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
2022-05-02 10:31:51	ga_ls8c_ard_3-2-1_102078_2022-05-02_final
2022-05-08 11:34:08	ga_ls8c_ard_3-2-1_112079_2022-05-08_final
2022-05-11 10:26:11	ga_ls8c_ard_3-2-1_101079_2022-05-11_final
2022-05-12 11:09:03	ga_ls8c_ard_3-2-1_108078_2022-05-12_final
2022-05-15 11:39:34	ga_ls8c_ard_3-2-1_113077_2022-05-15_final
2022-05-28 11:08:40	ga_ls8c_ard_3-2-1_108077_2022-05-28_final
2022-06-06 11:04:13	ga_ls8c_ard_3-2-1_107081_2022-06-06_final
2022-06-25 11:33:42	ga_ls8c_ard_3-2-1_112077_2022-06-25_final
2022-06-29 11:09:23	ga_ls8c_ard_3-2-1_108078_2022-06-29_final
2022-07-11 11:33:42	ga_ls8c_ard_3-2-1_112077_2022-07-11_final
2022-07-18 11:39:30	ga_ls8c_ard_3-2-1_113076_2022-07-18_final
2022-07-27 11:34:14	ga_ls8c_ard_3-2-1_112078_2022-07-27_final
2022-07-29 09:43:01	ga_ls8c_ard_3-2-1_094078_2022-07-29_final
2022-08-05 09:49:15	ga_ls8c_ard_3-2-1_095078_2022-08-05_final
2022-08-05 11:28:08	ga_ls8c_ard_3-2-1_111078_2022-08-05_final
2022-08-06 10:31:44	ga_ls8c_ard_3-2-1_102076_2022-08-06_final
2022-08-06 10:32:32	ga_ls8c_ard_3-2-1_102078_2022-08-06_final
2022-08-12 11:33:58	ga_ls8c_ard_3-2-1_112077_2022-08-12_final
2022-08-14 09:43:08	ga_ls8c_ard_3-2-1_094078_2022-08-14_final
2022-08-14 11:22:25	ga_ls8c_ard_3-2-1_110079_2022-08-14_final
2022-08-15 10:26:48	ga_ls8c_ard_3-2-1_101079_2022-08-15_final
2022-08-19 11:39:47	ga_ls8c_ard_3-2-1_113076_2022-08-19_final
2022-08-22 10:31:48	ga_ls8c_ard_3-2-1_102076_2022-08-22_final
2022-08-22 10:32:36	ga_ls8c_ard_3-2-1_102078_2022-08-22_final
2022-08-28 11:34:00	ga_ls8c_ard_3-2-1_112077_2022-08-28_final
2022-09-07 10:32:38	ga_ls8c_ard_3-2-1_102078_2022-09-07_final
2022-09-15 11:22:08	ga_ls8c_ard_3-2-1_110078_2022-09-15_final
2022-09-17 11:09:23	ga_ls8c_ard_3-2-1_108077_2022-09-17_final
2022-09-22 11:28:20	ga_ls8c_ard_3-2-1_111078_2022-09-22_final
2022-09-23 10:31:55	ga_ls8c_ard_3-2-1_102076_2022-09-23_final
2022-09-27 10:09:11	ga_ls8c_ard_3-2-1_098081_2022-09-27_final
2022-10-19 11:09:18	ga_ls8c_ard_3-2-1_108077_2022-10-19_final
2022-10-22 11:40:14	ga_ls8c_ard_3-2-1_113077_2022-10-22_final
2022-10-24 09:49:00	ga_ls8c_ard_3-2-1_095077_2022-10-24_final
2022-11-04 09:35:17	ga_ls8c_ard_3-2-1_092089_2022-11-04_final
2022-11-04 11:09:23	ga_ls8c_ard_3-2-1_108077_2022-11-04_final
2022-11-18 09:43:08	ga_ls8c_ard_3-2-1_094078_2022-11-18_final
2022-11-23 11:40:11	ga_ls8c_ard_3-2-1_113077_2022-11-23_final
2022-11-25 09:48:57	ga_ls8c_ard_3-2-1_095077_2022-11-25_final
2022-11-25 09:49:21	ga_ls8c_ard_3-2-1_095078_2022-11-25_final
2022-12-09 11:40:11	ga_ls8c_ard_3-2-1_113077_2022-12-09_final
2022-12-11 09:48:55	ga_ls8c_ard_3-2-1_095077_2022-12-11_final
2022-12-11 09:49:19	ga_ls8c_ard_3-2-1_095078_2022-12-11_final
2022-12-18 11:34:18	ga_ls8c_ard_3-2-1_112078_2022-12-18_final
2022-12-27 09:48:48	ga_ls8c_ard_3-2-1_095077_2022-12-27_final
2022-12-30 11:58:36	ga_ls8c_ard_3-2-1_116077_2022-12-30_final
2023-01-03 11:34:17	ga_ls8c_ard_3-2-1_112078_2023-01-03_final
2023-01-07 11:09:09	ga_ls8c_ard_3-2-1_108077_2023-01-07_final
2023-01-19 11:34:33	ga_ls8c_ard_3-2-1_112079_2023-01-19_final
2023-01-23 11:09:05	ga_ls8c_ard_3-2-1_108077_2023-01-23_final
