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
2018-08-17 09:54:49	ga_ls8c_ard_3-0-0_096079_2018-08-17_final
2018-08-17 09:55:13	ga_ls8c_ard_3-0-0_096080_2018-08-17_final
2018-08-17 11:33:42	ga_ls8c_ard_3-0-0_112079_2018-08-17_final
2018-08-17 11:34:06	ga_ls8c_ard_3-0-0_112080_2018-08-17_final
2018-08-18 10:38:06	ga_ls8c_ard_3-0-0_103079_2018-08-18_final
2018-08-18 10:38:30	ga_ls8c_ard_3-0-0_103080_2018-08-18_final
2018-08-19 09:42:29	ga_ls8c_ard_3-0-0_094079_2018-08-19_final
2018-08-19 09:42:53	ga_ls8c_ard_3-0-0_094080_2018-08-19_final
2018-08-19 11:21:22	ga_ls8c_ard_3-0-0_110079_2018-08-19_final
2018-08-19 11:21:46	ga_ls8c_ard_3-0-0_110080_2018-08-19_final
2018-08-20 10:25:45	ga_ls8c_ard_3-0-0_101079_2018-08-20_final
2018-08-20 10:26:09	ga_ls8c_ard_3-0-0_101080_2018-08-20_final
2018-09-02 09:54:56	ga_ls8c_ard_3-0-0_096079_2018-09-02_final
2018-09-02 09:55:20	ga_ls8c_ard_3-0-0_096080_2018-09-02_final
2018-09-02 11:33:49	ga_ls8c_ard_3-0-0_112079_2018-09-02_final
2018-09-02 11:34:13	ga_ls8c_ard_3-0-0_112080_2018-09-02_final
2018-09-03 10:38:12	ga_ls8c_ard_3-0-0_103079_2018-09-03_final
2018-09-03 10:38:36	ga_ls8c_ard_3-0-0_103080_2018-09-03_final
2018-09-04 09:42:35	ga_ls8c_ard_3-0-0_094079_2018-09-04_final
2018-09-04 09:42:59	ga_ls8c_ard_3-0-0_094080_2018-09-04_final
2018-09-04 11:21:28	ga_ls8c_ard_3-0-0_110079_2018-09-04_final
2018-09-04 11:21:52	ga_ls8c_ard_3-0-0_110080_2018-09-04_final
2018-09-05 10:25:51	ga_ls8c_ard_3-0-0_101079_2018-09-05_final
2018-09-05 10:26:15	ga_ls8c_ard_3-0-0_101080_2018-09-05_final
2018-09-16 10:07:22	ga_ls8c_ard_3-0-0_098079_2018-09-16_final
2018-09-16 10:07:46	ga_ls8c_ard_3-0-0_098080_2018-09-16_final
2018-09-16 11:46:15	ga_ls8c_ard_3-0-0_114079_2018-09-16_final
2018-09-16 11:46:39	ga_ls8c_ard_3-0-0_114080_2018-09-16_final
2018-09-17 09:11:45	ga_ls8c_ard_3-0-0_089079_2018-09-16_final
2018-09-17 09:12:09	ga_ls8c_ard_3-0-0_089080_2018-09-16_final
2018-09-17 10:50:38	ga_ls8c_ard_3-0-0_105079_2018-09-17_final
2018-09-17 10:51:02	ga_ls8c_ard_3-0-0_105080_2018-09-17_final
2019-01-06 10:07:36	ga_ls8c_ard_3-0-0_098079_2019-01-06_final
2019-01-06 10:08:00	ga_ls8c_ard_3-0-0_098080_2019-01-06_final
2019-01-06 11:46:29	ga_ls8c_ard_3-0-0_114079_2019-01-06_final
2019-01-06 11:46:53	ga_ls8c_ard_3-0-0_114080_2019-01-06_final
2019-01-07 09:11:59	ga_ls8c_ard_3-0-0_089079_2019-01-06_final
2019-01-07 09:12:23	ga_ls8c_ard_3-0-0_089080_2019-01-06_final
2019-01-07 10:50:52	ga_ls8c_ard_3-0-0_105079_2019-01-07_final
2019-01-07 10:51:16	ga_ls8c_ard_3-0-0_105080_2019-01-07_final
2023-03-23 10:50:50	ga_ls8c_ard_3-2-1_105079_2023-03-23_final
2023-03-23 10:51:14	ga_ls8c_ard_3-2-1_105080_2023-03-23_final
2023-03-24 09:55:13	ga_ls8c_ard_3-2-1_096079_2023-03-24_final
2023-03-24 09:55:37	ga_ls8c_ard_3-2-1_096080_2023-03-24_final
2023-03-24 11:34:06	ga_ls8c_ard_3-2-1_112079_2023-03-24_final
2023-03-24 11:34:30	ga_ls8c_ard_3-2-1_112080_2023-03-24_final
2023-03-25 10:38:28	ga_ls8c_ard_3-2-1_103079_2023-03-25_final
2023-03-25 10:38:52	ga_ls8c_ard_3-2-1_103080_2023-03-25_final
2023-03-26 09:42:51	ga_ls8c_ard_3-2-1_094079_2023-03-26_final
2023-03-26 09:43:15	ga_ls8c_ard_3-2-1_094080_2023-03-26_final
