ard_3-2-1_099077_2023-03-29_final
2023-03-30 09:16:30	ga_ls8c_ard_3-2-1_090075_2023-03-29_final
2023-04-02 11:24:15	ga_ls8c_ard_3-2-1_111070_2023-04-02_final
2023-04-08 10:46:15	ga_ls8c_ard_3-2-1_105068_2023-04-08_final
2023-04-10 10:35:25	ga_ls8c_ard_3-2-1_103072_2023-04-10_final
2023-04-13 09:33:24	ga_ls8c_ard_3-2-1_092087_2023-04-13_final
2023-05-04 11:23:08	ga_ls8c_ard_3-2-1_111068_2023-05-04_final
2023-05-07 10:18:42	ga_ls8c_ard_3-2-1_100077_2023-05-07_final
2023-05-08 09:26:39	ga_ls8c_ard_3-2-1_091086_2023-05-07_final
2023-06-16 09:34:07	ga_ls8c_ard_3-2-1_092089_2023-06-16_final
2023-07-09 11:17:24	ga_ls8c_ard_3-2-1_109084_2023-07-09_final
2023-07-12 10:07:02	ga_ls8c_ard_3-2-1_098078_2023-07-12_final
2023-07-13 10:49:30	ga_ls8c_ard_3-2-1_105076_2023-07-13_final
2023-07-29 10:49:13	ga_ls8c_ard_3-2-1_105075_2023-07-29_final
2023-08-05 10:55:26	ga_ls8c_ard_3-2-1_106075_2023-08-05_final
2023-08-14 10:48:54	ga_ls8c_ard_3-2-1_105074_2023-08-14_final
2023-08-22 09:57:09	ga_ls8c_ard_3-2-1_097068_2023-08-22_final
2023-08-30 10:49:00	ga_ls8c_ard_3-2-1_105074_2023-08-30_final
2023-09-02 09:39:49	ga_ls8c_ard_3-2-1_094071_2023-09-02_final
2023-09-12 11:58:13	ga_ls8c_ard_3-2-1_116077_2023-09-12_final
2023-09-22 10:56:03	ga_ls8c_ard_3-2-1_106076_2023-09-22_final
2023-10-01 10:49:08	ga_ls8c_ard_3-2-1_105074_2023-10-01_final
2023-10-07 10:09:15	ga_ls8c_ard_3-2-1_099067_2023-10-07_final
2023-10-07 11:53:20	ga_ls8c_ard_3-2-1_115080_2023-10-07_final
2023-10-11 09:46:10	ga_ls8c_ard_3-2-1_095071_2023-10-11_final
2023-10-13 09:34:37	ga_ls8c_ard_3-2-1_093073_2023-10-13_final
2023-10-15 09:21:51	ga_ls8c_ard_3-2-1_091072_2023-10-14_final
2023-10-16 10:09:30	ga_ls8c_ard_3-2-1_098083_2023-10-16_final
2023-10-18 09:52:44	ga_ls8c_ard_3-2-1_096072_2023-10-18_final
2023-11-08 10:11:17	ga_ls8c_ard_3-2-1_099072_2023-11-08_final
2023-11-24 10:10:11	ga_ls8c_ard_3-2-1_099069_2023-11-24_final
2023-11-27 10:40:40	ga_ls8c_ard_3-2-1_104068_2023-11-27_final
2023-11-28 11:25:31	ga_ls8c_ard_3-2-1_111072_2023-11-28_final
2023-12-11 10:52:56	ga_ls8c_ard_3-2-1_106068_2023-12-11_final
2023-12-23 11:24:07	ga_ls8c_ard_3-2-1_110084_2023-12-23_final
2024-01-04 10:07:25	ga_ls8c_ard_3-2-1_098078_2024-01-04_final
2024-01-05 09:13:47	ga_ls8c_ard_3-2-1_089083_2024-01-04_final
2024-01-11 10:10:03	ga_ls8c_ard_3-2-1_099069_2024-01-11_final
2024-01-11 11:52:31	ga_ls8c_ard_3-2-1_115078_2024-01-11_final
2024-01-27 10:08:44	ga_ls8c_ard_3-2-1_099066_2024-01-27_final
2024-02-13 10:54:28	ga_ls8c_ard_3-2-1_106072_2024-02-13_final
2024-02-20 09:22:33	ga_ls8c_ard_3-2-1_091074_2024-02-19_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