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
2022-01-14 10:03:34	ga_ls8c_ard_3-2-1_098068_2022-01-14_final
2022-08-25 11:02:42	ga_ls8c_ard_3-2-1_107076_2022-08-25_final
2022-09-11 10:05:33	ga_ls8c_ard_3-2-1_098072_2022-09-11_final
2022-09-11 10:06:21	ga_ls8c_ard_3-2-1_098074_2022-09-11_final
2022-09-14 10:34:52	ga_ls8c_ard_3-2-1_103068_2022-09-14_final
2022-09-22 09:47:27	ga_ls8c_ard_3-2-1_095073_2022-09-22_final
2022-09-22 11:25:32	ga_ls8c_ard_3-2-1_111071_2022-09-22_final
2022-10-05 09:22:54	ga_ls8c_ard_3-2-1_090089_2022-10-04_final
2022-10-08 09:52:34	ga_ls8c_ard_3-2-1_095086_2022-10-08_final
2022-10-08 09:52:58	ga_ls8c_ard_3-2-1_095087_2022-10-08_final
2022-10-12 11:05:28	ga_ls8c_ard_3-2-1_107083_2022-10-12_final
2022-10-17 09:46:45	ga_ls8c_ard_3-2-1_094087_2022-10-17_final
2022-10-17 11:24:02	ga_ls8c_ard_3-2-1_110083_2022-10-17_final
2022-10-19 11:06:54	ga_ls8c_ard_3-2-1_108071_2022-10-19_final
2022-10-19 11:08:30	ga_ls8c_ard_3-2-1_108075_2022-10-19_final
2022-10-21 09:22:52	ga_ls8c_ard_3-2-1_090089_2022-10-20_final
2022-10-21 10:56:34	ga_ls8c_ard_3-2-1_106076_2022-10-21_final
2022-10-22 09:59:21	ga_ls8c_ard_3-2-1_097072_2022-10-22_final
2022-10-23 10:41:50	ga_ls8c_ard_3-2-1_104070_2022-10-23_final
2022-10-24 11:29:29	ga_ls8c_ard_3-2-1_111081_2022-10-24_final
2022-10-28 11:02:48	ga_ls8c_ard_3-2-1_107076_2022-10-28_final
2022-10-31 09:53:14	ga_ls8c_ard_3-2-1_096072_2022-10-31_final
2022-10-31 11:36:06	ga_ls8c_ard_3-2-1_112082_2022-10-31_final
2022-11-01 10:34:54	ga_ls8c_ard_3-2-1_103068_2022-11-01_final
2022-11-05 11:53:27	ga_ls8c_ard_3-2-1_115079_2022-11-05_final
2022-11-07 09:59:24	ga_ls8c_ard_3-2-1_097072_2022-11-07_final
2022-11-13 11:02:44	ga_ls8c_ard_3-2-1_107076_2022-11-13_final
2022-11-14 10:06:18	ga_ls8c_ard_3-2-1_098074_2022-11-14_final
2022-11-14 10:06:42	ga_ls8c_ard_3-2-1_098075_2022-11-14_final
2022-11-15 09:14:40	ga_ls8c_ard_3-2-1_089084_2022-11-14_final
2022-11-18 09:46:43	ga_ls8c_ard_3-2-1_094087_2022-11-18_final
2022-11-19 10:23:12	ga_ls8c_ard_3-2-1_101070_2022-11-19_final
2022-11-22 09:22:49	ga_ls8c_ard_3-2-1_090089_2022-11-21_final
2022-11-24 10:42:34	ga_ls8c_ard_3-2-1_104072_2022-11-24_final
2022-11-25 09:47:21	ga_ls8c_ard_3-2-1_095073_2022-11-25_final
2022-11-27 09:37:48	ga_ls8c_ard_3-2-1_093080_2022-11-27_final
2022-12-02 11:32:02	ga_ls8c_ard_3-2-1_112072_2022-12-02_final
2022-12-02 11:36:01	ga_ls8c_ard_3-2-1_112082_2022-12-02_final
2022-12-05 10:28:02	ga_ls8c_ard_3-2-1_101082_2022-12-05_final
2022-12-09 09:58:54	ga_ls8c_ard_3-2-1_097071_2022-12-09_final
2022-12-09 10:00:06	ga_ls8c_ard_3-2-1_097074_2022-12-09_final
2022-12-12 10:28:59	ga_ls8c_ard_3-2-1_102069_2022-12-12_final
2022-12-15 11:04:39	ga_ls8c_ard_3-2-1_107081_2022-12-15_final
2022-12-16 10:07:49	ga_ls8c_ard_3-2-1_098078_2022-12-16_final
2022-12-18 09:53:02	ga_ls8c_ard_3-2-1_096072_2022-12-18_final
2022-12-22 09:31:26	ga_ls8c_ard_3-2-1_092080_2022-12-22_final
2022-12-22 11:08:19	ga_ls8c_ard_3-2-1_108075_2022-12-22_final
2022-12-25 09:59:09	ga_ls8c_ard_3-2-1_097072_2022-12-25_final
2022-12-25 11:41:38	ga_ls8c_ard_3-2-1_113081_2022-12-25_final
2022-12-27 09:52:48	ga_ls8c_ard_3-2-1_095087_2022-12-27_final
