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
2023-01-04 10:36:40	ga_ls8c_ard_3-2-1_103073_2023-01-04_final
2023-01-08 10:12:19	ga_ls8c_ard_3-2-1_099074_2023-01-08_final
2023-01-18 10:50:04	ga_ls8c_ard_3-2-1_105076_2023-01-18_final
2023-01-19 11:35:45	ga_ls8c_ard_3-2-1_112082_2023-01-19_final
2023-01-19 11:36:33	ga_ls8c_ard_3-2-1_112084_2023-01-19_final
2023-01-23 09:29:48	ga_ls8c_ard_3-2-1_092076_2023-01-22_final
2023-01-31 10:18:05	ga_ls8c_ard_3-2-1_100073_2023-01-31_final
2023-02-13 11:30:22	ga_ls8c_ard_3-2-1_111084_2023-02-13_final
2023-02-19 10:52:47	ga_ls8c_ard_3-2-1_105083_2023-02-19_final
2023-02-20 11:32:26	ga_ls8c_ard_3-2-1_112074_2023-02-20_final
2023-02-22 09:46:20	ga_ls8c_ard_3-2-1_094087_2023-02-22_final
2023-03-01 09:50:51	ga_ls8c_ard_3-2-1_095083_2023-03-01_final
2023-03-03 09:38:05	ga_ls8c_ard_3-2-1_093082_2023-03-03_final
2023-03-05 09:26:54	ga_ls8c_ard_3-2-1_091085_2023-03-04_final
2023-03-05 11:04:11	ga_ls8c_ard_3-2-1_107081_2023-03-05_final
2023-03-07 09:12:07	ga_ls8c_ard_3-2-1_089079_2023-03-06_final
2023-03-08 11:35:26	ga_ls8c_ard_3-2-1_112082_2023-03-08_final
2023-03-15 11:41:36	ga_ls8c_ard_3-2-1_113082_2023-03-15_final
2023-03-17 09:50:20	ga_ls8c_ard_3-2-1_095082_2023-03-17_final
2023-03-17 11:29:37	ga_ls8c_ard_3-2-1_111083_2023-03-17_final
2023-03-18 10:28:48	ga_ls8c_ard_3-2-1_102070_2023-03-18_final
2023-03-23 09:12:45	ga_ls8c_ard_3-2-1_089081_2023-03-22_final
2023-03-28 09:28:53	ga_ls8c_ard_3-2-1_092075_2023-03-27_final
2023-03-28 11:08:57	ga_ls8c_ard_3-2-1_108078_2023-03-28_final
2023-04-02 09:46:58	ga_ls8c_ard_3-2-1_095074_2023-04-02_final
2023-04-03 10:28:13	ga_ls8c_ard_3-2-1_102069_2023-04-03_final
2023-04-04 11:12:39	ga_ls8c_ard_3-2-1_109072_2023-04-04_final
2023-04-06 11:05:02	ga_ls8c_ard_3-2-1_107084_2023-04-06_final
2023-04-07 10:05:24	ga_ls8c_ard_3-2-1_098074_2023-04-07_final
2023-04-13 09:31:25	ga_ls8c_ard_3-2-1_092082_2023-04-13_final
2023-04-13 11:11:06	ga_ls8c_ard_3-2-1_108084_2023-04-13_final
2023-04-16 09:57:55	ga_ls8c_ard_3-2-1_097071_2023-04-16_final
2023-04-16 10:02:42	ga_ls8c_ard_3-2-1_097083_2023-04-16_final
2023-04-24 10:52:07	ga_ls8c_ard_3-2-1_105083_2023-04-24_final
2023-04-27 09:40:08	ga_ls8c_ard_3-2-1_094073_2023-04-27_final
2023-05-02 10:03:25	ga_ls8c_ard_3-2-1_097085_2023-05-02_final
2023-05-04 11:25:31	ga_ls8c_ard_3-2-1_111074_2023-05-04_final
2023-05-13 11:17:36	ga_ls8c_ard_3-2-1_110070_2023-05-13_final
2023-05-15 09:30:20	ga_ls8c_ard_3-2-1_092080_2023-05-15_final
2023-05-18 10:03:12	ga_ls8c_ard_3-2-1_097085_2023-05-18_final
2023-05-25 10:07:03	ga_ls8c_ard_3-2-1_098079_2023-05-25_final
2023-05-26 09:15:49	ga_ls8c_ard_3-2-1_089090_2023-05-25_final
2023-05-31 11:07:39	ga_ls8c_ard_3-2-1_108076_2023-05-31_final
2023-06-03 11:40:58	ga_ls8c_ard_3-2-1_113082_2023-06-03_final
2023-06-06 10:28:38	ga_ls8c_ard_3-2-1_102071_2023-06-06_final
2023-06-09 09:25:29	ga_ls8c_ard_3-2-1_091083_2023-06-08_final
2023-06-09 09:27:53	ga_ls8c_ard_3-2-1_091089_2023-06-08_final
2023-06-10 10:09:33	ga_ls8c_ard_3-2-1_098085_2023-06-10_final
2023-06-12 09:52:25	ga_ls8c_ard_3-2-1_096073_2023-06-12_final
2023-06-12 09:56:01	ga_ls8c_ard_3-2-1_096082_2023-06-12_final
