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
2022-04-05 10:50:22	ga_ls8c_ard_3-2-1_105078_2022-04-05_final
2022-04-13 10:03:23	ga_ls8c_ard_3-2-1_097084_2022-04-13_final
2022-04-15 09:51:02	ga_ls8c_ard_3-2-1_095084_2022-04-15_final
2022-04-20 11:46:51	ga_ls8c_ard_3-2-1_114080_2022-04-20_final
2022-04-30 10:44:59	ga_ls8c_ard_3-2-1_104080_2022-04-30_final
2022-05-02 10:30:16	ga_ls8c_ard_3-2-1_102074_2022-05-02_final
2022-05-04 10:21:55	ga_ls8c_ard_3-2-1_100084_2022-05-04_final
2022-05-08 09:51:39	ga_ls8c_ard_3-2-1_096070_2022-05-08_final
2022-05-10 09:44:54	ga_ls8c_ard_3-2-1_094084_2022-05-10_final
2022-05-14 10:54:42	ga_ls8c_ard_3-2-1_106073_2022-05-14_final
2022-05-22 10:04:53	ga_ls8c_ard_3-2-1_098072_2022-05-22_final
2022-05-23 09:14:27	ga_ls8c_ard_3-2-1_089085_2022-05-22_final
2022-05-24 09:57:43	ga_ls8c_ard_3-2-1_096085_2022-05-24_final
2022-05-31 09:56:45	ga_ls8c_ard_3-2-1_097067_2022-05-31_final
2022-05-31 10:01:08	ga_ls8c_ard_3-2-1_097078_2022-05-31_final
2022-06-04 11:17:45	ga_ls8c_ard_3-2-1_109084_2022-06-04_final
2022-06-05 10:18:33	ga_ls8c_ard_3-2-1_100075_2022-06-05_final
2022-06-08 09:13:48	ga_ls8c_ard_3-2-1_089083_2022-06-07_final
2022-06-11 09:41:09	ga_ls8c_ard_3-2-1_094074_2022-06-11_final
2022-06-11 11:18:26	ga_ls8c_ard_3-2-1_110070_2022-06-11_final
2022-06-13 09:31:12	ga_ls8c_ard_3-2-1_092080_2022-06-13_final
2022-06-13 11:09:41	ga_ls8c_ard_3-2-1_108079_2022-06-13_final
2022-06-15 09:18:04	ga_ls8c_ard_3-2-1_090078_2022-06-14_final
2022-06-15 10:55:21	ga_ls8c_ard_3-2-1_106074_2022-06-15_final
2022-06-15 10:58:33	ga_ls8c_ard_3-2-1_106082_2022-06-15_final
2022-06-20 11:12:20	ga_ls8c_ard_3-2-1_109070_2022-06-20_final
2022-06-24 09:15:08	ga_ls8c_ard_3-2-1_089086_2022-06-23_final
2022-07-02 10:01:48	ga_ls8c_ard_3-2-1_097079_2022-07-02_final
2022-07-06 11:12:22	ga_ls8c_ard_3-2-1_109070_2022-07-06_final
2022-07-07 10:21:56	ga_ls8c_ard_3-2-1_100083_2022-07-07_final
2022-07-22 09:39:32	ga_ls8c_ard_3-2-1_093085_2022-07-22_final
2022-07-23 10:21:37	ga_ls8c_ard_3-2-1_100082_2022-07-23_final
2022-07-25 10:05:17	ga_ls8c_ard_3-2-1_098072_2022-07-25_final
2022-08-05 09:51:39	ga_ls8c_ard_3-2-1_095084_2022-08-05_final
2022-08-07 09:37:19	ga_ls8c_ard_3-2-1_093079_2022-08-07_final
2022-08-10 10:05:26	ga_ls8c_ard_3-2-1_098072_2022-08-10_final
2022-08-19 09:58:54	ga_ls8c_ard_3-2-1_097071_2022-08-19_final
2022-08-23 09:35:47	ga_ls8c_ard_3-2-1_093075_2022-08-23_final
2022-09-06 09:52:09	ga_ls8c_ard_3-2-1_095085_2022-09-06_final
2022-09-08 09:35:49	ga_ls8c_ard_3-2-1_093075_2022-09-08_final
2022-09-09 10:19:29	ga_ls8c_ard_3-2-1_100076_2022-09-09_final
2022-09-13 09:52:48	ga_ls8c_ard_3-2-1_096071_2022-09-13_final
2022-09-19 10:55:50	ga_ls8c_ard_3-2-1_106074_2022-09-19_final
2022-09-20 09:58:13	ga_ls8c_ard_3-2-1_097069_2022-09-20_final
2022-09-20 09:58:37	ga_ls8c_ard_3-2-1_097070_2022-09-20_final
2022-09-27 10:08:23	ga_ls8c_ard_3-2-1_098079_2022-09-27_final
2022-09-28 09:14:21	ga_ls8c_ard_3-2-1_089083_2022-09-27_final
2022-10-05 10:55:00	ga_ls8c_ard_3-2-1_106072_2022-10-05_final
2022-10-05 10:55:47	ga_ls8c_ard_3-2-1_106074_2022-10-05_final
2022-10-06 10:02:09	ga_ls8c_ard_3-2-1_097079_2022-10-06_final