2022-12-29 09:39:38	ga_ls8c_ard_3-2-1_093085_2022-12-29_final
2022-12-31 11:04:34	ga_ls8c_ard_3-2-1_107081_2022-12-31_final
2023-01-03 09:53:00	ga_ls8c_ard_3-2-1_096072_2023-01-03_final
2023-01-03 11:35:29	ga_ls8c_ard_3-2-1_112081_2023-01-03_final
2023-01-04 10:35:52	ga_ls8c_ard_3-2-1_103071_2023-01-04_final
2023-01-05 09:44:38	ga_ls8c_ard_3-2-1_094082_2023-01-05_final
2023-01-05 09:45:49	ga_ls8c_ard_3-2-1_094085_2023-01-05_final
2023-01-07 09:31:28	ga_ls8c_ard_3-2-1_092080_2023-01-07_final
2023-01-20 10:39:21	ga_ls8c_ard_3-2-1_103080_2023-01-20_final
2023-01-21 09:44:08	ga_ls8c_ard_3-2-1_094081_2023-01-21_final
2023-01-21 11:20:14	ga_ls8c_ard_3-2-1_110074_2023-01-21_final
2023-01-23 09:29:24	ga_ls8c_ard_3-2-1_092075_2023-01-22_final
2023-01-23 09:31:24	ga_ls8c_ard_3-2-1_092080_2023-01-23_final
2023-01-25 10:58:44	ga_ls8c_ard_3-2-1_106082_2023-01-25_final
2023-01-26 11:41:37	ga_ls8c_ard_3-2-1_113081_2023-01-26_final
2023-01-30 11:13:19	ga_ls8c_ard_3-2-1_109072_2023-01-30_final
2023-02-05 10:35:01	ga_ls8c_ard_3-2-1_103069_2023-02-05_final
2023-02-06 09:41:23	ga_ls8c_ard_3-2-1_094074_2023-02-06_final
2023-02-07 10:24:15	ga_ls8c_ard_3-2-1_101073_2023-02-07_final
2023-02-10 10:55:55	ga_ls8c_ard_3-2-1_106075_2023-02-10_final
2023-02-11 09:57:53	ga_ls8c_ard_3-2-1_097069_2023-02-11_final
2023-02-13 09:47:05	ga_ls8c_ard_3-2-1_095073_2023-02-13_final
2023-02-17 09:29:06	ga_ls8c_ard_3-2-1_091090_2023-02-16_final
2023-02-17 11:04:23	ga_ls8c_ard_3-2-1_107081_2023-02-17_final
2023-02-19 10:51:59	ga_ls8c_ard_3-2-1_105081_2023-02-19_final
2023-02-22 09:44:20	ga_ls8c_ard_3-2-1_094082_2023-02-22_final
2023-03-02 10:28:31	ga_ls8c_ard_3-2-1_102069_2023-03-02_final
2023-03-04 11:57:49	ga_ls8c_ard_3-2-1_116076_2023-03-04_final
2023-03-08 09:52:34	ga_ls8c_ard_3-2-1_096072_2023-03-08_final
2023-03-09 10:34:37	ga_ls8c_ard_3-2-1_103069_2023-03-09_final
2023-03-10 09:45:23	ga_ls8c_ard_3-2-1_094085_2023-03-10_final
2023-03-12 09:29:02	ga_ls8c_ard_3-2-1_092075_2023-03-11_final
2023-03-13 10:13:06	ga_ls8c_ard_3-2-1_099077_2023-03-13_final
2023-03-17 09:52:20	ga_ls8c_ard_3-2-1_095087_2023-03-17_final
2023-03-28 09:28:53	ga_ls8c_ard_3-2-1_092075_2023-03-27_final
2023-04-07 10:09:47	ga_ls8c_ard_3-2-1_098085_2023-04-07_final
2023-04-08 10:48:38	ga_ls8c_ard_3-2-1_105074_2023-04-08_final
2023-04-08 10:49:02	ga_ls8c_ard_3-2-1_105075_2023-04-08_final
2023-04-16 11:40:47	ga_ls8c_ard_3-2-1_113081_2023-04-16_final
2023-04-20 09:34:45	ga_ls8c_ard_3-2-1_093075_2023-04-20_final
2023-04-27 09:40:08	ga_ls8c_ard_3-2-1_094073_2023-04-27_final
2023-04-27 11:17:49	ga_ls8c_ard_3-2-1_110070_2023-04-27_final
2023-04-29 09:27:21	ga_ls8c_ard_3-2-1_092072_2023-04-28_final
2023-05-01 09:20:34	ga_ls8c_ard_3-2-1_090086_2023-04-30_final
2023-05-08 11:04:20	ga_ls8c_ard_3-2-1_107083_2023-05-08_final
2023-05-10 09:15:27	ga_ls8c_ard_3-2-1_089089_2023-05-09_final
2023-05-11 09:51:54	ga_ls8c_ard_3-2-1_096072_2023-05-11_final
2023-05-12 10:38:44	ga_ls8c_ard_3-2-1_103081_2023-05-12_final
2023-05-13 09:39:55	ga_ls8c_ard_3-2-1_094073_2023-05-13_final
2023-05-13 09:43:30	ga_ls8c_ard_3-2-1_094082_2023-05-13_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