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
2016-11-24 08:11:03	ga_ls8c_ard_3-2-1_079080_2016-11-23_final
2017-11-11 08:10:59	ga_ls8c_ard_3-2-1_079080_2017-11-10_final
2021-01-25 08:42:33	ga_ls8c_ard_3-2-1_084082_2021-01-24_final
2021-02-09 09:35:45	ga_ls8c_ard_3-2-0_093076_2021-02-09_final
2021-04-15 08:42:06	ga_ls8c_ard_3-2-1_084082_2021-04-14_final
2021-07-01 09:48:41	ga_ls8c_ard_3-2-0_095078_2021-07-01_final
2021-07-05 12:37:22	ga_ls8c_ard_3-2-1_123067_2021-07-05_final
2021-08-18 08:10:52	ga_ls8c_ard_3-2-1_079080_2021-08-17_final
2021-10-18 09:18:19	ga_ls8c_ard_3-2-0_090078_2021-10-17_final
2022-01-04 11:09:23	ga_ls8c_ard_3-2-1_108078_2022-01-04_final
2022-01-09 09:49:02	ga_ls8c_ard_3-2-1_095078_2022-01-09_final
2022-01-18 09:43:37	ga_ls8c_ard_3-2-1_094080_2022-01-18_final
2022-01-20 11:09:20	ga_ls8c_ard_3-2-1_108078_2022-01-20_final
2022-01-25 08:10:52	ga_ls8c_ard_3-2-1_079080_2022-01-24_final
2022-02-05 11:08:52	ga_ls8c_ard_3-2-1_108077_2022-02-05_final
2022-02-05 11:09:16	ga_ls8c_ard_3-2-1_108078_2022-02-05_final
2022-03-21 11:33:44	ga_ls8c_ard_3-2-1_112078_2022-03-21_final
2022-03-25 11:08:33	ga_ls8c_ard_3-2-1_108077_2022-03-25_final
2022-03-25 11:08:57	ga_ls8c_ard_3-2-1_108078_2022-03-25_final
2022-03-30 09:48:08	ga_ls8c_ard_3-2-1_095077_2022-03-30_final
2022-03-30 09:48:32	ga_ls8c_ard_3-2-1_095078_2022-03-30_final
2022-04-09 10:26:05	ga_ls8c_ard_3-2-1_101079_2022-04-09_final
2022-04-10 11:08:33	ga_ls8c_ard_3-2-1_108077_2022-04-10_final
2022-04-10 11:08:57	ga_ls8c_ard_3-2-1_108078_2022-04-10_final
2022-04-15 09:48:14	ga_ls8c_ard_3-2-1_095077_2022-04-15_final
2022-04-22 11:33:40	ga_ls8c_ard_3-2-1_112078_2022-04-22_final
2022-04-26 11:08:55	ga_ls8c_ard_3-2-1_108078_2022-04-26_final
2022-06-18 09:48:36	ga_ls8c_ard_3-2-1_095077_2022-06-18_final
2022-06-25 11:34:06	ga_ls8c_ard_3-2-1_112078_2022-06-25_final
2022-06-28 10:26:31	ga_ls8c_ard_3-2-1_101079_2022-06-28_final
2022-07-04 11:27:56	ga_ls8c_ard_3-2-1_111078_2022-07-04_final
2022-07-11 11:34:06	ga_ls8c_ard_3-2-1_112078_2022-07-11_final
2022-07-14 10:26:30	ga_ls8c_ard_3-2-1_101079_2022-07-14_final
2022-07-15 11:09:21	ga_ls8c_ard_3-2-1_108078_2022-07-15_final
2022-07-20 09:49:05	ga_ls8c_ard_3-2-1_095078_2022-07-20_final
2022-07-31 11:09:33	ga_ls8c_ard_3-2-1_108078_2022-07-31_final
2022-08-12 11:34:22	ga_ls8c_ard_3-2-1_112078_2022-08-12_final
2022-08-14 11:22:01	ga_ls8c_ard_3-2-1_110078_2022-08-14_final
2022-08-16 11:09:40	ga_ls8c_ard_3-2-1_108078_2022-08-16_final
2022-08-21 09:49:20	ga_ls8c_ard_3-2-1_095078_2022-08-21_final
2022-08-21 11:28:13	ga_ls8c_ard_3-2-1_111078_2022-08-21_final
2022-09-06 09:48:57	ga_ls8c_ard_3-2-1_095077_2022-09-06_final
2022-09-17 11:09:47	ga_ls8c_ard_3-2-1_108078_2022-09-17_final
2022-09-20 10:01:24	ga_ls8c_ard_3-2-1_097077_2022-09-20_final
2022-09-22 09:49:03	ga_ls8c_ard_3-2-1_095077_2022-09-22_final
2022-10-19 11:09:42	ga_ls8c_ard_3-2-1_108078_2022-10-19_final
2022-10-25 10:32:16	ga_ls8c_ard_3-2-1_102077_2022-10-25_final
2022-11-04 11:09:47	ga_ls8c_ard_3-2-1_108078_2022-11-04_final
2022-12-06 11:09:42	ga_ls8c_ard_3-2-1_108078_2022-12-06_final
2023-01-07 11:09:33	ga_ls8c_ard_3-2-1_108078_2023-01-07_final