2023-02-08 09:29:49	ga_ls8c_ard_3-2-1_092076_2023-02-07_final
2023-02-13 09:48:41	ga_ls8c_ard_3-2-1_095077_2023-02-13_final
2023-02-20 11:33:38	ga_ls8c_ard_3-2-1_112077_2023-02-20_final
2023-02-23 10:26:23	ga_ls8c_ard_3-2-1_101079_2023-02-23_final
2023-02-24 11:08:25	ga_ls8c_ard_3-2-1_108076_2023-02-24_final
2023-03-02 10:32:07	ga_ls8c_ard_3-2-1_102078_2023-03-02_final
2023-03-06 10:08:33	ga_ls8c_ard_3-2-1_098081_2023-03-06_final
2023-03-08 11:33:27	ga_ls8c_ard_3-2-1_112077_2023-03-08_final
2023-03-08 11:33:51	ga_ls8c_ard_3-2-1_112078_2023-03-08_final
2023-03-08 11:34:15	ga_ls8c_ard_3-2-1_112079_2023-03-08_final
2023-03-11 10:26:15	ga_ls8c_ard_3-2-1_101079_2023-03-11_final
2023-03-12 11:08:43	ga_ls8c_ard_3-2-1_108077_2023-03-12_final
2023-03-18 10:31:59	ga_ls8c_ard_3-2-1_102078_2023-03-18_final
2023-03-24 11:33:18	ga_ls8c_ard_3-2-1_112077_2023-03-24_final
2023-03-26 09:42:27	ga_ls8c_ard_3-2-1_094078_2023-03-26_final
2023-04-11 09:42:11	ga_ls8c_ard_3-2-1_094078_2023-04-11_final
2023-04-16 11:38:47	ga_ls8c_ard_3-2-1_113076_2023-04-16_final
2023-04-16 11:39:11	ga_ls8c_ard_3-2-1_113077_2023-04-16_final
2023-04-18 09:47:55	ga_ls8c_ard_3-2-1_095077_2023-04-18_final
2023-04-18 09:48:19	ga_ls8c_ard_3-2-1_095078_2023-04-18_final
2023-04-25 11:32:35	ga_ls8c_ard_3-2-1_112076_2023-04-25_final
2023-04-27 09:42:07	ga_ls8c_ard_3-2-1_094078_2023-04-27_final
2023-05-11 11:32:47	ga_ls8c_ard_3-2-1_112077_2023-05-11_final
2023-05-17 10:58:02	ga_ls8c_ard_3-2-1_106083_2023-05-17_final
2023-05-20 11:26:57	ga_ls8c_ard_3-2-1_111078_2023-05-20_final
2023-05-27 11:32:46	ga_ls8c_ard_3-2-1_112077_2023-05-27_final
2023-05-29 09:41:56	ga_ls8c_ard_3-2-1_094078_2023-05-29_final
2023-06-03 11:39:22	ga_ls8c_ard_3-2-1_113078_2023-06-03_final
2023-06-05 11:27:02	ga_ls8c_ard_3-2-1_111078_2023-06-05_final
2023-06-12 11:33:42	ga_ls8c_ard_3-2-1_112079_2023-06-12_final
2023-06-28 11:33:02	ga_ls8c_ard_3-2-1_112077_2023-06-28_final
2023-06-28 11:33:49	ga_ls8c_ard_3-2-1_112079_2023-06-28_final
2023-07-07 09:48:28	ga_ls8c_ard_3-2-1_095078_2023-07-07_final
2023-07-16 11:21:36	ga_ls8c_ard_3-2-1_110079_2023-07-16_final
2023-07-21 11:38:57	ga_ls8c_ard_3-2-1_113076_2023-07-21_final
2023-07-23 09:48:08	ga_ls8c_ard_3-2-1_095077_2023-07-23_final
2023-07-25 11:15:29	ga_ls8c_ard_3-2-1_109079_2023-07-25_final
2023-07-30 11:32:53	ga_ls8c_ard_3-2-1_112076_2023-07-30_final
2023-07-30 11:34:05	ga_ls8c_ard_3-2-1_112079_2023-07-30_final
2023-08-01 09:42:27	ga_ls8c_ard_3-2-1_094078_2023-08-01_final
2023-08-01 11:21:44	ga_ls8c_ard_3-2-1_110079_2023-08-01_final
2023-08-02 10:26:07	ga_ls8c_ard_3-2-1_101079_2023-08-02_final
2023-08-03 11:09:00	ga_ls8c_ard_3-2-1_108078_2023-08-03_final
2023-08-06 11:39:06	ga_ls8c_ard_3-2-1_113076_2023-08-06_final
2023-08-09 10:32:19	ga_ls8c_ard_3-2-1_102079_2023-08-09_final
2023-08-10 11:15:34	ga_ls8c_ard_3-2-1_109079_2023-08-10_final
2023-08-15 11:33:23	ga_ls8c_ard_3-2-1_112077_2023-08-15_final
2023-08-15 11:34:11	ga_ls8c_ard_3-2-1_112079_2023-08-15_final
2023-08-19 11:08:42	ga_ls8c_ard_3-2-1_108077_2023-08-19_final
2023-09-04 11:08:43	ga_ls8c_ard_3-2-1_108077_2023-09-04_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