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
2022-07-29 11:18:18	ga_ls8c_ard_3-2-1_110069_2022-07-29_final
2022-08-11 09:14:13	ga_ls8c_ard_3-2-1_089083_2022-08-10_final
2022-08-14 11:20:49	ga_ls8c_ard_3-2-1_110075_2022-08-14_final
2022-08-17 10:14:27	ga_ls8c_ard_3-2-1_099079_2022-08-17_final
2022-09-02 10:10:51	ga_ls8c_ard_3-2-1_099070_2022-09-02_final
2022-09-06 09:46:34	ga_ls8c_ard_3-2-1_095071_2022-09-06_final
2022-09-06 09:47:22	ga_ls8c_ard_3-2-1_095073_2022-09-06_final
2022-09-06 09:52:33	ga_ls8c_ard_3-2-1_095086_2022-09-06_final
2022-09-06 11:30:38	ga_ls8c_ard_3-2-1_111084_2022-09-06_final
2022-09-10 11:00:22	ga_ls8c_ard_3-2-1_107070_2022-09-10_final
2022-09-11 10:10:20	ga_ls8c_ard_3-2-1_098084_2022-09-11_final
2022-09-20 09:57:25	ga_ls8c_ard_3-2-1_097067_2022-09-20_final
2022-09-22 11:29:56	ga_ls8c_ard_3-2-1_111082_2022-09-22_final
2022-09-24 11:14:46	ga_ls8c_ard_3-2-1_109075_2022-09-24_final
2022-09-25 10:21:57	ga_ls8c_ard_3-2-1_100082_2022-09-25_final
2022-09-27 10:07:59	ga_ls8c_ard_3-2-1_098078_2022-09-27_final
2022-09-28 09:16:45	ga_ls8c_ard_3-2-1_089089_2022-09-27_final
2022-09-28 10:47:39	ga_ls8c_ard_3-2-1_105069_2022-09-28_final
2022-10-08 11:26:16	ga_ls8c_ard_3-2-1_111073_2022-10-08_final
2022-10-12 11:00:17	ga_ls8c_ard_3-2-1_107070_2022-10-12_final
2022-10-14 09:12:12	ga_ls8c_ard_3-2-1_089078_2022-10-13_final
2022-10-15 11:36:46	ga_ls8c_ard_3-2-1_112084_2022-10-15_final
2022-10-20 10:11:18	ga_ls8c_ard_3-2-1_099071_2022-10-20_final
2022-10-22 09:58:09	ga_ls8c_ard_3-2-1_097069_2022-10-22_final
2022-10-24 09:51:00	ga_ls8c_ard_3-2-1_095082_2022-10-24_final
2022-10-27 10:21:55	ga_ls8c_ard_3-2-1_100082_2022-10-27_final
2022-10-30 10:47:15	ga_ls8c_ard_3-2-1_105068_2022-10-30_final
2022-11-06 09:21:20	ga_ls8c_ard_3-2-1_090085_2022-11-05_final
2022-11-15 10:49:33	ga_ls8c_ard_3-2-1_105074_2022-11-15_final
2022-11-23 09:57:19	ga_ls8c_ard_3-2-1_097067_2022-11-23_final
2022-11-30 11:45:11	ga_ls8c_ard_3-2-1_114074_2022-11-30_final
2022-12-05 10:24:03	ga_ls8c_ard_3-2-1_101072_2022-12-05_final
2022-12-06 11:08:06	ga_ls8c_ard_3-2-1_108074_2022-12-06_final
2022-12-07 10:14:04	ga_ls8c_ard_3-2-1_099078_2022-12-07_final
2022-12-08 10:53:44	ga_ls8c_ard_3-2-1_106069_2022-12-08_final
2022-12-08 10:54:08	ga_ls8c_ard_3-2-1_106070_2022-12-08_final
2022-12-15 09:27:21	ga_ls8c_ard_3-2-1_091085_2022-12-14_final
2022-12-19 10:36:17	ga_ls8c_ard_3-2-1_103072_2022-12-19_final
2022-12-22 09:32:14	ga_ls8c_ard_3-2-1_092082_2022-12-22_final
2022-12-26 10:46:25	ga_ls8c_ard_3-2-1_104082_2022-12-26_final
2022-12-28 10:29:16	ga_ls8c_ard_3-2-1_102070_2022-12-28_final
2022-12-29 09:40:50	ga_ls8c_ard_3-2-1_093088_2022-12-29_final
2023-01-07 09:31:04	ga_ls8c_ard_3-2-1_092079_2023-01-07_final
2023-01-15 10:19:13	ga_ls8c_ard_3-2-1_100076_2023-01-15_final
2023-01-18 09:16:23	ga_ls8c_ard_3-2-1_089089_2023-01-17_final
2023-01-19 11:36:33	ga_ls8c_ard_3-2-1_112084_2023-01-19_final
2023-01-25 10:56:45	ga_ls8c_ard_3-2-1_106077_2023-01-25_final
2023-01-30 09:39:13	ga_ls8c_ard_3-2-1_093084_2023-01-30_final
2023-02-04 09:52:34	ga_ls8c_ard_3-2-1_096071_2023-02-04_final
2023-02-10 09:21:49	ga_ls8c_ard_3-2-1_090087_2023-02-09_final
