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
2022-07-17 09:20:56	ga_ls8c_ard_3-2-1_090085_2022-07-16_final
2022-07-22 11:12:26	ga_ls8c_ard_3-2-1_109070_2022-07-22_final
2022-07-24 09:24:49	ga_ls8c_ard_3-2-1_091079_2022-07-23_final
2022-07-27 11:34:38	ga_ls8c_ard_3-2-1_112079_2022-07-27_final
2022-07-28 10:35:02	ga_ls8c_ard_3-2-1_103069_2022-07-28_final
2022-08-21 09:48:32	ga_ls8c_ard_3-2-1_095076_2022-08-21_final
2022-08-26 11:45:34	ga_ls8c_ard_3-2-1_114075_2022-08-26_final
2022-08-26 11:47:10	ga_ls8c_ard_3-2-1_114079_2022-08-26_final
2022-09-18 10:16:57	ga_ls8c_ard_3-2-1_099085_2022-09-18_final
2022-09-27 11:45:40	ga_ls8c_ard_3-2-1_114075_2022-09-27_final
2022-10-05 09:19:42	ga_ls8c_ard_3-2-1_090081_2022-10-04_final
2022-10-06 10:04:33	ga_ls8c_ard_3-2-1_097085_2022-10-06_final
2022-10-13 11:47:55	ga_ls8c_ard_3-2-1_114081_2022-10-13_final
2022-10-15 09:53:05	ga_ls8c_ard_3-2-1_096072_2022-10-15_final
2022-10-30 10:48:03	ga_ls8c_ard_3-2-1_105070_2022-10-30_final
2022-10-31 11:34:54	ga_ls8c_ard_3-2-1_112079_2022-10-31_final
2022-11-08 10:41:51	ga_ls8c_ard_3-2-1_104070_2022-11-08_final
2022-11-14 11:45:35	ga_ls8c_ard_3-2-1_114075_2022-11-14_final
2022-11-18 09:40:20	ga_ls8c_ard_3-2-1_094071_2022-11-18_final
2022-11-20 09:30:47	ga_ls8c_ard_3-2-1_092078_2022-11-20_final
2022-11-27 11:16:41	ga_ls8c_ard_3-2-1_109080_2022-11-27_final
2022-11-28 10:21:27	ga_ls8c_ard_3-2-1_100081_2022-11-28_final
2022-12-01 10:48:22	ga_ls8c_ard_3-2-1_105071_2022-12-01_final
2022-12-07 11:51:21	ga_ls8c_ard_3-2-1_115074_2022-12-07_final
2022-12-18 11:35:06	ga_ls8c_ard_3-2-1_112080_2022-12-18_final
2022-12-24 10:59:09	ga_ls8c_ard_3-2-1_106083_2022-12-24_final
2023-01-10 11:42:01	ga_ls8c_ard_3-2-1_113082_2023-01-10_final
2023-01-19 09:53:40	ga_ls8c_ard_3-2-1_096074_2023-01-19_final
2023-01-19 11:34:57	ga_ls8c_ard_3-2-1_112080_2023-01-19_final
2023-01-21 09:42:08	ga_ls8c_ard_3-2-1_094076_2023-01-21_final
2023-01-30 11:15:42	ga_ls8c_ard_3-2-1_109078_2023-01-30_final
2023-02-08 11:10:42	ga_ls8c_ard_3-2-1_108081_2023-02-08_final
2023-02-13 09:51:29	ga_ls8c_ard_3-2-1_095084_2023-02-13_final
2023-02-13 09:51:53	ga_ls8c_ard_3-2-1_095085_2023-02-13_final
2023-02-15 11:17:35	ga_ls8c_ard_3-2-1_109083_2023-02-15_final
2023-02-17 11:00:00	ga_ls8c_ard_3-2-1_107070_2023-02-17_final
2023-02-20 09:54:45	ga_ls8c_ard_3-2-1_096077_2023-02-20_final
2023-02-24 09:34:43	ga_ls8c_ard_3-2-1_092089_2023-02-24_final
2023-03-06 10:06:33	ga_ls8c_ard_3-2-1_098076_2023-03-06_final
2023-03-12 09:29:50	ga_ls8c_ard_3-2-1_092077_2023-03-11_final
2023-03-15 10:01:07	ga_ls8c_ard_3-2-1_097078_2023-03-15_final
2023-03-22 11:46:29	ga_ls8c_ard_3-2-1_114079_2023-03-22_final
2023-03-23 10:50:50	ga_ls8c_ard_3-2-1_105079_2023-03-23_final
2023-03-26 11:22:32	ga_ls8c_ard_3-2-1_110081_2023-03-26_final
2023-04-11 11:20:40	ga_ls8c_ard_3-2-1_110077_2023-04-11_final
2023-04-14 11:50:22	ga_ls8c_ard_3-2-1_115074_2023-04-14_final
2023-04-17 10:44:45	ga_ls8c_ard_3-2-1_104080_2023-04-17_final
2023-04-18 11:27:12	ga_ls8c_ard_3-2-1_111078_2023-04-18_final
2023-04-19 10:33:10	ga_ls8c_ard_3-2-1_102082_2023-04-19_final
2023-04-24 09:14:26	ga_ls8c_ard_3-2-1_089086_2023-04-23_final
