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
2022-05-04 10:19:55	ga_ls8c_ard_3-2-1_100079_2022-05-04_final
2022-05-14 10:55:06	ga_ls8c_ard_3-2-1_106074_2022-05-14_final
2022-05-15 10:01:05	ga_ls8c_ard_3-2-1_097078_2022-05-15_final
2022-05-17 09:51:08	ga_ls8c_ard_3-2-1_095084_2022-05-17_final
2022-05-20 10:20:02	ga_ls8c_ard_3-2-1_100079_2022-05-20_final
2022-05-20 10:21:38	ga_ls8c_ard_3-2-1_100083_2022-05-20_final
2022-05-23 10:50:08	ga_ls8c_ard_3-2-1_105077_2022-05-23_final
2022-05-28 09:29:23	ga_ls8c_ard_3-2-1_092076_2022-05-27_final
2022-06-01 10:40:25	ga_ls8c_ard_3-2-1_104068_2022-06-01_final
2022-06-15 09:20:28	ga_ls8c_ard_3-2-1_090084_2022-06-14_final
2022-06-20 11:12:44	ga_ls8c_ard_3-2-1_109071_2022-06-20_final
2022-06-28 10:25:43	ga_ls8c_ard_3-2-1_101077_2022-06-28_final
2022-06-29 09:32:54	ga_ls8c_ard_3-2-1_092084_2022-06-29_final
2022-06-29 11:05:47	ga_ls8c_ard_3-2-1_108069_2022-06-29_final
2022-06-29 11:06:35	ga_ls8c_ard_3-2-1_108071_2022-06-29_final
2022-07-02 10:03:24	ga_ls8c_ard_3-2-1_097083_2022-07-02_final
2022-07-06 11:12:46	ga_ls8c_ard_3-2-1_109071_2022-07-06_final
2022-07-15 11:06:34	ga_ls8c_ard_3-2-1_108071_2022-07-15_final
2022-07-18 09:59:49	ga_ls8c_ard_3-2-1_097074_2022-07-18_final
2022-07-22 11:17:38	ga_ls8c_ard_3-2-1_109083_2022-07-22_final
2022-07-25 10:08:05	ga_ls8c_ard_3-2-1_098079_2022-07-25_final
2022-07-26 10:47:22	ga_ls8c_ard_3-2-1_105069_2022-07-26_final
2022-07-29 11:21:30	ga_ls8c_ard_3-2-1_110077_2022-07-29_final
2022-07-31 09:31:28	ga_ls8c_ard_3-2-1_092080_2022-07-31_final
2022-08-03 11:40:05	ga_ls8c_ard_3-2-1_113077_2022-08-03_final
2022-08-04 10:46:28	ga_ls8c_ard_3-2-1_104082_2022-08-04_final
2022-08-09 09:23:46	ga_ls8c_ard_3-2-1_091076_2022-08-08_final
2022-08-14 11:21:13	ga_ls8c_ard_3-2-1_110076_2022-08-14_final
2022-08-15 10:26:24	ga_ls8c_ard_3-2-1_101078_2022-08-15_final
2022-08-16 09:29:35	ga_ls8c_ard_3-2-1_092075_2022-08-15_final
2022-08-16 11:06:52	ga_ls8c_ard_3-2-1_108071_2022-08-16_final
2022-08-22 10:29:24	ga_ls8c_ard_3-2-1_102070_2022-08-22_final
2022-08-27 09:13:27	ga_ls8c_ard_3-2-1_089081_2022-08-26_final
2022-08-27 10:52:20	ga_ls8c_ard_3-2-1_105081_2022-08-27_final
2022-08-31 10:25:37	ga_ls8c_ard_3-2-1_101076_2022-08-31_final
2022-09-03 10:55:43	ga_ls8c_ard_3-2-1_106074_2022-09-03_final
2022-09-03 10:58:06	ga_ls8c_ard_3-2-1_106080_2022-09-03_final
2022-09-15 11:19:20	ga_ls8c_ard_3-2-1_110071_2022-09-15_final
2022-09-17 09:31:18	ga_ls8c_ard_3-2-1_092079_2022-09-17_final
2022-09-17 11:11:46	ga_ls8c_ard_3-2-1_108083_2022-09-17_final
2022-09-22 09:47:51	ga_ls8c_ard_3-2-1_095074_2022-09-22_final
2022-09-24 09:35:29	ga_ls8c_ard_3-2-1_093074_2022-09-24_final
2022-09-29 11:33:18	ga_ls8c_ard_3-2-1_112075_2022-09-29_final
2022-10-03 11:06:58	ga_ls8c_ard_3-2-1_108071_2022-10-03_final
2022-10-04 11:51:25	ga_ls8c_ard_3-2-1_115074_2022-10-04_final
2022-10-12 09:25:47	ga_ls8c_ard_3-2-1_091081_2022-10-11_final
2022-10-13 11:45:07	ga_ls8c_ard_3-2-1_114074_2022-10-13_final
2022-10-14 09:14:12	ga_ls8c_ard_3-2-1_089083_2022-10-13_final
2022-10-15 09:53:53	ga_ls8c_ard_3-2-1_096074_2022-10-15_final
2022-10-22 09:59:21	ga_ls8c_ard_3-2-1_097072_2022-10-22_final
