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
2022-01-14 10:06:46	ga_ls8c_ard_3-2-1_098076_2022-01-14_final
2022-05-26 09:46:08	ga_ls8c_ard_3-2-1_094087_2022-05-26_final
2022-05-28 11:08:16	ga_ls8c_ard_3-2-1_108076_2022-05-28_final
2022-06-01 10:40:25	ga_ls8c_ard_3-2-1_104068_2022-06-01_final
2022-06-06 09:25:44	ga_ls8c_ard_3-2-1_091082_2022-06-05_final
2022-06-06 09:26:56	ga_ls8c_ard_3-2-1_091085_2022-06-05_final
2022-06-11 09:41:09	ga_ls8c_ard_3-2-1_094074_2022-06-11_final
2022-06-13 09:32:48	ga_ls8c_ard_3-2-1_092084_2022-06-13_final
2022-06-15 09:21:16	ga_ls8c_ard_3-2-1_090086_2022-06-14_final
2022-06-15 10:53:22	ga_ls8c_ard_3-2-1_106069_2022-06-15_final
2022-06-16 11:41:01	ga_ls8c_ard_3-2-1_113080_2022-06-16_final
2022-06-19 10:28:40	ga_ls8c_ard_3-2-1_102069_2022-06-19_final
2022-06-24 09:13:32	ga_ls8c_ard_3-2-1_089082_2022-06-23_final
2022-06-28 10:25:43	ga_ls8c_ard_3-2-1_101077_2022-06-28_final
2022-07-09 10:07:11	ga_ls8c_ard_3-2-1_098077_2022-07-09_final
2022-07-09 11:46:52	ga_ls8c_ard_3-2-1_114079_2022-07-09_final
2022-07-17 09:21:19	ga_ls8c_ard_3-2-1_090086_2022-07-16_final
2022-07-18 09:58:13	ga_ls8c_ard_3-2-1_097070_2022-07-18_final
2022-07-19 10:40:42	ga_ls8c_ard_3-2-1_104068_2022-07-19_final
2022-07-23 10:17:38	ga_ls8c_ard_3-2-1_100072_2022-07-23_final
2022-07-26 09:11:41	ga_ls8c_ard_3-2-1_089077_2022-07-25_final
2022-07-27 11:36:14	ga_ls8c_ard_3-2-1_112083_2022-07-27_final
2022-07-31 11:06:46	ga_ls8c_ard_3-2-1_108071_2022-07-31_final
2022-08-01 10:14:44	ga_ls8c_ard_3-2-1_099080_2022-08-01_final
2022-08-02 09:20:43	ga_ls8c_ard_3-2-1_090084_2022-08-01_final
2022-08-16 11:06:52	ga_ls8c_ard_3-2-1_108071_2022-08-16_final
2022-08-24 11:58:19	ga_ls8c_ard_3-2-1_116076_2022-08-24_final
2022-08-25 11:00:42	ga_ls8c_ard_3-2-1_107071_2022-08-25_final
2022-08-31 10:26:01	ga_ls8c_ard_3-2-1_101077_2022-08-31_final
2022-09-01 11:06:52	ga_ls8c_ard_3-2-1_108071_2022-09-01_final
2022-09-03 10:55:19	ga_ls8c_ard_3-2-1_106073_2022-09-03_final
2022-09-03 10:58:06	ga_ls8c_ard_3-2-1_106080_2022-09-03_final
2022-09-08 11:13:54	ga_ls8c_ard_3-2-1_109073_2022-09-08_final
2022-09-15 09:41:15	ga_ls8c_ard_3-2-1_094073_2022-09-15_final
2022-09-16 10:23:43	ga_ls8c_ard_3-2-1_101071_2022-09-16_final
2022-09-17 11:11:46	ga_ls8c_ard_3-2-1_108083_2022-09-17_final
2022-09-24 09:37:53	ga_ls8c_ard_3-2-1_093080_2022-09-24_final
2022-09-24 09:39:29	ga_ls8c_ard_3-2-1_093084_2022-09-24_final
2022-10-01 09:44:51	ga_ls8c_ard_3-2-1_094082_2022-10-01_final
2022-10-01 09:45:39	ga_ls8c_ard_3-2-1_094084_2022-10-01_final
2022-10-06 09:58:58	ga_ls8c_ard_3-2-1_097071_2022-10-06_final
2022-10-06 10:00:10	ga_ls8c_ard_3-2-1_097074_2022-10-06_final
2022-10-09 10:29:50	ga_ls8c_ard_3-2-1_102071_2022-10-09_final
2022-10-19 11:07:42	ga_ls8c_ard_3-2-1_108073_2022-10-19_final
2022-10-20 11:53:22	ga_ls8c_ard_3-2-1_115079_2022-10-20_final
2022-10-22 10:02:09	ga_ls8c_ard_3-2-1_097079_2022-10-22_final
2022-11-04 09:34:06	ga_ls8c_ard_3-2-1_092086_2022-11-04_final
2022-11-05 10:13:22	ga_ls8c_ard_3-2-1_099076_2022-11-05_final
2022-11-10 10:32:16	ga_ls8c_ard_3-2-1_102077_2022-11-10_final
2022-11-11 09:35:26	ga_ls8c_ard_3-2-1_093074_2022-11-11_final
