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
2022-02-26 11:27:18	ga_ls8c_ard_3-2-1_111077_2022-02-26_final
2022-03-17 10:20:25	ga_ls8c_ard_3-2-1_100080_2022-03-17_final
2022-03-24 10:23:19	ga_ls8c_ard_3-2-1_101072_2022-03-24_final
2022-03-25 11:08:09	ga_ls8c_ard_3-2-1_108076_2022-03-25_final
2022-04-11 10:11:44	ga_ls8c_ard_3-2-1_099074_2022-04-11_final
2022-04-20 10:07:58	ga_ls8c_ard_3-2-1_098080_2022-04-20_final
2022-04-21 10:50:01	ga_ls8c_ard_3-2-1_105077_2022-04-21_final
2022-04-29 11:41:24	ga_ls8c_ard_3-2-1_113082_2022-04-29_final
2022-04-29 11:41:48	ga_ls8c_ard_3-2-1_113083_2022-04-29_final
2022-05-12 11:08:15	ga_ls8c_ard_3-2-1_108076_2022-05-12_final
2022-05-15 10:00:41	ga_ls8c_ard_3-2-1_097077_2022-05-15_final
2022-05-19 11:12:28	ga_ls8c_ard_3-2-1_109071_2022-05-19_final
2022-05-24 09:52:55	ga_ls8c_ard_3-2-1_096073_2022-05-24_final
2022-05-26 11:21:26	ga_ls8c_ard_3-2-1_110078_2022-05-26_final
2022-06-01 10:40:49	ga_ls8c_ard_3-2-1_104069_2022-06-01_final
2022-06-04 11:15:21	ga_ls8c_ard_3-2-1_109078_2022-06-04_final
2022-06-05 10:20:33	ga_ls8c_ard_3-2-1_100080_2022-06-05_final
2022-06-06 11:01:02	ga_ls8c_ard_3-2-1_107073_2022-06-06_final
2022-06-07 10:08:37	ga_ls8c_ard_3-2-1_098081_2022-06-07_final
2022-06-08 10:52:41	ga_ls8c_ard_3-2-1_105083_2022-06-08_final
2022-06-15 10:58:33	ga_ls8c_ard_3-2-1_106082_2022-06-15_final
2022-06-25 09:56:24	ga_ls8c_ard_3-2-1_096081_2022-06-25_final
2022-06-27 11:21:20	ga_ls8c_ard_3-2-1_110077_2022-06-27_final
2022-07-04 09:50:38	ga_ls8c_ard_3-2-1_095082_2022-07-04_final
2022-07-07 11:58:02	ga_ls8c_ard_3-2-1_116076_2022-07-07_final
2022-07-09 10:06:23	ga_ls8c_ard_3-2-1_098075_2022-07-09_final
2022-07-10 09:14:45	ga_ls8c_ard_3-2-1_089085_2022-07-09_final
2022-07-13 09:44:26	ga_ls8c_ard_3-2-1_094082_2022-07-13_final
2022-07-17 09:19:44	ga_ls8c_ard_3-2-1_090082_2022-07-16_final
2022-07-21 10:29:58	ga_ls8c_ard_3-2-1_102072_2022-07-21_final
2022-07-29 09:44:12	ga_ls8c_ard_3-2-1_094081_2022-07-29_final
2022-07-31 11:05:58	ga_ls8c_ard_3-2-1_108069_2022-07-31_final
2022-07-31 11:11:57	ga_ls8c_ard_3-2-1_108084_2022-07-31_final
2022-08-07 11:17:24	ga_ls8c_ard_3-2-1_109082_2022-08-07_final
2022-08-10 11:47:55	ga_ls8c_ard_3-2-1_114081_2022-08-10_final
2022-08-12 09:53:05	ga_ls8c_ard_3-2-1_096072_2022-08-12_final
2022-08-12 11:36:22	ga_ls8c_ard_3-2-1_112083_2022-08-12_final
2022-08-14 09:43:32	ga_ls8c_ard_3-2-1_094079_2022-08-14_final
2022-09-03 10:58:54	ga_ls8c_ard_3-2-1_106082_2022-09-03_final
2022-09-04 11:38:11	ga_ls8c_ard_3-2-1_113072_2022-09-04_final
2022-09-04 11:40:11	ga_ls8c_ard_3-2-1_113077_2022-09-04_final
2022-09-10 11:01:34	ga_ls8c_ard_3-2-1_107073_2022-09-10_final
2022-09-11 11:47:38	ga_ls8c_ard_3-2-1_114080_2022-09-11_final
2022-09-16 10:26:55	ga_ls8c_ard_3-2-1_101079_2022-09-16_final
2022-09-17 09:32:53	ga_ls8c_ard_3-2-1_092083_2022-09-17_final
2022-09-24 11:17:10	ga_ls8c_ard_3-2-1_109081_2022-09-24_final
2022-09-26 09:25:55	ga_ls8c_ard_3-2-1_091081_2022-09-25_final
2022-09-27 11:46:52	ga_ls8c_ard_3-2-1_114078_2022-09-27_final
2022-09-29 09:54:01	ga_ls8c_ard_3-2-1_096074_2022-09-29_final
2022-10-04 11:52:13	ga_ls8c_ard_3-2-1_115076_2022-10-04_final
