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
2022-01-06 10:55:26	ga_ls8c_ard_3-2-1_106074_2022-01-06_final
2022-01-06 10:56:14	ga_ls8c_ard_3-2-1_106076_2022-01-06_final
2022-01-15 09:12:44	ga_ls8c_ard_3-2-1_089080_2022-01-14_final
2022-01-15 10:46:26	ga_ls8c_ard_3-2-1_105067_2022-01-15_final
2022-01-29 09:25:01	ga_ls8c_ard_3-2-1_091080_2022-01-28_final
2022-02-04 10:25:37	ga_ls8c_ard_3-2-1_101077_2022-02-04_final
2022-02-07 10:56:06	ga_ls8c_ard_3-2-1_106076_2022-02-07_final
2022-02-14 11:05:26	ga_ls8c_ard_3-2-1_107084_2022-02-14_final
2022-02-17 09:57:26	ga_ls8c_ard_3-2-1_096084_2022-02-17_final
2022-02-26 09:52:01	ga_ls8c_ard_3-2-1_095086_2022-02-26_final
2022-02-28 09:35:16	ga_ls8c_ard_3-2-1_093075_2022-02-28_final
2022-03-07 11:19:30	ga_ls8c_ard_3-2-1_110073_2022-03-07_final
2022-03-09 11:06:44	ga_ls8c_ard_3-2-1_108072_2022-03-09_final
2022-03-10 11:51:35	ga_ls8c_ard_3-2-1_115076_2022-03-10_final
2022-03-11 10:53:34	ga_ls8c_ard_3-2-1_106070_2022-03-11_final
2022-03-17 10:22:00	ga_ls8c_ard_3-2-1_100084_2022-03-17_final
2022-03-22 10:39:41	ga_ls8c_ard_3-2-1_103082_2022-03-22_final
2022-03-29 10:40:11	ga_ls8c_ard_3-2-1_104068_2022-03-29_final
2022-04-01 09:38:58	ga_ls8c_ard_3-2-1_093085_2022-04-01_final
2022-04-01 11:15:27	ga_ls8c_ard_3-2-1_109079_2022-04-01_final
2022-04-08 09:44:24	ga_ls8c_ard_3-2-1_094083_2022-04-08_final
2022-04-08 11:18:30	ga_ls8c_ard_3-2-1_110071_2022-04-08_final
2022-04-21 10:46:02	ga_ls8c_ard_3-2-1_105067_2022-04-21_final
2022-04-22 11:32:05	ga_ls8c_ard_3-2-1_112074_2022-04-22_final
2022-04-24 11:19:18	ga_ls8c_ard_3-2-1_110073_2022-04-24_final
2022-05-13 11:51:31	ga_ls8c_ard_3-2-1_115076_2022-05-13_final
2022-05-31 10:03:56	ga_ls8c_ard_3-2-1_097085_2022-05-31_final
2022-06-04 11:11:46	ga_ls8c_ard_3-2-1_109069_2022-06-04_final
2022-06-08 09:13:24	ga_ls8c_ard_3-2-1_089082_2022-06-07_final
2022-06-11 09:45:08	ga_ls8c_ard_3-2-1_094084_2022-06-11_final
2022-06-11 09:45:56	ga_ls8c_ard_3-2-1_094086_2022-06-11_final
2022-06-11 11:23:38	ga_ls8c_ard_3-2-1_110083_2022-06-11_final
2022-06-13 09:31:36	ga_ls8c_ard_3-2-1_092081_2022-06-13_final
2022-06-18 11:28:41	ga_ls8c_ard_3-2-1_111080_2022-06-18_final
2022-06-28 10:28:07	ga_ls8c_ard_3-2-1_101083_2022-06-28_final
2022-06-30 11:52:39	ga_ls8c_ard_3-2-1_115078_2022-06-30_final
2022-07-01 10:56:14	ga_ls8c_ard_3-2-1_106076_2022-07-01_final
2022-07-15 11:06:10	ga_ls8c_ard_3-2-1_108070_2022-07-15_final
2022-07-20 11:25:34	ga_ls8c_ard_3-2-1_111072_2022-07-20_final
2022-08-03 09:58:24	ga_ls8c_ard_3-2-1_097070_2022-08-03_final
2022-08-10 11:47:31	ga_ls8c_ard_3-2-1_114080_2022-08-10_final
2022-08-15 10:23:13	ga_ls8c_ard_3-2-1_101070_2022-08-15_final
2022-08-17 10:10:03	ga_ls8c_ard_3-2-1_099068_2022-08-17_final
2022-08-17 11:52:08	ga_ls8c_ard_3-2-1_115076_2022-08-17_final
2022-08-27 09:13:51	ga_ls8c_ard_3-2-1_089082_2022-08-26_final
2022-09-02 10:16:02	ga_ls8c_ard_3-2-1_099083_2022-09-02_final
2022-09-10 11:01:58	ga_ls8c_ard_3-2-1_107074_2022-09-10_final
2022-09-15 11:20:56	ga_ls8c_ard_3-2-1_110075_2022-09-15_final
2022-09-18 10:14:57	ga_ls8c_ard_3-2-1_099080_2022-09-18_final
2022-09-19 10:53:50	ga_ls8c_ard_3-2-1_106069_2022-09-19_final
