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
2022-08-24 10:21:50	ga_ls8c_ard_3-2-1_100082_2022-08-24_final
2022-08-25 09:23:25	ga_ls8c_ard_3-2-1_091075_2022-08-24_final
2022-08-25 09:29:24	ga_ls8c_ard_3-2-1_091090_2022-08-24_final
2022-09-01 11:08:28	ga_ls8c_ard_3-2-1_108075_2022-09-01_final
2022-09-02 10:10:27	ga_ls8c_ard_3-2-1_099069_2022-09-02_final
2022-09-03 09:22:49	ga_ls8c_ard_3-2-1_090089_2022-09-02_final
2022-09-04 10:04:29	ga_ls8c_ard_3-2-1_097085_2022-09-04_final
2022-09-05 10:46:34	ga_ls8c_ard_3-2-1_104082_2022-09-05_final
2022-09-07 10:29:50	ga_ls8c_ard_3-2-1_102071_2022-09-07_final
2022-09-11 10:04:45	ga_ls8c_ard_3-2-1_098070_2022-09-11_final
2022-09-12 10:52:25	ga_ls8c_ard_3-2-1_105081_2022-09-12_final
2022-09-15 09:45:39	ga_ls8c_ard_3-2-1_094084_2022-09-15_final
2022-09-15 09:46:50	ga_ls8c_ard_3-2-1_094087_2022-09-15_final
2022-09-15 11:21:20	ga_ls8c_ard_3-2-1_110076_2022-09-15_final
2022-09-15 11:23:44	ga_ls8c_ard_3-2-1_110082_2022-09-15_final
2022-09-24 09:37:53	ga_ls8c_ard_3-2-1_093080_2022-09-24_final
2022-09-24 09:39:29	ga_ls8c_ard_3-2-1_093084_2022-09-24_final
2022-10-01 09:45:39	ga_ls8c_ard_3-2-1_094084_2022-10-01_final
2022-10-01 09:46:51	ga_ls8c_ard_3-2-1_094087_2022-10-01_final
2022-10-04 11:53:25	ga_ls8c_ard_3-2-1_115079_2022-10-04_final
2022-10-06 11:41:50	ga_ls8c_ard_3-2-1_113081_2022-10-06_final
2022-10-08 09:52:34	ga_ls8c_ard_3-2-1_095086_2022-10-08_final
2022-10-12 09:23:48	ga_ls8c_ard_3-2-1_091076_2022-10-11_final
2022-10-13 11:45:07	ga_ls8c_ard_3-2-1_114074_2022-10-13_final
2022-10-15 09:53:53	ga_ls8c_ard_3-2-1_096074_2022-10-15_final
2022-10-15 09:55:05	ga_ls8c_ard_3-2-1_096077_2022-10-15_final
2022-10-15 11:36:22	ga_ls8c_ard_3-2-1_112083_2022-10-15_final
2022-10-17 09:44:45	ga_ls8c_ard_3-2-1_094082_2022-10-17_final
2022-10-17 11:23:14	ga_ls8c_ard_3-2-1_110081_2022-10-17_final
2022-10-20 10:16:29	ga_ls8c_ard_3-2-1_099084_2022-10-20_final
2022-10-21 10:54:34	ga_ls8c_ard_3-2-1_106071_2022-10-21_final
2022-10-21 10:54:58	ga_ls8c_ard_3-2-1_106072_2022-10-21_final
2022-10-21 10:58:09	ga_ls8c_ard_3-2-1_106080_2022-10-21_final
2022-10-27 10:19:08	ga_ls8c_ard_3-2-1_100075_2022-10-27_final
2022-10-28 09:24:19	ga_ls8c_ard_3-2-1_091077_2022-10-27_final
2022-10-29 10:08:22	ga_ls8c_ard_3-2-1_098079_2022-10-29_final
2022-10-29 11:45:16	ga_ls8c_ard_3-2-1_114074_2022-10-29_final
2022-10-30 09:14:21	ga_ls8c_ard_3-2-1_089083_2022-10-29_final
2022-10-30 10:48:51	ga_ls8c_ard_3-2-1_105072_2022-10-30_final
2022-11-03 10:26:07	ga_ls8c_ard_3-2-1_101077_2022-11-03_final
2022-11-06 10:55:01	ga_ls8c_ard_3-2-1_106072_2022-11-06_final
2022-11-06 10:55:25	ga_ls8c_ard_3-2-1_106073_2022-11-06_final
2022-11-09 09:47:25	ga_ls8c_ard_3-2-1_095073_2022-11-09_final
2022-11-11 09:35:50	ga_ls8c_ard_3-2-1_093075_2022-11-11_final
2022-11-11 11:17:07	ga_ls8c_ard_3-2-1_109081_2022-11-11_final
2022-11-13 11:04:20	ga_ls8c_ard_3-2-1_107080_2022-11-13_final
2022-11-14 10:07:54	ga_ls8c_ard_3-2-1_098078_2022-11-14_final
2022-11-14 10:10:42	ga_ls8c_ard_3-2-1_098085_2022-11-14_final
2022-11-15 09:12:40	ga_ls8c_ard_3-2-1_089079_2022-11-14_final
2022-11-16 09:57:31	ga_ls8c_ard_3-2-1_096083_2022-11-16_final
