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
2022-01-28 11:57:55	ga_ls8c_ard_3-2-1_116076_2022-01-28_final
2022-02-16 10:49:28	ga_ls8c_ard_3-2-1_105075_2022-02-16_final
2022-02-18 10:35:54	ga_ls8c_ard_3-2-1_103072_2022-02-18_final
2022-02-23 09:16:44	ga_ls8c_ard_3-2-1_090075_2022-02-22_final
2022-03-07 09:44:13	ga_ls8c_ard_3-2-1_094082_2022-03-07_final
2022-03-18 11:02:28	ga_ls8c_ard_3-2-1_107077_2022-03-18_final
2022-03-27 10:52:34	ga_ls8c_ard_3-2-1_106068_2022-03-27_final
2022-03-28 10:03:43	ga_ls8c_ard_3-2-1_097085_2022-03-28_final
2022-04-03 11:02:18	ga_ls8c_ard_3-2-1_107077_2022-04-03_final
2022-04-07 10:39:13	ga_ls8c_ard_3-2-1_103081_2022-04-07_final
2022-04-10 11:10:33	ga_ls8c_ard_3-2-1_108082_2022-04-10_final
2022-04-14 10:40:16	ga_ls8c_ard_3-2-1_104068_2022-04-14_final
2022-04-16 10:30:42	ga_ls8c_ard_3-2-1_102075_2022-04-16_final
2022-04-21 09:12:44	ga_ls8c_ard_3-2-1_089081_2022-04-20_final
2022-04-24 09:46:00	ga_ls8c_ard_3-2-1_094087_2022-04-24_final
2022-05-05 11:02:24	ga_ls8c_ard_3-2-1_107077_2022-05-05_final
2022-05-05 11:04:24	ga_ls8c_ard_3-2-1_107082_2022-05-05_final
2022-05-10 09:44:06	ga_ls8c_ard_3-2-1_094082_2022-05-10_final
2022-05-19 11:14:52	ga_ls8c_ard_3-2-1_109077_2022-05-19_final
2022-06-02 11:25:42	ga_ls8c_ard_3-2-1_111073_2022-06-02_final
2022-06-06 09:27:44	ga_ls8c_ard_3-2-1_091087_2022-06-05_final
2022-06-13 11:06:54	ga_ls8c_ard_3-2-1_108072_2022-06-13_final
2022-06-17 10:45:00	ga_ls8c_ard_3-2-1_104079_2022-06-17_final
2022-06-20 09:36:39	ga_ls8c_ard_3-2-1_093078_2022-06-20_final
2022-06-23 10:10:21	ga_ls8c_ard_3-2-1_098085_2022-06-23_final
2022-07-08 11:04:48	ga_ls8c_ard_3-2-1_107082_2022-07-08_final
2022-07-24 11:02:54	ga_ls8c_ard_3-2-1_107077_2022-07-24_final
2022-08-04 10:44:04	ga_ls8c_ard_3-2-1_104076_2022-08-04_final
2022-08-07 09:34:07	ga_ls8c_ard_3-2-1_093071_2022-08-07_final
2022-08-14 11:20:49	ga_ls8c_ard_3-2-1_110075_2022-08-14_final
2022-09-03 10:58:30	ga_ls8c_ard_3-2-1_106081_2022-09-03_final
2022-09-12 10:50:25	ga_ls8c_ard_3-2-1_105076_2022-09-12_final
2022-09-27 10:05:12	ga_ls8c_ard_3-2-1_098071_2022-09-27_final
2022-10-08 09:46:59	ga_ls8c_ard_3-2-1_095072_2022-10-08_final
2022-10-12 11:04:40	ga_ls8c_ard_3-2-1_107081_2022-10-12_final
2022-10-17 11:24:50	ga_ls8c_ard_3-2-1_110085_2022-10-17_final
2022-10-18 10:23:14	ga_ls8c_ard_3-2-1_101070_2022-10-18_final
2022-10-21 10:58:09	ga_ls8c_ard_3-2-1_106080_2022-10-21_final
2022-11-02 11:18:57	ga_ls8c_ard_3-2-1_110070_2022-11-02_final
2022-11-05 10:11:22	ga_ls8c_ard_3-2-1_099071_2022-11-05_final
2022-11-13 11:05:56	ga_ls8c_ard_3-2-1_107084_2022-11-13_final
2022-11-14 10:09:30	ga_ls8c_ard_3-2-1_098082_2022-11-14_final
2022-11-24 10:40:59	ga_ls8c_ard_3-2-1_104068_2022-11-24_final
2022-11-27 09:38:35	ga_ls8c_ard_3-2-1_093082_2022-11-27_final
2022-11-30 10:10:18	ga_ls8c_ard_3-2-1_098084_2022-11-30_final
2022-12-03 10:34:49	ga_ls8c_ard_3-2-1_103068_2022-12-03_final
2022-12-04 09:44:46	ga_ls8c_ard_3-2-1_094082_2022-12-04_final
2022-12-06 09:31:37	ga_ls8c_ard_3-2-1_092080_2022-12-06_final
2022-12-11 09:50:55	ga_ls8c_ard_3-2-1_095082_2022-12-11_final
2022-12-13 11:16:14	ga_ls8c_ard_3-2-1_109079_2022-12-13_final
