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
2022-02-24 11:38:28	ga_ls8c_ard_3-2-1_113074_2022-02-24_final
2022-02-27 10:28:30	ga_ls8c_ard_3-2-1_102069_2022-02-27_final
2022-03-08 10:25:28	ga_ls8c_ard_3-2-1_101077_2022-03-08_final
2022-03-10 11:52:47	ga_ls8c_ard_3-2-1_115079_2022-03-10_final
2022-04-01 11:14:39	ga_ls8c_ard_3-2-1_109077_2022-04-01_final
2022-04-05 09:12:40	ga_ls8c_ard_3-2-1_089081_2022-04-04_final
2022-04-10 09:32:52	ga_ls8c_ard_3-2-1_092085_2022-04-10_final
2022-04-18 10:17:56	ga_ls8c_ard_3-2-1_100074_2022-04-18_final
2022-05-16 10:42:21	ga_ls8c_ard_3-2-1_104073_2022-05-16_final
2022-05-29 11:53:09	ga_ls8c_ard_3-2-1_115080_2022-05-29_final
2022-06-03 10:30:29	ga_ls8c_ard_3-2-1_102074_2022-06-03_final
2022-06-07 10:07:01	ga_ls8c_ard_3-2-1_098077_2022-06-07_final
2022-06-12 10:23:14	ga_ls8c_ard_3-2-1_101071_2022-06-12_final
2022-06-19 10:30:16	ga_ls8c_ard_3-2-1_102073_2022-06-19_final
2022-07-02 10:04:12	ga_ls8c_ard_3-2-1_097085_2022-07-02_final
2022-07-16 10:09:21	ga_ls8c_ard_3-2-1_099067_2022-07-16_final
2022-07-18 10:04:12	ga_ls8c_ard_3-2-1_097085_2022-07-18_final
2022-07-24 09:27:12	ga_ls8c_ard_3-2-1_091085_2022-07-23_final
2022-07-26 09:16:28	ga_ls8c_ard_3-2-1_089089_2022-07-25_final
2022-08-03 09:58:24	ga_ls8c_ard_3-2-1_097070_2022-08-03_final
2022-08-07 09:34:31	ga_ls8c_ard_3-2-1_093072_2022-08-07_final
2022-08-14 09:44:44	ga_ls8c_ard_3-2-1_094082_2022-08-14_final
2022-08-23 09:40:34	ga_ls8c_ard_3-2-1_093087_2022-08-23_final
2022-08-25 09:29:00	ga_ls8c_ard_3-2-1_091089_2022-08-24_final
2022-08-26 10:04:17	ga_ls8c_ard_3-2-1_098069_2022-08-26_final
2022-08-30 11:20:26	ga_ls8c_ard_3-2-1_110074_2022-08-30_final
2022-09-03 09:22:49	ga_ls8c_ard_3-2-1_090089_2022-09-02_final
2022-09-12 10:47:13	ga_ls8c_ard_3-2-1_105068_2022-09-12_final
2022-09-27 10:09:59	ga_ls8c_ard_3-2-1_098083_2022-09-27_final
2022-09-29 09:52:26	ga_ls8c_ard_3-2-1_096070_2022-09-29_final
2022-10-11 10:20:38	ga_ls8c_ard_3-2-1_100079_2022-10-11_final
2022-10-14 09:16:36	ga_ls8c_ard_3-2-1_089089_2022-10-13_final
2022-10-14 10:52:41	ga_ls8c_ard_3-2-1_105082_2022-10-14_final
2022-10-22 09:58:33	ga_ls8c_ard_3-2-1_097070_2022-10-22_final
2022-11-04 09:28:30	ga_ls8c_ard_3-2-1_092072_2022-11-03_final
2022-11-06 10:54:13	ga_ls8c_ard_3-2-1_106070_2022-11-06_final
2022-11-14 10:03:55	ga_ls8c_ard_3-2-1_098068_2022-11-14_final
2022-11-16 11:36:47	ga_ls8c_ard_3-2-1_112084_2022-11-16_final
2022-11-25 09:51:45	ga_ls8c_ard_3-2-1_095084_2022-11-25_final
2022-11-26 10:29:01	ga_ls8c_ard_3-2-1_102069_2022-11-26_final
2022-11-27 11:15:05	ga_ls8c_ard_3-2-1_109076_2022-11-27_final
2022-12-01 10:47:34	ga_ls8c_ard_3-2-1_105069_2022-12-01_final
2022-12-12 10:28:35	ga_ls8c_ard_3-2-1_102068_2022-12-12_final
2022-12-19 10:35:29	ga_ls8c_ard_3-2-1_103070_2022-12-19_final
2022-12-21 10:25:53	ga_ls8c_ard_3-2-1_101077_2022-12-21_final
2022-12-25 11:38:50	ga_ls8c_ard_3-2-1_113074_2022-12-25_final
2022-12-30 10:22:06	ga_ls8c_ard_3-2-1_100083_2022-12-30_final
2023-01-07 09:33:27	ga_ls8c_ard_3-2-1_092085_2023-01-07_final
2023-01-10 09:58:45	ga_ls8c_ard_3-2-1_097071_2023-01-10_final
2023-01-23 09:29:48	ga_ls8c_ard_3-2-1_092076_2023-01-22_final
