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
2022-11-05 10:11:46	ga_ls8c_ard_3-2-1_099072_2022-11-05_final
2022-11-06 10:58:13	ga_ls8c_ard_3-2-1_106080_2022-11-06_final
2022-11-07 10:02:11	ga_ls8c_ard_3-2-1_097079_2022-11-07_final
2022-11-08 10:44:15	ga_ls8c_ard_3-2-1_104076_2022-11-08_final
2022-11-09 09:52:12	ga_ls8c_ard_3-2-1_095085_2022-11-09_final
2022-11-09 11:27:06	ga_ls8c_ard_3-2-1_111075_2022-11-09_final
2022-11-09 11:30:42	ga_ls8c_ard_3-2-1_111084_2022-11-09_final
2022-11-10 10:31:04	ga_ls8c_ard_3-2-1_102074_2022-11-10_final
2022-11-13 09:25:03	ga_ls8c_ard_3-2-1_091079_2022-11-12_final
2022-11-18 09:46:43	ga_ls8c_ard_3-2-1_094087_2022-11-18_final
2022-11-20 09:31:35	ga_ls8c_ard_3-2-1_092080_2022-11-20_final
2022-11-23 09:59:42	ga_ls8c_ard_3-2-1_097073_2022-11-23_final
2022-11-24 10:42:10	ga_ls8c_ard_3-2-1_104071_2022-11-24_final
2022-11-26 10:29:25	ga_ls8c_ard_3-2-1_102070_2022-11-26_final
2022-11-29 11:01:56	ga_ls8c_ard_3-2-1_107074_2022-11-29_final
2022-12-01 09:14:40	ga_ls8c_ard_3-2-1_089084_2022-11-30_final
2022-12-04 09:46:22	ga_ls8c_ard_3-2-1_094086_2022-12-04_final
2022-12-05 10:24:26	ga_ls8c_ard_3-2-1_101073_2022-12-05_final
2022-12-06 09:32:24	ga_ls8c_ard_3-2-1_092082_2022-12-06_final
2022-12-06 09:33:12	ga_ls8c_ard_3-2-1_092084_2022-12-06_final
2022-12-11 11:25:25	ga_ls8c_ard_3-2-1_111071_2022-12-11_final
2022-12-12 10:29:23	ga_ls8c_ard_3-2-1_102070_2022-12-12_final
2022-12-13 11:15:02	ga_ls8c_ard_3-2-1_109076_2022-12-13_final
2022-12-14 11:58:17	ga_ls8c_ard_3-2-1_116076_2022-12-14_final
2022-12-16 10:05:49	ga_ls8c_ard_3-2-1_098073_2022-12-16_final
2022-12-16 10:06:13	ga_ls8c_ard_3-2-1_098074_2022-12-16_final
2022-12-16 10:07:25	ga_ls8c_ard_3-2-1_098077_2022-12-16_final
2022-12-18 09:52:14	ga_ls8c_ard_3-2-1_096070_2022-12-18_final
2022-12-18 09:53:50	ga_ls8c_ard_3-2-1_096074_2022-12-18_final
2022-12-20 09:45:50	ga_ls8c_ard_3-2-1_094085_2022-12-20_final
2022-12-20 11:23:07	ga_ls8c_ard_3-2-1_110081_2022-12-20_final
2022-12-26 10:42:01	ga_ls8c_ard_3-2-1_104071_2022-12-26_final
2022-12-27 09:50:48	ga_ls8c_ard_3-2-1_095082_2022-12-27_final
2022-12-27 11:29:41	ga_ls8c_ard_3-2-1_111082_2022-12-27_final
2022-12-29 09:36:51	ga_ls8c_ard_3-2-1_093078_2022-12-29_final
2022-12-31 09:26:05	ga_ls8c_ard_3-2-1_091082_2022-12-30_final
2022-12-31 09:28:05	ga_ls8c_ard_3-2-1_091087_2022-12-30_final
2023-01-05 11:23:55	ga_ls8c_ard_3-2-1_110083_2023-01-05_final
2023-01-09 09:21:29	ga_ls8c_ard_3-2-1_090086_2023-01-08_final
2023-01-09 09:22:41	ga_ls8c_ard_3-2-1_090089_2023-01-08_final
2023-01-09 10:58:46	ga_ls8c_ard_3-2-1_106082_2023-01-09_final
2023-01-10 11:42:01	ga_ls8c_ard_3-2-1_113082_2023-01-10_final
2023-01-12 11:29:38	ga_ls8c_ard_3-2-1_111082_2023-01-12_final
2023-01-14 11:13:16	ga_ls8c_ard_3-2-1_109072_2023-01-14_final
2023-01-16 09:27:10	ga_ls8c_ard_3-2-1_091085_2023-01-15_final
2023-01-16 11:02:28	ga_ls8c_ard_3-2-1_107076_2023-01-16_final
2023-01-17 11:45:18	ga_ls8c_ard_3-2-1_114075_2023-01-17_final
2023-01-17 11:46:54	ga_ls8c_ard_3-2-1_114079_2023-01-17_final
2023-01-20 10:34:57	ga_ls8c_ard_3-2-1_103069_2023-01-20_final
2023-01-21 11:20:14	ga_ls8c_ard_3-2-1_110074_2023-01-21_final
