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
2020-01-23 08:42:33	ga_ls8c_ard_3-2-1_084082_2020-01-22_final
2020-07-01 08:42:11	ga_ls8c_ard_3-2-1_084082_2020-06-30_final
2021-03-24 12:31:05	ga_ls8c_ard_3-2-1_122067_2021-03-24_final
2022-03-11 12:31:15	ga_ls8c_ard_3-2-1_122067_2022-03-11_final
2022-04-19 11:04:23	ga_ls8c_ard_3-2-1_107082_2022-04-19_final
2022-04-22 09:57:35	ga_ls8c_ard_3-2-1_096085_2022-04-22_final
2022-04-27 10:08:30	ga_ls8c_ard_3-2-1_099066_2022-04-27_final
2022-04-28 10:58:32	ga_ls8c_ard_3-2-1_106083_2022-04-28_final
2022-05-23 10:51:44	ga_ls8c_ard_3-2-1_105081_2022-05-23_final
2022-05-26 11:19:50	ga_ls8c_ard_3-2-1_110074_2022-05-26_final
2022-05-31 10:03:56	ga_ls8c_ard_3-2-1_097085_2022-05-31_final
2022-06-02 09:52:24	ga_ls8c_ard_3-2-1_095087_2022-06-02_final
2022-06-06 11:05:01	ga_ls8c_ard_3-2-1_107083_2022-06-06_final
2022-06-13 09:31:36	ga_ls8c_ard_3-2-1_092081_2022-06-13_final
2022-06-15 09:22:04	ga_ls8c_ard_3-2-1_090088_2022-06-14_final
2022-06-17 10:45:00	ga_ls8c_ard_3-2-1_104079_2022-06-17_final
2022-06-22 11:04:47	ga_ls8c_ard_3-2-1_107082_2022-06-22_final
2022-06-23 10:10:21	ga_ls8c_ard_3-2-1_098085_2022-06-23_final
2022-06-27 11:20:09	ga_ls8c_ard_3-2-1_110074_2022-06-27_final
2022-07-05 10:28:43	ga_ls8c_ard_3-2-1_102069_2022-07-05_final
2022-07-08 11:04:48	ga_ls8c_ard_3-2-1_107082_2022-07-08_final
2022-07-24 11:02:54	ga_ls8c_ard_3-2-1_107077_2022-07-24_final
2022-07-24 11:03:18	ga_ls8c_ard_3-2-1_107078_2022-07-24_final
2022-08-02 10:58:25	ga_ls8c_ard_3-2-1_106081_2022-08-02_final
2022-08-09 09:29:21	ga_ls8c_ard_3-2-1_091090_2022-08-08_final
2022-09-03 10:58:54	ga_ls8c_ard_3-2-1_106082_2022-09-03_final
2022-09-07 10:28:38	ga_ls8c_ard_3-2-1_102068_2022-09-07_final
2022-09-18 10:16:33	ga_ls8c_ard_3-2-1_099084_2022-09-18_final
2022-10-05 10:56:35	ga_ls8c_ard_3-2-1_106076_2022-10-05_final
2022-10-10 11:14:16	ga_ls8c_ard_3-2-1_109074_2022-10-10_final
2022-10-10 11:15:04	ga_ls8c_ard_3-2-1_109076_2022-10-10_final
2022-10-21 10:58:09	ga_ls8c_ard_3-2-1_106080_2022-10-21_final
2022-11-11 11:15:07	ga_ls8c_ard_3-2-1_109076_2022-11-11_final
2022-11-18 09:41:08	ga_ls8c_ard_3-2-1_094073_2022-11-18_final
2022-11-21 10:15:39	ga_ls8c_ard_3-2-1_099082_2022-11-21_final
2022-11-22 09:21:14	ga_ls8c_ard_3-2-1_090085_2022-11-21_final
2022-11-22 10:58:07	ga_ls8c_ard_3-2-1_106080_2022-11-22_final
2022-11-27 09:37:24	ga_ls8c_ard_3-2-1_093079_2022-11-27_final
2022-12-04 09:41:11	ga_ls8c_ard_3-2-1_094073_2022-12-04_final
2022-12-05 10:28:02	ga_ls8c_ard_3-2-1_101082_2022-12-05_final
2022-12-12 10:31:23	ga_ls8c_ard_3-2-1_102075_2022-12-12_final
2022-12-22 11:10:43	ga_ls8c_ard_3-2-1_108081_2022-12-22_final
2022-12-30 10:18:07	ga_ls8c_ard_3-2-1_100073_2022-12-30_final
2023-01-02 09:13:20	ga_ls8c_ard_3-2-1_089081_2023-01-01_final
2023-01-18 10:46:29	ga_ls8c_ard_3-2-1_105067_2023-01-18_final
2023-01-20 10:39:21	ga_ls8c_ard_3-2-1_103080_2023-01-20_final
2023-01-24 10:16:16	ga_ls8c_ard_3-2-1_099084_2023-01-24_final
2023-01-29 10:28:51	ga_ls8c_ard_3-2-1_102069_2023-01-29_final
2023-01-31 10:22:29	ga_ls8c_ard_3-2-1_100084_2023-01-31_final
2023-02-02 11:47:48	ga_ls8c_ard_3-2-1_114081_2023-02-02_final
