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
2018-02-03 09:19:57	ga_ls8c_ard_3-0-0_091068_2018-02-02_final
2018-02-03 10:58:50	ga_ls8c_ard_3-0-0_107068_2018-02-03_final
2018-02-26 11:04:53	ga_ls8c_ard_3-0-0_108068_2018-02-26_final
2018-02-27 10:09:15	ga_ls8c_ard_3-0-0_099068_2018-02-27_final
2018-02-28 10:52:30	ga_ls8c_ard_3-0-0_106068_2018-02-28_final
2018-03-01 09:56:52	ga_ls8c_ard_3-0-0_097068_2018-03-01_final
2018-03-02 10:40:07	ga_ls8c_ard_3-0-0_104068_2018-03-02_final
2018-03-07 09:19:44	ga_ls8c_ard_3-0-0_091068_2018-03-06_final
2018-03-07 10:58:37	ga_ls8c_ard_3-0-0_107068_2018-03-07_final
2018-03-30 11:04:37	ga_ls8c_ard_3-0-0_108068_2018-03-30_final
2018-03-31 10:08:59	ga_ls8c_ard_3-0-0_099068_2018-03-31_final
2018-04-01 10:52:14	ga_ls8c_ard_3-0-0_106068_2018-04-01_final
2018-04-02 09:56:36	ga_ls8c_ard_3-0-0_097068_2018-04-02_final
2018-04-03 10:39:52	ga_ls8c_ard_3-0-0_104068_2018-04-03_final
2018-09-16 10:02:58	ga_ls8c_ard_3-0-0_098068_2018-09-16_final
2018-09-16 10:03:22	ga_ls8c_ard_3-0-0_098069_2018-09-16_final
2018-09-17 10:46:14	ga_ls8c_ard_3-0-0_105068_2018-09-17_final
2018-09-17 10:46:38	ga_ls8c_ard_3-0-0_105069_2018-09-17_final
2019-01-06 10:03:13	ga_ls8c_ard_3-0-0_098068_2019-01-06_final
2019-01-07 10:46:28	ga_ls8c_ard_3-0-0_105068_2019-01-07_final
2022-11-09 11:24:19	ga_ls8c_ard_3-2-1_111068_2022-11-09_final
2022-11-10 10:28:41	ga_ls8c_ard_3-2-1_102068_2022-11-10_final
2022-11-13 10:59:33	ga_ls8c_ard_3-2-1_107068_2022-11-13_final
2022-11-14 10:03:55	ga_ls8c_ard_3-2-1_098068_2022-11-14_final
2022-11-15 10:47:10	ga_ls8c_ard_3-2-1_105068_2022-11-15_final
2022-11-17 10:34:46	ga_ls8c_ard_3-2-1_103068_2022-11-17_final
2022-11-21 10:10:04	ga_ls8c_ard_3-2-1_099068_2022-11-21_final
2022-11-21 10:10:28	ga_ls8c_ard_3-2-1_099069_2022-11-21_final
2022-11-22 10:53:20	ga_ls8c_ard_3-2-1_106068_2022-11-22_final
2022-11-23 09:57:43	ga_ls8c_ard_3-2-1_097068_2022-11-23_final
2022-11-24 10:40:59	ga_ls8c_ard_3-2-1_104068_2022-11-24_final
2022-11-25 11:24:15	ga_ls8c_ard_3-2-1_111068_2022-11-25_final
2022-11-26 10:28:37	ga_ls8c_ard_3-2-1_102068_2022-11-26_final
2022-11-26 10:29:01	ga_ls8c_ard_3-2-1_102069_2022-11-26_final
2022-11-29 10:59:32	ga_ls8c_ard_3-2-1_107068_2022-11-29_final
2022-11-30 10:03:55	ga_ls8c_ard_3-2-1_098068_2022-11-30_final
2022-12-01 10:47:10	ga_ls8c_ard_3-2-1_105068_2022-12-01_final
2022-12-03 10:34:49	ga_ls8c_ard_3-2-1_103068_2022-12-03_final
2022-12-07 10:10:05	ga_ls8c_ard_3-2-1_099068_2022-12-07_final
2022-12-07 10:10:29	ga_ls8c_ard_3-2-1_099069_2022-12-07_final
2022-12-08 10:53:20	ga_ls8c_ard_3-2-1_106068_2022-12-08_final
2022-12-09 09:57:43	ga_ls8c_ard_3-2-1_097068_2022-12-09_final
2022-12-10 10:40:58	ga_ls8c_ard_3-2-1_104068_2022-12-10_final
2022-12-11 11:24:13	ga_ls8c_ard_3-2-1_111068_2022-12-11_final
2022-12-12 10:28:35	ga_ls8c_ard_3-2-1_102068_2022-12-12_final
2022-12-15 10:59:27	ga_ls8c_ard_3-2-1_107068_2022-12-15_final
2022-12-16 10:03:49	ga_ls8c_ard_3-2-1_098068_2022-12-16_final
2022-12-17 10:47:04	ga_ls8c_ard_3-2-1_105068_2022-12-17_final
2022-12-23 10:09:54	ga_ls8c_ard_3-2-1_099068_2022-12-23_final
2022-12-24 10:53:10	ga_ls8c_ard_3-2-1_106068_2022-12-24_final
