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
2023-02-01 11:02:33	ga_ls8c_ard_3-2-1_107076_2023-02-01_final
2023-02-02 10:06:07	ga_ls8c_ard_3-2-1_098074_2023-02-02_final
2023-02-03 10:48:59	ga_ls8c_ard_3-2-1_105073_2023-02-03_final
2023-03-19 11:17:38	ga_ls8c_ard_3-2-1_109084_2023-03-19_final
2023-03-22 11:46:53	ga_ls8c_ard_3-2-1_114080_2023-03-22_final
2023-04-03 10:28:37	ga_ls8c_ard_3-2-1_102070_2023-04-03_final
2023-05-08 09:24:15	ga_ls8c_ard_3-2-1_091080_2023-05-07_final
2023-05-13 09:45:06	ga_ls8c_ard_3-2-1_094086_2023-05-13_final
2023-05-13 09:45:30	ga_ls8c_ard_3-2-1_094087_2023-05-13_final
2023-05-13 11:18:24	ga_ls8c_ard_3-2-1_110072_2023-05-13_final
2023-05-16 10:14:47	ga_ls8c_ard_3-2-1_099083_2023-05-16_final
2023-05-16 10:15:11	ga_ls8c_ard_3-2-1_099084_2023-05-16_final
2023-05-24 09:21:47	ga_ls8c_ard_3-2-1_091074_2023-05-23_final
2023-05-26 09:11:01	ga_ls8c_ard_3-2-1_089078_2023-05-25_final
2023-05-27 11:31:35	ga_ls8c_ard_3-2-1_112074_2023-05-27_final
2023-05-31 11:05:15	ga_ls8c_ard_3-2-1_108070_2023-05-31_final
2023-06-02 09:20:00	ga_ls8c_ard_3-2-1_090085_2023-06-01_final
2023-06-07 11:17:06	ga_ls8c_ard_3-2-1_109084_2023-06-07_final
2023-06-10 11:46:26	ga_ls8c_ard_3-2-1_114080_2023-06-10_final
2023-06-11 09:12:21	ga_ls8c_ard_3-2-1_089081_2023-06-10_final
2023-06-11 09:12:45	ga_ls8c_ard_3-2-1_089082_2023-06-10_final
2023-06-13 10:35:17	ga_ls8c_ard_3-2-1_103072_2023-06-13_final
2023-06-14 11:18:10	ga_ls8c_ard_3-2-1_110071_2023-06-14_final
2023-06-17 11:52:16	ga_ls8c_ard_3-2-1_115079_2023-06-17_final
2023-06-19 11:41:30	ga_ls8c_ard_3-2-1_113083_2023-06-19_final
2023-06-21 11:29:09	ga_ls8c_ard_3-2-1_111083_2023-06-21_final
2023-06-27 09:11:16	ga_ls8c_ard_3-2-1_089078_2023-06-26_final
2023-07-02 11:10:45	ga_ls8c_ard_3-2-1_108083_2023-07-02_final
2023-07-03 10:15:33	ga_ls8c_ard_3-2-1_099084_2023-07-03_final
2023-07-08 10:29:44	ga_ls8c_ard_3-2-1_102073_2023-07-08_final
2023-07-09 11:13:25	ga_ls8c_ard_3-2-1_109074_2023-07-09_final
2023-07-11 09:24:34	ga_ls8c_ard_3-2-1_091080_2023-07-10_final
2023-07-11 09:26:34	ga_ls8c_ard_3-2-1_091085_2023-07-10_final
2023-07-12 10:04:15	ga_ls8c_ard_3-2-1_098071_2023-07-12_final
2023-07-12 11:47:07	ga_ls8c_ard_3-2-1_114081_2023-07-12_final
2023-07-13 10:45:55	ga_ls8c_ard_3-2-1_105067_2023-07-13_final
2023-07-13 10:46:19	ga_ls8c_ard_3-2-1_105068_2023-07-13_final
2023-07-16 09:45:31	ga_ls8c_ard_3-2-1_094086_2023-07-16_final
2023-07-18 09:32:45	ga_ls8c_ard_3-2-1_092085_2023-07-18_final
2023-07-20 09:17:35	ga_ls8c_ard_3-2-1_090078_2023-07-19_final
2023-07-21 10:01:15	ga_ls8c_ard_3-2-1_097079_2023-07-21_final
2023-07-24 10:28:37	ga_ls8c_ard_3-2-1_102070_2023-07-24_final
2023-07-25 11:11:54	ga_ls8c_ard_3-2-1_109070_2023-07-25_final
2023-07-26 10:16:41	ga_ls8c_ard_3-2-1_100071_2023-07-26_final
2023-07-28 10:09:08	ga_ls8c_ard_3-2-1_098083_2023-07-28_final
2023-08-01 11:19:21	ga_ls8c_ard_3-2-1_110073_2023-08-01_final
2023-08-04 10:10:59	ga_ls8c_ard_3-2-1_099072_2023-08-04_final
2023-08-08 11:25:33	ga_ls8c_ard_3-2-1_111073_2023-08-08_final
2023-08-09 10:28:19	ga_ls8c_ard_3-2-1_102069_2023-08-09_final
2023-08-10 09:39:05	ga_ls8c_ard_3-2-1_093085_2023-08-10_final
