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
2021-10-05 11:25:40	ga_ls8c_ard_3-2-0_111072_2021-10-05_final
2021-11-10 09:22:04	ga_ls8c_ard_3-2-0_091072_2021-11-09_final
2021-11-12 10:49:46	ga_ls8c_ard_3-2-0_105075_2021-11-12_final
2021-11-19 09:21:01	ga_ls8c_ard_3-2-0_090085_2021-11-18_final
2021-12-18 10:23:01	ga_ls8c_ard_3-2-1_101070_2021-12-18_final
2021-12-24 11:26:23	ga_ls8c_ard_3-2-1_111074_2021-12-24_final
2021-12-27 11:58:52	ga_ls8c_ard_3-2-1_116078_2021-12-27_final
2021-12-29 11:47:41	ga_ls8c_ard_3-2-1_114081_2021-12-29_final
2021-12-30 09:16:46	ga_ls8c_ard_3-2-1_089090_2021-12-29_final
2022-01-23 10:03:20	ga_ls8c_ard_3-2-1_097083_2022-01-23_final
2022-02-08 09:58:53	ga_ls8c_ard_3-2-1_097072_2022-02-08_final
2022-02-12 09:35:20	ga_ls8c_ard_3-2-1_093075_2022-02-12_final
2022-02-14 09:23:46	ga_ls8c_ard_3-2-1_091077_2022-02-13_final
2022-02-14 09:26:33	ga_ls8c_ard_3-2-1_091084_2022-02-13_final
2022-02-21 11:07:10	ga_ls8c_ard_3-2-1_108073_2022-02-21_final
2022-02-24 11:37:41	ga_ls8c_ard_3-2-1_113072_2022-02-24_final
2022-03-11 09:22:39	ga_ls8c_ard_3-2-1_090090_2022-03-10_final
2022-04-08 11:18:54	ga_ls8c_ard_3-2-1_110072_2022-04-08_final
2022-04-11 11:52:13	ga_ls8c_ard_3-2-1_115078_2022-04-11_final
2022-04-18 10:18:44	ga_ls8c_ard_3-2-1_100076_2022-04-18_final
2022-05-02 10:28:16	ga_ls8c_ard_3-2-1_102069_2022-05-02_final
2022-05-13 11:52:43	ga_ls8c_ard_3-2-1_115079_2022-05-13_final
2022-05-14 09:18:13	ga_ls8c_ard_3-2-1_090079_2022-05-13_final
2022-05-15 11:41:10	ga_ls8c_ard_3-2-1_113081_2022-05-15_final
2022-05-22 10:07:17	ga_ls8c_ard_3-2-1_098078_2022-05-22_final
2022-05-26 11:19:50	ga_ls8c_ard_3-2-1_110074_2022-05-26_final
2022-06-20 09:39:50	ga_ls8c_ard_3-2-1_093086_2022-06-20_final
2022-06-20 11:17:55	ga_ls8c_ard_3-2-1_109084_2022-06-20_final
2022-07-09 10:07:35	ga_ls8c_ard_3-2-1_098078_2022-07-09_final
2022-07-17 09:16:56	ga_ls8c_ard_3-2-1_090075_2022-07-16_final
2022-07-25 10:04:30	ga_ls8c_ard_3-2-1_098070_2022-07-25_final
2022-08-18 10:53:19	ga_ls8c_ard_3-2-1_106068_2022-08-18_final
2022-08-18 10:53:43	ga_ls8c_ard_3-2-1_106069_2022-08-18_final
2022-08-19 09:57:18	ga_ls8c_ard_3-2-1_097067_2022-08-19_final
2022-08-30 11:19:38	ga_ls8c_ard_3-2-1_110072_2022-08-30_final
2022-09-03 09:21:37	ga_ls8c_ard_3-2-1_090086_2022-09-02_final
2022-09-09 10:21:53	ga_ls8c_ard_3-2-1_100082_2022-09-09_final
2022-09-10 09:23:05	ga_ls8c_ard_3-2-1_091074_2022-09-09_final
2022-09-18 10:15:45	ga_ls8c_ard_3-2-1_099082_2022-09-18_final
2022-09-20 11:39:06	ga_ls8c_ard_3-2-1_113074_2022-09-20_final
2022-09-22 11:30:44	ga_ls8c_ard_3-2-1_111084_2022-09-22_final
2022-09-26 09:27:31	ga_ls8c_ard_3-2-1_091085_2022-09-25_final
2022-10-04 10:16:08	ga_ls8c_ard_3-2-1_099083_2022-10-04_final
2022-10-28 11:05:35	ga_ls8c_ard_3-2-1_107083_2022-10-28_final
2022-10-31 11:32:55	ga_ls8c_ard_3-2-1_112074_2022-10-31_final
2022-11-03 10:26:07	ga_ls8c_ard_3-2-1_101077_2022-11-03_final
2022-11-07 11:39:05	ga_ls8c_ard_3-2-1_113074_2022-11-07_final
2022-11-07 11:41:52	ga_ls8c_ard_3-2-1_113081_2022-11-07_final
2022-11-14 10:03:31	ga_ls8c_ard_3-2-1_098067_2022-11-14_final
2022-11-21 11:51:20	ga_ls8c_ard_3-2-1_115074_2022-11-21_final