2023-04-24 10:49:43	ga_ls8c_ard_3-2-1_105077_2023-04-24_final
2023-04-30 11:52:17	ga_ls8c_ard_3-2-1_115079_2023-04-30_final
2023-05-09 11:45:11	ga_ls8c_ard_3-2-1_114077_2023-05-09_final
2023-05-10 10:49:32	ga_ls8c_ard_3-2-1_105077_2023-05-10_final
2023-05-22 11:11:01	ga_ls8c_ard_3-2-1_109069_2023-05-22_final
2023-05-24 11:03:52	ga_ls8c_ard_3-2-1_107082_2023-05-24_final
2023-05-27 11:33:34	ga_ls8c_ard_3-2-1_112079_2023-05-27_final
2023-05-28 10:36:21	ga_ls8c_ard_3-2-1_103075_2023-05-28_final
2023-06-08 11:57:11	ga_ls8c_ard_3-2-1_116076_2023-06-08_final
2023-06-11 09:15:32	ga_ls8c_ard_3-2-1_089089_2023-06-10_final
2023-06-12 09:56:01	ga_ls8c_ard_3-2-1_096082_2023-06-12_final
2023-06-19 09:59:50	ga_ls8c_ard_3-2-1_097076_2023-06-19_final
2023-06-21 09:47:52	ga_ls8c_ard_3-2-1_095077_2023-06-21_final
2023-06-21 11:24:45	ga_ls8c_ard_3-2-1_111072_2023-06-21_final
2023-06-23 11:11:36	ga_ls8c_ard_3-2-1_109070_2023-06-23_final
2023-07-07 09:51:16	ga_ls8c_ard_3-2-1_095085_2023-07-07_final
2023-07-11 11:05:03	ga_ls8c_ard_3-2-1_107084_2023-07-11_final
2023-07-12 10:06:38	ga_ls8c_ard_3-2-1_098077_2023-07-12_final
2023-07-12 11:46:19	ga_ls8c_ard_3-2-1_114079_2023-07-12_final
2023-08-01 11:22:56	ga_ls8c_ard_3-2-1_110082_2023-08-01_final
2023-08-10 11:12:23	ga_ls8c_ard_3-2-1_109071_2023-08-10_final
2023-08-12 09:25:09	ga_ls8c_ard_3-2-1_091081_2023-08-11_final
2023-08-20 10:15:05	ga_ls8c_ard_3-2-1_099082_2023-08-20_final
2023-08-22 09:59:09	ga_ls8c_ard_3-2-1_097073_2023-08-22_final
2023-08-23 10:42:49	ga_ls8c_ard_3-2-1_104074_2023-08-23_final
2023-08-24 09:47:12	ga_ls8c_ard_3-2-1_095074_2023-08-24_final
2023-08-27 10:18:30	ga_ls8c_ard_3-2-1_100075_2023-08-27_final
2023-09-02 11:21:06	ga_ls8c_ard_3-2-1_110077_2023-09-02_final
2023-09-03 10:24:16	ga_ls8c_ard_3-2-1_101074_2023-09-03_final
2023-09-07 10:00:19	ga_ls8c_ard_3-2-1_097076_2023-09-07_final
2023-09-15 10:47:52	ga_ls8c_ard_3-2-1_105071_2023-09-15_final
2023-09-16 09:56:14	ga_ls8c_ard_3-2-1_096081_2023-09-16_final
2023-09-16 09:57:02	ga_ls8c_ard_3-2-1_096083_2023-09-16_final
2023-09-18 11:21:34	ga_ls8c_ard_3-2-1_110078_2023-09-18_final
2023-09-26 10:29:46	ga_ls8c_ard_3-2-1_102072_2023-09-26_final
2023-09-28 10:18:37	ga_ls8c_ard_3-2-1_100075_2023-09-28_final
2023-09-28 11:57:54	ga_ls8c_ard_3-2-1_116076_2023-09-28_final
2023-10-13 09:37:00	ga_ls8c_ard_3-2-1_093079_2023-10-13_final
2023-10-14 11:57:57	ga_ls8c_ard_3-2-1_116076_2023-10-14_final
2023-10-16 10:09:06	ga_ls8c_ard_3-2-1_098082_2023-10-16_final
2023-10-18 09:56:19	ga_ls8c_ard_3-2-1_096081_2023-10-18_final
2023-10-25 10:02:09	ga_ls8c_ard_3-2-1_097080_2023-10-25_final
2023-10-30 10:17:55	ga_ls8c_ard_3-2-1_100073_2023-10-30_final
2023-10-30 11:58:00	ga_ls8c_ard_3-2-1_116076_2023-10-30_final
2023-11-03 09:56:23	ga_ls8c_ard_3-2-1_096081_2023-11-03_final
2023-11-10 10:01:41	ga_ls8c_ard_3-2-1_097079_2023-11-10_final
2023-11-10 11:41:46	ga_ls8c_ard_3-2-1_113082_2023-11-10_final
2023-11-14 11:15:06	ga_ls8c_ard_3-2-1_109077_2023-11-14_final
2023-11-21 09:44:03	ga_ls8c_ard_3-2-1_094081_2023-11-21_final
2023-11-22 10:25:20	ga_ls8c_ard_3-2-1_101076_2023-11-22_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