2023-06-16 11:09:24	ga_ls8c_ard_3-2-1_108080_2023-06-16_final
2023-06-17 10:09:24	ga_ls8c_ard_3-2-1_099069_2023-06-17_final
2023-06-19 09:59:02	ga_ls8c_ard_3-2-1_097074_2023-06-19_final
2023-06-19 11:38:43	ga_ls8c_ard_3-2-1_113076_2023-06-19_final
2023-07-10 10:17:48	ga_ls8c_ard_3-2-1_100074_2023-07-10_final
2023-07-16 09:44:43	ga_ls8c_ard_3-2-1_094084_2023-07-16_final
2023-07-27 11:01:57	ga_ls8c_ard_3-2-1_107076_2023-07-27_final
2023-07-30 11:31:18	ga_ls8c_ard_3-2-1_112072_2023-07-30_final
2023-08-06 09:59:25	ga_ls8c_ard_3-2-1_097074_2023-08-06_final
2023-08-06 11:41:30	ga_ls8c_ard_3-2-1_113082_2023-08-06_final
2023-08-12 09:25:56	ga_ls8c_ard_3-2-1_091083_2023-08-11_final
2023-08-14 10:52:06	ga_ls8c_ard_3-2-1_105082_2023-08-14_final
2023-08-15 11:35:46	ga_ls8c_ard_3-2-1_112083_2023-08-15_final
2023-08-16 10:34:11	ga_ls8c_ard_3-2-1_103068_2023-08-16_final
2023-08-23 09:06:19	ga_ls8c_ard_3-2-1_088080_2023-08-22_final
2023-08-24 09:46:48	ga_ls8c_ard_3-2-1_095073_2023-08-24_final
2023-08-28 10:59:46	ga_ls8c_ard_3-2-1_107070_2023-08-28_final
2023-08-30 10:49:00	ga_ls8c_ard_3-2-1_105074_2023-08-30_final
2023-09-04 09:29:02	ga_ls8c_ard_3-2-1_092075_2023-09-03_final
2023-09-10 10:33:16	ga_ls8c_ard_3-2-1_102081_2023-09-10_final
2023-09-13 09:26:55	ga_ls8c_ard_3-2-1_091085_2023-09-12_final
2023-09-16 09:52:15	ga_ls8c_ard_3-2-1_096071_2023-09-16_final
2023-09-18 09:41:05	ga_ls8c_ard_3-2-1_094074_2023-09-18_final
2023-09-18 11:23:58	ga_ls8c_ard_3-2-1_110084_2023-09-18_final
2023-09-22 10:58:26	ga_ls8c_ard_3-2-1_106082_2023-09-22_final
2023-09-23 11:40:55	ga_ls8c_ard_3-2-1_113080_2023-09-23_final
2023-09-24 10:42:06	ga_ls8c_ard_3-2-1_104072_2023-09-24_final
2023-09-29 09:27:00	ga_ls8c_ard_3-2-1_091085_2023-09-28_final
2023-10-02 09:52:43	ga_ls8c_ard_3-2-1_096072_2023-10-02_final
2023-10-07 10:11:15	ga_ls8c_ard_3-2-1_099072_2023-10-07_final
2023-10-08 10:57:43	ga_ls8c_ard_3-2-1_106080_2023-10-08_final
2023-10-13 09:35:24	ga_ls8c_ard_3-2-1_093075_2023-10-13_final
2023-10-13 11:15:05	ga_ls8c_ard_3-2-1_109077_2023-10-13_final
2023-10-16 10:07:30	ga_ls8c_ard_3-2-1_098078_2023-10-16_final
2023-10-18 09:53:08	ga_ls8c_ard_3-2-1_096073_2023-10-18_final
2023-10-19 10:39:35	ga_ls8c_ard_3-2-1_103081_2023-10-19_final
2023-10-21 10:24:26	ga_ls8c_ard_3-2-1_101074_2023-10-21_final
2023-10-24 10:54:34	ga_ls8c_ard_3-2-1_106072_2023-10-24_final
2023-10-27 09:51:00	ga_ls8c_ard_3-2-1_095083_2023-10-27_final
2023-10-30 10:19:55	ga_ls8c_ard_3-2-1_100078_2023-10-30_final
2023-10-31 11:04:46	ga_ls8c_ard_3-2-1_107082_2023-10-31_final
2023-11-05 09:45:12	ga_ls8c_ard_3-2-1_094084_2023-11-05_final
2023-11-05 11:18:30	ga_ls8c_ard_3-2-1_110070_2023-11-05_final
2023-11-05 11:24:05	ga_ls8c_ard_3-2-1_110084_2023-11-05_final
2023-11-07 09:32:25	ga_ls8c_ard_3-2-1_092083_2023-11-07_final
2023-11-09 10:56:07	ga_ls8c_ard_3-2-1_106076_2023-11-09_final
2023-11-10 11:41:46	ga_ls8c_ard_3-2-1_113082_2023-11-10_final
2023-11-15 10:21:05	ga_ls8c_ard_3-2-1_100081_2023-11-15_final
2023-11-16 09:26:16	ga_ls8c_ard_3-2-1_091083_2023-11-15_final
2023-11-18 09:14:20	ga_ls8c_ard_3-2-1_089084_2023-11-17_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