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:

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First 100 results (query limit)

Time (local)	Label
2021-12-21 09:21:49	ga_ls8c_ard_3-2-1_090087_2021-12-20_final
2021-12-25 10:32:21	ga_ls8c_ard_3-2-1_102078_2021-12-25_final
2021-12-28 11:04:50	ga_ls8c_ard_3-2-1_107082_2021-12-28_final
2021-12-29 10:08:48	ga_ls8c_ard_3-2-1_098081_2021-12-29_final
2022-01-08 10:41:52	ga_ls8c_ard_3-2-1_104071_2022-01-08_final
2022-01-09 09:48:14	ga_ls8c_ard_3-2-1_095076_2022-01-09_final
2022-01-09 11:27:31	ga_ls8c_ard_3-2-1_111077_2022-01-09_final
2022-01-09 11:28:43	ga_ls8c_ard_3-2-1_111080_2022-01-09_final
2022-01-10 10:31:06	ga_ls8c_ard_3-2-1_102075_2022-01-10_final
2022-01-11 09:36:16	ga_ls8c_ard_3-2-1_093077_2022-01-11_final
2022-01-11 09:38:40	ga_ls8c_ard_3-2-1_093083_2022-01-11_final
2022-01-13 11:04:47	ga_ls8c_ard_3-2-1_107082_2022-01-13_final
2022-01-16 11:33:17	ga_ls8c_ard_3-2-1_112076_2022-01-16_final
2022-01-18 09:42:02	ga_ls8c_ard_3-2-1_094076_2022-01-18_final
2022-01-24 10:44:59	ga_ls8c_ard_3-2-1_104079_2022-01-24_final
2022-01-25 11:27:26	ga_ls8c_ard_3-2-1_111077_2022-01-25_final
2022-02-01 11:33:12	ga_ls8c_ard_3-2-1_112076_2022-02-01_final
2022-02-03 09:43:09	ga_ls8c_ard_3-2-1_094079_2022-02-03_final
2022-02-05 09:33:35	ga_ls8c_ard_3-2-1_092086_2022-02-05_final
2022-02-17 09:55:02	ga_ls8c_ard_3-2-1_096078_2022-02-17_final
2022-02-19 09:43:51	ga_ls8c_ard_3-2-1_094081_2022-02-19_final
2022-02-19 09:44:39	ga_ls8c_ard_3-2-1_094083_2022-02-19_final
2022-02-20 10:24:19	ga_ls8c_ard_3-2-1_101074_2022-02-20_final
2022-02-23 10:56:24	ga_ls8c_ard_3-2-1_106077_2022-02-23_final
2022-02-24 11:39:40	ga_ls8c_ard_3-2-1_113077_2022-02-24_final
2022-02-25 10:44:03	ga_ls8c_ard_3-2-1_104077_2022-02-25_final
2022-02-26 09:48:01	ga_ls8c_ard_3-2-1_095076_2022-02-26_final
2022-03-01 10:20:55	ga_ls8c_ard_3-2-1_100081_2022-03-01_final
2022-03-01 11:57:48	ga_ls8c_ard_3-2-1_116076_2022-03-01_final
2022-03-12 10:02:43	ga_ls8c_ard_3-2-1_097082_2022-03-12_final
2022-03-12 11:38:48	ga_ls8c_ard_3-2-1_113075_2022-03-12_final
2022-03-12 11:39:36	ga_ls8c_ard_3-2-1_113077_2022-03-12_final
2022-03-13 10:42:47	ga_ls8c_ard_3-2-1_104074_2022-03-13_final
2022-03-13 10:44:22	ga_ls8c_ard_3-2-1_104078_2022-03-13_final
2022-03-14 09:47:57	ga_ls8c_ard_3-2-1_095076_2022-03-14_final
2022-03-15 10:30:48	ga_ls8c_ard_3-2-1_102075_2022-03-15_final
2022-03-16 09:38:21	ga_ls8c_ard_3-2-1_093083_2022-03-16_final
2022-03-18 11:03:40	ga_ls8c_ard_3-2-1_107080_2022-03-18_final
2022-03-20 10:47:41	ga_ls8c_ard_3-2-1_105071_2022-03-20_final
2022-03-21 09:53:15	ga_ls8c_ard_3-2-1_096074_2022-03-21_final
2022-03-21 09:56:50	ga_ls8c_ard_3-2-1_096083_2022-03-21_final
2022-03-24 10:24:54	ga_ls8c_ard_3-2-1_101076_2022-03-24_final
2022-03-29 10:43:22	ga_ls8c_ard_3-2-1_104076_2022-03-29_final
2022-03-30 09:47:44	ga_ls8c_ard_3-2-1_095076_2022-03-30_final
2022-04-01 09:35:46	ga_ls8c_ard_3-2-1_093077_2022-04-01_final
2022-04-04 10:06:17	ga_ls8c_ard_3-2-1_098076_2022-04-04_final
2022-04-08 09:42:01	ga_ls8c_ard_3-2-1_094077_2022-04-08_final
2022-04-08 11:22:30	ga_ls8c_ard_3-2-1_110081_2022-04-08_final
2022-04-12 09:19:19	ga_ls8c_ard_3-2-1_090082_2022-04-11_final