2022-11-11 11:15:07	ga_ls8c_ard_3-2-1_109076_2022-11-11_final
2022-11-15 09:13:04	ga_ls8c_ard_3-2-1_089080_2022-11-14_final
2022-11-23 09:58:54	ga_ls8c_ard_3-2-1_097071_2022-11-23_final
2022-11-25 11:25:26	ga_ls8c_ard_3-2-1_111071_2022-11-25_final
2022-11-29 09:25:26	ga_ls8c_ard_3-2-1_091080_2022-11-28_final
2022-12-04 11:23:39	ga_ls8c_ard_3-2-1_110082_2022-12-04_final
2022-12-08 10:55:44	ga_ls8c_ard_3-2-1_106074_2022-12-08_final
2022-12-13 09:35:21	ga_ls8c_ard_3-2-1_093074_2022-12-13_final
2022-12-13 11:16:14	ga_ls8c_ard_3-2-1_109079_2022-12-13_final
2022-12-22 09:31:26	ga_ls8c_ard_3-2-1_092080_2022-12-22_final
2022-12-22 11:06:44	ga_ls8c_ard_3-2-1_108071_2022-12-22_final
2022-12-22 11:08:19	ga_ls8c_ard_3-2-1_108075_2022-12-22_final
2022-12-25 09:58:21	ga_ls8c_ard_3-2-1_097070_2022-12-25_final
2022-12-25 11:39:14	ga_ls8c_ard_3-2-1_113075_2022-12-25_final
2022-12-30 11:59:00	ga_ls8c_ard_3-2-1_116078_2022-12-30_final
2023-01-07 09:33:03	ga_ls8c_ard_3-2-1_092084_2023-01-07_final
2023-01-14 11:14:51	ga_ls8c_ard_3-2-1_109076_2023-01-14_final
2023-01-16 09:29:10	ga_ls8c_ard_3-2-1_091090_2023-01-15_final
2023-01-17 11:47:42	ga_ls8c_ard_3-2-1_114081_2023-01-17_final
2023-01-19 09:57:40	ga_ls8c_ard_3-2-1_096084_2023-01-19_final
2023-01-21 09:45:20	ga_ls8c_ard_3-2-1_094084_2023-01-21_final
2023-01-21 11:21:02	ga_ls8c_ard_3-2-1_110076_2023-01-21_final
2023-01-23 09:33:24	ga_ls8c_ard_3-2-1_092085_2023-01-23_final
2023-01-30 11:15:18	ga_ls8c_ard_3-2-1_109077_2023-01-30_final
2023-02-13 09:52:17	ga_ls8c_ard_3-2-1_095086_2023-02-13_final
2023-02-17 11:02:00	ga_ls8c_ard_3-2-1_107075_2023-02-17_final
2023-02-23 10:23:59	ga_ls8c_ard_3-2-1_101073_2023-02-23_final
2023-02-23 10:25:35	ga_ls8c_ard_3-2-1_101077_2023-02-23_final
2023-03-07 09:13:19	ga_ls8c_ard_3-2-1_089082_2023-03-06_final
2023-03-12 09:29:02	ga_ls8c_ard_3-2-1_092075_2023-03-11_final
2023-03-26 11:19:20	ga_ls8c_ard_3-2-1_110073_2023-03-26_final
2023-04-01 10:43:24	ga_ls8c_ard_3-2-1_104076_2023-04-01_final
2023-04-02 11:24:39	ga_ls8c_ard_3-2-1_111071_2023-04-02_final
2023-04-08 09:11:45	ga_ls8c_ard_3-2-1_089079_2023-04-07_final
2023-04-08 10:47:02	ga_ls8c_ard_3-2-1_105070_2023-04-08_final
2023-04-09 11:35:52	ga_ls8c_ard_3-2-1_112084_2023-04-09_final
2023-04-15 10:57:56	ga_ls8c_ard_3-2-1_106082_2023-04-15_final
2023-04-24 10:46:56	ga_ls8c_ard_3-2-1_105070_2023-04-24_final
2023-04-25 09:51:42	ga_ls8c_ard_3-2-1_096071_2023-04-25_final
2023-04-25 09:52:30	ga_ls8c_ard_3-2-1_096073_2023-04-25_final
2023-04-27 11:20:13	ga_ls8c_ard_3-2-1_110076_2023-04-27_final
2023-05-02 09:57:50	ga_ls8c_ard_3-2-1_097071_2023-05-02_final
2023-05-05 10:32:17	ga_ls8c_ard_3-2-1_102080_2023-05-05_final
2023-05-08 09:26:15	ga_ls8c_ard_3-2-1_091085_2023-05-07_final
2023-05-09 11:45:59	ga_ls8c_ard_3-2-1_114079_2023-05-09_final
2023-05-10 09:14:15	ga_ls8c_ard_3-2-1_089086_2023-05-09_final
2023-05-11 09:57:05	ga_ls8c_ard_3-2-1_096085_2023-05-11_final
2023-05-14 10:24:22	ga_ls8c_ard_3-2-1_101076_2023-05-14_final
2023-05-16 11:50:28	ga_ls8c_ard_3-2-1_115075_2023-05-16_final
2023-05-17 10:52:51	ga_ls8c_ard_3-2-1_106070_2023-05-17_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