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
2022-06-22 09:27:05	ga_ls8c_ard_3-2-1_091085_2022-06-21_final
2022-06-23 11:46:51	ga_ls8c_ard_3-2-1_114079_2022-06-23_final
2022-07-01 10:55:26	ga_ls8c_ard_3-2-1_106074_2022-07-01_final
2022-07-08 11:04:00	ga_ls8c_ard_3-2-1_107080_2022-07-08_final
2022-07-09 10:08:22	ga_ls8c_ard_3-2-1_098080_2022-07-09_final
2022-07-12 10:38:28	ga_ls8c_ard_3-2-1_103078_2022-07-12_final
2022-07-13 09:43:38	ga_ls8c_ard_3-2-1_094080_2022-07-13_final
2022-07-13 09:44:02	ga_ls8c_ard_3-2-1_094081_2022-07-13_final
2022-07-15 09:29:40	ga_ls8c_ard_3-2-1_092076_2022-07-14_final
2022-07-15 09:32:04	ga_ls8c_ard_3-2-1_092082_2022-07-15_final
2022-07-15 11:08:33	ga_ls8c_ard_3-2-1_108076_2022-07-15_final
2022-07-15 11:10:33	ga_ls8c_ard_3-2-1_108081_2022-07-15_final
2022-07-22 11:16:26	ga_ls8c_ard_3-2-1_109080_2022-07-22_final
2022-07-22 11:17:14	ga_ls8c_ard_3-2-1_109082_2022-07-22_final
2022-07-24 09:24:49	ga_ls8c_ard_3-2-1_091079_2022-07-23_final
2022-07-25 10:08:29	ga_ls8c_ard_3-2-1_098080_2022-07-25_final
2022-07-25 11:46:10	ga_ls8c_ard_3-2-1_114077_2022-07-25_final
2022-07-25 11:46:58	ga_ls8c_ard_3-2-1_114079_2022-07-25_final
2022-08-06 10:29:20	ga_ls8c_ard_3-2-1_102070_2022-08-06_final
2022-08-07 09:38:07	ga_ls8c_ard_3-2-1_093081_2022-08-07_final
2022-08-12 11:36:46	ga_ls8c_ard_3-2-1_112084_2022-08-12_final
2022-08-18 10:54:31	ga_ls8c_ard_3-2-1_106071_2022-08-18_final
2022-08-22 10:29:48	ga_ls8c_ard_3-2-1_102071_2022-08-22_final
2022-08-25 11:01:30	ga_ls8c_ard_3-2-1_107073_2022-08-25_final
2022-08-28 11:36:24	ga_ls8c_ard_3-2-1_112083_2022-08-28_final
2022-08-29 10:35:59	ga_ls8c_ard_3-2-1_103071_2022-08-29_final
2022-09-01 09:31:35	ga_ls8c_ard_3-2-1_092080_2022-09-01_final
2022-09-02 10:15:38	ga_ls8c_ard_3-2-1_099082_2022-09-02_final
2022-09-03 10:54:31	ga_ls8c_ard_3-2-1_106071_2022-09-03_final
2022-09-08 11:13:54	ga_ls8c_ard_3-2-1_109073_2022-09-08_final
2022-09-12 10:49:13	ga_ls8c_ard_3-2-1_105073_2022-09-12_final
2022-09-14 10:38:28	ga_ls8c_ard_3-2-1_103077_2022-09-14_final
2022-09-14 10:39:16	ga_ls8c_ard_3-2-1_103079_2022-09-14_final
2022-09-19 09:20:56	ga_ls8c_ard_3-2-1_090084_2022-09-18_final
2022-09-20 09:59:01	ga_ls8c_ard_3-2-1_097071_2022-09-20_final
2022-10-02 10:25:43	ga_ls8c_ard_3-2-1_101076_2022-10-02_final
2022-10-03 11:11:22	ga_ls8c_ard_3-2-1_108082_2022-10-03_final
2022-10-05 09:19:18	ga_ls8c_ard_3-2-1_090080_2022-10-04_final
2022-10-06 10:04:09	ga_ls8c_ard_3-2-1_097084_2022-10-06_final
2022-10-10 09:36:35	ga_ls8c_ard_3-2-1_093077_2022-10-10_final
2022-10-10 09:38:59	ga_ls8c_ard_3-2-1_093083_2022-10-10_final
2022-10-10 11:13:52	ga_ls8c_ard_3-2-1_109073_2022-10-10_final
2022-10-21 10:58:09	ga_ls8c_ard_3-2-1_106080_2022-10-21_final
2022-10-27 10:21:31	ga_ls8c_ard_3-2-1_100081_2022-10-27_final
2022-10-31 09:56:49	ga_ls8c_ard_3-2-1_096081_2022-10-31_final
2022-10-31 09:57:37	ga_ls8c_ard_3-2-1_096083_2022-10-31_final
2022-11-02 11:21:45	ga_ls8c_ard_3-2-1_110077_2022-11-02_final
2022-11-04 09:30:06	ga_ls8c_ard_3-2-1_092076_2022-11-04_final
2022-11-05 10:16:09	ga_ls8c_ard_3-2-1_099083_2022-11-05_final
2022-11-07 11:42:16	ga_ls8c_ard_3-2-1_113082_2022-11-07_final
