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
2021-10-01 10:09:53	ga_ls8c_ard_3-2-0_099068_2021-10-01_final
2021-10-11 09:11:44	ga_ls8c_ard_3-2-0_089077_2021-10-10_final
2021-10-11 10:50:13	ga_ls8c_ard_3-2-0_105076_2021-10-11_final
2021-10-28 09:52:13	ga_ls8c_ard_3-2-0_096070_2021-10-28_final
2021-10-30 11:18:44	ga_ls8c_ard_3-2-0_110070_2021-10-30_final
2021-11-01 11:07:58	ga_ls8c_ard_3-2-0_108074_2021-11-01_final
2021-11-12 10:49:22	ga_ls8c_ard_3-2-0_105074_2021-11-12_final
2021-11-17 09:34:35	ga_ls8c_ard_3-2-0_092088_2021-11-17_final
2021-11-26 09:29:13	ga_ls8c_ard_3-2-0_091090_2021-11-25_final
2021-12-14 09:12:28	ga_ls8c_ard_3-2-1_089079_2021-12-13_final
2022-01-13 11:01:36	ga_ls8c_ard_3-2-1_107074_2022-01-13_final
2022-01-29 09:23:49	ga_ls8c_ard_3-2-1_091077_2022-01-28_final
2022-01-30 11:47:33	ga_ls8c_ard_3-2-1_114081_2022-01-30_final
2022-02-06 11:53:20	ga_ls8c_ard_3-2-1_115080_2022-02-06_final
2022-02-11 10:29:22	ga_ls8c_ard_3-2-1_102071_2022-02-11_final
2022-02-13 10:19:47	ga_ls8c_ard_3-2-1_100078_2022-02-13_final
2022-02-15 10:03:01	ga_ls8c_ard_3-2-1_098067_2022-02-15_final
2022-02-15 11:47:30	ga_ls8c_ard_3-2-1_114081_2022-02-15_final
2022-02-20 10:27:30	ga_ls8c_ard_3-2-1_101082_2022-02-20_final
2022-03-01 11:58:12	ga_ls8c_ard_3-2-1_116077_2022-03-01_final
2022-03-10 10:11:06	ga_ls8c_ard_3-2-1_099072_2022-03-10_final
2022-03-27 09:22:04	ga_ls8c_ard_3-2-1_090089_2022-03-26_final
2022-04-01 09:34:11	ga_ls8c_ard_3-2-1_093073_2022-04-01_final
2022-04-06 11:32:02	ga_ls8c_ard_3-2-1_112074_2022-04-06_final
2022-04-12 10:57:48	ga_ls8c_ard_3-2-1_106081_2022-04-12_final
2022-04-13 09:56:36	ga_ls8c_ard_3-2-1_097067_2022-04-13_final
2022-04-27 10:08:54	ga_ls8c_ard_3-2-1_099067_2022-04-27_final
2022-05-02 10:28:16	ga_ls8c_ard_3-2-1_102069_2022-05-02_final
2022-05-03 09:35:27	ga_ls8c_ard_3-2-1_093076_2022-05-03_final
2022-05-28 09:32:58	ga_ls8c_ard_3-2-1_092085_2022-05-28_final
2022-06-06 11:05:01	ga_ls8c_ard_3-2-1_107083_2022-06-06_final
2022-06-17 09:07:43	ga_ls8c_ard_3-2-1_088083_2022-06-16_final
2022-06-20 09:39:50	ga_ls8c_ard_3-2-1_093086_2022-06-20_final
2022-06-22 11:02:23	ga_ls8c_ard_3-2-1_107076_2022-06-22_final
2022-06-23 10:03:34	ga_ls8c_ard_3-2-1_098068_2022-06-23_final
2022-06-24 10:49:38	ga_ls8c_ard_3-2-1_105075_2022-06-24_final
2022-06-26 10:39:40	ga_ls8c_ard_3-2-1_103081_2022-06-26_final
2022-07-09 10:03:11	ga_ls8c_ard_3-2-1_098067_2022-07-09_final
2022-07-16 11:52:37	ga_ls8c_ard_3-2-1_115078_2022-07-16_final
2022-07-17 09:17:44	ga_ls8c_ard_3-2-1_090077_2022-07-16_final
2022-07-17 09:22:55	ga_ls8c_ard_3-2-1_090090_2022-07-16_final
2022-07-22 11:16:02	ga_ls8c_ard_3-2-1_109079_2022-07-22_final
2022-07-24 11:04:30	ga_ls8c_ard_3-2-1_107081_2022-07-24_final
2022-07-25 10:04:54	ga_ls8c_ard_3-2-1_098071_2022-07-25_final
2022-07-29 11:24:17	ga_ls8c_ard_3-2-1_110084_2022-07-29_final
2022-08-11 09:14:37	ga_ls8c_ard_3-2-1_089084_2022-08-10_final
2022-08-25 09:23:49	ga_ls8c_ard_3-2-1_091076_2022-08-24_final
2022-09-17 09:34:05	ga_ls8c_ard_3-2-1_092086_2022-09-17_final
2022-09-23 10:33:54	ga_ls8c_ard_3-2-1_102081_2022-09-23_final
2022-09-28 10:50:27	ga_ls8c_ard_3-2-1_105076_2022-09-28_final
