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
2022-07-19 09:07:00	ga_ls8c_ard_3-2-1_088081_2022-07-18_final
2022-07-21 10:30:22	ga_ls8c_ard_3-2-1_102073_2022-07-21_final
2022-08-13 10:40:21	ga_ls8c_ard_3-2-1_103082_2022-08-13_final
2022-08-14 11:24:25	ga_ls8c_ard_3-2-1_110084_2022-08-14_final
2022-08-23 09:40:34	ga_ls8c_ard_3-2-1_093087_2022-08-23_final
2022-08-26 10:03:53	ga_ls8c_ard_3-2-1_098068_2022-08-26_final
2022-08-27 09:13:03	ga_ls8c_ard_3-2-1_089080_2022-08-26_final
2022-08-27 10:47:09	ga_ls8c_ard_3-2-1_105068_2022-08-27_final
2022-08-28 09:58:42	ga_ls8c_ard_3-2-1_096086_2022-08-28_final
2022-09-01 11:06:29	ga_ls8c_ard_3-2-1_108070_2022-09-01_final
2022-09-03 09:21:37	ga_ls8c_ard_3-2-1_090086_2022-09-02_final
2022-09-06 11:26:39	ga_ls8c_ard_3-2-1_111074_2022-09-06_final
2022-09-10 09:25:52	ga_ls8c_ard_3-2-1_091081_2022-09-09_final
2022-09-12 09:17:07	ga_ls8c_ard_3-2-1_089090_2022-09-11_final
2022-09-13 09:57:59	ga_ls8c_ard_3-2-1_096084_2022-09-13_final
2022-09-19 10:56:38	ga_ls8c_ard_3-2-1_106076_2022-09-19_final
2022-09-22 11:30:20	ga_ls8c_ard_3-2-1_111083_2022-09-22_final
2022-09-23 10:29:07	ga_ls8c_ard_3-2-1_102069_2022-09-23_final
2022-09-24 09:40:17	ga_ls8c_ard_3-2-1_093086_2022-09-24_final
2022-09-24 11:12:47	ga_ls8c_ard_3-2-1_109070_2022-09-24_final
2022-09-26 09:22:44	ga_ls8c_ard_3-2-1_091073_2022-09-25_final
2022-09-26 09:23:08	ga_ls8c_ard_3-2-1_091074_2022-09-25_final
2022-09-30 10:40:05	ga_ls8c_ard_3-2-1_103081_2022-09-30_final
2022-10-01 11:20:32	ga_ls8c_ard_3-2-1_110074_2022-10-01_final
2022-10-03 09:33:40	ga_ls8c_ard_3-2-1_092085_2022-10-03_final
2022-10-06 10:01:45	ga_ls8c_ard_3-2-1_097078_2022-10-06_final
2022-10-14 09:13:00	ga_ls8c_ard_3-2-1_089080_2022-10-13_final
2022-10-17 09:46:21	ga_ls8c_ard_3-2-1_094086_2022-10-17_final
2022-10-17 11:20:26	ga_ls8c_ard_3-2-1_110074_2022-10-17_final
2022-10-17 11:24:26	ga_ls8c_ard_3-2-1_110084_2022-10-17_final
2022-10-21 10:56:34	ga_ls8c_ard_3-2-1_106076_2022-10-21_final
2022-10-26 09:38:15	ga_ls8c_ard_3-2-1_093081_2022-10-26_final
2022-10-26 11:14:21	ga_ls8c_ard_3-2-1_109074_2022-10-26_final
2022-10-29 10:03:59	ga_ls8c_ard_3-2-1_098068_2022-10-29_final
2022-10-30 09:15:33	ga_ls8c_ard_3-2-1_089086_2022-10-29_final
2022-11-01 10:39:41	ga_ls8c_ard_3-2-1_103080_2022-11-01_final
2022-11-04 09:32:06	ga_ls8c_ard_3-2-1_092081_2022-11-04_final
2022-11-06 10:56:37	ga_ls8c_ard_3-2-1_106076_2022-11-06_final
2022-11-11 09:35:50	ga_ls8c_ard_3-2-1_093075_2022-11-11_final
2022-11-12 10:18:17	ga_ls8c_ard_3-2-1_100073_2022-11-12_final
2022-11-12 10:20:17	ga_ls8c_ard_3-2-1_100078_2022-11-12_final
2022-11-14 10:06:18	ga_ls8c_ard_3-2-1_098074_2022-11-14_final
2022-11-15 09:12:40	ga_ls8c_ard_3-2-1_089079_2022-11-14_final
2022-11-18 11:21:13	ga_ls8c_ard_3-2-1_110076_2022-11-18_final
2022-11-18 11:23:36	ga_ls8c_ard_3-2-1_110082_2022-11-18_final
2022-11-20 09:29:35	ga_ls8c_ard_3-2-1_092075_2022-11-19_final
2022-11-20 09:34:46	ga_ls8c_ard_3-2-1_092088_2022-11-20_final
2022-11-27 09:40:11	ga_ls8c_ard_3-2-1_093086_2022-11-27_final
2022-11-27 11:12:41	ga_ls8c_ard_3-2-1_109070_2022-11-27_final
2022-11-27 11:13:05	ga_ls8c_ard_3-2-1_109071_2022-11-27_final
