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
2022-01-04 09:29:18	ga_ls8c_ard_3-2-1_092075_2022-01-03_final
2022-01-07 09:58:36	ga_ls8c_ard_3-2-1_097071_2022-01-07_final
2022-01-21 11:51:48	ga_ls8c_ard_3-2-1_115076_2022-01-21_final
2022-01-24 10:42:35	ga_ls8c_ard_3-2-1_104073_2022-01-24_final
2022-01-26 10:29:25	ga_ls8c_ard_3-2-1_102071_2022-01-26_final
2022-02-03 11:18:51	ga_ls8c_ard_3-2-1_110071_2022-02-03_final
2022-02-03 11:20:50	ga_ls8c_ard_3-2-1_110076_2022-02-03_final
2022-02-08 10:03:40	ga_ls8c_ard_3-2-1_097084_2022-02-08_final
2022-02-08 11:39:46	ga_ls8c_ard_3-2-1_113077_2022-02-08_final
2022-02-18 10:35:54	ga_ls8c_ard_3-2-1_103072_2022-02-18_final
2022-03-09 09:33:50	ga_ls8c_ard_3-2-1_092087_2022-03-09_final
2022-03-22 10:34:30	ga_ls8c_ard_3-2-1_103069_2022-03-22_final
2022-04-03 10:59:30	ga_ls8c_ard_3-2-1_107070_2022-04-03_final
2022-04-21 09:12:44	ga_ls8c_ard_3-2-1_089081_2022-04-20_final
2022-05-31 10:01:56	ga_ls8c_ard_3-2-1_097080_2022-05-31_final
2022-05-31 10:03:32	ga_ls8c_ard_3-2-1_097084_2022-05-31_final
2022-06-02 11:29:41	ga_ls8c_ard_3-2-1_111083_2022-06-02_final
2022-06-03 10:28:29	ga_ls8c_ard_3-2-1_102069_2022-06-03_final
2022-06-08 10:46:42	ga_ls8c_ard_3-2-1_105068_2022-06-08_final
2022-06-08 10:49:30	ga_ls8c_ard_3-2-1_105075_2022-06-08_final
2022-06-08 10:52:17	ga_ls8c_ard_3-2-1_105082_2022-06-08_final
2022-07-03 10:42:40	ga_ls8c_ard_3-2-1_104073_2022-07-03_final
2022-07-27 09:57:45	ga_ls8c_ard_3-2-1_096084_2022-07-27_final
2022-08-06 10:28:32	ga_ls8c_ard_3-2-1_102068_2022-08-06_final
2022-08-10 10:04:15	ga_ls8c_ard_3-2-1_098069_2022-08-10_final
2022-08-19 09:57:18	ga_ls8c_ard_3-2-1_097067_2022-08-19_final
2022-08-27 09:13:03	ga_ls8c_ard_3-2-1_089080_2022-08-26_final
2022-08-28 09:57:54	ga_ls8c_ard_3-2-1_096084_2022-08-28_final
2022-09-18 10:15:45	ga_ls8c_ard_3-2-1_099082_2022-09-18_final
2022-09-26 11:02:01	ga_ls8c_ard_3-2-1_107074_2022-09-26_final
2022-09-28 09:13:58	ga_ls8c_ard_3-2-1_089082_2022-09-27_final
2022-10-01 09:40:28	ga_ls8c_ard_3-2-1_094071_2022-10-01_final
2022-10-12 09:25:23	ga_ls8c_ard_3-2-1_091080_2022-10-11_final
2022-10-19 09:34:48	ga_ls8c_ard_3-2-1_092088_2022-10-19_final
2022-10-25 10:28:41	ga_ls8c_ard_3-2-1_102068_2022-10-25_final
2022-10-27 10:22:43	ga_ls8c_ard_3-2-1_100084_2022-10-27_final
2022-10-30 09:15:33	ga_ls8c_ard_3-2-1_089086_2022-10-29_final
2022-10-30 10:50:27	ga_ls8c_ard_3-2-1_105076_2022-10-30_final
2022-11-04 09:28:30	ga_ls8c_ard_3-2-1_092072_2022-11-03_final
2022-11-04 09:32:30	ga_ls8c_ard_3-2-1_092082_2022-11-04_final
2022-11-05 10:16:57	ga_ls8c_ard_3-2-1_099085_2022-11-05_final
2022-11-07 11:39:05	ga_ls8c_ard_3-2-1_113074_2022-11-07_final
2022-11-09 09:52:36	ga_ls8c_ard_3-2-1_095086_2022-11-09_final
2022-11-13 09:28:15	ga_ls8c_ard_3-2-1_091087_2022-11-12_final
2022-11-15 09:13:28	ga_ls8c_ard_3-2-1_089081_2022-11-14_final
2022-11-18 11:23:36	ga_ls8c_ard_3-2-1_110082_2022-11-18_final
2022-11-22 09:18:26	ga_ls8c_ard_3-2-1_090078_2022-11-21_final
2022-11-23 10:04:30	ga_ls8c_ard_3-2-1_097085_2022-11-23_final
2022-11-27 09:40:35	ga_ls8c_ard_3-2-1_093087_2022-11-27_final
2022-12-01 09:14:40	ga_ls8c_ard_3-2-1_089084_2022-11-30_final
