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
2022-06-06 11:05:25	ga_ls8c_ard_3-2-1_107084_2022-06-06_final
2022-06-23 11:47:15	ga_ls8c_ard_3-2-1_114080_2022-06-23_final
2022-07-05 10:30:18	ga_ls8c_ard_3-2-1_102073_2022-07-05_final
2022-07-06 09:37:53	ga_ls8c_ard_3-2-1_093081_2022-07-06_final
2022-07-10 10:52:26	ga_ls8c_ard_3-2-1_105082_2022-07-10_final
2022-07-12 10:34:29	ga_ls8c_ard_3-2-1_103068_2022-07-12_final
2022-07-13 09:46:02	ga_ls8c_ard_3-2-1_094086_2022-07-13_final
2022-07-18 11:38:42	ga_ls8c_ard_3-2-1_113074_2022-07-18_final
2022-07-18 11:41:53	ga_ls8c_ard_3-2-1_113082_2022-07-18_final
2022-07-22 09:37:09	ga_ls8c_ard_3-2-1_093079_2022-07-22_final
2022-07-24 11:00:06	ga_ls8c_ard_3-2-1_107070_2022-07-24_final
2022-07-31 09:29:28	ga_ls8c_ard_3-2-1_092075_2022-07-30_final
2022-08-13 10:39:33	ga_ls8c_ard_3-2-1_103080_2022-08-13_final
2022-08-14 11:18:50	ga_ls8c_ard_3-2-1_110070_2022-08-14_final
2022-08-25 11:01:54	ga_ls8c_ard_3-2-1_107074_2022-08-25_final
2022-09-02 10:11:39	ga_ls8c_ard_3-2-1_099072_2022-09-02_final
2022-09-15 11:23:44	ga_ls8c_ard_3-2-1_110082_2022-09-15_final
2022-09-18 11:53:03	ga_ls8c_ard_3-2-1_115078_2022-09-18_final
2022-09-19 10:53:50	ga_ls8c_ard_3-2-1_106069_2022-09-19_final
2022-10-04 10:15:20	ga_ls8c_ard_3-2-1_099081_2022-10-04_final
2022-10-05 10:54:36	ga_ls8c_ard_3-2-1_106071_2022-10-05_final
2022-10-29 10:03:59	ga_ls8c_ard_3-2-1_098068_2022-10-29_final
2022-10-30 09:15:09	ga_ls8c_ard_3-2-1_089085_2022-10-29_final
2022-11-09 09:47:25	ga_ls8c_ard_3-2-1_095073_2022-11-09_final
2022-11-09 09:53:00	ga_ls8c_ard_3-2-1_095087_2022-11-09_final
2022-11-15 09:14:40	ga_ls8c_ard_3-2-1_089084_2022-11-14_final
2022-11-18 09:40:20	ga_ls8c_ard_3-2-1_094071_2022-11-18_final
2022-11-18 09:45:55	ga_ls8c_ard_3-2-1_094085_2022-11-18_final
2022-11-22 09:18:26	ga_ls8c_ard_3-2-1_090078_2022-11-21_final
2022-11-23 09:57:19	ga_ls8c_ard_3-2-1_097067_2022-11-23_final
2022-11-24 10:40:59	ga_ls8c_ard_3-2-1_104068_2022-11-24_final
2022-11-26 10:30:37	ga_ls8c_ard_3-2-1_102073_2022-11-26_final
2022-11-29 11:02:43	ga_ls8c_ard_3-2-1_107076_2022-11-29_final
2022-12-09 09:59:18	ga_ls8c_ard_3-2-1_097072_2022-12-09_final
2022-12-29 09:35:39	ga_ls8c_ard_3-2-1_093075_2022-12-29_final
2023-01-02 09:14:08	ga_ls8c_ard_3-2-1_089083_2023-01-01_final
2023-01-09 09:23:05	ga_ls8c_ard_3-2-1_090090_2023-01-08_final
2023-01-14 09:39:34	ga_ls8c_ard_3-2-1_093085_2023-01-14_final
2023-01-21 09:45:20	ga_ls8c_ard_3-2-1_094084_2023-01-21_final
2023-02-03 09:14:53	ga_ls8c_ard_3-2-1_089085_2023-02-02_final
2023-02-04 11:35:50	ga_ls8c_ard_3-2-1_112082_2023-02-04_final
2023-02-06 11:19:29	ga_ls8c_ard_3-2-1_110072_2023-02-06_final
2023-02-20 09:58:21	ga_ls8c_ard_3-2-1_096086_2023-02-20_final
2023-02-27 10:01:37	ga_ls8c_ard_3-2-1_097079_2023-02-27_final
2023-03-13 11:52:47	ga_ls8c_ard_3-2-1_115079_2023-03-13_final
2023-03-14 09:21:04	ga_ls8c_ard_3-2-1_090086_2023-03-13_final
2023-03-19 09:34:45	ga_ls8c_ard_3-2-1_093074_2023-03-19_final
2023-03-29 10:15:19	ga_ls8c_ard_3-2-1_099083_2023-03-29_final
2023-03-31 09:58:09	ga_ls8c_ard_3-2-1_097071_2023-03-31_final
2023-04-05 11:57:29	ga_ls8c_ard_3-2-1_116076_2023-04-05_final
