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
2023-08-08 11:25:33	ga_ls8c_ard_3-2-1_111073_2023-08-08_final
2023-08-10 09:36:41	ga_ls8c_ard_3-2-1_093079_2023-08-10_final
2023-08-10 11:12:23	ga_ls8c_ard_3-2-1_109071_2023-08-10_final
2023-08-10 11:15:34	ga_ls8c_ard_3-2-1_109079_2023-08-10_final
2023-08-11 10:21:09	ga_ls8c_ard_3-2-1_100082_2023-08-11_final
2023-08-12 11:02:50	ga_ls8c_ard_3-2-1_107078_2023-08-12_final
2023-08-13 10:03:14	ga_ls8c_ard_3-2-1_098068_2023-08-13_final
2023-08-13 11:46:54	ga_ls8c_ard_3-2-1_114080_2023-08-13_final
2023-08-14 10:46:31	ga_ls8c_ard_3-2-1_105068_2023-08-14_final
2023-08-14 10:52:06	ga_ls8c_ard_3-2-1_105082_2023-08-14_final
2023-08-18 10:27:50	ga_ls8c_ard_3-2-1_101083_2023-08-18_final
2023-08-21 09:18:16	ga_ls8c_ard_3-2-1_090079_2023-08-20_final
2023-08-23 10:46:00	ga_ls8c_ard_3-2-1_104082_2023-08-23_final
2023-08-24 11:28:28	ga_ls8c_ard_3-2-1_111080_2023-08-24_final
2023-08-24 11:28:52	ga_ls8c_ard_3-2-1_111081_2023-08-24_final
2023-08-25 10:32:03	ga_ls8c_ard_3-2-1_102078_2023-08-25_final
2023-08-25 10:32:27	ga_ls8c_ard_3-2-1_102079_2023-08-25_final
2023-08-26 11:12:08	ga_ls8c_ard_3-2-1_109070_2023-08-26_final
2023-08-29 11:46:13	ga_ls8c_ard_3-2-1_114078_2023-08-29_final
2023-08-30 09:13:19	ga_ls8c_ard_3-2-1_089082_2023-08-29_final
2023-08-31 09:55:46	ga_ls8c_ard_3-2-1_096080_2023-08-31_final
2023-09-02 11:17:54	ga_ls8c_ard_3-2-1_110069_2023-09-02_final
2023-09-03 10:25:28	ga_ls8c_ard_3-2-1_101077_2023-09-03_final
2023-09-03 10:26:16	ga_ls8c_ard_3-2-1_101079_2023-09-03_final
2023-09-04 09:30:38	ga_ls8c_ard_3-2-1_092079_2023-09-04_final
2023-09-04 09:34:38	ga_ls8c_ard_3-2-1_092089_2023-09-04_final
2023-09-04 11:08:43	ga_ls8c_ard_3-2-1_108077_2023-09-04_final
2023-09-06 10:52:45	ga_ls8c_ard_3-2-1_106068_2023-09-06_final
2023-09-06 10:53:33	ga_ls8c_ard_3-2-1_106070_2023-09-06_final
2023-09-07 09:57:08	ga_ls8c_ard_3-2-1_097068_2023-09-07_final
2023-09-09 11:28:28	ga_ls8c_ard_3-2-1_111080_2023-09-09_final
2023-09-10 10:31:40	ga_ls8c_ard_3-2-1_102077_2023-09-10_final
2023-09-11 11:12:09	ga_ls8c_ard_3-2-1_109070_2023-09-11_final
2023-09-12 10:21:43	ga_ls8c_ard_3-2-1_100083_2023-09-12_final
2023-09-14 11:45:52	ga_ls8c_ard_3-2-1_114077_2023-09-14_final
2023-09-15 09:12:10	ga_ls8c_ard_3-2-1_089079_2023-09-14_final
2023-09-20 09:29:56	ga_ls8c_ard_3-2-1_092077_2023-09-19_final
2023-09-20 11:09:37	ga_ls8c_ard_3-2-1_108079_2023-09-20_final
2023-09-21 11:50:53	ga_ls8c_ard_3-2-1_115074_2023-09-21_final
2023-09-25 11:26:35	ga_ls8c_ard_3-2-1_111075_2023-09-25_final
2023-09-25 11:28:10	ga_ls8c_ard_3-2-1_111079_2023-09-25_final
2023-09-25 11:28:34	ga_ls8c_ard_3-2-1_111080_2023-09-25_final
2023-09-27 11:12:14	ga_ls8c_ard_3-2-1_109070_2023-09-27_final
2023-09-27 11:13:02	ga_ls8c_ard_3-2-1_109072_2023-09-27_final
2023-09-27 11:14:38	ga_ls8c_ard_3-2-1_109076_2023-09-27_final
2023-09-28 10:21:49	ga_ls8c_ard_3-2-1_100083_2023-09-28_final
2023-09-29 09:24:36	ga_ls8c_ard_3-2-1_091079_2023-09-28_final
2023-09-30 11:44:45	ga_ls8c_ard_3-2-1_114074_2023-09-30_final
2023-10-01 10:52:19	ga_ls8c_ard_3-2-1_105082_2023-10-01_final
2023-10-03 10:37:10	ga_ls8c_ard_3-2-1_103075_2023-10-03_final
