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
2016-12-13 08:42:42	ga_ls8c_ard_3-2-1_084082_2016-12-12_final
2017-12-13 08:10:52	ga_ls8c_ard_3-2-1_079080_2017-12-12_final
2022-02-13 10:18:35	ga_ls8c_ard_3-2-1_100075_2022-02-13_final
2022-02-13 10:21:23	ga_ls8c_ard_3-2-1_100082_2022-02-13_final
2022-02-19 11:22:44	ga_ls8c_ard_3-2-1_110081_2022-02-19_final
2022-03-09 11:09:31	ga_ls8c_ard_3-2-1_108079_2022-03-09_final
2022-03-12 11:37:37	ga_ls8c_ard_3-2-1_113072_2022-03-12_final
2022-03-25 09:31:16	ga_ls8c_ard_3-2-1_092081_2022-03-25_final
2022-04-01 09:35:22	ga_ls8c_ard_3-2-1_093076_2022-04-01_final
2022-04-04 10:02:42	ga_ls8c_ard_3-2-1_098067_2022-04-04_final
2022-04-30 10:40:36	ga_ls8c_ard_3-2-1_104069_2022-04-30_final
2022-05-01 11:29:28	ga_ls8c_ard_3-2-1_111083_2022-05-01_final
2022-05-16 10:42:45	ga_ls8c_ard_3-2-1_104074_2022-05-16_final
2022-05-17 11:29:37	ga_ls8c_ard_3-2-1_111083_2022-05-17_final
2022-05-21 09:26:49	ga_ls8c_ard_3-2-1_091085_2022-05-20_final
2022-06-10 10:35:10	ga_ls8c_ard_3-2-1_103070_2022-06-10_final
2022-06-10 10:36:22	ga_ls8c_ard_3-2-1_103073_2022-06-10_final
2022-06-25 09:55:13	ga_ls8c_ard_3-2-1_096078_2022-06-25_final
2022-07-25 10:08:05	ga_ls8c_ard_3-2-1_098079_2022-07-25_final
2022-07-29 09:41:01	ga_ls8c_ard_3-2-1_094073_2022-07-29_final
2022-07-30 10:24:17	ga_ls8c_ard_3-2-1_101073_2022-07-30_final
2022-08-22 10:32:12	ga_ls8c_ard_3-2-1_102077_2022-08-22_final
2022-08-23 11:12:16	ga_ls8c_ard_3-2-1_109069_2022-08-23_final
2022-08-30 09:43:57	ga_ls8c_ard_3-2-1_094080_2022-08-30_final
2022-09-12 10:48:01	ga_ls8c_ard_3-2-1_105070_2022-09-12_final
2022-09-20 09:58:37	ga_ls8c_ard_3-2-1_097070_2022-09-20_final
2022-09-27 11:45:40	ga_ls8c_ard_3-2-1_114075_2022-09-27_final
2022-10-11 10:21:50	ga_ls8c_ard_3-2-1_100082_2022-10-11_final
2022-10-11 10:22:14	ga_ls8c_ard_3-2-1_100083_2022-10-11_final
2022-10-14 10:46:42	ga_ls8c_ard_3-2-1_105067_2022-10-14_final
2022-10-22 11:41:26	ga_ls8c_ard_3-2-1_113080_2022-10-22_final
2022-11-03 10:23:20	ga_ls8c_ard_3-2-1_101070_2022-11-03_final
2022-11-04 09:32:30	ga_ls8c_ard_3-2-1_092082_2022-11-04_final
2022-11-06 09:20:56	ga_ls8c_ard_3-2-1_090084_2022-11-05_final
2022-11-07 11:40:16	ga_ls8c_ard_3-2-1_113077_2022-11-07_final
2022-11-07 11:41:28	ga_ls8c_ard_3-2-1_113080_2022-11-07_final
2022-11-18 09:43:55	ga_ls8c_ard_3-2-1_094080_2022-11-18_final
2022-11-24 10:42:58	ga_ls8c_ard_3-2-1_104073_2022-11-24_final
2022-11-26 10:32:37	ga_ls8c_ard_3-2-1_102078_2022-11-26_final
2022-11-29 11:01:32	ga_ls8c_ard_3-2-1_107073_2022-11-29_final
2023-01-05 09:45:02	ga_ls8c_ard_3-2-1_094083_2023-01-05_final
2023-01-05 11:24:18	ga_ls8c_ard_3-2-1_110084_2023-01-05_final
2023-01-15 11:58:54	ga_ls8c_ard_3-2-1_116078_2023-01-15_final
2023-01-16 09:26:46	ga_ls8c_ard_3-2-1_091084_2023-01-15_final
2023-02-08 11:11:29	ga_ls8c_ard_3-2-1_108083_2023-02-08_final
2023-02-11 10:02:40	ga_ls8c_ard_3-2-1_097081_2023-02-11_final
2023-02-12 10:43:55	ga_ls8c_ard_3-2-1_104076_2023-02-12_final
2023-02-16 10:21:33	ga_ls8c_ard_3-2-1_100082_2023-02-16_final
2023-03-04 11:57:49	ga_ls8c_ard_3-2-1_116076_2023-03-04_final
2023-03-14 09:19:04	ga_ls8c_ard_3-2-1_090081_2023-03-13_final
