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
2021-10-21 09:52:25	ga_ls8c_ard_3-2-0_095086_2021-10-21_final
2021-11-06 11:26:06	ga_ls8c_ard_3-2-0_111073_2021-11-06_final
2021-11-16 10:23:02	ga_ls8c_ard_3-2-0_101070_2021-11-16_final
2021-11-20 10:04:17	ga_ls8c_ard_3-2-0_097085_2021-11-20_final
2021-12-10 11:14:29	ga_ls8c_ard_3-2-1_109075_2021-12-10_final
2021-12-11 10:19:39	ga_ls8c_ard_3-2-1_100077_2021-12-11_final
2021-12-17 11:19:51	ga_ls8c_ard_3-2-1_110073_2021-12-17_final
2022-01-05 11:52:15	ga_ls8c_ard_3-2-1_115077_2022-01-05_final
2022-01-06 10:53:26	ga_ls8c_ard_3-2-1_106069_2022-01-06_final
2022-01-09 11:26:19	ga_ls8c_ard_3-2-1_111074_2022-01-09_final
2022-01-18 11:19:19	ga_ls8c_ard_3-2-1_110072_2022-01-18_final
2022-01-23 09:58:08	ga_ls8c_ard_3-2-1_097070_2022-01-23_final
2022-01-31 09:13:51	ga_ls8c_ard_3-2-1_089083_2022-01-30_final
2022-02-03 11:18:27	ga_ls8c_ard_3-2-1_110070_2022-02-03_final
2022-02-08 10:02:28	ga_ls8c_ard_3-2-1_097081_2022-02-08_final
2022-02-18 10:39:53	ga_ls8c_ard_3-2-1_103082_2022-02-18_final
2022-02-19 11:19:57	ga_ls8c_ard_3-2-1_110074_2022-02-19_final
2022-02-24 11:40:52	ga_ls8c_ard_3-2-1_113080_2022-02-24_final
2022-03-01 11:58:36	ga_ls8c_ard_3-2-1_116078_2022-03-01_final
2022-03-02 09:28:29	ga_ls8c_ard_3-2-1_091089_2022-03-01_final
2022-03-05 09:51:48	ga_ls8c_ard_3-2-1_096070_2022-03-05_final
2022-03-08 10:27:28	ga_ls8c_ard_3-2-1_101082_2022-03-08_final
2022-03-09 11:07:08	ga_ls8c_ard_3-2-1_108073_2022-03-09_final
2022-03-18 09:27:58	ga_ls8c_ard_3-2-1_091088_2022-03-17_final
2022-03-25 11:08:09	ga_ls8c_ard_3-2-1_108076_2022-03-25_final
2022-04-05 09:15:52	ga_ls8c_ard_3-2-1_089089_2022-04-04_final
2022-06-04 09:37:40	ga_ls8c_ard_3-2-1_093081_2022-06-04_final
2022-06-06 09:25:20	ga_ls8c_ard_3-2-1_091081_2022-06-05_final
2022-06-12 10:28:01	ga_ls8c_ard_3-2-1_101083_2022-06-12_final
2022-06-24 10:46:26	ga_ls8c_ard_3-2-1_105067_2022-06-24_final
2022-06-27 11:20:56	ga_ls8c_ard_3-2-1_110076_2022-06-27_final
2022-06-28 10:28:07	ga_ls8c_ard_3-2-1_101083_2022-06-28_final
2022-07-10 10:46:51	ga_ls8c_ard_3-2-1_105068_2022-07-10_final
2022-07-15 11:07:46	ga_ls8c_ard_3-2-1_108074_2022-07-15_final
2022-07-24 09:27:36	ga_ls8c_ard_3-2-1_091086_2022-07-23_final
2022-08-03 11:41:17	ga_ls8c_ard_3-2-1_113080_2022-08-03_final
2022-08-08 11:58:40	ga_ls8c_ard_3-2-1_116077_2022-08-08_final
2022-08-19 09:57:42	ga_ls8c_ard_3-2-1_097068_2022-08-19_final
2022-08-27 09:12:15	ga_ls8c_ard_3-2-1_089078_2022-08-26_final
2022-09-03 10:59:18	ga_ls8c_ard_3-2-1_106083_2022-09-03_final
2022-09-04 10:02:54	ga_ls8c_ard_3-2-1_097081_2022-09-04_final
2022-09-17 09:32:53	ga_ls8c_ard_3-2-1_092083_2022-09-17_final
2022-09-18 11:53:27	ga_ls8c_ard_3-2-1_115079_2022-09-18_final
2022-10-01 09:45:39	ga_ls8c_ard_3-2-1_094084_2022-10-01_final
2022-10-01 11:20:32	ga_ls8c_ard_3-2-1_110074_2022-10-01_final
2022-10-02 10:23:43	ga_ls8c_ard_3-2-1_101071_2022-10-02_final
2022-10-03 11:06:10	ga_ls8c_ard_3-2-1_108069_2022-10-03_final
2022-10-08 11:25:28	ga_ls8c_ard_3-2-1_111071_2022-10-08_final
2022-10-15 09:53:53	ga_ls8c_ard_3-2-1_096074_2022-10-15_final
2022-10-17 09:46:21	ga_ls8c_ard_3-2-1_094086_2022-10-17_final
