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
2023-02-03 10:49:23	ga_ls8c_ard_3-2-1_105074_2023-02-03_final
2023-02-03 10:50:11	ga_ls8c_ard_3-2-1_105076_2023-02-03_final
2023-03-17 11:23:38	ga_ls8c_ard_3-2-1_111068_2023-03-17_final
2023-03-20 10:22:00	ga_ls8c_ard_3-2-1_100084_2023-03-20_final
2023-03-22 10:04:01	ga_ls8c_ard_3-2-1_098070_2023-03-22_final
2023-03-24 09:51:37	ga_ls8c_ard_3-2-1_096070_2023-03-24_final
2023-03-24 09:52:25	ga_ls8c_ard_3-2-1_096072_2023-03-24_final
2023-04-03 10:27:49	ga_ls8c_ard_3-2-1_102068_2023-04-03_final
2023-05-02 10:03:25	ga_ls8c_ard_3-2-1_097085_2023-05-02_final
2023-05-03 09:06:35	ga_ls8c_ard_3-2-1_088082_2023-05-02_final
2023-05-04 11:24:44	ga_ls8c_ard_3-2-1_111072_2023-05-04_final
2023-05-08 09:27:51	ga_ls8c_ard_3-2-1_091089_2023-05-07_final
2023-05-08 11:01:32	ga_ls8c_ard_3-2-1_107076_2023-05-08_final
2023-05-10 09:15:51	ga_ls8c_ard_3-2-1_089090_2023-05-09_final
2023-05-13 11:19:36	ga_ls8c_ard_3-2-1_110075_2023-05-13_final
2023-05-26 09:11:25	ga_ls8c_ard_3-2-1_089079_2023-05-25_final
2023-05-27 09:57:05	ga_ls8c_ard_3-2-1_096085_2023-05-27_final
2023-06-02 09:20:48	ga_ls8c_ard_3-2-1_090087_2023-06-01_final
2023-06-07 11:16:42	ga_ls8c_ard_3-2-1_109083_2023-06-07_final
2023-06-09 11:03:34	ga_ls8c_ard_3-2-1_107081_2023-06-09_final
2023-06-10 10:03:10	ga_ls8c_ard_3-2-1_098069_2023-06-10_final
2023-06-11 09:15:56	ga_ls8c_ard_3-2-1_089090_2023-06-10_final
2023-06-14 11:17:46	ga_ls8c_ard_3-2-1_110070_2023-06-14_final
2023-06-14 11:18:34	ga_ls8c_ard_3-2-1_110072_2023-06-14_final
2023-06-16 11:06:36	ga_ls8c_ard_3-2-1_108073_2023-06-16_final
2023-06-18 09:21:45	ga_ls8c_ard_3-2-1_090089_2023-06-17_final
2023-06-20 09:06:12	ga_ls8c_ard_3-2-1_088081_2023-06-19_final
2023-06-21 11:29:33	ga_ls8c_ard_3-2-1_111084_2023-06-21_final
2023-06-23 09:38:18	ga_ls8c_ard_3-2-1_093084_2023-06-23_final
2023-06-25 09:21:59	ga_ls8c_ard_3-2-1_091074_2023-06-24_final
2023-06-26 10:07:16	ga_ls8c_ard_3-2-1_098079_2023-06-26_final
2023-06-30 11:19:54	ga_ls8c_ard_3-2-1_110075_2023-06-30_final
2023-07-04 10:54:50	ga_ls8c_ard_3-2-1_106074_2023-07-04_final
2023-07-05 11:38:06	ga_ls8c_ard_3-2-1_113074_2023-07-05_final
2023-07-11 09:26:10	ga_ls8c_ard_3-2-1_091084_2023-07-10_final
2023-07-11 11:03:51	ga_ls8c_ard_3-2-1_107081_2023-07-11_final
2023-07-13 09:16:13	ga_ls8c_ard_3-2-1_089090_2023-07-12_final
2023-07-16 11:20:25	ga_ls8c_ard_3-2-1_110076_2023-07-16_final
2023-07-16 11:23:36	ga_ls8c_ard_3-2-1_110084_2023-07-16_final
2023-07-19 10:15:37	ga_ls8c_ard_3-2-1_099084_2023-07-19_final
2023-07-27 09:26:16	ga_ls8c_ard_3-2-1_091084_2023-07-26_final
2023-07-27 11:01:33	ga_ls8c_ard_3-2-1_107075_2023-07-27_final
2023-07-27 11:01:57	ga_ls8c_ard_3-2-1_107076_2023-07-27_final
2023-07-28 11:46:50	ga_ls8c_ard_3-2-1_114080_2023-07-28_final
2023-08-01 09:45:15	ga_ls8c_ard_3-2-1_094085_2023-08-01_final
2023-08-01 11:19:21	ga_ls8c_ard_3-2-1_110073_2023-08-01_final
2023-08-03 09:28:55	ga_ls8c_ard_3-2-1_092075_2023-08-02_final
2023-08-03 09:34:30	ga_ls8c_ard_3-2-1_092089_2023-08-03_final
2023-08-03 11:07:00	ga_ls8c_ard_3-2-1_108073_2023-08-03_final
2023-08-11 10:21:57	ga_ls8c_ard_3-2-1_100084_2023-08-11_final