2023-08-10 11:14:23	ga_ls8c_ard_3-2-1_109076_2023-08-10_final
2023-08-11 10:18:45	ga_ls8c_ard_3-2-1_100076_2023-08-11_final
2023-08-11 11:58:02	ga_ls8c_ard_3-2-1_116077_2023-08-11_final
2023-08-12 09:24:45	ga_ls8c_ard_3-2-1_091080_2023-08-11_final
2023-08-14 09:11:37	ga_ls8c_ard_3-2-1_089078_2023-08-13_final
2023-08-15 09:51:42	ga_ls8c_ard_3-2-1_096070_2023-08-15_final
2023-08-17 11:23:02	ga_ls8c_ard_3-2-1_110082_2023-08-17_final
2023-08-20 11:51:11	ga_ls8c_ard_3-2-1_115075_2023-08-20_final
2023-08-21 09:20:40	ga_ls8c_ard_3-2-1_090085_2023-08-20_final
2023-08-24 09:51:59	ga_ls8c_ard_3-2-1_095086_2023-08-24_final
2023-08-28 09:24:53	ga_ls8c_ard_3-2-1_091080_2023-08-27_final
2023-08-29 10:04:33	ga_ls8c_ard_3-2-1_098071_2023-08-29_final
2023-08-29 10:06:56	ga_ls8c_ard_3-2-1_098077_2023-08-29_final
2023-08-29 10:07:44	ga_ls8c_ard_3-2-1_098079_2023-08-29_final
2023-08-31 09:57:46	ga_ls8c_ard_3-2-1_096085_2023-08-31_final
2023-08-31 11:31:52	ga_ls8c_ard_3-2-1_112073_2023-08-31_final
2023-09-02 11:18:18	ga_ls8c_ard_3-2-1_110070_2023-09-02_final
2023-09-04 11:11:31	ga_ls8c_ard_3-2-1_108084_2023-09-04_final
2023-09-15 09:14:58	ga_ls8c_ard_3-2-1_089086_2023-09-14_final
2023-09-20 09:34:43	ga_ls8c_ard_3-2-1_092089_2023-09-20_final
2023-09-21 10:11:12	ga_ls8c_ard_3-2-1_099072_2023-09-21_final
2023-10-01 09:12:38	ga_ls8c_ard_3-2-1_089080_2023-09-30_final
2023-10-01 09:13:02	ga_ls8c_ard_3-2-1_089081_2023-09-30_final
2023-10-04 09:40:44	ga_ls8c_ard_3-2-1_094073_2023-10-04_final
2023-10-07 11:51:44	ga_ls8c_ard_3-2-1_115076_2023-10-07_final
2023-10-07 11:52:08	ga_ls8c_ard_3-2-1_115077_2023-10-07_final
2023-10-11 09:46:34	ga_ls8c_ard_3-2-1_095072_2023-10-11_final
2023-10-12 10:33:25	ga_ls8c_ard_3-2-1_102081_2023-10-12_final
2023-10-13 11:12:18	ga_ls8c_ard_3-2-1_109070_2023-10-13_final
2023-10-15 09:28:14	ga_ls8c_ard_3-2-1_091088_2023-10-14_final
2023-10-21 10:28:01	ga_ls8c_ard_3-2-1_101083_2023-10-21_final
2023-10-24 10:54:10	ga_ls8c_ard_3-2-1_106071_2023-10-24_final
2023-10-27 11:26:18	ga_ls8c_ard_3-2-1_111074_2023-10-27_final
2023-10-31 10:59:59	ga_ls8c_ard_3-2-1_107070_2023-10-31_final
2023-11-02 10:46:49	ga_ls8c_ard_3-2-1_105068_2023-11-02_final
2023-11-05 11:18:54	ga_ls8c_ard_3-2-1_110071_2023-11-05_final
2023-11-06 10:25:40	ga_ls8c_ard_3-2-1_101077_2023-11-06_final
2023-11-08 10:09:17	ga_ls8c_ard_3-2-1_099067_2023-11-08_final
2023-11-08 11:52:09	ga_ls8c_ard_3-2-1_115077_2023-11-08_final
2023-11-09 10:53:19	ga_ls8c_ard_3-2-1_106069_2023-11-09_final
2023-11-09 10:54:07	ga_ls8c_ard_3-2-1_106071_2023-11-09_final
2023-11-09 10:58:54	ga_ls8c_ard_3-2-1_106083_2023-11-09_final
2023-11-12 09:51:21	ga_ls8c_ard_3-2-1_095084_2023-11-12_final
2023-11-14 11:12:18	ga_ls8c_ard_3-2-1_109070_2023-11-14_final
2023-11-16 09:25:05	ga_ls8c_ard_3-2-1_091080_2023-11-15_final
2023-11-16 09:27:04	ga_ls8c_ard_3-2-1_091085_2023-11-15_final
2023-11-16 10:59:58	ga_ls8c_ard_3-2-1_107070_2023-11-16_final
2023-11-16 11:01:10	ga_ls8c_ard_3-2-1_107073_2023-11-16_final
2023-11-18 09:14:20	ga_ls8c_ard_3-2-1_089084_2023-11-17_final
2023-11-18 10:47:14	ga_ls8c_ard_3-2-1_105069_2023-11-18_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