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 10:58:26	ga_ls8c_ard_3-0-0_107067_2018-02-03_final
2018-02-19 10:58:21	ga_ls8c_ard_3-0-0_107067_2018-02-19_final
2018-02-24 09:37:58	ga_ls8c_ard_3-0-0_094067_2018-02-24_final
2018-02-24 11:16:51	ga_ls8c_ard_3-0-0_110067_2018-02-24_final
2018-02-25 10:21:14	ga_ls8c_ard_3-0-0_101067_2018-02-25_final
2018-02-26 09:25:36	ga_ls8c_ard_3-0-0_092067_2018-02-25_final
2018-02-26 11:04:29	ga_ls8c_ard_3-0-0_108067_2018-02-26_final
2018-02-27 10:08:51	ga_ls8c_ard_3-0-0_099067_2018-02-27_final
2018-02-28 10:52:06	ga_ls8c_ard_3-0-0_106067_2018-02-28_final
2018-03-01 09:56:28	ga_ls8c_ard_3-1-0_097067_2018-03-01_final
2018-03-01 11:35:21	ga_ls8c_ard_3-0-0_113067_2018-03-01_final
2018-03-02 10:39:44	ga_ls8c_ard_3-0-0_104067_2018-03-02_final
2018-03-05 11:10:36	ga_ls8c_ard_3-0-0_109067_2018-03-05_final
2018-03-06 10:14:58	ga_ls8c_ard_3-0-0_100067_2018-03-06_final
2018-03-07 10:58:13	ga_ls8c_ard_3-0-0_107067_2018-03-07_final
2018-03-10 09:50:12	ga_ls8c_ard_3-0-0_096067_2018-03-10_final
2018-03-10 11:29:05	ga_ls8c_ard_3-0-0_112067_2018-03-10_final
2018-03-11 10:33:28	ga_ls8c_ard_3-0-0_103067_2018-03-11_final
2018-03-12 09:37:50	ga_ls8c_ard_3-0-0_094067_2018-03-12_final
2018-03-12 11:16:43	ga_ls8c_ard_3-0-0_110067_2018-03-12_final
2018-03-13 10:21:05	ga_ls8c_ard_3-0-0_101067_2018-03-13_final
2018-03-14 09:25:27	ga_ls8c_ard_3-0-0_092067_2018-03-13_final
2018-04-08 10:57:57	ga_ls8c_ard_3-0-0_107067_2018-04-08_final
2018-04-20 09:43:40	ga_ls8c_ard_3-0-0_095067_2018-04-20_final
2018-04-20 11:22:33	ga_ls8c_ard_3-0-0_111067_2018-04-20_final
2018-04-21 10:26:55	ga_ls8c_ard_3-0-0_102067_2018-04-21_final
2018-04-22 09:31:18	ga_ls8c_ard_3-0-0_093067_2018-04-22_final
2018-04-22 11:10:11	ga_ls8c_ard_3-0-0_109067_2018-04-22_final
2018-04-23 10:14:33	ga_ls8c_ard_3-0-0_100067_2018-04-23_final
2018-05-02 10:08:17	ga_ls8c_ard_3-0-0_099067_2018-05-02_final
2018-05-03 10:51:32	ga_ls8c_ard_3-0-0_106067_2018-05-03_final
2018-05-04 09:55:54	ga_ls8c_ard_3-0-0_097067_2018-05-04_final
2018-05-04 11:34:47	ga_ls8c_ard_3-0-0_113067_2018-05-04_final
2018-05-05 10:39:10	ga_ls8c_ard_3-0-0_104067_2018-05-05_final
2018-05-18 10:08:07	ga_ls8c_ard_3-0-0_099067_2018-05-18_final
2018-05-19 10:51:21	ga_ls8c_ard_3-0-0_106067_2018-05-19_final
2018-05-20 09:55:43	ga_ls8c_ard_3-0-0_097067_2018-05-20_final
2018-05-20 11:34:36	ga_ls8c_ard_3-0-0_113067_2018-05-20_final
2018-05-21 10:38:58	ga_ls8c_ard_3-0-0_104067_2018-05-21_final
2018-09-16 10:02:34	ga_ls8c_ard_3-0-0_098067_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
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
2019-06-03 09:37:58	ga_ls8c_ard_3-0-0_094067_2019-06-03_final
2019-06-03 11:16:51	ga_ls8c_ard_3-0-0_110067_2019-06-03_final
2019-06-04 10:21:14	ga_ls8c_ard_3-0-0_101067_2019-06-04_final
