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
2022-04-13 10:00:11	ga_ls8c_ard_3-2-1_097076_2022-04-13_final
2022-04-19 09:24:42	ga_ls8c_ard_3-2-1_091080_2022-04-18_final
2022-04-19 11:01:59	ga_ls8c_ard_3-2-1_107076_2022-04-19_final
2022-05-03 09:34:39	ga_ls8c_ard_3-2-1_093074_2022-05-03_final
2022-05-03 09:39:03	ga_ls8c_ard_3-2-1_093085_2022-05-03_final
2022-05-03 09:39:27	ga_ls8c_ard_3-2-1_093086_2022-05-03_final
2022-05-06 10:04:48	ga_ls8c_ard_3-2-1_098072_2022-05-06_final
2022-05-06 10:07:59	ga_ls8c_ard_3-2-1_098080_2022-05-06_final
2022-05-15 09:59:29	ga_ls8c_ard_3-2-1_097074_2022-05-15_final
2022-05-19 11:17:16	ga_ls8c_ard_3-2-1_109083_2022-05-19_final
2022-05-26 11:18:14	ga_ls8c_ard_3-2-1_110070_2022-05-26_final
2022-05-28 11:05:28	ga_ls8c_ard_3-2-1_108069_2022-05-28_final
2022-06-04 11:17:21	ga_ls8c_ard_3-2-1_109083_2022-06-04_final
2022-06-11 09:40:45	ga_ls8c_ard_3-2-1_094073_2022-06-11_final
2022-06-13 11:08:30	ga_ls8c_ard_3-2-1_108076_2022-06-13_final
2022-06-15 10:54:09	ga_ls8c_ard_3-2-1_106071_2022-06-15_final
2022-06-16 11:41:49	ga_ls8c_ard_3-2-1_113082_2022-06-16_final
2022-06-20 11:17:32	ga_ls8c_ard_3-2-1_109083_2022-06-20_final
2022-06-23 10:08:22	ga_ls8c_ard_3-2-1_098080_2022-06-23_final
2022-06-23 11:46:03	ga_ls8c_ard_3-2-1_114077_2022-06-23_final
2022-06-27 09:40:52	ga_ls8c_ard_3-2-1_094073_2022-06-27_final
2022-06-30 11:51:51	ga_ls8c_ard_3-2-1_115076_2022-06-30_final
2022-07-01 10:55:02	ga_ls8c_ard_3-2-1_106073_2022-07-01_final
2022-07-09 11:46:52	ga_ls8c_ard_3-2-1_114079_2022-07-09_final
2022-07-11 11:32:06	ga_ls8c_ard_3-2-1_112073_2022-07-11_final
2022-07-17 10:54:13	ga_ls8c_ard_3-2-1_106071_2022-07-17_final
2022-07-20 11:29:34	ga_ls8c_ard_3-2-1_111082_2022-07-20_final
2022-07-29 11:18:42	ga_ls8c_ard_3-2-1_110070_2022-07-29_final
2022-07-31 11:11:57	ga_ls8c_ard_3-2-1_108084_2022-07-31_final
2022-08-02 09:20:43	ga_ls8c_ard_3-2-1_090084_2022-08-01_final
2022-08-02 10:55:13	ga_ls8c_ard_3-2-1_106073_2022-08-02_final
2022-08-04 10:44:04	ga_ls8c_ard_3-2-1_104076_2022-08-04_final
2022-08-06 10:29:44	ga_ls8c_ard_3-2-1_102071_2022-08-06_final
2022-08-10 11:47:07	ga_ls8c_ard_3-2-1_114079_2022-08-10_final
2022-08-11 09:13:25	ga_ls8c_ard_3-2-1_089081_2022-08-10_final
2022-08-13 10:34:46	ga_ls8c_ard_3-2-1_103068_2022-08-13_final
2022-08-17 11:51:20	ga_ls8c_ard_3-2-1_115074_2022-08-17_final
2022-08-24 10:19:26	ga_ls8c_ard_3-2-1_100076_2022-08-24_final
2022-08-27 10:48:45	ga_ls8c_ard_3-2-1_105072_2022-08-27_final
2022-09-03 10:58:54	ga_ls8c_ard_3-2-1_106082_2022-09-03_final
2022-09-09 11:58:22	ga_ls8c_ard_3-2-1_116076_2022-09-09_final
2022-09-12 10:53:12	ga_ls8c_ard_3-2-1_105083_2022-09-12_final
2022-09-19 09:20:08	ga_ls8c_ard_3-2-1_090082_2022-09-18_final
2022-10-02 10:24:07	ga_ls8c_ard_3-2-1_101072_2022-10-02_final
2022-10-03 09:32:29	ga_ls8c_ard_3-2-1_092082_2022-10-03_final
2022-10-07 09:06:55	ga_ls8c_ard_3-2-1_088080_2022-10-06_final