2022-11-09 11:30:42	ga_ls8c_ard_3-2-1_111084_2022-11-09_final
2022-11-14 10:08:42	ga_ls8c_ard_3-2-1_098080_2022-11-14_final
2022-11-14 11:45:35	ga_ls8c_ard_3-2-1_114075_2022-11-14_final
2022-11-14 11:45:59	ga_ls8c_ard_3-2-1_114076_2022-11-14_final
2022-11-14 11:47:35	ga_ls8c_ard_3-2-1_114080_2022-11-14_final
2022-11-20 11:10:52	ga_ls8c_ard_3-2-1_108081_2022-11-20_final
2022-11-23 11:42:11	ga_ls8c_ard_3-2-1_113082_2022-11-23_final
2022-11-27 09:35:24	ga_ls8c_ard_3-2-1_093074_2022-11-27_final
2022-12-05 10:25:14	ga_ls8c_ard_3-2-1_101075_2022-12-05_final
2022-12-06 09:32:24	ga_ls8c_ard_3-2-1_092082_2022-12-06_final
2022-12-06 11:10:54	ga_ls8c_ard_3-2-1_108081_2022-12-06_final
2022-12-09 11:41:23	ga_ls8c_ard_3-2-1_113080_2022-12-09_final
2022-12-12 10:30:11	ga_ls8c_ard_3-2-1_102072_2022-12-12_final
2022-12-15 09:25:46	ga_ls8c_ard_3-2-1_091081_2022-12-14_final
2022-12-16 10:07:25	ga_ls8c_ard_3-2-1_098077_2022-12-16_final
2022-12-22 11:10:43	ga_ls8c_ard_3-2-1_108081_2022-12-22_final
2022-12-31 09:25:17	ga_ls8c_ard_3-2-1_091080_2022-12-30_final
2022-12-31 11:02:11	ga_ls8c_ard_3-2-1_107075_2022-12-31_final
2023-01-01 11:46:38	ga_ls8c_ard_3-2-1_114078_2023-01-01_final
2023-01-05 09:45:49	ga_ls8c_ard_3-2-1_094085_2023-01-05_final
2023-01-06 10:23:06	ga_ls8c_ard_3-2-1_101070_2023-01-06_final
2023-01-09 10:57:58	ga_ls8c_ard_3-2-1_106080_2023-01-09_final
2023-01-10 11:39:14	ga_ls8c_ard_3-2-1_113075_2023-01-10_final
2023-01-16 11:03:40	ga_ls8c_ard_3-2-1_107079_2023-01-16_final
2023-01-19 09:53:40	ga_ls8c_ard_3-2-1_096074_2023-01-19_final
2023-01-21 11:21:02	ga_ls8c_ard_3-2-1_110076_2023-01-21_final
2023-01-23 09:31:24	ga_ls8c_ard_3-2-1_092080_2023-01-23_final
2023-01-24 10:13:04	ga_ls8c_ard_3-2-1_099076_2023-01-24_final
2023-01-25 10:57:56	ga_ls8c_ard_3-2-1_106080_2023-01-25_final
2023-01-26 10:01:56	ga_ls8c_ard_3-2-1_097079_2023-01-26_final
2023-01-30 09:36:01	ga_ls8c_ard_3-2-1_093076_2023-01-30_final
2023-01-31 10:20:53	ga_ls8c_ard_3-2-1_100080_2023-01-31_final
2023-02-08 11:06:18	ga_ls8c_ard_3-2-1_108070_2023-02-08_final
2023-02-08 11:07:06	ga_ls8c_ard_3-2-1_108072_2023-02-08_final
2023-02-08 11:09:54	ga_ls8c_ard_3-2-1_108079_2023-02-08_final
2023-02-08 11:11:29	ga_ls8c_ard_3-2-1_108083_2023-02-08_final
2023-02-11 10:01:53	ga_ls8c_ard_3-2-1_097079_2023-02-11_final
2023-02-13 09:51:05	ga_ls8c_ard_3-2-1_095083_2023-02-13_final
2023-02-13 11:26:46	ga_ls8c_ard_3-2-1_111075_2023-02-13_final
2023-02-17 09:27:30	ga_ls8c_ard_3-2-1_091086_2023-02-16_final
2023-02-18 11:45:14	ga_ls8c_ard_3-2-1_114075_2023-02-18_final
2023-02-22 09:42:21	ga_ls8c_ard_3-2-1_094077_2023-02-22_final
2023-02-25 11:50:52	ga_ls8c_ard_3-2-1_115074_2023-02-25_final
2023-02-27 10:01:13	ga_ls8c_ard_3-2-1_097078_2023-02-27_final
2023-03-01 09:50:51	ga_ls8c_ard_3-2-1_095083_2023-03-01_final
2023-03-03 11:16:34	ga_ls8c_ard_3-2-1_109081_2023-03-03_final
2023-03-05 11:01:47	ga_ls8c_ard_3-2-1_107075_2023-03-05_final
2023-03-07 09:14:55	ga_ls8c_ard_3-2-1_089086_2023-03-06_final
2023-03-07 10:47:48	ga_ls8c_ard_3-2-1_105071_2023-03-07_final
2023-03-09 10:37:49	ga_ls8c_ard_3-2-1_103077_2023-03-09_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