2023-02-13 11:26:22	ga_ls8c_ard_3-2-1_111074_2023-02-13_final
2023-02-27 11:38:30	ga_ls8c_ard_3-2-1_113074_2023-02-27_final
2023-02-28 09:06:24	ga_ls8c_ard_3-2-1_088080_2023-02-27_final
2023-03-03 11:13:46	ga_ls8c_ard_3-2-1_109074_2023-03-03_final
2023-03-23 09:12:22	ga_ls8c_ard_3-2-1_089080_2023-03-22_final
2023-04-04 09:33:22	ga_ls8c_ard_3-2-1_093071_2023-04-04_final
2023-04-16 11:41:35	ga_ls8c_ard_3-2-1_113083_2023-04-16_final
2023-04-24 09:12:26	ga_ls8c_ard_3-2-1_089081_2023-04-23_final
2023-04-28 10:27:22	ga_ls8c_ard_3-2-1_101083_2023-04-28_final
2023-04-29 09:33:21	ga_ls8c_ard_3-2-1_092087_2023-04-29_final
2023-04-29 09:34:08	ga_ls8c_ard_3-2-1_092089_2023-04-29_final
2023-04-30 10:09:01	ga_ls8c_ard_3-2-1_099068_2023-04-30_final
2023-05-02 10:01:01	ga_ls8c_ard_3-2-1_097079_2023-05-02_final
2023-05-04 09:51:26	ga_ls8c_ard_3-2-1_095086_2023-05-04_final
2023-05-07 11:57:59	ga_ls8c_ard_3-2-1_116078_2023-05-07_final
2023-05-16 10:08:48	ga_ls8c_ard_3-2-1_099068_2023-05-16_final
2023-05-23 11:57:05	ga_ls8c_ard_3-2-1_116076_2023-05-23_final
2023-05-24 09:27:46	ga_ls8c_ard_3-2-1_091089_2023-05-23_final
2023-05-30 10:24:47	ga_ls8c_ard_3-2-1_101077_2023-05-30_final
2023-05-31 11:07:15	ga_ls8c_ard_3-2-1_108075_2023-05-31_final
2023-06-07 11:13:55	ga_ls8c_ard_3-2-1_109076_2023-06-07_final
2023-06-09 11:01:10	ga_ls8c_ard_3-2-1_107075_2023-06-09_final
2023-06-10 11:46:50	ga_ls8c_ard_3-2-1_114081_2023-06-10_final
2023-06-16 11:11:00	ga_ls8c_ard_3-2-1_108084_2023-06-16_final
2023-06-21 09:46:16	ga_ls8c_ard_3-2-1_095073_2023-06-21_final
2023-07-12 10:02:39	ga_ls8c_ard_3-2-1_098067_2023-07-12_final
2023-07-19 11:52:30	ga_ls8c_ard_3-2-1_115079_2023-07-19_final
2023-07-27 09:27:04	ga_ls8c_ard_3-2-1_091086_2023-07-26_final
2023-07-30 09:57:12	ga_ls8c_ard_3-2-1_096084_2023-07-30_final
2023-08-04 10:10:11	ga_ls8c_ard_3-2-1_099070_2023-08-04_final
2023-08-06 09:57:26	ga_ls8c_ard_3-2-1_097069_2023-08-06_final
2023-08-12 09:28:20	ga_ls8c_ard_3-2-1_091089_2023-08-11_final
2023-08-29 10:03:45	ga_ls8c_ard_3-2-1_098069_2023-08-29_final
2023-09-05 10:10:18	ga_ls8c_ard_3-2-1_099070_2023-09-05_final
2023-09-10 10:28:05	ga_ls8c_ard_3-2-1_102068_2023-09-10_final
2023-09-20 11:07:37	ga_ls8c_ard_3-2-1_108074_2023-09-20_final
2023-09-27 11:13:50	ga_ls8c_ard_3-2-1_109074_2023-09-27_final
2023-09-29 09:23:24	ga_ls8c_ard_3-2-1_091076_2023-09-28_final
2023-10-03 10:35:58	ga_ls8c_ard_3-2-1_103072_2023-10-03_final
2023-10-04 11:19:37	ga_ls8c_ard_3-2-1_110073_2023-10-04_final
2023-10-08 10:52:56	ga_ls8c_ard_3-2-1_106068_2023-10-08_final
2023-10-21 10:23:14	ga_ls8c_ard_3-2-1_101071_2023-10-21_final
2023-10-23 10:11:18	ga_ls8c_ard_3-2-1_099072_2023-10-23_final
2023-10-24 09:16:53	ga_ls8c_ard_3-2-1_090075_2023-10-23_final
2023-10-26 10:46:13	ga_ls8c_ard_3-2-1_104082_2023-10-26_final
2023-11-08 10:09:17	ga_ls8c_ard_3-2-1_099067_2023-11-08_final
2023-11-08 10:09:41	ga_ls8c_ard_3-2-1_099068_2023-11-08_final
2023-11-08 11:52:57	ga_ls8c_ard_3-2-1_115079_2023-11-08_final
2023-11-09 10:52:55	ga_ls8c_ard_3-2-1_106068_2023-11-09_final
2023-11-23 11:07:24	ga_ls8c_ard_3-2-1_108073_2023-11-23_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