2023-01-29 10:29:15	ga_ls8c_ard_3-2-1_102070_2023-01-29_final
2023-02-07 10:27:50	ga_ls8c_ard_3-2-1_101082_2023-02-07_final
2023-02-08 09:34:12	ga_ls8c_ard_3-2-1_092087_2023-02-08_final
2023-02-16 10:19:09	ga_ls8c_ard_3-2-1_100076_2023-02-16_final
2023-02-20 11:31:38	ga_ls8c_ard_3-2-1_112072_2023-02-20_final
2023-02-28 10:40:53	ga_ls8c_ard_3-2-1_104069_2023-02-28_final
2023-03-03 11:14:34	ga_ls8c_ard_3-2-1_109076_2023-03-03_final
2023-03-10 11:19:53	ga_ls8c_ard_3-2-1_110074_2023-03-10_final
2023-03-12 09:29:26	ga_ls8c_ard_3-2-1_092076_2023-03-11_final
2023-03-17 11:26:02	ga_ls8c_ard_3-2-1_111074_2023-03-17_final
2023-03-18 10:30:00	ga_ls8c_ard_3-2-1_102073_2023-03-18_final
2023-03-21 10:59:39	ga_ls8c_ard_3-2-1_107070_2023-03-21_final
2023-03-26 11:20:32	ga_ls8c_ard_3-2-1_110076_2023-03-26_final
2023-03-31 09:59:21	ga_ls8c_ard_3-2-1_097074_2023-03-31_final
2023-04-11 09:40:11	ga_ls8c_ard_3-2-1_094073_2023-04-11_final
2023-04-14 10:15:52	ga_ls8c_ard_3-2-1_099085_2023-04-14_final
2023-04-16 09:58:19	ga_ls8c_ard_3-2-1_097072_2023-04-16_final
2023-04-18 09:51:31	ga_ls8c_ard_3-2-1_095086_2023-04-18_final
2023-04-18 11:29:36	ga_ls8c_ard_3-2-1_111084_2023-04-18_final
2023-04-24 10:48:31	ga_ls8c_ard_3-2-1_105074_2023-04-24_final
2023-04-29 09:34:08	ga_ls8c_ard_3-2-1_092089_2023-04-29_final
2023-05-15 09:32:44	ga_ls8c_ard_3-2-1_092086_2023-05-15_final
2023-05-25 10:03:51	ga_ls8c_ard_3-2-1_098071_2023-05-25_final
2023-06-11 09:14:20	ga_ls8c_ard_3-2-1_089086_2023-06-10_final
2023-06-11 10:46:02	ga_ls8c_ard_3-2-1_105068_2023-06-11_final
2023-06-14 11:22:57	ga_ls8c_ard_3-2-1_110083_2023-06-14_final
2023-07-02 09:28:41	ga_ls8c_ard_3-2-1_092075_2023-07-01_final
2023-07-22 09:06:03	ga_ls8c_ard_3-2-1_088080_2023-07-21_final
2023-07-22 09:06:27	ga_ls8c_ard_3-2-1_088081_2023-07-21_final
2023-07-23 11:25:01	ga_ls8c_ard_3-2-1_111072_2023-07-23_final
2023-07-28 10:04:21	ga_ls8c_ard_3-2-1_098071_2023-07-28_final
2023-08-05 10:55:50	ga_ls8c_ard_3-2-1_106076_2023-08-05_final
2023-08-17 11:19:03	ga_ls8c_ard_3-2-1_110072_2023-08-17_final
2023-08-17 11:23:26	ga_ls8c_ard_3-2-1_110083_2023-08-17_final
2023-08-20 11:51:11	ga_ls8c_ard_3-2-1_115075_2023-08-20_final
2023-08-29 10:09:44	ga_ls8c_ard_3-2-1_098084_2023-08-29_final
2023-09-02 09:45:24	ga_ls8c_ard_3-2-1_094085_2023-09-02_final
2023-09-02 09:46:12	ga_ls8c_ard_3-2-1_094087_2023-09-02_final
2023-09-13 09:27:43	ga_ls8c_ard_3-2-1_091087_2023-09-12_final
2023-09-18 09:45:53	ga_ls8c_ard_3-2-1_094086_2023-09-18_final
2023-09-27 09:40:08	ga_ls8c_ard_3-2-1_093087_2023-09-27_final
2023-10-07 10:10:51	ga_ls8c_ard_3-2-1_099071_2023-10-07_final
2023-10-22 11:10:30	ga_ls8c_ard_3-2-1_108081_2023-10-22_final
2023-10-27 11:30:17	ga_ls8c_ard_3-2-1_111084_2023-10-27_final
2023-10-29 09:35:03	ga_ls8c_ard_3-2-1_093074_2023-10-29_final
2023-10-31 09:27:05	ga_ls8c_ard_3-2-1_091085_2023-10-30_final
2023-11-02 10:46:49	ga_ls8c_ard_3-2-1_105068_2023-11-02_final
2023-11-05 11:23:18	ga_ls8c_ard_3-2-1_110082_2023-11-05_final
2023-11-16 09:26:40	ga_ls8c_ard_3-2-1_091084_2023-11-15_final
2023-11-17 10:10:21	ga_ls8c_ard_3-2-1_098085_2023-11-17_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