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
2018-09-16 10:02:34	ga_ls8c_ard_3-0-0_098067_2018-09-16_final
2018-09-16 10:02:58	ga_ls8c_ard_3-0-0_098068_2018-09-16_final
2018-09-16 11:41:28	ga_ls8c_ard_3-0-0_114067_2018-09-16_final
2018-09-17 10:45:50	ga_ls8c_ard_3-0-0_105067_2018-09-17_final
2018-09-17 10:46:14	ga_ls8c_ard_3-0-0_105068_2018-09-17_final
2019-01-06 10:02:49	ga_ls8c_ard_3-0-0_098067_2019-01-06_final
2019-01-06 11:41:42	ga_ls8c_ard_3-0-0_114067_2019-01-06_final
2019-01-07 10:46:04	ga_ls8c_ard_3-0-0_105067_2019-01-07_final
2022-08-19 09:57:18	ga_ls8c_ard_3-2-1_097067_2022-08-19_final
2022-08-20 10:40:34	ga_ls8c_ard_3-2-1_104067_2022-08-20_final
2022-08-22 10:28:12	ga_ls8c_ard_3-2-1_102067_2022-08-22_final
2022-08-22 10:28:36	ga_ls8c_ard_3-2-1_102068_2022-08-22_final
2022-08-25 12:38:00	ga_ls8c_ard_3-2-1_123067_2022-08-25_final
2022-08-26 10:03:29	ga_ls8c_ard_3-2-1_098067_2022-08-26_final
2022-09-03 10:52:55	ga_ls8c_ard_3-2-1_106067_2022-09-03_final
2022-09-03 10:53:19	ga_ls8c_ard_3-2-1_106068_2022-09-03_final
2022-09-03 12:31:48	ga_ls8c_ard_3-2-1_122067_2022-09-03_final
2022-09-04 09:57:18	ga_ls8c_ard_3-2-1_097067_2022-09-04_final
2022-09-04 09:57:42	ga_ls8c_ard_3-2-1_097068_2022-09-04_final
2022-09-05 10:40:35	ga_ls8c_ard_3-2-1_104067_2022-09-05_final
2022-09-06 11:24:15	ga_ls8c_ard_3-2-1_111068_2022-09-06_final
2022-09-07 10:28:14	ga_ls8c_ard_3-2-1_102067_2022-09-07_final
2022-09-07 10:28:38	ga_ls8c_ard_3-2-1_102068_2022-09-07_final
2022-09-12 10:46:49	ga_ls8c_ard_3-2-1_105067_2022-09-12_final
2022-09-14 10:34:52	ga_ls8c_ard_3-2-1_103068_2022-09-14_final
2022-09-18 10:09:46	ga_ls8c_ard_3-2-1_099067_2022-09-18_final
2022-09-19 10:53:02	ga_ls8c_ard_3-2-1_106067_2022-09-19_final
2022-09-19 12:31:55	ga_ls8c_ard_3-2-1_122067_2022-09-19_final
2022-09-20 09:57:25	ga_ls8c_ard_3-2-1_097067_2022-09-20_final
2022-09-21 10:40:41	ga_ls8c_ard_3-2-1_104067_2022-09-21_final
2022-09-23 10:28:19	ga_ls8c_ard_3-2-1_102067_2022-09-23_final
2022-09-23 10:28:43	ga_ls8c_ard_3-2-1_102068_2022-09-23_final
2022-09-26 12:38:06	ga_ls8c_ard_3-2-1_123067_2022-09-26_final
2022-09-27 10:03:36	ga_ls8c_ard_3-2-1_098067_2022-09-27_final
2022-09-27 10:04:00	ga_ls8c_ard_3-2-1_098068_2022-09-27_final
2022-09-28 10:46:51	ga_ls8c_ard_3-2-1_105067_2022-09-28_final
2022-09-28 10:47:15	ga_ls8c_ard_3-2-1_105068_2022-09-28_final
2022-09-30 10:34:53	ga_ls8c_ard_3-2-1_103068_2022-09-30_final
2022-10-04 10:09:45	ga_ls8c_ard_3-2-1_099067_2022-10-04_final
2022-10-04 10:10:09	ga_ls8c_ard_3-2-1_099068_2022-10-04_final
2022-10-23 10:40:38	ga_ls8c_ard_3-2-1_104067_2022-10-23_final
2022-10-23 10:41:02	ga_ls8c_ard_3-2-1_104068_2022-10-23_final
2022-10-25 10:28:17	ga_ls8c_ard_3-2-1_102067_2022-10-25_final
2022-10-28 12:38:05	ga_ls8c_ard_3-2-1_123067_2022-10-28_final
2022-10-29 10:03:35	ga_ls8c_ard_3-2-1_098067_2022-10-29_final
2022-10-30 10:46:51	ga_ls8c_ard_3-2-1_105067_2022-10-30_final
2022-10-30 10:47:15	ga_ls8c_ard_3-2-1_105068_2022-10-30_final
2022-11-05 10:09:46	ga_ls8c_ard_3-2-1_099067_2022-11-05_final
2022-11-05 10:10:10	ga_ls8c_ard_3-2-1_099068_2022-11-05_final
2022-11-06 10:53:02	ga_ls8c_ard_3-2-1_106067_2022-11-06_final