2023-08-12 09:21:57	ga_ls8c_ard_3-2-1_091073_2023-08-11_final
2023-08-12 09:26:44	ga_ls8c_ard_3-2-1_091085_2023-08-11_final
2023-08-15 09:57:17	ga_ls8c_ard_3-2-1_096084_2023-08-15_final
2023-08-15 09:58:05	ga_ls8c_ard_3-2-1_096086_2023-08-15_final
2023-08-18 10:27:50	ga_ls8c_ard_3-2-1_101083_2023-08-18_final
2023-08-20 10:10:18	ga_ls8c_ard_3-2-1_099070_2023-08-20_final
2023-08-20 11:52:22	ga_ls8c_ard_3-2-1_115078_2023-08-20_final
2023-08-24 09:52:23	ga_ls8c_ard_3-2-1_095087_2023-08-24_final
2023-08-28 09:27:40	ga_ls8c_ard_3-2-1_091087_2023-08-27_final
2023-08-28 09:28:52	ga_ls8c_ard_3-2-1_091090_2023-08-27_final
2023-08-28 11:01:46	ga_ls8c_ard_3-2-1_107075_2023-08-28_final
2023-08-29 10:09:44	ga_ls8c_ard_3-2-1_098084_2023-08-29_final
2023-08-30 09:11:19	ga_ls8c_ard_3-2-1_089077_2023-08-29_final
2023-09-04 11:07:31	ga_ls8c_ard_3-2-1_108074_2023-09-04_final
2023-09-07 09:57:56	ga_ls8c_ard_3-2-1_097070_2023-09-07_final
2023-09-09 11:25:17	ga_ls8c_ard_3-2-1_111072_2023-09-09_final
2023-09-13 09:21:43	ga_ls8c_ard_3-2-1_091072_2023-09-12_final
2023-09-15 09:11:22	ga_ls8c_ard_3-2-1_089077_2023-09-14_final
2023-09-15 09:11:46	ga_ls8c_ard_3-2-1_089078_2023-09-14_final
2023-09-15 09:14:58	ga_ls8c_ard_3-2-1_089086_2023-09-14_final
2023-09-16 11:32:20	ga_ls8c_ard_3-2-1_112074_2023-09-16_final
2023-09-19 10:25:33	ga_ls8c_ard_3-2-1_101077_2023-09-19_final
2023-09-19 10:27:57	ga_ls8c_ard_3-2-1_101083_2023-09-19_final
2023-09-21 10:15:11	ga_ls8c_ard_3-2-1_099082_2023-09-21_final
2023-09-23 11:41:19	ga_ls8c_ard_3-2-1_113081_2023-09-23_final
2023-10-04 11:20:25	ga_ls8c_ard_3-2-1_110075_2023-10-04_final
2023-10-06 11:06:27	ga_ls8c_ard_3-2-1_108071_2023-10-06_final
2023-10-08 09:20:50	ga_ls8c_ard_3-2-1_090085_2023-10-07_final
2023-10-08 10:57:43	ga_ls8c_ard_3-2-1_106080_2023-10-08_final
2023-10-10 10:46:10	ga_ls8c_ard_3-2-1_104082_2023-10-10_final
2023-10-12 10:28:38	ga_ls8c_ard_3-2-1_102069_2023-10-12_final
2023-10-14 10:17:04	ga_ls8c_ard_3-2-1_100071_2023-10-14_final
2023-10-15 11:05:07	ga_ls8c_ard_3-2-1_107083_2023-10-15_final
2023-10-22 11:06:07	ga_ls8c_ard_3-2-1_108070_2023-10-22_final
2023-10-23 10:10:54	ga_ls8c_ard_3-2-1_099071_2023-10-23_final
2023-10-23 10:11:18	ga_ls8c_ard_3-2-1_099072_2023-10-23_final
2023-10-24 09:21:40	ga_ls8c_ard_3-2-1_090087_2023-10-23_final
2023-10-28 10:28:41	ga_ls8c_ard_3-2-1_102069_2023-10-28_final
2023-10-29 11:17:32	ga_ls8c_ard_3-2-1_109083_2023-10-29_final
2023-11-01 10:07:33	ga_ls8c_ard_3-2-1_098078_2023-11-01_final
2023-11-02 09:16:19	ga_ls8c_ard_3-2-1_089089_2023-11-01_final
2023-11-05 11:19:18	ga_ls8c_ard_3-2-1_110072_2023-11-05_final
2023-11-09 09:20:49	ga_ls8c_ard_3-2-1_090085_2023-11-08_final
2023-11-09 10:54:55	ga_ls8c_ard_3-2-1_106073_2023-11-09_final
2023-11-10 10:03:40	ga_ls8c_ard_3-2-1_097084_2023-11-10_final
2023-11-12 09:51:21	ga_ls8c_ard_3-2-1_095084_2023-11-12_final
2023-11-20 10:34:53	ga_ls8c_ard_3-2-1_103069_2023-11-20_final
2023-11-20 10:39:16	ga_ls8c_ard_3-2-1_103080_2023-11-20_final
2023-11-21 11:19:45	ga_ls8c_ard_3-2-1_110073_2023-11-21_final
2023-11-22 10:25:44	ga_ls8c_ard_3-2-1_101077_2023-11-22_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