2022-10-23 10:43:01	ga_ls8c_ard_3-2-1_104073_2022-10-23_final
2022-10-25 10:30:17	ga_ls8c_ard_3-2-1_102072_2022-10-25_final
2022-10-31 09:52:26	ga_ls8c_ard_3-2-1_096070_2022-10-31_final
2022-10-31 09:52:50	ga_ls8c_ard_3-2-1_096071_2022-10-31_final
2022-11-03 10:26:55	ga_ls8c_ard_3-2-1_101079_2022-11-03_final
2022-11-04 11:06:59	ga_ls8c_ard_3-2-1_108071_2022-11-04_final
2022-11-06 09:19:20	ga_ls8c_ard_3-2-1_090080_2022-11-05_final
2022-11-14 11:45:11	ga_ls8c_ard_3-2-1_114074_2022-11-14_final
2022-11-27 09:37:24	ga_ls8c_ard_3-2-1_093079_2022-11-27_final
2022-11-28 11:58:21	ga_ls8c_ard_3-2-1_116076_2022-11-28_final
2022-11-29 09:25:50	ga_ls8c_ard_3-2-1_091081_2022-11-28_final
2022-12-01 10:50:46	ga_ls8c_ard_3-2-1_105077_2022-12-01_final
2022-12-04 09:45:34	ga_ls8c_ard_3-2-1_094084_2022-12-04_final
2022-12-06 11:07:42	ga_ls8c_ard_3-2-1_108073_2022-12-06_final
2022-12-13 09:36:09	ga_ls8c_ard_3-2-1_093076_2022-12-13_final
2022-12-15 09:25:22	ga_ls8c_ard_3-2-1_091080_2022-12-14_final
2022-12-18 09:52:38	ga_ls8c_ard_3-2-1_096071_2022-12-18_final
2022-12-21 10:27:29	ga_ls8c_ard_3-2-1_101081_2022-12-21_final
2022-12-26 10:44:49	ga_ls8c_ard_3-2-1_104078_2022-12-26_final
2022-12-30 11:59:00	ga_ls8c_ard_3-2-1_116078_2022-12-30_final
2023-01-01 11:45:03	ga_ls8c_ard_3-2-1_114074_2023-01-01_final
2023-01-05 09:45:25	ga_ls8c_ard_3-2-1_094084_2023-01-05_final
2023-01-08 11:52:24	ga_ls8c_ard_3-2-1_115077_2023-01-08_final
2023-01-12 11:26:51	ga_ls8c_ard_3-2-1_111075_2023-01-12_final
2023-01-13 10:30:01	ga_ls8c_ard_3-2-1_102072_2023-01-13_final
2023-01-14 11:13:16	ga_ls8c_ard_3-2-1_109072_2023-01-14_final
2023-01-17 10:08:25	ga_ls8c_ard_3-2-1_098080_2023-01-17_final
2023-01-17 11:45:18	ga_ls8c_ard_3-2-1_114075_2023-01-17_final
2023-01-23 09:35:00	ga_ls8c_ard_3-2-1_092089_2023-01-23_final
2023-01-23 11:11:29	ga_ls8c_ard_3-2-1_108083_2023-01-23_final
2023-01-25 09:18:16	ga_ls8c_ard_3-2-1_090078_2023-01-24_final
2023-01-29 10:31:38	ga_ls8c_ard_3-2-1_102076_2023-01-29_final
2023-02-09 10:12:16	ga_ls8c_ard_3-2-1_099074_2023-02-09_final
2023-02-10 09:19:50	ga_ls8c_ard_3-2-1_090082_2023-02-09_final
2023-02-17 11:05:35	ga_ls8c_ard_3-2-1_107084_2023-02-17_final
2023-02-22 11:20:50	ga_ls8c_ard_3-2-1_110076_2023-02-22_final
2023-03-04 10:22:08	ga_ls8c_ard_3-2-1_100084_2023-03-04_final
2023-03-04 11:57:49	ga_ls8c_ard_3-2-1_116076_2023-03-04_final
2023-03-04 11:58:37	ga_ls8c_ard_3-2-1_116078_2023-03-04_final
2023-03-06 10:08:09	ga_ls8c_ard_3-2-1_098080_2023-03-06_final
2023-03-07 09:13:19	ga_ls8c_ard_3-2-1_089082_2023-03-06_final
2023-03-10 09:44:11	ga_ls8c_ard_3-2-1_094082_2023-03-10_final
2023-03-20 11:57:41	ga_ls8c_ard_3-2-1_116076_2023-03-20_final
2023-03-31 11:39:50	ga_ls8c_ard_3-2-1_113078_2023-03-31_final
2023-04-02 11:26:39	ga_ls8c_ard_3-2-1_111076_2023-04-02_final
2023-04-21 10:17:13	ga_ls8c_ard_3-2-1_100073_2023-04-21_final
2023-05-02 09:57:50	ga_ls8c_ard_3-2-1_097071_2023-05-02_final
2023-05-08 09:24:15	ga_ls8c_ard_3-2-1_091080_2023-05-07_final
2023-05-10 09:14:15	ga_ls8c_ard_3-2-1_089086_2023-05-09_final
2023-05-11 11:35:10	ga_ls8c_ard_3-2-1_112083_2023-05-11_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