2022-11-06 10:53:26	ga_ls8c_ard_3-2-1_106068_2022-11-06_final
2022-11-06 12:31:55	ga_ls8c_ard_3-2-1_122067_2022-11-06_final
2022-11-07 09:57:24	ga_ls8c_ard_3-2-1_097067_2022-11-07_final
2022-11-07 09:57:48	ga_ls8c_ard_3-2-1_097068_2022-11-07_final
2022-11-08 10:40:39	ga_ls8c_ard_3-2-1_104067_2022-11-08_final
2022-11-10 10:28:17	ga_ls8c_ard_3-2-1_102067_2022-11-10_final
2022-11-10 10:28:41	ga_ls8c_ard_3-2-1_102068_2022-11-10_final
2022-11-15 10:46:46	ga_ls8c_ard_3-2-1_105067_2022-11-15_final
2022-11-17 10:34:46	ga_ls8c_ard_3-2-1_103068_2022-11-17_final
2022-11-21 10:09:40	ga_ls8c_ard_3-2-1_099067_2022-11-21_final
2022-11-22 10:52:56	ga_ls8c_ard_3-2-1_106067_2022-11-22_final
2022-11-22 10:53:20	ga_ls8c_ard_3-2-1_106068_2022-11-22_final
2022-11-22 12:31:49	ga_ls8c_ard_3-2-1_122067_2022-11-22_final
2022-11-23 09:57:19	ga_ls8c_ard_3-2-1_097067_2022-11-23_final
2022-11-24 10:40:35	ga_ls8c_ard_3-2-1_104067_2022-11-24_final
2022-11-26 10:28:14	ga_ls8c_ard_3-2-1_102067_2022-11-26_final
2022-11-26 10:28:37	ga_ls8c_ard_3-2-1_102068_2022-11-26_final
2022-11-29 12:38:01	ga_ls8c_ard_3-2-1_123067_2022-11-29_final
2022-11-30 10:03:31	ga_ls8c_ard_3-2-1_098067_2022-11-30_final
2022-11-30 10:03:55	ga_ls8c_ard_3-2-1_098068_2022-11-30_final
2022-12-01 10:46:46	ga_ls8c_ard_3-2-1_105067_2022-12-01_final
2022-12-03 10:34:49	ga_ls8c_ard_3-2-1_103068_2022-12-03_final
2022-12-07 10:09:41	ga_ls8c_ard_3-2-1_099067_2022-12-07_final
2022-12-07 10:10:05	ga_ls8c_ard_3-2-1_099068_2022-12-07_final
2022-12-08 10:52:56	ga_ls8c_ard_3-2-1_106067_2022-12-08_final
2022-12-08 12:31:49	ga_ls8c_ard_3-2-1_122067_2022-12-08_final
2022-12-09 09:57:19	ga_ls8c_ard_3-2-1_097067_2022-12-09_final
2022-12-10 10:40:34	ga_ls8c_ard_3-2-1_104067_2022-12-10_final
2022-12-10 10:40:58	ga_ls8c_ard_3-2-1_104068_2022-12-10_final
2022-12-12 10:28:11	ga_ls8c_ard_3-2-1_102067_2022-12-12_final
2022-12-15 10:59:27	ga_ls8c_ard_3-2-1_107068_2022-12-15_final
2022-12-15 12:37:57	ga_ls8c_ard_3-2-1_123067_2022-12-15_final
2022-12-16 10:03:25	ga_ls8c_ard_3-2-1_098067_2022-12-16_final
2022-12-17 10:46:40	ga_ls8c_ard_3-2-1_105067_2022-12-17_final
2022-12-23 10:09:30	ga_ls8c_ard_3-2-1_099067_2022-12-23_final
2022-12-24 10:52:46	ga_ls8c_ard_3-2-1_106067_2022-12-24_final
2022-12-24 12:31:40	ga_ls8c_ard_3-2-1_122067_2022-12-24_final
2022-12-25 09:57:10	ga_ls8c_ard_3-2-1_097067_2022-12-25_final
2022-12-26 10:40:26	ga_ls8c_ard_3-2-1_104067_2022-12-26_final
2022-12-28 10:28:05	ga_ls8c_ard_3-2-1_102067_2022-12-28_final
2022-12-31 12:37:52	ga_ls8c_ard_3-2-1_123067_2022-12-31_final
2023-01-01 10:03:22	ga_ls8c_ard_3-2-1_098067_2023-01-01_final
2023-01-02 10:46:38	ga_ls8c_ard_3-2-1_105067_2023-01-02_final
2023-03-18 10:27:36	ga_ls8c_ard_3-2-1_102067_2023-03-18_final
2023-03-21 12:37:20	ga_ls8c_ard_3-2-1_123067_2023-03-21_final
2023-03-22 10:02:49	ga_ls8c_ard_3-2-1_098067_2023-03-22_final
2023-03-23 10:46:03	ga_ls8c_ard_3-2-1_105067_2023-03-23_final
2023-04-03 10:27:25	ga_ls8c_ard_3-2-1_102067_2023-04-03_final
2023-04-16 09:56:19	ga_ls8c_ard_3-2-1_097067_2023-04-16_final
2023-04-17 10:39:34	ga_ls8c_ard_3-2-1_104067_2023-04-17_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