2019-06-05 09:25:38	ga_ls8c_ard_3-0-0_092067_2019-06-04_final
2020-04-09 09:44:03	ga_ls8c_ard_3-1-0_095067_2020-04-09_final
2020-04-09 11:22:56	ga_ls8c_ard_3-1-0_111067_2020-04-09_final
2020-04-10 10:27:18	ga_ls8c_ard_3-1-0_102067_2020-04-10_final
2020-04-11 09:31:41	ga_ls8c_ard_3-1-0_093067_2020-04-11_final
2020-04-11 11:10:34	ga_ls8c_ard_3-1-0_109067_2020-04-11_final
2020-04-12 10:14:56	ga_ls8c_ard_3-1-0_100067_2020-04-12_final
2020-04-13 10:58:11	ga_ls8c_ard_3-1-0_107067_2020-04-13_final
2020-04-13 12:37:04	ga_ls8c_ard_3-2-1_123067_2020-04-13_final
2020-04-14 10:02:33	ga_ls8c_ard_3-1-0_098067_2020-04-14_final
2020-04-14 11:41:26	ga_ls8c_ard_3-1-0_114067_2020-04-14_final
2020-04-27 11:10:26	ga_ls8c_ard_3-1-0_109067_2020-04-27_final
2020-04-28 10:14:48	ga_ls8c_ard_3-1-0_100067_2020-04-28_final
2020-04-30 10:02:25	ga_ls8c_ard_3-1-0_098067_2020-04-30_final
2020-04-30 11:41:19	ga_ls8c_ard_3-1-0_114067_2020-04-30_final
2020-05-01 10:45:41	ga_ls8c_ard_3-1-0_105067_2020-05-01_final
2020-05-16 10:02:22	ga_ls8c_ard_3-1-0_098067_2020-05-16_final
2020-05-16 11:41:15	ga_ls8c_ard_3-1-0_114067_2020-05-16_final
2020-05-17 10:45:38	ga_ls8c_ard_3-1-0_105067_2020-05-17_final
2022-08-10 10:03:27	ga_ls8c_ard_3-2-1_098067_2022-08-10_final
2022-08-11 10:46:43	ga_ls8c_ard_3-2-1_105067_2022-08-11_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
2022-11-05 10:09:46	ga_ls8c_ard_3-2-1_099067_2022-11-05_final
2022-11-06 10:53:02	ga_ls8c_ard_3-2-1_106067_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
2022-11-08 10:40:39	ga_ls8c_ard_3-2-1_104067_2022-11-08_final
2022-11-22 10:52:56	ga_ls8c_ard_3-2-1_106067_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
2022-11-30 10:03:31	ga_ls8c_ard_3-2-1_098067_2022-11-30_final
2022-12-10 10:40:34	ga_ls8c_ard_3-2-1_104067_2022-12-10_final
2022-12-24 10:52:46	ga_ls8c_ard_3-2-1_106067_2022-12-24_final
2023-01-16 12:37:45	ga_ls8c_ard_3-2-1_123067_2023-01-16_final
2023-01-17 10:03:14	ga_ls8c_ard_3-2-1_098067_2023-01-17_final
2023-01-18 10:46:29	ga_ls8c_ard_3-2-1_105067_2023-01-18_final
2023-01-24 10:09:29	ga_ls8c_ard_3-2-1_099067_2023-01-24_final
2023-01-25 10:52:45	ga_ls8c_ard_3-2-1_106067_2023-01-25_final
2023-01-25 12:31:38	ga_ls8c_ard_3-2-1_122067_2023-01-25_final
2023-01-26 09:57:08	ga_ls8c_ard_3-2-1_097067_2023-01-26_final
2023-01-29 10:28:03	ga_ls8c_ard_3-2-1_102067_2023-01-29_final
2023-02-09 10:09:29	ga_ls8c_ard_3-2-1_099067_2023-02-09_final
2023-02-10 10:52:43	ga_ls8c_ard_3-2-1_106067_2023-02-10_final
2023-02-10 12:31:36	ga_ls8c_ard_3-2-1_122067_2023-02-10_final
2023-02-11 09:57:05	ga_ls8c_ard_3-2-1_097067_2023-02-11_final
2023-02-14 10:27:57	ga_ls8c_ard_3-2-1_102067_2023-02-14_final
2023-06-01 10:08:26	ga_ls8c_ard_3-2-1_099067_2023-06-01_final
2023-06-02 10:51:42	ga_ls8c_ard_3-2-1_106067_2023-06-02_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