2022-10-20 11:52:58	ga_ls8c_ard_3-2-1_115078_2022-10-20_final
2022-10-22 09:57:22	ga_ls8c_ard_3-2-1_097067_2022-10-22_final
2022-10-24 09:47:01	ga_ls8c_ard_3-2-1_095072_2022-10-24_final
2022-11-05 10:10:34	ga_ls8c_ard_3-2-1_099069_2022-11-05_final
2022-11-23 09:58:07	ga_ls8c_ard_3-2-1_097069_2022-11-23_final
2022-12-01 10:46:46	ga_ls8c_ard_3-2-1_105067_2022-12-01_final
2022-12-04 09:46:46	ga_ls8c_ard_3-2-1_094087_2022-12-04_final
2022-12-04 11:21:16	ga_ls8c_ard_3-2-1_110076_2022-12-04_final
2022-12-17 09:12:35	ga_ls8c_ard_3-2-1_089079_2022-12-16_final
2023-01-07 09:34:39	ga_ls8c_ard_3-2-1_092088_2023-01-07_final
2023-01-07 11:06:21	ga_ls8c_ard_3-2-1_108070_2023-01-07_final
2023-01-13 10:29:37	ga_ls8c_ard_3-2-1_102071_2023-01-13_final
2023-01-14 09:36:22	ga_ls8c_ard_3-2-1_093077_2023-01-14_final
2023-01-15 10:19:37	ga_ls8c_ard_3-2-1_100077_2023-01-15_final
2023-01-23 11:07:06	ga_ls8c_ard_3-2-1_108072_2023-01-23_final
2023-01-25 10:53:57	ga_ls8c_ard_3-2-1_106070_2023-01-25_final
2023-01-25 10:59:08	ga_ls8c_ard_3-2-1_106083_2023-01-25_final
2023-02-03 09:14:06	ga_ls8c_ard_3-2-1_089083_2023-02-02_final
2023-02-17 09:25:31	ga_ls8c_ard_3-2-1_091081_2023-02-16_final
2023-02-19 10:52:23	ga_ls8c_ard_3-2-1_105082_2023-02-19_final
2023-03-13 10:13:30	ga_ls8c_ard_3-2-1_099078_2023-03-13_final
2023-03-23 09:11:58	ga_ls8c_ard_3-2-1_089079_2023-03-22_final
2023-03-24 09:51:37	ga_ls8c_ard_3-2-1_096070_2023-03-24_final
2023-03-30 09:20:29	ga_ls8c_ard_3-2-1_090085_2023-03-29_final
2023-03-30 10:57:47	ga_ls8c_ard_3-2-1_106081_2023-03-30_final
2023-03-31 09:57:21	ga_ls8c_ard_3-2-1_097069_2023-03-31_final
2023-03-31 11:40:38	ga_ls8c_ard_3-2-1_113080_2023-03-31_final
2023-04-06 09:22:34	ga_ls8c_ard_3-2-1_091075_2023-04-05_final
2023-04-06 09:25:45	ga_ls8c_ard_3-2-1_091083_2023-04-05_final
2023-04-29 11:05:26	ga_ls8c_ard_3-2-1_108070_2023-04-29_final
2023-05-06 11:11:32	ga_ls8c_ard_3-2-1_109070_2023-05-06_final
2023-05-09 11:43:59	ga_ls8c_ard_3-2-1_114074_2023-05-09_final
2023-05-12 10:39:08	ga_ls8c_ard_3-2-1_103082_2023-05-12_final
2023-05-15 11:04:49	ga_ls8c_ard_3-2-1_108069_2023-05-15_final
2023-05-18 11:40:06	ga_ls8c_ard_3-2-1_113080_2023-05-18_final
2023-05-23 10:19:00	ga_ls8c_ard_3-2-1_100078_2023-05-23_final
2023-05-24 09:27:22	ga_ls8c_ard_3-2-1_091088_2023-05-23_final
2023-05-30 10:27:11	ga_ls8c_ard_3-2-1_101083_2023-05-30_final
2023-06-02 09:21:12	ga_ls8c_ard_3-2-1_090088_2023-06-01_final
2023-06-08 10:21:06	ga_ls8c_ard_3-2-1_100083_2023-06-08_final
2023-06-14 11:18:58	ga_ls8c_ard_3-2-1_110073_2023-06-14_final
2023-06-16 11:05:01	ga_ls8c_ard_3-2-1_108069_2023-06-16_final
2023-06-19 10:01:25	ga_ls8c_ard_3-2-1_097080_2023-06-19_final
2023-06-23 11:13:36	ga_ls8c_ard_3-2-1_109075_2023-06-23_final
2023-07-09 09:39:43	ga_ls8c_ard_3-2-1_093087_2023-07-09_final
2023-07-16 09:39:32	ga_ls8c_ard_3-2-1_094071_2023-07-16_final
2023-07-28 11:46:26	ga_ls8c_ard_3-2-1_114079_2023-07-28_final
2023-08-01 11:20:33	ga_ls8c_ard_3-2-1_110076_2023-08-01_final
2023-08-20 10:09:30	ga_ls8c_ard_3-2-1_099068_2023-08-20_final
2023-08-30 09:11:19	ga_ls8c_ard_3-2-1_089077_2023-08-29_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