2022-12-04 09:44:46	ga_ls8c_ard_3-2-1_094082_2022-12-04_final
2022-12-22 11:09:55	ga_ls8c_ard_3-2-1_108079_2022-12-22_final
2022-12-24 09:21:28	ga_ls8c_ard_3-2-1_090086_2022-12-23_final
2023-01-18 10:46:29	ga_ls8c_ard_3-2-1_105067_2023-01-18_final
2023-01-26 11:38:49	ga_ls8c_ard_3-2-1_113074_2023-01-26_final
2023-01-31 10:18:05	ga_ls8c_ard_3-2-1_100073_2023-01-31_final
2023-02-03 09:16:29	ga_ls8c_ard_3-2-1_089089_2023-02-02_final
2023-02-23 10:23:11	ga_ls8c_ard_3-2-1_101071_2023-02-23_final
2023-03-06 11:47:26	ga_ls8c_ard_3-2-1_114081_2023-03-06_final
2023-03-09 10:35:01	ga_ls8c_ard_3-2-1_103070_2023-03-09_final
2023-03-22 10:07:12	ga_ls8c_ard_3-2-1_098078_2023-03-22_final
2023-04-05 10:18:36	ga_ls8c_ard_3-2-1_100076_2023-04-05_final
2023-04-09 11:31:52	ga_ls8c_ard_3-2-1_112074_2023-04-09_final
2023-05-07 10:21:29	ga_ls8c_ard_3-2-1_100084_2023-05-07_final
2023-05-13 11:22:47	ga_ls8c_ard_3-2-1_110083_2023-05-13_final
2023-05-17 09:20:45	ga_ls8c_ard_3-2-1_090087_2023-05-16_final
2023-05-23 10:16:12	ga_ls8c_ard_3-2-1_100071_2023-05-23_final
2023-05-24 10:59:04	ga_ls8c_ard_3-2-1_107070_2023-05-24_final
2023-05-31 11:10:03	ga_ls8c_ard_3-2-1_108082_2023-05-31_final
2023-06-02 09:21:36	ga_ls8c_ard_3-2-1_090089_2023-06-01_final
2023-06-10 11:44:03	ga_ls8c_ard_3-2-1_114074_2023-06-10_final
2023-06-12 09:57:37	ga_ls8c_ard_3-2-1_096086_2023-06-12_final
2023-06-17 10:09:00	ga_ls8c_ard_3-2-1_099068_2023-06-17_final
2023-06-19 10:03:25	ga_ls8c_ard_3-2-1_097085_2023-06-19_final
2023-07-13 10:46:19	ga_ls8c_ard_3-2-1_105068_2023-07-13_final
2023-07-28 10:03:33	ga_ls8c_ard_3-2-1_098069_2023-07-28_final
2023-08-03 09:32:54	ga_ls8c_ard_3-2-1_092085_2023-08-03_final
2023-08-04 10:09:23	ga_ls8c_ard_3-2-1_099068_2023-08-04_final
2023-08-05 10:55:26	ga_ls8c_ard_3-2-1_106075_2023-08-05_final
2023-08-10 09:33:30	ga_ls8c_ard_3-2-1_093071_2023-08-10_final
2023-08-12 11:01:14	ga_ls8c_ard_3-2-1_107074_2023-08-12_final
2023-08-14 10:49:18	ga_ls8c_ard_3-2-1_105075_2023-08-14_final
2023-09-02 11:23:53	ga_ls8c_ard_3-2-1_110084_2023-09-02_final
2023-09-16 09:57:26	ga_ls8c_ard_3-2-1_096084_2023-09-16_final
2023-09-18 09:45:29	ga_ls8c_ard_3-2-1_094085_2023-09-18_final
2023-10-20 11:19:38	ga_ls8c_ard_3-2-1_110073_2023-10-20_final
2023-10-24 09:21:40	ga_ls8c_ard_3-2-1_090087_2023-10-23_final
2023-11-01 10:03:10	ga_ls8c_ard_3-2-1_098067_2023-11-01_final
2023-12-27 10:56:10	ga_ls8c_ard_3-2-1_106076_2023-12-27_final
2024-01-10 09:29:58	ga_ls8c_ard_3-2-1_092077_2024-01-09_final
2024-01-11 10:08:51	ga_ls8c_ard_3-2-1_099066_2024-01-11_final
2024-01-12 10:55:18	ga_ls8c_ard_3-2-1_106074_2024-01-12_final
2024-01-16 10:29:23	ga_ls8c_ard_3-2-1_102071_2024-01-16_final
2024-01-17 09:35:22	ga_ls8c_ard_3-2-1_093075_2024-01-17_final
2024-01-18 11:57:30	ga_ls8c_ard_3-2-1_116075_2024-01-18_final
2024-01-18 11:57:54	ga_ls8c_ard_3-2-1_116076_2024-01-18_final
2024-01-21 10:50:17	ga_ls8c_ard_3-2-1_105077_2024-01-21_final
2024-01-25 10:23:07	ga_ls8c_ard_3-2-1_101071_2024-01-25_final
2024-02-01 10:28:32	ga_ls8c_ard_3-2-1_102069_2024-02-01_final
2024-02-05 10:03:03	ga_ls8c_ard_3-2-1_098067_2024-02-05_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years