2023-03-17 11:26:26	ga_ls8c_ard_3-2-1_111075_2023-03-17_final
2023-03-19 11:12:03	ga_ls8c_ard_3-2-1_109070_2023-03-19_final
2023-03-22 10:08:00	ga_ls8c_ard_3-2-1_098080_2023-03-22_final
2023-04-03 10:28:13	ga_ls8c_ard_3-2-1_102069_2023-04-03_final
2023-04-09 09:52:59	ga_ls8c_ard_3-2-1_096074_2023-04-09_final
2023-04-26 10:35:45	ga_ls8c_ard_3-2-1_103073_2023-04-26_final
2023-05-07 10:20:41	ga_ls8c_ard_3-2-1_100082_2023-05-07_final
2023-05-11 09:51:54	ga_ls8c_ard_3-2-1_096072_2023-05-11_final
2023-05-17 10:54:02	ga_ls8c_ard_3-2-1_106073_2023-05-17_final
2023-05-18 09:58:49	ga_ls8c_ard_3-2-1_097074_2023-05-18_final
2023-05-26 09:10:38	ga_ls8c_ard_3-2-1_089077_2023-05-25_final
2023-05-31 11:07:39	ga_ls8c_ard_3-2-1_108076_2023-05-31_final
2023-06-07 09:34:37	ga_ls8c_ard_3-2-1_093075_2023-06-07_final
2023-06-09 09:21:05	ga_ls8c_ard_3-2-1_091072_2023-06-08_final
2023-06-13 10:35:41	ga_ls8c_ard_3-2-1_103073_2023-06-13_final
2023-06-23 11:12:24	ga_ls8c_ard_3-2-1_109072_2023-06-23_final
2023-06-26 11:44:33	ga_ls8c_ard_3-2-1_114075_2023-06-26_final
2023-07-23 11:29:49	ga_ls8c_ard_3-2-1_111084_2023-07-23_final
2023-08-03 09:32:30	ga_ls8c_ard_3-2-1_092084_2023-08-03_final
2023-08-15 11:35:22	ga_ls8c_ard_3-2-1_112082_2023-08-15_final
2023-08-16 10:34:11	ga_ls8c_ard_3-2-1_103068_2023-08-16_final
2023-09-11 09:38:27	ga_ls8c_ard_3-2-1_093083_2023-09-11_final
2023-09-12 11:58:37	ga_ls8c_ard_3-2-1_116078_2023-09-12_final
2023-09-19 10:23:57	ga_ls8c_ard_3-2-1_101073_2023-09-19_final
2023-09-22 09:17:58	ga_ls8c_ard_3-2-1_090078_2023-09-21_final
2023-09-25 09:50:05	ga_ls8c_ard_3-2-1_095081_2023-09-25_final
2023-09-26 10:32:34	ga_ls8c_ard_3-2-1_102079_2023-09-26_final
2023-10-24 10:57:46	ga_ls8c_ard_3-2-1_106080_2023-10-24_final
2023-10-25 10:02:57	ga_ls8c_ard_3-2-1_097082_2023-10-25_final
2023-11-01 11:46:26	ga_ls8c_ard_3-2-1_114078_2023-11-01_final
2023-11-10 09:59:41	ga_ls8c_ard_3-2-1_097074_2023-11-10_final
2023-11-13 10:31:50	ga_ls8c_ard_3-2-1_102077_2023-11-13_final
2023-12-16 09:39:02	ga_ls8c_ard_3-2-1_093084_2023-12-16_final
2023-12-19 11:46:50	ga_ls8c_ard_3-2-1_114079_2023-12-19_final
2023-12-27 09:18:53	ga_ls8c_ard_3-2-1_090080_2023-12-26_final
2023-12-28 10:00:33	ga_ls8c_ard_3-2-1_097076_2023-12-28_final
2024-01-02 10:21:01	ga_ls8c_ard_3-2-1_100081_2024-01-02_final
2024-01-07 10:35:08	ga_ls8c_ard_3-2-1_103070_2024-01-07_final
2024-01-07 10:37:32	ga_ls8c_ard_3-2-1_103076_2024-01-07_final
2024-01-07 10:37:56	ga_ls8c_ard_3-2-1_103077_2024-01-07_final
2024-01-08 11:23:36	ga_ls8c_ard_3-2-1_110083_2024-01-08_final
2024-01-10 11:06:28	ga_ls8c_ard_3-2-1_108071_2024-01-10_final
2024-01-10 11:08:27	ga_ls8c_ard_3-2-1_108076_2024-01-10_final
2024-01-13 10:01:41	ga_ls8c_ard_3-2-1_097079_2024-01-13_final
2024-02-05 11:45:07	ga_ls8c_ard_3-2-1_114075_2024-02-05_final
2024-02-11 11:06:27	ga_ls8c_ard_3-2-1_108071_2024-02-11_final
2024-02-11 11:07:15	ga_ls8c_ard_3-2-1_108073_2024-02-11_final
2024-02-25 09:45:27	ga_ls8c_ard_3-2-1_094085_2024-02-25_final
2024-03-01 10:00:20	ga_ls8c_ard_3-2-1_097076_2024-03-01_final
2024-03-01 11:38:49	ga_ls8c_ard_3-2-1_113075_2024-03-01_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years