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
2022-10-04 10:12:08	ga_ls8c_ard_3-2-1_099073_2022-10-04_final
2022-10-08 09:52:58	ga_ls8c_ard_3-2-1_095087_2022-10-08_final
2022-10-11 10:17:50	ga_ls8c_ard_3-2-1_100072_2022-10-11_final
2022-10-11 10:20:14	ga_ls8c_ard_3-2-1_100078_2022-10-11_final
2022-10-12 09:23:48	ga_ls8c_ard_3-2-1_091076_2022-10-11_final
2022-10-12 11:00:41	ga_ls8c_ard_3-2-1_107071_2022-10-12_final
2022-10-17 11:20:02	ga_ls8c_ard_3-2-1_110073_2022-10-17_final
2022-10-17 11:23:38	ga_ls8c_ard_3-2-1_110082_2022-10-17_final
2022-10-22 11:42:14	ga_ls8c_ard_3-2-1_113082_2022-10-22_final
2022-10-29 11:47:16	ga_ls8c_ard_3-2-1_114079_2022-10-29_final
2022-11-02 11:20:33	ga_ls8c_ard_3-2-1_110074_2022-11-02_final
2022-11-03 10:24:08	ga_ls8c_ard_3-2-1_101072_2022-11-03_final
2022-11-04 09:32:06	ga_ls8c_ard_3-2-1_092081_2022-11-04_final
2022-11-04 09:34:06	ga_ls8c_ard_3-2-1_092086_2022-11-04_final
2022-11-05 11:52:39	ga_ls8c_ard_3-2-1_115077_2022-11-05_final
2022-11-06 09:19:20	ga_ls8c_ard_3-2-1_090080_2022-11-05_final
2022-11-08 10:45:51	ga_ls8c_ard_3-2-1_104080_2022-11-08_final
2022-11-09 11:27:06	ga_ls8c_ard_3-2-1_111075_2022-11-09_final
2022-11-11 09:39:02	ga_ls8c_ard_3-2-1_093083_2022-11-11_final
2022-11-11 11:12:20	ga_ls8c_ard_3-2-1_109069_2022-11-11_final
2022-11-14 11:46:47	ga_ls8c_ard_3-2-1_114078_2022-11-14_final
2022-11-15 09:14:16	ga_ls8c_ard_3-2-1_089083_2022-11-14_final
2022-11-15 10:48:45	ga_ls8c_ard_3-2-1_105072_2022-11-15_final
2022-11-17 10:35:34	ga_ls8c_ard_3-2-1_103070_2022-11-17_final
2022-11-18 09:41:32	ga_ls8c_ard_3-2-1_094074_2022-11-18_final
2022-11-18 09:45:55	ga_ls8c_ard_3-2-1_094085_2022-11-18_final
2022-11-18 11:21:37	ga_ls8c_ard_3-2-1_110077_2022-11-18_final
2022-11-20 11:07:16	ga_ls8c_ard_3-2-1_108072_2022-11-20_final
2022-11-22 09:19:38	ga_ls8c_ard_3-2-1_090081_2022-11-21_final
2022-11-23 10:04:30	ga_ls8c_ard_3-2-1_097085_2022-11-23_final
2022-11-24 10:45:46	ga_ls8c_ard_3-2-1_104080_2022-11-24_final
2022-11-28 11:59:09	ga_ls8c_ard_3-2-1_116078_2022-11-28_final
2022-11-29 09:25:26	ga_ls8c_ard_3-2-1_091080_2022-11-28_final
2022-11-30 10:08:18	ga_ls8c_ard_3-2-1_098079_2022-11-30_final
2022-12-02 11:36:01	ga_ls8c_ard_3-2-1_112082_2022-12-02_final
2022-12-04 11:20:04	ga_ls8c_ard_3-2-1_110073_2022-12-04_final
2022-12-08 09:18:27	ga_ls8c_ard_3-2-1_090078_2022-12-07_final
2022-12-08 10:55:44	ga_ls8c_ard_3-2-1_106074_2022-12-08_final
2022-12-09 11:39:23	ga_ls8c_ard_3-2-1_113075_2022-12-09_final
2022-12-10 10:44:57	ga_ls8c_ard_3-2-1_104078_2022-12-10_final
2022-12-11 09:48:08	ga_ls8c_ard_3-2-1_095075_2022-12-11_final
2022-12-14 11:58:41	ga_ls8c_ard_3-2-1_116077_2022-12-14_final
2022-12-16 10:07:01	ga_ls8c_ard_3-2-1_098076_2022-12-16_final
2022-12-17 10:49:04	ga_ls8c_ard_3-2-1_105073_2022-12-17_final
2022-12-20 11:18:43	ga_ls8c_ard_3-2-1_110070_2022-12-20_final
2022-12-21 10:27:29	ga_ls8c_ard_3-2-1_101081_2022-12-21_final
2022-12-24 10:57:34	ga_ls8c_ard_3-2-1_106079_2022-12-24_final
2022-12-25 09:58:45	ga_ls8c_ard_3-2-1_097071_2022-12-25_final
2022-12-25 10:04:20	ga_ls8c_ard_3-2-1_097085_2022-12-25_final
2022-12-26 10:42:01	ga_ls8c_ard_3-2-1_104071_2022-12-26_final