2022-04-15 09:47:26	ga_ls8c_ard_3-2-1_095075_2022-04-15_final
2022-04-24 11:20:54	ga_ls8c_ard_3-2-1_110077_2022-04-24_final
2022-04-29 11:40:12	ga_ls8c_ard_3-2-1_113079_2022-04-29_final
2022-04-30 10:40:36	ga_ls8c_ard_3-2-1_104069_2022-04-30_final
2022-04-30 10:45:23	ga_ls8c_ard_3-2-1_104081_2022-04-30_final
2022-05-01 11:29:04	ga_ls8c_ard_3-2-1_111082_2022-05-01_final
2022-05-03 09:38:39	ga_ls8c_ard_3-2-1_093084_2022-05-03_final
2022-05-06 10:05:35	ga_ls8c_ard_3-2-1_098074_2022-05-06_final
2022-05-07 10:47:16	ga_ls8c_ard_3-2-1_105070_2022-05-07_final
2022-05-07 10:48:28	ga_ls8c_ard_3-2-1_105073_2022-05-07_final
2022-05-14 10:57:54	ga_ls8c_ard_3-2-1_106081_2022-05-14_final
2022-05-19 11:15:16	ga_ls8c_ard_3-2-1_109078_2022-05-19_final
2022-05-21 11:04:30	ga_ls8c_ard_3-2-1_107082_2022-05-21_final
2022-05-22 10:05:41	ga_ls8c_ard_3-2-1_098074_2022-05-22_final
2022-05-23 10:51:44	ga_ls8c_ard_3-2-1_105081_2022-05-23_final
2022-05-24 09:56:07	ga_ls8c_ard_3-2-1_096081_2022-05-24_final
2022-05-26 09:41:21	ga_ls8c_ard_3-2-1_094075_2022-05-26_final
2022-05-26 09:44:09	ga_ls8c_ard_3-2-1_094082_2022-05-26_final
2022-05-26 09:44:32	ga_ls8c_ard_3-2-1_094083_2022-05-26_final
2022-05-27 10:23:24	ga_ls8c_ard_3-2-1_101072_2022-05-27_final
2022-05-28 09:29:47	ga_ls8c_ard_3-2-1_092077_2022-05-27_final
2022-05-30 10:56:44	ga_ls8c_ard_3-2-1_106078_2022-05-30_final
2022-06-01 10:42:01	ga_ls8c_ard_3-2-1_104072_2022-06-01_final
2022-06-07 10:08:37	ga_ls8c_ard_3-2-1_098081_2022-06-07_final
2022-06-08 10:47:54	ga_ls8c_ard_3-2-1_105071_2022-06-08_final
2022-06-09 09:53:05	ga_ls8c_ard_3-2-1_096073_2022-06-09_final
2022-06-10 10:38:45	ga_ls8c_ard_3-2-1_103079_2022-06-10_final
2022-06-11 11:22:26	ga_ls8c_ard_3-2-1_110080_2022-06-11_final
2022-06-13 09:30:00	ga_ls8c_ard_3-2-1_092077_2022-06-13_final
2022-06-20 09:37:27	ga_ls8c_ard_3-2-1_093080_2022-06-20_final
2022-06-20 09:37:51	ga_ls8c_ard_3-2-1_093081_2022-06-20_final
2022-06-21 10:21:07	ga_ls8c_ard_3-2-1_100081_2022-06-21_final
2022-06-21 11:58:48	ga_ls8c_ard_3-2-1_116078_2022-06-21_final
2022-06-23 10:05:58	ga_ls8c_ard_3-2-1_098074_2022-06-23_final
2022-06-25 09:52:49	ga_ls8c_ard_3-2-1_096072_2022-06-25_final
2022-06-25 09:56:00	ga_ls8c_ard_3-2-1_096080_2022-06-25_final
2022-06-27 09:42:27	ga_ls8c_ard_3-2-1_094077_2022-06-27_final
2022-07-02 09:59:24	ga_ls8c_ard_3-2-1_097073_2022-07-02_final
2022-07-02 11:41:05	ga_ls8c_ard_3-2-1_113080_2022-07-02_final
2022-07-03 10:42:16	ga_ls8c_ard_3-2-1_104072_2022-07-03_final
2022-07-05 10:29:55	ga_ls8c_ard_3-2-1_102072_2022-07-05_final
2022-07-06 09:38:17	ga_ls8c_ard_3-2-1_093082_2022-07-06_final
2022-07-06 09:38:41	ga_ls8c_ard_3-2-1_093083_2022-07-06_final
2022-07-10 10:48:03	ga_ls8c_ard_3-2-1_105071_2022-07-10_final
2022-07-11 09:56:24	ga_ls8c_ard_3-2-1_096081_2022-07-11_final
2022-07-12 10:34:53	ga_ls8c_ard_3-2-1_103069_2022-07-12_final
2022-07-13 11:18:32	ga_ls8c_ard_3-2-1_110070_2022-07-13_final
2022-07-15 11:08:33	ga_ls8c_ard_3-2-1_108076_2022-07-15_final
2022-07-16 10:12:08	ga_ls8c_ard_3-2-1_099074_2022-07-16_final
2022-07-17 09:19:44	ga_ls8c_ard_3-2-1_090082_2022-07-16_final
2022-07-24 11:03:18	ga_ls8c_ard_3-2-1_107078_2022-07-24_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