2023-01-10 09:58:45	ga_ls8c_ard_3-2-1_097071_2023-01-10_final
2023-01-10 11:40:01	ga_ls8c_ard_3-2-1_113077_2023-01-10_final
2023-01-15 08:42:44	ga_ls8c_ard_3-2-1_084082_2023-01-14_final
2023-01-23 11:09:29	ga_ls8c_ard_3-2-1_108078_2023-01-23_final
2023-02-08 11:09:06	ga_ls8c_ard_3-2-1_108077_2023-02-08_final
2023-02-08 11:09:30	ga_ls8c_ard_3-2-1_108078_2023-02-08_final
2023-03-17 09:48:20	ga_ls8c_ard_3-2-1_095077_2023-03-17_final
2023-03-17 09:48:44	ga_ls8c_ard_3-2-1_095078_2023-03-17_final
2023-04-12 10:25:50	ga_ls8c_ard_3-2-1_101079_2023-04-12_final
2023-05-04 09:48:14	ga_ls8c_ard_3-2-1_095078_2023-05-04_final
2023-05-11 11:33:11	ga_ls8c_ard_3-2-1_112078_2023-05-11_final
2023-05-11 11:33:34	ga_ls8c_ard_3-2-1_112079_2023-05-11_final
2023-05-30 10:25:35	ga_ls8c_ard_3-2-1_101079_2023-05-30_final
2023-05-31 11:08:27	ga_ls8c_ard_3-2-1_108078_2023-05-31_final
2023-06-12 11:33:18	ga_ls8c_ard_3-2-1_112078_2023-06-12_final
2023-06-15 10:25:44	ga_ls8c_ard_3-2-1_101079_2023-06-15_final
2023-06-16 11:08:36	ga_ls8c_ard_3-2-1_108078_2023-06-16_final
2023-06-21 09:48:16	ga_ls8c_ard_3-2-1_095078_2023-06-21_final
2023-06-28 09:54:08	ga_ls8c_ard_3-2-1_096077_2023-06-28_final
2023-06-28 11:33:26	ga_ls8c_ard_3-2-1_112078_2023-06-28_final
2023-07-07 09:48:04	ga_ls8c_ard_3-2-1_095077_2023-07-07_final
2023-07-30 11:33:17	ga_ls8c_ard_3-2-1_112077_2023-07-30_final
2023-07-30 11:33:41	ga_ls8c_ard_3-2-1_112078_2023-07-30_final
2023-08-08 11:27:32	ga_ls8c_ard_3-2-1_111078_2023-08-08_final
2023-08-15 11:33:47	ga_ls8c_ard_3-2-1_112078_2023-08-15_final
2023-08-19 11:09:06	ga_ls8c_ard_3-2-1_108078_2023-08-19_final
2023-08-22 11:39:14	ga_ls8c_ard_3-2-1_113076_2023-08-22_final
2023-08-22 11:39:38	ga_ls8c_ard_3-2-1_113077_2023-08-22_final
2023-08-31 11:33:28	ga_ls8c_ard_3-2-1_112077_2023-08-31_final
2023-08-31 11:34:16	ga_ls8c_ard_3-2-1_112079_2023-08-31_final
2023-09-04 11:09:07	ga_ls8c_ard_3-2-1_108078_2023-09-04_final
2023-09-07 11:39:36	ga_ls8c_ard_3-2-1_113077_2023-09-07_final
2023-09-20 11:09:13	ga_ls8c_ard_3-2-1_108078_2023-09-20_final
2023-09-25 09:48:29	ga_ls8c_ard_3-2-1_095077_2023-09-25_final
2023-09-25 09:48:53	ga_ls8c_ard_3-2-1_095078_2023-09-25_final
2023-10-04 09:42:44	ga_ls8c_ard_3-2-1_094078_2023-10-04_final
2023-10-11 09:48:34	ga_ls8c_ard_3-2-1_095077_2023-10-11_final
2023-10-11 09:48:58	ga_ls8c_ard_3-2-1_095078_2023-10-11_final
2023-10-25 11:39:50	ga_ls8c_ard_3-2-1_113077_2023-10-25_final
2023-10-27 09:48:36	ga_ls8c_ard_3-2-1_095077_2023-10-27_final
2023-10-27 09:49:00	ga_ls8c_ard_3-2-1_095078_2023-10-27_final
2023-11-10 11:39:46	ga_ls8c_ard_3-2-1_113077_2023-11-10_final
2023-11-23 11:08:59	ga_ls8c_ard_3-2-1_108077_2023-11-23_final
2023-11-23 11:09:23	ga_ls8c_ard_3-2-1_108078_2023-11-23_final
2023-12-25 11:09:21	ga_ls8c_ard_3-2-1_108078_2023-12-25_final
2023-12-30 09:48:57	ga_ls8c_ard_3-2-1_095078_2023-12-30_final
2024-01-10 11:08:51	ga_ls8c_ard_3-2-1_108077_2024-01-10_final
2024-01-24 11:21:56	ga_ls8c_ard_3-2-1_110079_2024-01-24_final
2024-01-26 09:30:16	ga_ls8c_ard_3-2-1_092078_2024-01-26_final
2024-01-29 11:39:40	ga_ls8c_ard_3-2-1_113077_2024-01-29_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years