2022-12-31 09:25:17	ga_ls8c_ard_3-2-1_091080_2022-12-30_final
2023-01-01 11:46:38	ga_ls8c_ard_3-2-1_114078_2023-01-01_final
2023-01-01 11:47:26	ga_ls8c_ard_3-2-1_114080_2023-01-01_final
2023-01-02 10:49:25	ga_ls8c_ard_3-2-1_105074_2023-01-02_final
2023-01-04 10:34:40	ga_ls8c_ard_3-2-1_103068_2023-01-04_final
2023-01-05 09:42:14	ga_ls8c_ard_3-2-1_094076_2023-01-05_final
2023-01-06 10:26:41	ga_ls8c_ard_3-2-1_101079_2023-01-06_final
2023-01-07 09:35:03	ga_ls8c_ard_3-2-1_092089_2023-01-07_final
2023-01-08 10:12:43	ga_ls8c_ard_3-2-1_099075_2023-01-08_final
2023-01-08 10:15:55	ga_ls8c_ard_3-2-1_099083_2023-01-08_final
2023-01-09 09:19:29	ga_ls8c_ard_3-2-1_090081_2023-01-08_final
2023-01-13 10:31:37	ga_ls8c_ard_3-2-1_102076_2023-01-13_final
2023-01-13 10:32:00	ga_ls8c_ard_3-2-1_102077_2023-01-13_final
2023-01-14 09:36:46	ga_ls8c_ard_3-2-1_093078_2023-01-14_final
2023-01-16 09:25:11	ga_ls8c_ard_3-2-1_091080_2023-01-15_final
2023-01-16 09:26:22	ga_ls8c_ard_3-2-1_091083_2023-01-15_final
2023-01-16 11:01:40	ga_ls8c_ard_3-2-1_107074_2023-01-16_final
2023-01-18 10:48:53	ga_ls8c_ard_3-2-1_105073_2023-01-18_final
2023-01-21 09:44:32	ga_ls8c_ard_3-2-1_094082_2023-01-21_final
2023-01-21 11:20:14	ga_ls8c_ard_3-2-1_110074_2023-01-21_final
2023-01-22 10:28:13	ga_ls8c_ard_3-2-1_101083_2023-01-22_final
2023-01-26 10:04:19	ga_ls8c_ard_3-2-1_097085_2023-01-26_final
2023-01-26 11:39:13	ga_ls8c_ard_3-2-1_113075_2023-01-26_final
2023-01-26 11:42:24	ga_ls8c_ard_3-2-1_113083_2023-01-26_final
2023-01-30 11:14:54	ga_ls8c_ard_3-2-1_109076_2023-01-30_final
2023-01-31 11:58:58	ga_ls8c_ard_3-2-1_116078_2023-01-31_final
2023-02-01 09:25:39	ga_ls8c_ard_3-2-1_091081_2023-01-31_final
2023-02-08 11:07:30	ga_ls8c_ard_3-2-1_108073_2023-02-08_final
2023-02-09 10:12:40	ga_ls8c_ard_3-2-1_099075_2023-02-09_final
2023-02-10 09:19:50	ga_ls8c_ard_3-2-1_090082_2023-02-09_final
2023-02-15 11:13:12	ga_ls8c_ard_3-2-1_109072_2023-02-15_final
2023-02-17 09:23:55	ga_ls8c_ard_3-2-1_091077_2023-02-16_final
2023-02-17 11:03:36	ga_ls8c_ard_3-2-1_107079_2023-02-17_final
2023-02-18 10:10:21	ga_ls8c_ard_3-2-1_098085_2023-02-18_final
2023-02-21 10:35:12	ga_ls8c_ard_3-2-1_103070_2023-02-21_final
2023-02-21 10:37:59	ga_ls8c_ard_3-2-1_103077_2023-02-21_final
2023-02-26 10:55:14	ga_ls8c_ard_3-2-1_106074_2023-02-26_final
2023-02-27 11:42:06	ga_ls8c_ard_3-2-1_113083_2023-02-27_final
2023-03-03 11:16:58	ga_ls8c_ard_3-2-1_109082_2023-03-03_final
2023-03-06 10:06:57	ga_ls8c_ard_3-2-1_098077_2023-03-06_final
2023-03-06 11:46:14	ga_ls8c_ard_3-2-1_114078_2023-03-06_final
2023-03-07 09:16:06	ga_ls8c_ard_3-2-1_089089_2023-03-06_final
2023-03-07 10:49:48	ga_ls8c_ard_3-2-1_105076_2023-03-07_final
2023-03-09 10:36:13	ga_ls8c_ard_3-2-1_103073_2023-03-09_final
2023-03-11 10:23:28	ga_ls8c_ard_3-2-1_101072_2023-03-11_final
2023-03-11 10:23:52	ga_ls8c_ard_3-2-1_101073_2023-03-11_final
2023-03-12 09:29:26	ga_ls8c_ard_3-2-1_092076_2023-03-11_final
2023-03-12 09:30:14	ga_ls8c_ard_3-2-1_092078_2023-03-12_final
2023-03-14 09:20:40	ga_ls8c_ard_3-2-1_090085_2023-03-13_final
2023-03-14 10:55:57	ga_ls8c_ard_3-2-1_106076_2023-03-14_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