2023-03-26 11:21:44	ga_ls8c_ard_3-2-1_110079_2023-03-26_final
2023-03-26 11:22:08	ga_ls8c_ard_3-2-1_110080_2023-03-26_final
2023-03-29 10:13:44	ga_ls8c_ard_3-2-1_099079_2023-03-29_final
2023-03-29 10:14:08	ga_ls8c_ard_3-2-1_099080_2023-03-29_final
2023-03-29 11:52:37	ga_ls8c_ard_3-2-1_115079_2023-03-29_final
2023-03-29 11:53:01	ga_ls8c_ard_3-2-1_115080_2023-03-29_final
2023-03-30 09:18:06	ga_ls8c_ard_3-2-1_090079_2023-03-29_final
2023-03-30 09:18:30	ga_ls8c_ard_3-2-1_090080_2023-03-29_final
2023-04-06 09:24:33	ga_ls8c_ard_3-2-1_091080_2023-04-05_final
2023-04-06 11:03:02	ga_ls8c_ard_3-2-1_107079_2023-04-06_final
2023-04-06 11:03:26	ga_ls8c_ard_3-2-1_107080_2023-04-06_final
2023-04-08 10:50:38	ga_ls8c_ard_3-2-1_105079_2023-04-08_final
2023-04-08 10:51:02	ga_ls8c_ard_3-2-1_105080_2023-04-08_final
2023-04-09 09:54:59	ga_ls8c_ard_3-2-1_096079_2023-04-09_final
2023-04-09 09:55:23	ga_ls8c_ard_3-2-1_096080_2023-04-09_final
2023-04-14 10:13:28	ga_ls8c_ard_3-2-1_099079_2023-04-14_final
2023-04-14 10:13:52	ga_ls8c_ard_3-2-1_099080_2023-04-14_final
2023-04-14 11:52:21	ga_ls8c_ard_3-2-1_115079_2023-04-14_final
2023-04-14 11:52:45	ga_ls8c_ard_3-2-1_115080_2023-04-14_final
2023-04-15 09:17:51	ga_ls8c_ard_3-2-1_090079_2023-04-14_final
2023-04-15 09:18:15	ga_ls8c_ard_3-2-1_090080_2023-04-14_final
2023-04-15 10:56:44	ga_ls8c_ard_3-2-1_106079_2023-04-15_final
2023-04-15 10:57:08	ga_ls8c_ard_3-2-1_106080_2023-04-15_final
2023-04-20 11:15:14	ga_ls8c_ard_3-2-1_109079_2023-04-20_final
2023-04-20 11:15:37	ga_ls8c_ard_3-2-1_109080_2023-04-20_final
2023-04-21 10:19:36	ga_ls8c_ard_3-2-1_100079_2023-04-21_final
2023-04-21 10:20:00	ga_ls8c_ard_3-2-1_100080_2023-04-21_final
2023-04-24 09:11:38	ga_ls8c_ard_3-2-1_089079_2023-04-23_final
2023-04-24 09:12:02	ga_ls8c_ard_3-2-1_089080_2023-04-23_final
2023-04-24 10:50:31	ga_ls8c_ard_3-2-1_105079_2023-04-24_final
2023-04-24 10:50:55	ga_ls8c_ard_3-2-1_105080_2023-04-24_final
2023-04-25 09:54:54	ga_ls8c_ard_3-2-1_096079_2023-04-25_final
2023-04-25 09:55:17	ga_ls8c_ard_3-2-1_096080_2023-04-25_final
2023-04-27 11:21:24	ga_ls8c_ard_3-2-1_110079_2023-04-27_final
2023-04-27 11:21:48	ga_ls8c_ard_3-2-1_110080_2023-04-27_final
2023-04-28 10:25:47	ga_ls8c_ard_3-2-1_101079_2023-04-28_final
2023-04-28 10:26:11	ga_ls8c_ard_3-2-1_101080_2023-04-28_final
2023-05-01 10:56:39	ga_ls8c_ard_3-2-1_106079_2023-05-01_final
2023-05-01 10:57:03	ga_ls8c_ard_3-2-1_106080_2023-05-01_final
2023-05-02 10:01:01	ga_ls8c_ard_3-2-1_097079_2023-05-02_final
2023-05-02 10:01:25	ga_ls8c_ard_3-2-1_097080_2023-05-02_final
2023-05-02 11:39:54	ga_ls8c_ard_3-2-1_113079_2023-05-02_final
2023-05-02 11:40:18	ga_ls8c_ard_3-2-1_113080_2023-05-02_final
2023-05-08 09:23:51	ga_ls8c_ard_3-2-1_091079_2023-05-07_final
2023-05-08 09:24:15	ga_ls8c_ard_3-2-1_091080_2023-05-07_final
2023-07-26 10:19:53	ga_ls8c_ard_3-2-1_100079_2023-07-26_final
2023-07-26 10:20:17	ga_ls8c_ard_3-2-1_100080_2023-07-26_final
2023-07-27 09:24:16	ga_ls8c_ard_3-2-1_091079_2023-07-26_final
2023-07-27 09:24:40	ga_ls8c_ard_3-2-1_091080_2023-07-26_final
2023-07-27 11:03:09	ga_ls8c_ard_3-2-1_107079_2023-07-27_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