2022-10-08 09:47:47	ga_ls8c_ard_3-2-1_095074_2022-10-08_final
2022-10-15 09:52:42	ga_ls8c_ard_3-2-1_096071_2022-10-15_final
2022-10-17 09:41:33	ga_ls8c_ard_3-2-1_094074_2022-10-17_final
2022-10-19 09:35:12	ga_ls8c_ard_3-2-1_092089_2022-10-19_final
2022-10-29 11:45:16	ga_ls8c_ard_3-2-1_114074_2022-10-29_final
2022-11-01 10:40:29	ga_ls8c_ard_3-2-1_103082_2022-11-01_final
2022-11-11 11:13:55	ga_ls8c_ard_3-2-1_109073_2022-11-11_final
2022-11-16 09:53:07	ga_ls8c_ard_3-2-1_096072_2022-11-16_final
2022-11-22 09:20:02	ga_ls8c_ard_3-2-1_090082_2022-11-21_final
2022-12-04 11:23:39	ga_ls8c_ard_3-2-1_110082_2022-12-04_final
2022-12-09 10:02:06	ga_ls8c_ard_3-2-1_097079_2022-12-09_final
2022-12-11 11:27:01	ga_ls8c_ard_3-2-1_111075_2022-12-11_final
2022-12-14 11:58:17	ga_ls8c_ard_3-2-1_116076_2022-12-14_final
2022-12-16 11:45:54	ga_ls8c_ard_3-2-1_114076_2022-12-16_final
2022-12-16 11:46:18	ga_ls8c_ard_3-2-1_114077_2022-12-16_final
2022-12-25 10:03:57	ga_ls8c_ard_3-2-1_097084_2022-12-25_final
2022-12-27 11:26:53	ga_ls8c_ard_3-2-1_111075_2022-12-27_final
2022-12-31 09:27:41	ga_ls8c_ard_3-2-1_091086_2022-12-30_final
2023-01-03 11:35:29	ga_ls8c_ard_3-2-1_112081_2023-01-03_final
2023-01-08 10:12:43	ga_ls8c_ard_3-2-1_099075_2023-01-08_final
2023-01-12 09:47:34	ga_ls8c_ard_3-2-1_095074_2023-01-12_final
2023-01-16 09:28:46	ga_ls8c_ard_3-2-1_091089_2023-01-15_final
2023-01-18 09:14:23	ga_ls8c_ard_3-2-1_089084_2023-01-17_final
2023-01-18 10:50:28	ga_ls8c_ard_3-2-1_105077_2023-01-18_final
2023-01-20 10:34:57	ga_ls8c_ard_3-2-1_103069_2023-01-20_final
2023-01-23 11:06:18	ga_ls8c_ard_3-2-1_108070_2023-01-23_final
2023-01-26 09:59:56	ga_ls8c_ard_3-2-1_097074_2023-01-26_final
2023-02-05 10:35:01	ga_ls8c_ard_3-2-1_103069_2023-02-05_final
2023-02-06 09:44:35	ga_ls8c_ard_3-2-1_094082_2023-02-06_final
2023-02-10 09:20:37	ga_ls8c_ard_3-2-1_090084_2023-02-09_final
2023-02-13 09:47:29	ga_ls8c_ard_3-2-1_095074_2023-02-13_final
2023-02-19 09:15:06	ga_ls8c_ard_3-2-1_089086_2023-02-18_final
2023-02-19 10:52:47	ga_ls8c_ard_3-2-1_105083_2023-02-19_final
2023-03-01 09:47:15	ga_ls8c_ard_3-2-1_095074_2023-03-01_final
2023-03-01 09:51:39	ga_ls8c_ard_3-2-1_095085_2023-03-01_final
2023-03-06 10:06:57	ga_ls8c_ard_3-2-1_098077_2023-03-06_final
2023-03-14 10:54:21	ga_ls8c_ard_3-2-1_106072_2023-03-14_final
2023-03-27 10:24:06	ga_ls8c_ard_3-2-1_101074_2023-03-27_final
2023-03-29 10:16:07	ga_ls8c_ard_3-2-1_099085_2023-03-29_final
2023-03-30 09:18:54	ga_ls8c_ard_3-2-1_090081_2023-03-29_final
2023-03-31 10:00:57	ga_ls8c_ard_3-2-1_097078_2023-03-31_final
2023-04-04 09:35:46	ga_ls8c_ard_3-2-1_093077_2023-04-04_final
2023-04-06 11:01:51	ga_ls8c_ard_3-2-1_107076_2023-04-06_final
2023-04-27 09:40:08	ga_ls8c_ard_3-2-1_094073_2023-04-27_final
2023-05-01 10:57:51	ga_ls8c_ard_3-2-1_106082_2023-05-01_final
2023-05-04 09:46:38	ga_ls8c_ard_3-2-1_095074_2023-05-04_final
2023-05-05 10:30:17	ga_ls8c_ard_3-2-1_102075_2023-05-05_final
2023-05-06 11:11:56	ga_ls8c_ard_3-2-1_109071_2023-05-06_final
2023-05-06 11:12:44	ga_ls8c_ard_3-2-1_109073_2023-05-06_final
2023-05-07 10:18:18	ga_ls8c_ard_3-2-1_100076_2023-05-07_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