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
2022-07-19 10:41:30	ga_ls8c_ard_3-2-1_104070_2022-07-19_final
2022-07-19 10:42:42	ga_ls8c_ard_3-2-1_104073_2022-07-19_final
2022-07-19 10:43:05	ga_ls8c_ard_3-2-1_104074_2022-07-19_final
2022-07-19 10:43:29	ga_ls8c_ard_3-2-1_104075_2022-07-19_final
2022-07-20 09:46:41	ga_ls8c_ard_3-2-1_095072_2022-07-20_final
2022-07-20 09:50:41	ga_ls8c_ard_3-2-1_095082_2022-07-20_final
2022-07-20 09:51:05	ga_ls8c_ard_3-2-1_095083_2022-07-20_final
2022-07-20 11:25:10	ga_ls8c_ard_3-2-1_111071_2022-07-20_final
2022-07-20 11:27:58	ga_ls8c_ard_3-2-1_111078_2022-07-20_final
2022-07-20 11:28:46	ga_ls8c_ard_3-2-1_111080_2022-07-20_final
2022-07-20 11:29:10	ga_ls8c_ard_3-2-1_111081_2022-07-20_final
2022-07-21 10:29:58	ga_ls8c_ard_3-2-1_102072_2022-07-21_final
2022-07-21 10:30:22	ga_ls8c_ard_3-2-1_102073_2022-07-21_final
2022-07-21 10:30:46	ga_ls8c_ard_3-2-1_102074_2022-07-21_final
2022-07-21 10:31:10	ga_ls8c_ard_3-2-1_102075_2022-07-21_final
2022-07-22 09:33:57	ga_ls8c_ard_3-2-1_093071_2022-07-22_final
2022-07-22 09:34:21	ga_ls8c_ard_3-2-1_093072_2022-07-22_final
2022-07-22 09:35:33	ga_ls8c_ard_3-2-1_093075_2022-07-22_final
2022-07-22 09:35:57	ga_ls8c_ard_3-2-1_093076_2022-07-22_final
2022-07-22 09:36:21	ga_ls8c_ard_3-2-1_093077_2022-07-22_final
2022-07-22 09:37:09	ga_ls8c_ard_3-2-1_093079_2022-07-22_final
2022-07-22 09:37:33	ga_ls8c_ard_3-2-1_093080_2022-07-22_final
2022-07-22 09:37:57	ga_ls8c_ard_3-2-1_093081_2022-07-22_final
2022-07-22 09:39:56	ga_ls8c_ard_3-2-1_093086_2022-07-22_final
2022-07-22 11:13:14	ga_ls8c_ard_3-2-1_109072_2022-07-22_final
2022-07-22 11:14:26	ga_ls8c_ard_3-2-1_109075_2022-07-22_final
2022-07-22 11:15:14	ga_ls8c_ard_3-2-1_109077_2022-07-22_final
2022-07-22 11:16:02	ga_ls8c_ard_3-2-1_109079_2022-07-22_final
2022-07-23 10:19:37	ga_ls8c_ard_3-2-1_100077_2022-07-23_final
2022-07-23 10:20:49	ga_ls8c_ard_3-2-1_100080_2022-07-23_final
2022-07-23 10:21:13	ga_ls8c_ard_3-2-1_100081_2022-07-23_final
2022-07-23 10:21:37	ga_ls8c_ard_3-2-1_100082_2022-07-23_final
2022-07-23 11:58:07	ga_ls8c_ard_3-2-1_116076_2022-07-23_final
2022-07-23 11:58:31	ga_ls8c_ard_3-2-1_116077_2022-07-23_final
2022-07-24 09:28:24	ga_ls8c_ard_3-2-1_091088_2022-07-23_final
2022-07-24 09:28:48	ga_ls8c_ard_3-2-1_091089_2022-07-23_final
2022-07-24 11:01:42	ga_ls8c_ard_3-2-1_107074_2022-07-24_final
2022-07-24 11:04:30	ga_ls8c_ard_3-2-1_107081_2022-07-24_final
2022-07-24 11:05:18	ga_ls8c_ard_3-2-1_107083_2022-07-24_final
2022-07-25 10:04:30	ga_ls8c_ard_3-2-1_098070_2022-07-25_final
2022-07-25 10:06:29	ga_ls8c_ard_3-2-1_098075_2022-07-25_final
2022-07-25 10:08:29	ga_ls8c_ard_3-2-1_098080_2022-07-25_final
2022-07-25 10:08:53	ga_ls8c_ard_3-2-1_098081_2022-07-25_final
2022-07-25 10:10:29	ga_ls8c_ard_3-2-1_098085_2022-07-25_final
2022-07-25 11:45:22	ga_ls8c_ard_3-2-1_114075_2022-07-25_final
2022-07-25 11:46:10	ga_ls8c_ard_3-2-1_114077_2022-07-25_final
2022-07-25 11:46:58	ga_ls8c_ard_3-2-1_114079_2022-07-25_final
2022-07-25 11:47:22	ga_ls8c_ard_3-2-1_114080_2022-07-25_final
2022-07-26 09:11:17	ga_ls8c_ard_3-2-1_089076_2022-07-25_final
2022-07-26 09:11:41	ga_ls8c_ard_3-2-1_089077_2022-07-25_final
