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
2022-07-20 09:48:17	ga_ls8c_ard_3-2-1_095076_2022-07-20_final
2022-07-22 09:38:21	ga_ls8c_ard_3-2-1_093082_2022-07-22_final
2022-07-25 10:08:53	ga_ls8c_ard_3-2-1_098081_2022-07-25_final
2022-07-26 10:50:58	ga_ls8c_ard_3-2-1_105078_2022-07-26_final
2022-07-27 09:56:09	ga_ls8c_ard_3-2-1_096080_2022-07-27_final
2022-07-27 11:33:02	ga_ls8c_ard_3-2-1_112075_2022-07-27_final
2022-07-29 09:41:49	ga_ls8c_ard_3-2-1_094075_2022-07-29_final
2022-07-29 11:22:18	ga_ls8c_ard_3-2-1_110079_2022-07-29_final
2022-07-29 11:24:41	ga_ls8c_ard_3-2-1_110085_2022-07-29_final
2022-08-03 11:39:17	ga_ls8c_ard_3-2-1_113075_2022-08-03_final
2022-08-09 09:24:34	ga_ls8c_ard_3-2-1_091078_2022-08-08_final
2022-08-11 10:51:30	ga_ls8c_ard_3-2-1_105079_2022-08-11_final
2022-08-11 10:51:54	ga_ls8c_ard_3-2-1_105080_2022-08-11_final
2022-08-12 11:33:10	ga_ls8c_ard_3-2-1_112075_2022-08-12_final
2022-08-14 09:42:44	ga_ls8c_ard_3-2-1_094077_2022-08-14_final
2022-08-14 09:43:32	ga_ls8c_ard_3-2-1_094079_2022-08-14_final
2022-08-14 11:22:49	ga_ls8c_ard_3-2-1_110080_2022-08-14_final
2022-08-16 11:10:04	ga_ls8c_ard_3-2-1_108079_2022-08-16_final
2022-08-17 10:15:15	ga_ls8c_ard_3-2-1_099081_2022-08-17_final
2022-08-18 09:19:14	ga_ls8c_ard_3-2-1_090080_2022-08-17_final
2022-08-18 10:59:18	ga_ls8c_ard_3-2-1_106083_2022-08-18_final
2022-08-19 10:03:17	ga_ls8c_ard_3-2-1_097082_2022-08-19_final
2022-08-19 11:39:23	ga_ls8c_ard_3-2-1_113075_2022-08-19_final
2022-08-21 09:48:32	ga_ls8c_ard_3-2-1_095076_2022-08-21_final
2022-08-21 11:29:01	ga_ls8c_ard_3-2-1_111080_2022-08-21_final
2022-08-25 11:01:06	ga_ls8c_ard_3-2-1_107072_2022-08-25_final
2022-08-28 09:55:55	ga_ls8c_ard_3-2-1_096079_2022-08-28_final
2022-08-30 11:22:50	ga_ls8c_ard_3-2-1_110080_2022-08-30_final
2022-09-04 10:03:17	ga_ls8c_ard_3-2-1_097082_2022-09-04_final
2022-09-05 10:43:46	ga_ls8c_ard_3-2-1_104075_2022-09-05_final
2022-09-05 10:44:10	ga_ls8c_ard_3-2-1_104076_2022-09-05_final
2022-09-07 10:31:50	ga_ls8c_ard_3-2-1_102076_2022-09-07_final
2022-09-13 09:55:36	ga_ls8c_ard_3-2-1_096078_2022-09-13_final
2022-09-14 10:38:52	ga_ls8c_ard_3-2-1_103078_2022-09-14_final
2022-09-15 09:42:03	ga_ls8c_ard_3-2-1_094075_2022-09-15_final
2022-09-18 10:15:21	ga_ls8c_ard_3-2-1_099081_2022-09-18_final
2022-09-20 11:40:17	ga_ls8c_ard_3-2-1_113077_2022-09-20_final
2022-09-21 10:42:16	ga_ls8c_ard_3-2-1_104071_2022-09-21_final
2022-09-23 10:33:07	ga_ls8c_ard_3-2-1_102079_2022-09-23_final
2022-09-24 11:16:46	ga_ls8c_ard_3-2-1_109080_2022-09-24_final
2022-09-29 09:54:25	ga_ls8c_ard_3-2-1_096075_2022-09-29_final
2022-09-29 11:33:42	ga_ls8c_ard_3-2-1_112076_2022-09-29_final
2022-09-29 11:34:06	ga_ls8c_ard_3-2-1_112077_2022-09-29_final
2022-09-30 10:37:17	ga_ls8c_ard_3-2-1_103074_2022-09-30_final
2022-10-04 10:12:56	ga_ls8c_ard_3-2-1_099075_2022-10-04_final
2022-10-05 10:56:59	ga_ls8c_ard_3-2-1_106077_2022-10-05_final
2022-10-07 10:45:00	ga_ls8c_ard_3-2-1_104078_2022-10-07_final
2022-10-07 10:45:24	ga_ls8c_ard_3-2-1_104079_2022-10-07_final
2022-10-08 11:27:52	ga_ls8c_ard_3-2-1_111077_2022-10-08_final
2022-10-14 10:51:29	ga_ls8c_ard_3-2-1_105079_2022-10-14_final