2022-12-15 09:26:34	ga_ls8c_ard_3-2-1_091083_2022-12-14_final
2022-12-19 10:40:16	ga_ls8c_ard_3-2-1_103082_2022-12-19_final
2022-12-20 11:18:43	ga_ls8c_ard_3-2-1_110070_2022-12-20_final
2022-12-29 11:14:08	ga_ls8c_ard_3-2-1_109074_2022-12-29_final
2023-01-09 10:57:58	ga_ls8c_ard_3-2-1_106080_2023-01-09_final
2023-01-12 09:46:46	ga_ls8c_ard_3-2-1_095072_2023-01-12_final
2023-01-16 11:02:52	ga_ls8c_ard_3-2-1_107077_2023-01-16_final
2023-01-20 10:34:33	ga_ls8c_ard_3-2-1_103068_2023-01-20_final
2023-01-20 10:38:33	ga_ls8c_ard_3-2-1_103078_2023-01-20_final
2023-01-23 11:07:53	ga_ls8c_ard_3-2-1_108074_2023-01-23_final
2023-02-01 09:23:16	ga_ls8c_ard_3-2-1_091075_2023-01-31_final
2023-02-02 10:06:31	ga_ls8c_ard_3-2-1_098075_2023-02-02_final
2023-02-03 10:49:23	ga_ls8c_ard_3-2-1_105074_2023-02-03_final
2023-02-10 09:21:01	ga_ls8c_ard_3-2-1_090085_2023-02-09_final
2023-03-12 11:11:07	ga_ls8c_ard_3-2-1_108083_2023-03-12_final
2023-03-15 10:03:55	ga_ls8c_ard_3-2-1_097085_2023-03-15_final
2023-03-22 10:09:12	ga_ls8c_ard_3-2-1_098083_2023-03-22_final
2023-03-26 09:44:03	ga_ls8c_ard_3-2-1_094082_2023-03-26_final
2023-04-04 09:38:57	ga_ls8c_ard_3-2-1_093085_2023-04-04_final
2023-04-06 11:02:14	ga_ls8c_ard_3-2-1_107077_2023-04-06_final
2023-04-08 10:51:02	ga_ls8c_ard_3-2-1_105080_2023-04-08_final
2023-04-10 10:33:50	ga_ls8c_ard_3-2-1_103068_2023-04-10_final
2023-04-14 10:13:52	ga_ls8c_ard_3-2-1_099080_2023-04-14_final
2023-04-15 10:58:20	ga_ls8c_ard_3-2-1_106083_2023-04-15_final
2023-04-18 09:49:55	ga_ls8c_ard_3-2-1_095082_2023-04-18_final
2023-04-26 10:38:33	ga_ls8c_ard_3-2-1_103080_2023-04-26_final
2023-04-28 10:22:35	ga_ls8c_ard_3-2-1_101071_2023-04-28_final
2023-04-29 09:32:09	ga_ls8c_ard_3-2-1_092084_2023-04-29_final
2023-05-05 10:32:17	ga_ls8c_ard_3-2-1_102080_2023-05-05_final
2023-05-06 11:16:44	ga_ls8c_ard_3-2-1_109083_2023-05-06_final
2023-05-07 10:16:18	ga_ls8c_ard_3-2-1_100071_2023-05-07_final
2023-05-08 11:01:56	ga_ls8c_ard_3-2-1_107077_2023-05-08_final
2023-05-19 10:44:53	ga_ls8c_ard_3-2-1_104081_2023-05-19_final
2023-05-20 09:49:40	ga_ls8c_ard_3-2-1_095082_2023-05-20_final
2023-05-24 09:27:46	ga_ls8c_ard_3-2-1_091089_2023-05-23_final
2023-05-29 09:45:31	ga_ls8c_ard_3-2-1_094087_2023-05-29_final
2023-06-02 09:20:00	ga_ls8c_ard_3-2-1_090085_2023-06-01_final
2023-06-18 10:58:15	ga_ls8c_ard_3-2-1_106083_2023-06-18_final
2023-06-23 11:15:35	ga_ls8c_ard_3-2-1_109080_2023-06-23_final
2023-06-25 11:03:40	ga_ls8c_ard_3-2-1_107081_2023-06-25_final
2023-07-07 09:47:16	ga_ls8c_ard_3-2-1_095075_2023-07-07_final
2023-07-11 11:02:39	ga_ls8c_ard_3-2-1_107078_2023-07-11_final
2023-07-14 11:34:46	ga_ls8c_ard_3-2-1_112081_2023-07-14_final
2023-07-22 10:44:32	ga_ls8c_ard_3-2-1_104079_2023-07-22_final
2023-07-22 10:45:20	ga_ls8c_ard_3-2-1_104081_2023-07-22_final
2023-07-27 11:04:21	ga_ls8c_ard_3-2-1_107082_2023-07-27_final
2023-08-07 10:45:29	ga_ls8c_ard_3-2-1_104081_2023-08-07_final
2023-08-08 09:51:51	ga_ls8c_ard_3-2-1_095086_2023-08-08_final
2023-08-08 11:26:44	ga_ls8c_ard_3-2-1_111076_2023-08-08_final
2023-08-22 10:03:32	ga_ls8c_ard_3-2-1_097084_2023-08-22_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