2022-09-30 10:40:05	ga_ls8c_ard_3-2-1_103081_2022-09-30_final
2022-10-07 10:43:01	ga_ls8c_ard_3-2-1_104073_2022-10-07_final
2022-10-09 10:29:02	ga_ls8c_ard_3-2-1_102069_2022-10-09_final
2022-10-10 09:40:11	ga_ls8c_ard_3-2-1_093086_2022-10-10_final
2022-10-18 10:25:14	ga_ls8c_ard_3-2-1_101075_2022-10-18_final
2022-10-21 10:53:46	ga_ls8c_ard_3-2-1_106069_2022-10-21_final
2022-10-22 11:42:14	ga_ls8c_ard_3-2-1_113082_2022-10-22_final
2022-10-28 09:27:30	ga_ls8c_ard_3-2-1_091085_2022-10-27_final
2022-10-30 09:13:33	ga_ls8c_ard_3-2-1_089081_2022-10-29_final
2022-11-02 09:44:52	ga_ls8c_ard_3-2-1_094082_2022-11-02_final
2022-11-05 10:11:46	ga_ls8c_ard_3-2-1_099072_2022-11-05_final
2022-11-07 11:38:17	ga_ls8c_ard_3-2-1_113072_2022-11-07_final
2022-11-09 11:25:54	ga_ls8c_ard_3-2-1_111072_2022-11-09_final
2022-11-15 09:12:40	ga_ls8c_ard_3-2-1_089079_2022-11-14_final
2022-11-30 10:10:42	ga_ls8c_ard_3-2-1_098085_2022-11-30_final
2022-12-07 10:16:28	ga_ls8c_ard_3-2-1_099084_2022-12-07_final
2022-12-11 11:25:25	ga_ls8c_ard_3-2-1_111071_2022-12-11_final
2023-01-10 10:03:08	ga_ls8c_ard_3-2-1_097082_2023-01-10_final
2023-01-12 11:26:27	ga_ls8c_ard_3-2-1_111074_2023-01-12_final
2023-01-21 11:19:50	ga_ls8c_ard_3-2-1_110073_2023-01-21_final
2023-01-22 10:25:49	ga_ls8c_ard_3-2-1_101077_2023-01-22_final
2023-01-23 09:32:36	ga_ls8c_ard_3-2-1_092083_2023-01-23_final
2023-02-03 09:12:30	ga_ls8c_ard_3-2-1_089079_2023-02-02_final
2023-02-03 09:13:42	ga_ls8c_ard_3-2-1_089082_2023-02-02_final
2023-02-10 09:21:49	ga_ls8c_ard_3-2-1_090087_2023-02-09_final
2023-02-22 11:20:26	ga_ls8c_ard_3-2-1_110075_2023-02-22_final
2023-02-27 11:40:54	ga_ls8c_ard_3-2-1_113080_2023-02-27_final
2023-03-01 09:46:51	ga_ls8c_ard_3-2-1_095073_2023-03-01_final
2023-03-14 10:55:33	ga_ls8c_ard_3-2-1_106075_2023-03-14_final
2023-03-17 11:28:49	ga_ls8c_ard_3-2-1_111081_2023-03-17_final
2023-03-19 11:14:26	ga_ls8c_ard_3-2-1_109076_2023-03-19_final
2023-03-20 10:21:36	ga_ls8c_ard_3-2-1_100083_2023-03-20_final
2023-03-26 11:18:56	ga_ls8c_ard_3-2-1_110072_2023-03-26_final
2023-04-05 10:17:00	ga_ls8c_ard_3-2-1_100072_2023-04-05_final
2023-05-09 10:08:41	ga_ls8c_ard_3-2-1_098083_2023-05-09_final
2023-05-10 10:48:20	ga_ls8c_ard_3-2-1_105074_2023-05-10_final
2023-06-05 09:46:57	ga_ls8c_ard_3-2-1_095075_2023-06-05_final
2023-06-09 09:27:05	ga_ls8c_ard_3-2-1_091087_2023-06-08_final
2023-06-11 09:15:32	ga_ls8c_ard_3-2-1_089089_2023-06-10_final
2023-06-23 11:13:12	ga_ls8c_ard_3-2-1_109074_2023-06-23_final
2023-07-06 09:06:24	ga_ls8c_ard_3-2-1_088081_2023-07-05_final
2023-07-06 10:42:53	ga_ls8c_ard_3-2-1_104075_2023-07-06_final
2023-07-15 10:39:32	ga_ls8c_ard_3-2-1_103082_2023-07-15_final
2023-07-20 10:55:17	ga_ls8c_ard_3-2-1_106075_2023-07-20_final
2023-07-21 11:37:21	ga_ls8c_ard_3-2-1_113072_2023-07-21_final
2023-07-22 09:06:03	ga_ls8c_ard_3-2-1_088080_2023-07-21_final
2023-07-30 11:31:18	ga_ls8c_ard_3-2-1_112072_2023-07-30_final
2023-08-22 11:37:38	ga_ls8c_ard_3-2-1_113072_2023-08-22_final
2023-08-22 11:38:26	ga_ls8c_ard_3-2-1_113074_2023-08-22_final
2023-09-05 11:52:22	ga_ls8c_ard_3-2-1_115078_2023-09-05_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years