2022-12-01 10:46:46	ga_ls8c_ard_3-2-1_105067_2022-12-01_final
2022-12-01 10:47:34	ga_ls8c_ard_3-2-1_105069_2022-12-01_final
2022-12-08 09:21:14	ga_ls8c_ard_3-2-1_090085_2022-12-07_final
2022-12-29 09:40:02	ga_ls8c_ard_3-2-1_093086_2022-12-29_final
2023-01-07 09:33:27	ga_ls8c_ard_3-2-1_092085_2023-01-07_final
2023-01-13 10:28:49	ga_ls8c_ard_3-2-1_102069_2023-01-13_final
2023-01-16 11:00:52	ga_ls8c_ard_3-2-1_107072_2023-01-16_final
2023-01-29 10:30:27	ga_ls8c_ard_3-2-1_102073_2023-01-29_final
2023-02-03 09:14:53	ga_ls8c_ard_3-2-1_089085_2023-02-02_final
2023-02-05 10:34:37	ga_ls8c_ard_3-2-1_103068_2023-02-05_final
2023-02-08 11:08:18	ga_ls8c_ard_3-2-1_108075_2023-02-08_final
2023-02-10 10:54:43	ga_ls8c_ard_3-2-1_106072_2023-02-10_final
2023-02-10 10:55:31	ga_ls8c_ard_3-2-1_106074_2023-02-10_final
2023-02-15 11:14:23	ga_ls8c_ard_3-2-1_109075_2023-02-15_final
2023-02-19 09:14:18	ga_ls8c_ard_3-2-1_089084_2023-02-18_final
2023-02-20 11:31:38	ga_ls8c_ard_3-2-1_112072_2023-02-20_final
2023-02-22 11:23:13	ga_ls8c_ard_3-2-1_110082_2023-02-22_final
2023-03-05 09:26:54	ga_ls8c_ard_3-2-1_091085_2023-03-04_final
2023-03-05 09:28:06	ga_ls8c_ard_3-2-1_091088_2023-03-04_final
2023-03-11 10:25:28	ga_ls8c_ard_3-2-1_101077_2023-03-11_final
2023-03-13 10:09:06	ga_ls8c_ard_3-2-1_099067_2023-03-13_final
2023-03-14 09:20:40	ga_ls8c_ard_3-2-1_090085_2023-03-13_final
2023-03-16 10:42:23	ga_ls8c_ard_3-2-1_104073_2023-03-16_final
2023-03-23 10:46:03	ga_ls8c_ard_3-2-1_105067_2023-03-23_final
2023-03-24 11:35:17	ga_ls8c_ard_3-2-1_112082_2023-03-24_final
2023-03-30 10:57:47	ga_ls8c_ard_3-2-1_106081_2023-03-30_final
2023-04-13 09:31:01	ga_ls8c_ard_3-2-1_092081_2023-04-13_final
2023-04-14 10:13:52	ga_ls8c_ard_3-2-1_099080_2023-04-14_final
2023-04-27 09:45:19	ga_ls8c_ard_3-2-1_094086_2023-04-27_final
2023-05-11 09:51:06	ga_ls8c_ard_3-2-1_096070_2023-05-11_final
2023-05-13 11:22:47	ga_ls8c_ard_3-2-1_110083_2023-05-13_final
2023-05-13 11:23:11	ga_ls8c_ard_3-2-1_110084_2023-05-13_final
2023-05-26 10:48:19	ga_ls8c_ard_3-2-1_105074_2023-05-26_final
2023-06-11 09:14:20	ga_ls8c_ard_3-2-1_089086_2023-06-10_final
2023-06-12 11:34:54	ga_ls8c_ard_3-2-1_112082_2023-06-12_final
2023-06-25 09:25:59	ga_ls8c_ard_3-2-1_091084_2023-06-24_final
2023-07-02 09:31:04	ga_ls8c_ard_3-2-1_092081_2023-07-02_final
2023-07-05 11:40:30	ga_ls8c_ard_3-2-1_113080_2023-07-05_final
2023-07-11 11:03:51	ga_ls8c_ard_3-2-1_107081_2023-07-11_final
2023-07-13 10:48:42	ga_ls8c_ard_3-2-1_105074_2023-07-13_final
2023-07-19 10:10:49	ga_ls8c_ard_3-2-1_099072_2023-07-19_final
2023-07-23 11:25:25	ga_ls8c_ard_3-2-1_111073_2023-07-23_final
2023-08-03 09:33:18	ga_ls8c_ard_3-2-1_092086_2023-08-03_final
2023-08-05 10:52:39	ga_ls8c_ard_3-2-1_106068_2023-08-05_final
2023-08-12 09:22:45	ga_ls8c_ard_3-2-1_091075_2023-08-11_final
2023-08-12 09:24:45	ga_ls8c_ard_3-2-1_091080_2023-08-11_final
2023-08-13 10:04:26	ga_ls8c_ard_3-2-1_098071_2023-08-13_final
2023-08-18 10:27:50	ga_ls8c_ard_3-2-1_101083_2023-08-18_final
2023-08-26 11:14:07	ga_ls8c_ard_3-2-1_109075_2023-08-26_final
2023-08-29 10:04:33	ga_ls8c_ard_3-2-1_098071_2023-08-29_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