2023-10-03 10:37:58	ga_ls8c_ard_3-2-1_103077_2023-10-03_final
2023-10-05 10:25:36	ga_ls8c_ard_3-2-1_101077_2023-10-05_final
2023-10-06 09:27:58	ga_ls8c_ard_3-2-1_092072_2023-10-05_final
2023-10-06 11:09:39	ga_ls8c_ard_3-2-1_108079_2023-10-06_final
2023-10-08 09:17:38	ga_ls8c_ard_3-2-1_090077_2023-10-07_final
2023-10-09 09:58:07	ga_ls8c_ard_3-2-1_097070_2023-10-09_final
2023-10-09 10:01:18	ga_ls8c_ard_3-2-1_097078_2023-10-09_final
2023-10-09 10:01:42	ga_ls8c_ard_3-2-1_097079_2023-10-09_final
2023-10-09 11:39:24	ga_ls8c_ard_3-2-1_113076_2023-10-09_final
2023-10-10 10:45:46	ga_ls8c_ard_3-2-1_104081_2023-10-10_final
2023-10-11 11:28:15	ga_ls8c_ard_3-2-1_111079_2023-10-11_final
2023-10-12 10:31:50	ga_ls8c_ard_3-2-1_102077_2023-10-12_final
2023-10-13 11:12:42	ga_ls8c_ard_3-2-1_109071_2023-10-13_final
2023-10-13 11:13:06	ga_ls8c_ard_3-2-1_109072_2023-10-13_final
2023-10-13 11:13:30	ga_ls8c_ard_3-2-1_109073_2023-10-13_final
2023-10-13 11:15:53	ga_ls8c_ard_3-2-1_109079_2023-10-13_final
2023-10-15 09:24:15	ga_ls8c_ard_3-2-1_091078_2023-10-14_final
2023-10-17 09:11:52	ga_ls8c_ard_3-2-1_089078_2023-10-16_final
2023-10-17 10:52:21	ga_ls8c_ard_3-2-1_105082_2023-10-17_final
2023-10-19 10:38:47	ga_ls8c_ard_3-2-1_103079_2023-10-19_final
2023-10-20 11:21:38	ga_ls8c_ard_3-2-1_110078_2023-10-20_final
2023-10-20 11:23:14	ga_ls8c_ard_3-2-1_110082_2023-10-20_final
2023-10-22 11:07:42	ga_ls8c_ard_3-2-1_108074_2023-10-22_final
2023-10-22 11:08:30	ga_ls8c_ard_3-2-1_108076_2023-10-22_final
2023-10-22 11:10:54	ga_ls8c_ard_3-2-1_108082_2023-10-22_final
2023-10-24 10:58:34	ga_ls8c_ard_3-2-1_106082_2023-10-24_final
2023-10-25 11:39:26	ga_ls8c_ard_3-2-1_113076_2023-10-25_final
2023-10-26 09:06:32	ga_ls8c_ard_3-2-1_088080_2023-10-25_final
2023-10-27 11:26:42	ga_ls8c_ard_3-2-1_111075_2023-10-27_final
2023-10-29 09:37:03	ga_ls8c_ard_3-2-1_093079_2023-10-29_final
2023-10-29 11:13:33	ga_ls8c_ard_3-2-1_109073_2023-10-29_final
2023-10-29 11:15:32	ga_ls8c_ard_3-2-1_109078_2023-10-29_final
2023-10-29 11:15:56	ga_ls8c_ard_3-2-1_109079_2023-10-29_final
2023-10-30 10:21:31	ga_ls8c_ard_3-2-1_100082_2023-10-30_final
2023-11-02 10:47:13	ga_ls8c_ard_3-2-1_105069_2023-11-02_final
2023-11-03 09:55:59	ga_ls8c_ard_3-2-1_096080_2023-11-03_final
2023-11-05 11:20:06	ga_ls8c_ard_3-2-1_110074_2023-11-05_final
2023-11-06 10:24:52	ga_ls8c_ard_3-2-1_101075_2023-11-06_final
2023-11-06 10:25:16	ga_ls8c_ard_3-2-1_101076_2023-11-06_final
2023-11-06 10:26:28	ga_ls8c_ard_3-2-1_101079_2023-11-06_final
2023-11-07 11:07:43	ga_ls8c_ard_3-2-1_108074_2023-11-07_final
2023-11-10 11:39:22	ga_ls8c_ard_3-2-1_113076_2023-11-10_final
2023-11-12 11:25:50	ga_ls8c_ard_3-2-1_111073_2023-11-12_final
2023-11-12 11:27:50	ga_ls8c_ard_3-2-1_111078_2023-11-12_final
2023-11-14 11:12:18	ga_ls8c_ard_3-2-1_109070_2023-11-14_final
2023-11-16 11:03:34	ga_ls8c_ard_3-2-1_107079_2023-11-16_final
2023-11-17 11:46:26	ga_ls8c_ard_3-2-1_114078_2023-11-17_final
2023-11-20 10:38:52	ga_ls8c_ard_3-2-1_103079_2023-11-20_final
2023-11-21 11:22:56	ga_ls8c_ard_3-2-1_110081_2023-11-21_final
2023-11-22 10:26:31	ga_ls8c_ard_3-2-1_101079_2023-11-22_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