2023-02-16 10:22:21	ga_ls8c_ard_3-2-1_100084_2023-02-16_final
2023-02-28 10:45:40	ga_ls8c_ard_3-2-1_104081_2023-02-28_final
2023-03-01 09:51:39	ga_ls8c_ard_3-2-1_095085_2023-03-01_final
2023-03-03 11:14:34	ga_ls8c_ard_3-2-1_109076_2023-03-03_final
2023-03-08 09:52:34	ga_ls8c_ard_3-2-1_096072_2023-03-08_final
2023-03-11 10:22:40	ga_ls8c_ard_3-2-1_101070_2023-03-11_final
2023-03-14 10:58:45	ga_ls8c_ard_3-2-1_106083_2023-03-14_final
2023-03-16 10:45:34	ga_ls8c_ard_3-2-1_104081_2023-03-16_final
2023-04-04 09:33:22	ga_ls8c_ard_3-2-1_093071_2023-04-04_final
2023-04-04 11:14:39	ga_ls8c_ard_3-2-1_109077_2023-04-04_final
2023-04-16 10:03:30	ga_ls8c_ard_3-2-1_097085_2023-04-16_final
2023-04-27 11:19:49	ga_ls8c_ard_3-2-1_110075_2023-04-27_final
2023-05-01 10:58:15	ga_ls8c_ard_3-2-1_106083_2023-05-01_final
2023-05-03 10:45:04	ga_ls8c_ard_3-2-1_104081_2023-05-03_final
2023-05-06 11:13:32	ga_ls8c_ard_3-2-1_109075_2023-05-06_final
2023-05-20 11:24:58	ga_ls8c_ard_3-2-1_111073_2023-05-20_final
2023-05-24 11:02:16	ga_ls8c_ard_3-2-1_107078_2023-05-24_final
2023-05-27 11:31:11	ga_ls8c_ard_3-2-1_112073_2023-05-27_final
2023-06-05 11:23:27	ga_ls8c_ard_3-2-1_111069_2023-06-05_final
2023-06-09 11:01:58	ga_ls8c_ard_3-2-1_107077_2023-06-09_final
2023-06-24 08:41:54	ga_ls8c_ard_3-2-1_084082_2023-06-23_final
2023-06-25 11:02:04	ga_ls8c_ard_3-2-1_107077_2023-06-25_final
2023-06-25 11:04:04	ga_ls8c_ard_3-2-1_107082_2023-06-25_final
2023-07-05 09:56:25	ga_ls8c_ard_3-2-1_097067_2023-07-05_final
2023-07-11 11:02:15	ga_ls8c_ard_3-2-1_107077_2023-07-11_final
2023-07-11 11:02:39	ga_ls8c_ard_3-2-1_107078_2023-07-11_final
2023-07-22 10:44:32	ga_ls8c_ard_3-2-1_104079_2023-07-22_final
2023-07-25 11:13:53	ga_ls8c_ard_3-2-1_109075_2023-07-25_final
2023-08-24 09:51:59	ga_ls8c_ard_3-2-1_095086_2023-08-24_final
2023-09-12 08:42:27	ga_ls8c_ard_3-2-1_084082_2023-09-11_final
2023-09-20 09:33:07	ga_ls8c_ard_3-2-1_092085_2023-09-20_final
2023-10-16 11:47:35	ga_ls8c_ard_3-2-1_114081_2023-10-16_final
2023-10-24 10:52:58	ga_ls8c_ard_3-2-1_106068_2023-10-24_final
2023-10-28 10:33:28	ga_ls8c_ard_3-2-1_102081_2023-10-28_final
2023-11-07 09:32:25	ga_ls8c_ard_3-2-1_092083_2023-11-07_final
2023-11-25 09:21:20	ga_ls8c_ard_3-2-1_090086_2023-11-24_final
2023-11-30 11:14:20	ga_ls8c_ard_3-2-1_109075_2023-11-30_final
2023-12-04 10:51:33	ga_ls8c_ard_3-2-1_105080_2023-12-04_final
2023-12-20 09:13:08	ga_ls8c_ard_3-2-1_089081_2023-12-19_final
2024-01-02 10:17:01	ga_ls8c_ard_3-2-1_100071_2024-01-02_final
2024-01-07 10:39:07	ga_ls8c_ard_3-2-1_103080_2024-01-07_final
2024-01-14 10:45:45	ga_ls8c_ard_3-2-1_104081_2024-01-14_final
2024-01-27 11:52:48	ga_ls8c_ard_3-2-1_115079_2024-01-27_final
2024-02-13 10:54:52	ga_ls8c_ard_3-2-1_106073_2024-02-13_final
2024-03-15 10:10:33	ga_ls8c_ard_3-2-1_099071_2024-03-15_final
2024-03-16 10:55:48	ga_ls8c_ard_3-2-1_106076_2024-03-16_final
2024-03-17 10:03:45	ga_ls8c_ard_3-2-1_097085_2024-03-17_final
2024-03-18 10:45:25	ga_ls8c_ard_3-2-1_104081_2024-03-18_final
2024-03-27 10:34:39	ga_ls8c_ard_3-2-1_103070_2024-03-27_final
2024-04-04 09:51:12	ga_ls8c_ard_3-2-1_095085_2024-04-04_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