2022-10-22 11:40:14	ga_ls8c_ard_3-2-1_113077_2022-10-22_final
2022-10-26 09:38:39	ga_ls8c_ard_3-2-1_093082_2022-10-26_final
2022-10-31 09:54:25	ga_ls8c_ard_3-2-1_096075_2022-10-31_final
2022-10-31 11:34:30	ga_ls8c_ard_3-2-1_112078_2022-10-31_final
2022-10-31 11:34:54	ga_ls8c_ard_3-2-1_112079_2022-10-31_final
2022-11-02 11:22:33	ga_ls8c_ard_3-2-1_110079_2022-11-02_final
2022-11-09 09:49:01	ga_ls8c_ard_3-2-1_095077_2022-11-09_final
2022-11-09 11:28:18	ga_ls8c_ard_3-2-1_111078_2022-11-09_final
2022-11-12 10:18:41	ga_ls8c_ard_3-2-1_100074_2022-11-12_final
2022-11-16 11:34:00	ga_ls8c_ard_3-2-1_112077_2022-11-16_final
2022-11-16 11:35:12	ga_ls8c_ard_3-2-1_112080_2022-11-16_final
2022-11-23 11:40:59	ga_ls8c_ard_3-2-1_113079_2022-11-23_final
2022-11-24 10:45:22	ga_ls8c_ard_3-2-1_104079_2022-11-24_final
2022-11-25 09:48:33	ga_ls8c_ard_3-2-1_095076_2022-11-25_final
2022-11-25 11:28:14	ga_ls8c_ard_3-2-1_111078_2022-11-25_final
2022-11-28 10:21:03	ga_ls8c_ard_3-2-1_100080_2022-11-28_final
2022-12-02 09:55:32	ga_ls8c_ard_3-2-1_096078_2022-12-02_final
2022-12-02 09:56:20	ga_ls8c_ard_3-2-1_096080_2022-12-02_final
2022-12-02 11:34:25	ga_ls8c_ard_3-2-1_112078_2022-12-02_final
2022-12-03 10:39:12	ga_ls8c_ard_3-2-1_103079_2022-12-03_final
2022-12-03 10:40:24	ga_ls8c_ard_3-2-1_103082_2022-12-03_final
2022-12-07 11:51:21	ga_ls8c_ard_3-2-1_115074_2022-12-07_final
2022-12-11 09:50:07	ga_ls8c_ard_3-2-1_095080_2022-12-11_final
2022-12-18 11:34:42	ga_ls8c_ard_3-2-1_112079_2022-12-18_final
2022-12-19 10:39:04	ga_ls8c_ard_3-2-1_103079_2022-12-19_final
2022-12-27 09:48:24	ga_ls8c_ard_3-2-1_095076_2022-12-27_final
2022-12-29 09:38:27	ga_ls8c_ard_3-2-1_093082_2022-12-29_final
2023-01-03 09:56:12	ga_ls8c_ard_3-2-1_096080_2023-01-03_final
2023-01-04 10:39:03	ga_ls8c_ard_3-2-1_103079_2023-01-04_final
2023-01-06 10:27:29	ga_ls8c_ard_3-2-1_101081_2023-01-06_final
2023-01-10 11:40:49	ga_ls8c_ard_3-2-1_113079_2023-01-10_final
2023-01-12 09:50:21	ga_ls8c_ard_3-2-1_095081_2023-01-12_final
2023-01-16 11:03:16	ga_ls8c_ard_3-2-1_107078_2023-01-16_final
2023-01-18 10:50:52	ga_ls8c_ard_3-2-1_105078_2023-01-18_final
2023-01-21 11:22:13	ga_ls8c_ard_3-2-1_110079_2023-01-21_final
2023-02-13 09:49:53	ga_ls8c_ard_3-2-1_095080_2023-02-13_final
2023-02-18 10:08:45	ga_ls8c_ard_3-2-1_098081_2023-02-18_final
2023-02-19 10:51:36	ga_ls8c_ard_3-2-1_105080_2023-02-19_final
2023-02-21 10:38:47	ga_ls8c_ard_3-2-1_103079_2023-02-21_final
2023-02-23 10:26:23	ga_ls8c_ard_3-2-1_101079_2023-02-23_final
2023-02-24 09:30:20	ga_ls8c_ard_3-2-1_092078_2023-02-24_final
2023-02-28 10:44:29	ga_ls8c_ard_3-2-1_104078_2023-02-28_final
2023-02-28 10:44:53	ga_ls8c_ard_3-2-1_104079_2023-02-28_final
2023-03-01 09:48:03	ga_ls8c_ard_3-2-1_095076_2023-03-01_final
2023-03-01 11:27:20	ga_ls8c_ard_3-2-1_111077_2023-03-01_final
2023-03-01 11:27:44	ga_ls8c_ard_3-2-1_111078_2023-03-01_final
2023-03-01 11:28:08	ga_ls8c_ard_3-2-1_111079_2023-03-01_final
2023-03-04 11:58:13	ga_ls8c_ard_3-2-1_116077_2023-03-04_final
2023-03-05 11:02:59	ga_ls8c_ard_3-2-1_107078_2023-03-05_final
2023-03-06 10:08:33	ga_ls8c_ard_3-2-1_098081_2023-03-06_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