2023-01-02 10:47:02	ga_ls8c_ard_3-2-1_105068_2023-01-02_final
2023-01-04 10:34:40	ga_ls8c_ard_3-2-1_103068_2023-01-04_final
2023-01-11 10:40:48	ga_ls8c_ard_3-2-1_104068_2023-01-11_final
2023-01-12 11:24:03	ga_ls8c_ard_3-2-1_111068_2023-01-12_final
2023-01-16 10:59:16	ga_ls8c_ard_3-2-1_107068_2023-01-16_final
2023-01-17 10:03:38	ga_ls8c_ard_3-2-1_098068_2023-01-17_final
2023-01-24 10:09:53	ga_ls8c_ard_3-2-1_099068_2023-01-24_final
2023-01-25 10:53:09	ga_ls8c_ard_3-2-1_106068_2023-01-25_final
2023-01-26 09:57:32	ga_ls8c_ard_3-2-1_097068_2023-01-26_final
2023-02-01 10:59:21	ga_ls8c_ard_3-2-1_107068_2023-02-01_final
2023-02-02 10:03:44	ga_ls8c_ard_3-2-1_098068_2023-02-02_final
2023-02-03 10:46:59	ga_ls8c_ard_3-2-1_105068_2023-02-03_final
2023-02-05 10:34:37	ga_ls8c_ard_3-2-1_103068_2023-02-05_final
2023-02-09 10:09:52	ga_ls8c_ard_3-2-1_099068_2023-02-09_final
2023-02-10 10:53:07	ga_ls8c_ard_3-2-1_106068_2023-02-10_final
2023-02-11 09:57:29	ga_ls8c_ard_3-2-1_097068_2023-02-11_final
2023-02-12 10:40:44	ga_ls8c_ard_3-2-1_104068_2023-02-12_final
2023-02-13 11:23:59	ga_ls8c_ard_3-2-1_111068_2023-02-13_final
2023-02-14 10:28:21	ga_ls8c_ard_3-2-1_102068_2023-02-14_final
2023-02-17 10:59:12	ga_ls8c_ard_3-2-1_107068_2023-02-17_final
2023-02-18 10:03:34	ga_ls8c_ard_3-2-1_098068_2023-02-18_final
2023-02-19 10:46:48	ga_ls8c_ard_3-2-1_105068_2023-02-19_final
2023-02-21 10:34:24	ga_ls8c_ard_3-2-1_103068_2023-02-21_final
2023-02-25 10:09:35	ga_ls8c_ard_3-2-1_099068_2023-02-25_final
2023-02-26 10:52:51	ga_ls8c_ard_3-2-1_106068_2023-02-26_final
2023-02-27 09:57:14	ga_ls8c_ard_3-2-1_097068_2023-02-27_final
2023-02-28 10:40:29	ga_ls8c_ard_3-2-1_104068_2023-02-28_final
2023-03-05 10:59:00	ga_ls8c_ard_3-2-1_107068_2023-03-05_final
2023-03-06 10:03:22	ga_ls8c_ard_3-2-1_098068_2023-03-06_final
2023-03-09 10:34:13	ga_ls8c_ard_3-2-1_103068_2023-03-09_final
2023-03-13 10:09:30	ga_ls8c_ard_3-2-1_099068_2023-03-13_final
2023-03-14 10:52:46	ga_ls8c_ard_3-2-1_106068_2023-03-14_final
2023-03-15 09:57:08	ga_ls8c_ard_3-2-1_097068_2023-03-15_final
2023-03-16 10:40:23	ga_ls8c_ard_3-2-1_104068_2023-03-16_final
2023-03-17 11:23:38	ga_ls8c_ard_3-2-1_111068_2023-03-17_final
2023-03-18 10:28:00	ga_ls8c_ard_3-2-1_102068_2023-03-18_final
2023-03-21 10:58:51	ga_ls8c_ard_3-2-1_107068_2023-03-21_final
2023-03-22 10:03:13	ga_ls8c_ard_3-2-1_098068_2023-03-22_final
2023-03-30 10:52:35	ga_ls8c_ard_3-2-1_106068_2023-03-30_final
2023-03-31 09:56:57	ga_ls8c_ard_3-2-1_097068_2023-03-31_final
2023-04-01 10:40:12	ga_ls8c_ard_3-2-1_104068_2023-04-01_final
2023-04-06 10:58:39	ga_ls8c_ard_3-2-1_107068_2023-04-06_final
2023-04-07 10:03:00	ga_ls8c_ard_3-2-1_098068_2023-04-07_final
2023-04-08 10:46:15	ga_ls8c_ard_3-2-1_105068_2023-04-08_final
2023-04-10 10:33:50	ga_ls8c_ard_3-2-1_103068_2023-04-10_final
2023-04-14 10:09:05	ga_ls8c_ard_3-2-1_099068_2023-04-14_final
2023-04-15 10:52:20	ga_ls8c_ard_3-2-1_106068_2023-04-15_final
2023-07-20 10:52:29	ga_ls8c_ard_3-2-1_106068_2023-07-20_final
2023-07-20 10:52:53	ga_ls8c_ard_3-2-1_106069_2023-07-20_final
2023-07-23 11:23:26	ga_ls8c_ard_3-2-1_111068_2023-07-23_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