2022-10-10 09:40:35	ga_ls8c_ard_3-2-1_093087_2022-10-10_final
2022-10-10 11:15:04	ga_ls8c_ard_3-2-1_109076_2022-10-10_final
2022-10-10 11:17:04	ga_ls8c_ard_3-2-1_109081_2022-10-10_final
2022-10-12 11:05:52	ga_ls8c_ard_3-2-1_107084_2022-10-12_final
2022-10-17 11:22:50	ga_ls8c_ard_3-2-1_110080_2022-10-17_final
2022-10-19 11:06:54	ga_ls8c_ard_3-2-1_108071_2022-10-19_final
2022-10-22 09:58:57	ga_ls8c_ard_3-2-1_097071_2022-10-22_final
2022-10-22 11:41:50	ga_ls8c_ard_3-2-1_113081_2022-10-22_final
2022-10-28 09:27:54	ga_ls8c_ard_3-2-1_091086_2022-10-27_final
2022-10-29 11:47:16	ga_ls8c_ard_3-2-1_114079_2022-10-29_final
2022-10-30 09:14:21	ga_ls8c_ard_3-2-1_089083_2022-10-29_final
2022-10-30 10:46:51	ga_ls8c_ard_3-2-1_105067_2022-10-30_final
2022-11-02 09:45:39	ga_ls8c_ard_3-2-1_094084_2022-11-02_final
2022-11-04 11:11:47	ga_ls8c_ard_3-2-1_108083_2022-11-04_final
2022-11-11 11:12:20	ga_ls8c_ard_3-2-1_109069_2022-11-11_final
2022-11-13 11:00:21	ga_ls8c_ard_3-2-1_107070_2022-11-13_final
2022-11-18 09:45:55	ga_ls8c_ard_3-2-1_094085_2022-11-18_final
2022-11-21 11:53:44	ga_ls8c_ard_3-2-1_115080_2022-11-21_final
2022-11-27 11:17:52	ga_ls8c_ard_3-2-1_109083_2022-11-27_final
2022-12-01 09:14:40	ga_ls8c_ard_3-2-1_089084_2022-11-30_final
2022-12-02 09:53:09	ga_ls8c_ard_3-2-1_096072_2022-12-02_final
2022-12-05 10:28:02	ga_ls8c_ard_3-2-1_101082_2022-12-05_final
2022-12-09 11:42:11	ga_ls8c_ard_3-2-1_113082_2022-12-09_final
2022-12-12 10:29:47	ga_ls8c_ard_3-2-1_102071_2022-12-12_final
2022-12-16 10:09:48	ga_ls8c_ard_3-2-1_098083_2022-12-16_final
2023-01-01 10:08:09	ga_ls8c_ard_3-2-1_098079_2023-01-01_final
2023-01-08 11:52:00	ga_ls8c_ard_3-2-1_115076_2023-01-08_final
2023-01-19 11:36:09	ga_ls8c_ard_3-2-1_112083_2023-01-19_final
2023-01-22 10:23:49	ga_ls8c_ard_3-2-1_101072_2023-01-22_final
2023-02-06 11:19:29	ga_ls8c_ard_3-2-1_110072_2023-02-06_final
2023-02-06 11:19:53	ga_ls8c_ard_3-2-1_110073_2023-02-06_final
2023-02-07 10:23:51	ga_ls8c_ard_3-2-1_101072_2023-02-07_final
2023-02-09 10:15:52	ga_ls8c_ard_3-2-1_099083_2023-02-09_final
2023-02-09 11:53:09	ga_ls8c_ard_3-2-1_115079_2023-02-09_final
2023-02-24 11:07:13	ga_ls8c_ard_3-2-1_108073_2023-02-24_final
2023-03-08 09:53:22	ga_ls8c_ard_3-2-1_096074_2023-03-08_final
2023-03-09 10:35:01	ga_ls8c_ard_3-2-1_103070_2023-03-09_final
2023-03-10 11:19:05	ga_ls8c_ard_3-2-1_110072_2023-03-10_final
2023-03-15 11:42:00	ga_ls8c_ard_3-2-1_113083_2023-03-15_final
2023-03-28 09:28:53	ga_ls8c_ard_3-2-1_092075_2023-03-27_final
2023-03-30 10:53:23	ga_ls8c_ard_3-2-1_106070_2023-03-30_final
2023-04-01 10:42:12	ga_ls8c_ard_3-2-1_104073_2023-04-01_final
2023-04-02 11:25:51	ga_ls8c_ard_3-2-1_111074_2023-04-02_final
2023-04-16 09:58:19	ga_ls8c_ard_3-2-1_097072_2023-04-16_final
2023-04-16 10:01:06	ga_ls8c_ard_3-2-1_097079_2023-04-16_final
2023-04-27 11:19:01	ga_ls8c_ard_3-2-1_110073_2023-04-27_final
2023-05-11 11:35:34	ga_ls8c_ard_3-2-1_112084_2023-05-11_final
2023-05-13 11:19:36	ga_ls8c_ard_3-2-1_110075_2023-05-13_final
2023-05-19 09:05:36	ga_ls8c_ard_3-2-1_088080_2023-05-18_final
2023-05-19 10:41:41	ga_ls8c_ard_3-2-1_104073_2023-05-19_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