2022-10-07 09:06:55	ga_ls8c_ard_3-2-1_088080_2022-10-06_final
2022-10-14 09:15:24	ga_ls8c_ard_3-2-1_089086_2022-10-13_final
2022-10-19 11:10:54	ga_ls8c_ard_3-2-1_108081_2022-10-19_final
2022-10-24 09:49:48	ga_ls8c_ard_3-2-1_095079_2022-10-24_final
2022-10-24 11:27:53	ga_ls8c_ard_3-2-1_111077_2022-10-24_final
2022-11-03 10:24:32	ga_ls8c_ard_3-2-1_101073_2022-11-03_final
2022-11-04 09:30:54	ga_ls8c_ard_3-2-1_092078_2022-11-04_final
2022-11-14 10:05:54	ga_ls8c_ard_3-2-1_098073_2022-11-14_final
2022-11-18 11:22:25	ga_ls8c_ard_3-2-1_110079_2022-11-18_final
2022-11-19 10:25:12	ga_ls8c_ard_3-2-1_101075_2022-11-19_final
2022-11-20 09:32:23	ga_ls8c_ard_3-2-1_092082_2022-11-20_final
2022-11-22 10:58:07	ga_ls8c_ard_3-2-1_106080_2022-11-22_final
2022-11-24 10:44:58	ga_ls8c_ard_3-2-1_104078_2022-11-24_final
2022-12-05 10:26:50	ga_ls8c_ard_3-2-1_101079_2022-12-05_final
2022-12-10 10:45:45	ga_ls8c_ard_3-2-1_104080_2022-12-10_final
2022-12-11 09:51:43	ga_ls8c_ard_3-2-1_095084_2022-12-11_final
2022-12-22 11:09:07	ga_ls8c_ard_3-2-1_108077_2022-12-22_final
2022-12-27 09:51:36	ga_ls8c_ard_3-2-1_095084_2022-12-27_final
2022-12-28 10:33:16	ga_ls8c_ard_3-2-1_102080_2022-12-28_final
2022-12-28 10:33:40	ga_ls8c_ard_3-2-1_102081_2022-12-28_final
2023-01-03 09:53:00	ga_ls8c_ard_3-2-1_096072_2023-01-03_final
2023-01-06 10:26:17	ga_ls8c_ard_3-2-1_101078_2023-01-06_final
2023-01-10 11:41:13	ga_ls8c_ard_3-2-1_113080_2023-01-10_final
2023-01-14 09:38:46	ga_ls8c_ard_3-2-1_093083_2023-01-14_final
2023-01-16 11:03:40	ga_ls8c_ard_3-2-1_107079_2023-01-16_final
2023-01-20 10:38:09	ga_ls8c_ard_3-2-1_103077_2023-01-20_final
2023-01-25 10:57:56	ga_ls8c_ard_3-2-1_106080_2023-01-25_final
2023-02-05 10:38:13	ga_ls8c_ard_3-2-1_103077_2023-02-05_final
2023-02-08 09:32:36	ga_ls8c_ard_3-2-1_092083_2023-02-08_final
2023-02-09 10:12:40	ga_ls8c_ard_3-2-1_099075_2023-02-09_final
2023-02-20 11:32:50	ga_ls8c_ard_3-2-1_112075_2023-02-20_final
2023-02-25 10:14:46	ga_ls8c_ard_3-2-1_099081_2023-02-25_final
2023-03-01 11:26:32	ga_ls8c_ard_3-2-1_111075_2023-03-01_final
2023-03-01 11:26:56	ga_ls8c_ard_3-2-1_111076_2023-03-01_final
2023-03-05 11:03:47	ga_ls8c_ard_3-2-1_107080_2023-03-05_final
2023-03-07 10:47:48	ga_ls8c_ard_3-2-1_105071_2023-03-07_final
2023-03-08 09:56:57	ga_ls8c_ard_3-2-1_096083_2023-03-08_final
2023-03-17 11:26:26	ga_ls8c_ard_3-2-1_111075_2023-03-17_final
2023-03-26 09:44:03	ga_ls8c_ard_3-2-1_094082_2023-03-26_final
2023-04-04 11:11:51	ga_ls8c_ard_3-2-1_109070_2023-04-04_final
2023-04-11 09:43:46	ga_ls8c_ard_3-2-1_094082_2023-04-11_final
2023-04-14 10:15:52	ga_ls8c_ard_3-2-1_099085_2023-04-14_final
2023-04-20 11:17:13	ga_ls8c_ard_3-2-1_109084_2023-04-20_final
2023-04-21 10:20:48	ga_ls8c_ard_3-2-1_100082_2023-04-21_final
2023-04-29 11:05:50	ga_ls8c_ard_3-2-1_108071_2023-04-29_final
2023-05-01 10:57:03	ga_ls8c_ard_3-2-1_106080_2023-05-01_final
2023-05-04 09:49:50	ga_ls8c_ard_3-2-1_095082_2023-05-04_final
2023-05-04 09:51:02	ga_ls8c_ard_3-2-1_095085_2023-05-04_final
2023-05-07 10:19:30	ga_ls8c_ard_3-2-1_100079_2023-05-07_final
2023-05-11 09:51:54	ga_ls8c_ard_3-2-1_096072_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