2022-12-07 10:11:41	ga_ls8c_ard_3-2-1_099072_2022-12-07_final
2022-12-18 11:32:19	ga_ls8c_ard_3-2-1_112073_2022-12-18_final
2022-12-18 11:33:07	ga_ls8c_ard_3-2-1_112075_2022-12-18_final
2022-12-20 11:19:07	ga_ls8c_ard_3-2-1_110071_2022-12-20_final
2022-12-25 10:01:57	ga_ls8c_ard_3-2-1_097079_2022-12-25_final
2022-12-26 10:41:13	ga_ls8c_ard_3-2-1_104069_2022-12-26_final
2022-12-30 10:22:06	ga_ls8c_ard_3-2-1_100083_2022-12-30_final
2023-01-03 09:58:11	ga_ls8c_ard_3-2-1_096085_2023-01-03_final
2023-01-03 11:33:05	ga_ls8c_ard_3-2-1_112075_2023-01-03_final
2023-01-06 10:23:06	ga_ls8c_ard_3-2-1_101070_2023-01-06_final
2023-01-09 09:19:53	ga_ls8c_ard_3-2-1_090082_2023-01-08_final
2023-01-10 10:03:08	ga_ls8c_ard_3-2-1_097082_2023-01-10_final
2023-01-11 10:43:12	ga_ls8c_ard_3-2-1_104074_2023-01-11_final
2023-01-13 10:28:49	ga_ls8c_ard_3-2-1_102069_2023-01-13_final
2023-01-15 10:18:49	ga_ls8c_ard_3-2-1_100075_2023-01-15_final
2023-01-18 09:13:59	ga_ls8c_ard_3-2-1_089083_2023-01-17_final
2023-01-21 11:18:38	ga_ls8c_ard_3-2-1_110070_2023-01-21_final
2023-01-21 11:19:02	ga_ls8c_ard_3-2-1_110071_2023-01-21_final
2023-01-26 09:59:08	ga_ls8c_ard_3-2-1_097072_2023-01-26_final
2023-01-30 11:14:06	ga_ls8c_ard_3-2-1_109074_2023-01-30_final
2023-02-10 09:21:01	ga_ls8c_ard_3-2-1_090085_2023-02-09_final
2023-02-17 09:27:06	ga_ls8c_ard_3-2-1_091085_2023-02-16_final
2023-02-17 09:27:54	ga_ls8c_ard_3-2-1_091087_2023-02-16_final
2023-02-26 09:17:57	ga_ls8c_ard_3-2-1_090078_2023-02-25_final
2023-02-26 10:54:50	ga_ls8c_ard_3-2-1_106073_2023-02-26_final
2023-02-27 10:03:37	ga_ls8c_ard_3-2-1_097084_2023-02-27_final
2023-03-06 10:05:45	ga_ls8c_ard_3-2-1_098074_2023-03-06_final
2023-03-09 10:34:37	ga_ls8c_ard_3-2-1_103069_2023-03-09_final
2023-03-13 10:11:30	ga_ls8c_ard_3-2-1_099073_2023-03-13_final
2023-03-13 11:51:11	ga_ls8c_ard_3-2-1_115075_2023-03-13_final
2023-03-13 11:52:23	ga_ls8c_ard_3-2-1_115078_2023-03-13_final
2023-03-15 09:58:44	ga_ls8c_ard_3-2-1_097072_2023-03-15_final
2023-03-27 10:25:18	ga_ls8c_ard_3-2-1_101077_2023-03-27_final
2023-03-29 10:15:43	ga_ls8c_ard_3-2-1_099084_2023-03-29_final
2023-03-31 09:59:21	ga_ls8c_ard_3-2-1_097074_2023-03-31_final
2023-03-31 10:03:44	ga_ls8c_ard_3-2-1_097085_2023-03-31_final
2023-04-01 10:42:12	ga_ls8c_ard_3-2-1_104073_2023-04-01_final
2023-04-08 09:11:21	ga_ls8c_ard_3-2-1_089078_2023-04-07_final
2023-04-09 11:31:28	ga_ls8c_ard_3-2-1_112073_2023-04-09_final
2023-04-11 11:23:27	ga_ls8c_ard_3-2-1_110084_2023-04-11_final
2023-04-12 10:27:02	ga_ls8c_ard_3-2-1_101082_2023-04-12_final
2023-04-13 09:34:12	ga_ls8c_ard_3-2-1_092089_2023-04-13_final
2023-04-16 11:37:59	ga_ls8c_ard_3-2-1_113074_2023-04-16_final
2023-04-18 09:51:55	ga_ls8c_ard_3-2-1_095087_2023-04-18_final
2023-05-02 09:57:26	ga_ls8c_ard_3-2-1_097070_2023-05-02_final
2023-05-03 09:06:11	ga_ls8c_ard_3-2-1_088081_2023-05-02_final
2023-05-04 11:29:07	ga_ls8c_ard_3-2-1_111083_2023-05-04_final
2023-05-11 11:35:34	ga_ls8c_ard_3-2-1_112084_2023-05-11_final
2023-05-15 09:32:20	ga_ls8c_ard_3-2-1_092085_2023-05-15_final
2023-05-16 11:52:04	ga_ls8c_ard_3-2-1_115079_2023-05-16_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