2022-11-16 09:58:42	ga_ls8c_ard_3-2-1_096086_2022-11-16_final
2022-11-22 10:54:31	ga_ls8c_ard_3-2-1_106071_2022-11-22_final
2022-11-24 10:42:58	ga_ls8c_ard_3-2-1_104073_2022-11-24_final
2022-11-26 10:32:13	ga_ls8c_ard_3-2-1_102077_2022-11-26_final
2022-11-27 09:37:48	ga_ls8c_ard_3-2-1_093080_2022-11-27_final
2022-11-29 11:01:56	ga_ls8c_ard_3-2-1_107074_2022-11-29_final
2022-12-01 10:49:10	ga_ls8c_ard_3-2-1_105073_2022-12-01_final
2022-12-01 10:52:22	ga_ls8c_ard_3-2-1_105081_2022-12-01_final
2022-12-04 09:45:34	ga_ls8c_ard_3-2-1_094084_2022-12-04_final
2022-12-06 09:33:12	ga_ls8c_ard_3-2-1_092084_2022-12-06_final
2022-12-06 09:34:48	ga_ls8c_ard_3-2-1_092088_2022-12-06_final
2022-12-06 11:06:30	ga_ls8c_ard_3-2-1_108070_2022-12-06_final
2022-12-07 10:11:41	ga_ls8c_ard_3-2-1_099072_2022-12-07_final
2022-12-08 10:55:20	ga_ls8c_ard_3-2-1_106073_2022-12-08_final
2022-12-09 11:42:11	ga_ls8c_ard_3-2-1_113082_2022-12-09_final
2022-12-13 09:38:56	ga_ls8c_ard_3-2-1_093083_2022-12-13_final
2022-12-13 09:40:56	ga_ls8c_ard_3-2-1_093088_2022-12-13_final
2022-12-15 09:24:10	ga_ls8c_ard_3-2-1_091077_2022-12-14_final
2022-12-20 11:19:55	ga_ls8c_ard_3-2-1_110073_2022-12-20_final
2022-12-22 11:07:08	ga_ls8c_ard_3-2-1_108072_2022-12-22_final
2022-12-22 11:08:19	ga_ls8c_ard_3-2-1_108075_2022-12-22_final
2022-12-23 11:51:35	ga_ls8c_ard_3-2-1_115075_2022-12-23_final
2022-12-26 10:41:13	ga_ls8c_ard_3-2-1_104069_2022-12-26_final
2022-12-29 09:39:38	ga_ls8c_ard_3-2-1_093085_2022-12-29_final
2022-12-31 11:05:46	ga_ls8c_ard_3-2-1_107084_2022-12-31_final
2023-01-07 11:06:45	ga_ls8c_ard_3-2-1_108071_2023-01-07_final
2023-01-10 11:42:25	ga_ls8c_ard_3-2-1_113083_2023-01-10_final
2023-01-12 11:24:03	ga_ls8c_ard_3-2-1_111068_2023-01-12_final
2023-01-18 09:12:47	ga_ls8c_ard_3-2-1_089080_2023-01-17_final
2023-01-21 09:45:44	ga_ls8c_ard_3-2-1_094085_2023-01-21_final
2023-01-22 10:25:49	ga_ls8c_ard_3-2-1_101077_2023-01-22_final
2023-01-23 09:29:48	ga_ls8c_ard_3-2-1_092076_2023-01-22_final
2023-01-23 11:11:29	ga_ls8c_ard_3-2-1_108083_2023-01-23_final
2023-01-25 10:58:44	ga_ls8c_ard_3-2-1_106082_2023-01-25_final
2023-01-26 10:04:19	ga_ls8c_ard_3-2-1_097085_2023-01-26_final
2023-01-31 11:58:34	ga_ls8c_ard_3-2-1_116077_2023-01-31_final
2023-02-05 10:37:01	ga_ls8c_ard_3-2-1_103074_2023-02-05_final
2023-02-06 11:24:40	ga_ls8c_ard_3-2-1_110085_2023-02-06_final
2023-02-11 09:57:53	ga_ls8c_ard_3-2-1_097069_2023-02-11_final
2023-02-15 09:35:30	ga_ls8c_ard_3-2-1_093075_2023-02-15_final
2023-02-15 11:13:35	ga_ls8c_ard_3-2-1_109073_2023-02-15_final
2023-02-19 09:13:31	ga_ls8c_ard_3-2-1_089082_2023-02-18_final
2023-02-20 09:52:22	ga_ls8c_ard_3-2-1_096071_2023-02-20_final
2023-02-22 09:44:20	ga_ls8c_ard_3-2-1_094082_2023-02-22_final
2023-02-24 09:33:55	ga_ls8c_ard_3-2-1_092087_2023-02-24_final
2023-02-25 10:14:22	ga_ls8c_ard_3-2-1_099080_2023-02-25_final
2023-02-26 10:57:38	ga_ls8c_ard_3-2-1_106080_2023-02-26_final
2023-02-27 10:01:37	ga_ls8c_ard_3-2-1_097079_2023-02-27_final
2023-02-27 11:42:06	ga_ls8c_ard_3-2-1_113083_2023-02-27_final
2023-02-28 09:06:47	ga_ls8c_ard_3-2-1_088081_2023-02-27_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