2023-04-24 09:13:14	ga_ls8c_ard_3-2-1_089083_2023-04-23_final
2023-04-24 10:48:55	ga_ls8c_ard_3-2-1_105075_2023-04-24_final
2023-04-28 10:25:23	ga_ls8c_ard_3-2-1_101078_2023-04-28_final
2023-05-17 09:16:45	ga_ls8c_ard_3-2-1_090077_2023-05-16_final
2023-05-19 09:05:36	ga_ls8c_ard_3-2-1_088080_2023-05-18_final
2023-05-19 10:41:41	ga_ls8c_ard_3-2-1_104073_2023-05-19_final
2023-05-20 09:49:40	ga_ls8c_ard_3-2-1_095082_2023-05-20_final
2023-06-09 11:03:34	ga_ls8c_ard_3-2-1_107081_2023-06-09_final
2023-06-10 11:46:26	ga_ls8c_ard_3-2-1_114080_2023-06-10_final
2023-06-14 09:40:04	ga_ls8c_ard_3-2-1_094073_2023-06-14_final
2023-06-17 10:14:59	ga_ls8c_ard_3-2-1_099083_2023-06-17_final
2023-06-17 11:51:28	ga_ls8c_ard_3-2-1_115077_2023-06-17_final
2023-06-24 10:20:47	ga_ls8c_ard_3-2-1_100082_2023-06-24_final
2023-07-28 10:04:45	ga_ls8c_ard_3-2-1_098072_2023-07-28_final
2023-08-22 10:03:56	ga_ls8c_ard_3-2-1_097085_2023-08-22_final
2023-08-27 10:18:54	ga_ls8c_ard_3-2-1_100076_2023-08-27_final
2023-08-28 09:28:52	ga_ls8c_ard_3-2-1_091090_2023-08-27_final
2023-09-05 10:11:06	ga_ls8c_ard_3-2-1_099072_2023-09-05_final
2023-09-09 09:47:36	ga_ls8c_ard_3-2-1_095075_2023-09-09_final
2023-09-09 11:25:17	ga_ls8c_ard_3-2-1_111072_2023-09-09_final
2023-09-14 10:04:36	ga_ls8c_ard_3-2-1_098071_2023-09-14_final
2023-10-04 11:20:25	ga_ls8c_ard_3-2-1_110075_2023-10-04_final
2023-10-08 10:54:07	ga_ls8c_ard_3-2-1_106071_2023-10-08_final
2023-10-31 11:01:35	ga_ls8c_ard_3-2-1_107074_2023-10-31_final
2023-10-31 11:02:23	ga_ls8c_ard_3-2-1_107076_2023-10-31_final
2023-11-01 10:10:21	ga_ls8c_ard_3-2-1_098085_2023-11-01_final
2023-11-02 09:15:07	ga_ls8c_ard_3-2-1_089086_2023-11-01_final
2023-11-06 10:25:40	ga_ls8c_ard_3-2-1_101077_2023-11-06_final
2023-11-09 09:21:13	ga_ls8c_ard_3-2-1_090086_2023-11-08_final
2023-11-12 11:25:26	ga_ls8c_ard_3-2-1_111072_2023-11-12_final
2023-11-21 11:19:21	ga_ls8c_ard_3-2-1_110072_2023-11-21_final
2023-11-21 11:21:21	ga_ls8c_ard_3-2-1_110077_2023-11-21_final
2023-11-29 10:28:42	ga_ls8c_ard_3-2-1_102069_2023-11-29_final
2023-12-01 11:58:47	ga_ls8c_ard_3-2-1_116078_2023-12-01_final
2023-12-10 11:51:44	ga_ls8c_ard_3-2-1_115076_2023-12-10_final
2024-01-01 09:40:10	ga_ls8c_ard_3-2-1_093087_2024-01-01_final
2024-01-03 11:01:04	ga_ls8c_ard_3-2-1_107073_2024-01-03_final
2024-01-08 09:43:31	ga_ls8c_ard_3-2-1_094080_2024-01-08_final
2024-01-11 10:15:38	ga_ls8c_ard_3-2-1_099083_2024-01-11_final
2024-01-14 10:41:45	ga_ls8c_ard_3-2-1_104071_2024-01-14_final
2024-02-06 10:52:18	ga_ls8c_ard_3-2-1_105082_2024-02-06_final
2024-02-07 11:35:58	ga_ls8c_ard_3-2-1_112083_2024-02-07_final
2024-02-15 10:42:53	ga_ls8c_ard_3-2-1_104074_2024-02-15_final
2024-02-19 10:18:34	ga_ls8c_ard_3-2-1_100075_2024-02-19_final
2024-03-07 09:24:44	ga_ls8c_ard_3-2-1_091080_2024-03-06_final
2024-03-15 10:14:09	ga_ls8c_ard_3-2-1_099080_2024-03-15_final
2024-03-25 10:52:15	ga_ls8c_ard_3-2-1_105083_2024-03-25_final
2024-03-28 11:19:54	ga_ls8c_ard_3-2-1_110075_2024-03-28_final
2024-03-29 10:27:28	ga_ls8c_ard_3-2-1_101083_2024-03-29_final
2024-03-31 11:52:48	ga_ls8c_ard_3-2-1_115080_2024-03-31_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