2022-07-26 09:12:05	ga_ls8c_ard_3-2-1_089078_2022-07-25_final
2022-07-26 09:12:28	ga_ls8c_ard_3-2-1_089079_2022-07-25_final
2022-07-26 09:13:16	ga_ls8c_ard_3-2-1_089081_2022-07-25_final
2022-07-26 09:14:04	ga_ls8c_ard_3-2-1_089083_2022-07-25_final
2022-07-26 09:14:52	ga_ls8c_ard_3-2-1_089085_2022-07-25_final
2022-07-26 09:16:28	ga_ls8c_ard_3-2-1_089089_2022-07-25_final
2022-08-05 11:24:33	ga_ls8c_ard_3-2-1_111069_2022-08-05_final
2022-08-05 11:25:21	ga_ls8c_ard_3-2-1_111071_2022-08-05_final
2022-08-05 11:26:09	ga_ls8c_ard_3-2-1_111073_2022-08-05_final
2022-08-05 11:27:45	ga_ls8c_ard_3-2-1_111077_2022-08-05_final
2022-08-07 11:15:24	ga_ls8c_ard_3-2-1_109077_2022-08-07_final
2022-08-08 10:20:59	ga_ls8c_ard_3-2-1_100080_2022-08-08_final
2022-08-08 11:58:40	ga_ls8c_ard_3-2-1_116077_2022-08-08_final
2022-08-13 10:34:46	ga_ls8c_ard_3-2-1_103068_2022-08-13_final
2022-08-13 10:36:21	ga_ls8c_ard_3-2-1_103072_2022-08-13_final
2022-08-13 10:37:33	ga_ls8c_ard_3-2-1_103075_2022-08-13_final
2022-08-13 10:39:09	ga_ls8c_ard_3-2-1_103079_2022-08-13_final
2022-08-14 09:40:20	ga_ls8c_ard_3-2-1_094071_2022-08-14_final
2022-08-14 09:40:44	ga_ls8c_ard_3-2-1_094072_2022-08-14_final
2022-08-14 09:41:08	ga_ls8c_ard_3-2-1_094073_2022-08-14_final
2022-08-14 09:41:32	ga_ls8c_ard_3-2-1_094074_2022-08-14_final
2022-08-14 09:44:44	ga_ls8c_ard_3-2-1_094082_2022-08-14_final
2022-08-14 09:46:20	ga_ls8c_ard_3-2-1_094086_2022-08-14_final
2022-08-14 11:19:14	ga_ls8c_ard_3-2-1_110071_2022-08-14_final
2022-08-14 11:22:49	ga_ls8c_ard_3-2-1_110080_2022-08-14_final
2022-08-14 11:23:37	ga_ls8c_ard_3-2-1_110082_2022-08-14_final
2022-08-15 10:23:13	ga_ls8c_ard_3-2-1_101070_2022-08-15_final
2022-08-15 10:24:00	ga_ls8c_ard_3-2-1_101072_2022-08-15_final
2022-08-15 10:24:24	ga_ls8c_ard_3-2-1_101073_2022-08-15_final
2022-08-16 09:33:35	ga_ls8c_ard_3-2-1_092085_2022-08-16_final
2022-08-16 09:34:22	ga_ls8c_ard_3-2-1_092087_2022-08-16_final
2022-08-16 09:34:46	ga_ls8c_ard_3-2-1_092088_2022-08-16_final
2022-08-16 11:08:28	ga_ls8c_ard_3-2-1_108075_2022-08-16_final
2022-08-16 11:08:52	ga_ls8c_ard_3-2-1_108076_2022-08-16_final
2022-08-16 11:09:40	ga_ls8c_ard_3-2-1_108078_2022-08-16_final
2022-08-17 10:10:51	ga_ls8c_ard_3-2-1_099070_2022-08-17_final
2022-08-17 10:11:15	ga_ls8c_ard_3-2-1_099071_2022-08-17_final
2022-08-17 10:13:39	ga_ls8c_ard_3-2-1_099077_2022-08-17_final
2022-08-17 11:52:56	ga_ls8c_ard_3-2-1_115078_2022-08-17_final
2022-08-17 11:53:20	ga_ls8c_ard_3-2-1_115079_2022-08-17_final
2022-08-18 10:54:07	ga_ls8c_ard_3-2-1_106070_2022-08-18_final
2022-08-18 10:55:43	ga_ls8c_ard_3-2-1_106074_2022-08-18_final
2022-08-18 10:56:07	ga_ls8c_ard_3-2-1_106075_2022-08-18_final
2022-08-18 10:56:31	ga_ls8c_ard_3-2-1_106076_2022-08-18_final
2022-08-18 10:56:55	ga_ls8c_ard_3-2-1_106077_2022-08-18_final
2022-08-18 10:57:43	ga_ls8c_ard_3-2-1_106079_2022-08-18_final
2022-08-19 09:59:42	ga_ls8c_ard_3-2-1_097073_2022-08-19_final
2022-08-19 10:00:54	ga_ls8c_ard_3-2-1_097076_2022-08-19_final
2022-08-19 10:02:05	ga_ls8c_ard_3-2-1_097079_2022-08-19_final
2022-08-19 11:38:59	ga_ls8c_ard_3-2-1_113074_2022-08-19_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