2023-01-23 09:31:24	ga_ls8c_ard_3-2-1_092080_2023-01-23_final
2023-01-23 11:08:41	ga_ls8c_ard_3-2-1_108076_2023-01-23_final
2023-01-25 09:18:16	ga_ls8c_ard_3-2-1_090078_2023-01-24_final
2023-01-30 09:40:01	ga_ls8c_ard_3-2-1_093086_2023-01-30_final
2023-02-01 09:26:27	ga_ls8c_ard_3-2-1_091083_2023-01-31_final
2023-02-06 11:18:41	ga_ls8c_ard_3-2-1_110070_2023-02-06_final
2023-02-09 11:52:45	ga_ls8c_ard_3-2-1_115078_2023-02-09_final
2023-02-10 09:23:01	ga_ls8c_ard_3-2-1_090090_2023-02-09_final
2023-02-11 10:02:16	ga_ls8c_ard_3-2-1_097080_2023-02-11_final
2023-02-13 11:30:22	ga_ls8c_ard_3-2-1_111084_2023-02-13_final
2023-02-14 10:29:57	ga_ls8c_ard_3-2-1_102072_2023-02-14_final
2023-02-17 09:23:31	ga_ls8c_ard_3-2-1_091076_2023-02-16_final
2023-02-18 11:46:50	ga_ls8c_ard_3-2-1_114079_2023-02-18_final
2023-02-22 09:39:57	ga_ls8c_ard_3-2-1_094071_2023-02-22_final
2023-02-25 10:15:34	ga_ls8c_ard_3-2-1_099083_2023-02-25_final
2023-03-01 11:29:44	ga_ls8c_ard_3-2-1_111083_2023-03-01_final
2023-03-05 11:04:11	ga_ls8c_ard_3-2-1_107081_2023-03-05_final
2023-03-06 10:06:09	ga_ls8c_ard_3-2-1_098075_2023-03-06_final
2023-03-06 11:46:38	ga_ls8c_ard_3-2-1_114079_2023-03-06_final
2023-03-10 11:24:16	ga_ls8c_ard_3-2-1_110085_2023-03-10_final
2023-03-11 10:23:52	ga_ls8c_ard_3-2-1_101073_2023-03-11_final
2023-03-11 10:24:16	ga_ls8c_ard_3-2-1_101074_2023-03-11_final
2023-03-22 10:05:36	ga_ls8c_ard_3-2-1_098074_2023-03-22_final
2023-03-24 09:53:13	ga_ls8c_ard_3-2-1_096074_2023-03-24_final
2023-03-27 10:25:18	ga_ls8c_ard_3-2-1_101077_2023-03-27_final
2023-03-29 10:12:08	ga_ls8c_ard_3-2-1_099075_2023-03-29_final
2023-03-30 10:54:11	ga_ls8c_ard_3-2-1_106072_2023-03-30_final
2023-04-01 10:41:24	ga_ls8c_ard_3-2-1_104071_2023-04-01_final
2023-04-02 09:50:09	ga_ls8c_ard_3-2-1_095082_2023-04-02_final
2023-04-04 11:11:27	ga_ls8c_ard_3-2-1_109069_2023-04-04_final
2023-04-07 10:03:00	ga_ls8c_ard_3-2-1_098068_2023-04-07_final
2023-04-07 11:44:41	ga_ls8c_ard_3-2-1_114075_2023-04-07_final
2023-04-15 09:18:39	ga_ls8c_ard_3-2-1_090081_2023-04-14_final
2023-04-15 10:53:56	ga_ls8c_ard_3-2-1_106072_2023-04-15_final
2023-04-21 10:16:49	ga_ls8c_ard_3-2-1_100072_2023-04-21_final
2023-04-24 10:46:08	ga_ls8c_ard_3-2-1_105068_2023-04-24_final
2023-04-24 10:46:32	ga_ls8c_ard_3-2-1_105069_2023-04-24_final
2023-04-24 10:48:07	ga_ls8c_ard_3-2-1_105073_2023-04-24_final
2023-04-25 09:56:53	ga_ls8c_ard_3-2-1_096084_2023-04-25_final
2023-04-27 09:40:32	ga_ls8c_ard_3-2-1_094074_2023-04-27_final
2023-04-29 11:05:50	ga_ls8c_ard_3-2-1_108071_2023-04-29_final
2023-04-30 10:10:37	ga_ls8c_ard_3-2-1_099072_2023-04-30_final
2023-05-01 10:54:39	ga_ls8c_ard_3-2-1_106074_2023-05-01_final
2023-05-03 10:42:40	ga_ls8c_ard_3-2-1_104075_2023-05-03_final
2023-05-06 09:33:03	ga_ls8c_ard_3-2-1_093071_2023-05-06_final
2023-05-06 09:34:15	ga_ls8c_ard_3-2-1_093074_2023-05-06_final
2023-05-06 11:17:08	ga_ls8c_ard_3-2-1_109084_2023-05-06_final
2023-05-08 09:24:39	ga_ls8c_ard_3-2-1_091081_2023-05-07_final
2023-05-09 10:05:54	ga_ls8c_ard_3-2-1_098076_2023-05-09_final
2023-05-15 09:31:08	ga_ls8c_ard_3-2-1_092082_2023-05-15_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