2022-10-07 10:41:25	ga_ls8c_ard_3-2-1_104069_2022-10-07_final
2022-10-14 10:46:42	ga_ls8c_ard_3-2-1_105067_2022-10-14_final
2022-10-15 11:32:23	ga_ls8c_ard_3-2-1_112073_2022-10-15_final
2022-10-20 10:16:29	ga_ls8c_ard_3-2-1_099084_2022-10-20_final
2022-10-20 11:51:23	ga_ls8c_ard_3-2-1_115074_2022-10-20_final
2022-10-20 11:52:11	ga_ls8c_ard_3-2-1_115076_2022-10-20_final
2022-10-20 11:52:34	ga_ls8c_ard_3-2-1_115077_2022-10-20_final
2022-10-23 10:41:02	ga_ls8c_ard_3-2-1_104068_2022-10-23_final
2022-10-27 10:18:44	ga_ls8c_ard_3-2-1_100074_2022-10-27_final
2022-11-03 10:23:20	ga_ls8c_ard_3-2-1_101070_2022-11-03_final
2022-11-06 09:18:56	ga_ls8c_ard_3-2-1_090079_2022-11-05_final
2022-11-08 10:44:15	ga_ls8c_ard_3-2-1_104076_2022-11-08_final
2022-11-09 09:51:25	ga_ls8c_ard_3-2-1_095083_2022-11-09_final
2022-11-09 11:29:54	ga_ls8c_ard_3-2-1_111082_2022-11-09_final
2022-11-12 11:58:22	ga_ls8c_ard_3-2-1_116076_2022-11-12_final
2022-11-17 10:37:58	ga_ls8c_ard_3-2-1_103076_2022-11-17_final
2022-11-18 09:44:19	ga_ls8c_ard_3-2-1_094081_2022-11-18_final
2022-11-22 10:58:55	ga_ls8c_ard_3-2-1_106082_2022-11-22_final
2022-11-23 09:59:42	ga_ls8c_ard_3-2-1_097073_2022-11-23_final
2022-11-25 09:50:57	ga_ls8c_ard_3-2-1_095082_2022-11-25_final
2022-11-25 11:29:26	ga_ls8c_ard_3-2-1_111081_2022-11-25_final
2022-11-27 09:38:59	ga_ls8c_ard_3-2-1_093083_2022-11-27_final
2022-11-30 10:07:30	ga_ls8c_ard_3-2-1_098077_2022-11-30_final
2022-11-30 11:45:35	ga_ls8c_ard_3-2-1_114075_2022-11-30_final
2022-11-30 11:45:59	ga_ls8c_ard_3-2-1_114076_2022-11-30_final
2022-12-02 11:33:14	ga_ls8c_ard_3-2-1_112075_2022-12-02_final
2022-12-06 11:10:06	ga_ls8c_ard_3-2-1_108079_2022-12-06_final
2022-12-10 10:45:45	ga_ls8c_ard_3-2-1_104080_2022-12-10_final
2022-12-13 09:34:33	ga_ls8c_ard_3-2-1_093072_2022-12-13_final
2022-12-15 09:24:34	ga_ls8c_ard_3-2-1_091078_2022-12-14_final
2022-12-16 11:45:30	ga_ls8c_ard_3-2-1_114075_2022-12-16_final
2022-12-17 10:47:28	ga_ls8c_ard_3-2-1_105069_2022-12-17_final
2022-12-24 10:57:58	ga_ls8c_ard_3-2-1_106080_2022-12-24_final
2022-12-29 09:36:03	ga_ls8c_ard_3-2-1_093076_2022-12-29_final
2022-12-29 09:39:15	ga_ls8c_ard_3-2-1_093084_2022-12-29_final
2023-01-04 10:39:27	ga_ls8c_ard_3-2-1_103080_2023-01-04_final
2023-01-05 09:41:26	ga_ls8c_ard_3-2-1_094074_2023-01-05_final
2023-01-06 10:25:05	ga_ls8c_ard_3-2-1_101075_2023-01-06_final
2023-01-08 10:12:19	ga_ls8c_ard_3-2-1_099074_2023-01-08_final
2023-01-08 10:13:07	ga_ls8c_ard_3-2-1_099076_2023-01-08_final
2023-01-14 11:17:15	ga_ls8c_ard_3-2-1_109082_2023-01-14_final
2023-01-16 09:26:46	ga_ls8c_ard_3-2-1_091084_2023-01-15_final
2023-01-19 09:56:04	ga_ls8c_ard_3-2-1_096080_2023-01-19_final
2023-01-26 11:39:13	ga_ls8c_ard_3-2-1_113075_2023-01-26_final
2023-02-07 10:25:51	ga_ls8c_ard_3-2-1_101077_2023-02-07_final
2023-02-07 10:28:14	ga_ls8c_ard_3-2-1_101083_2023-02-07_final
2023-02-08 11:05:54	ga_ls8c_ard_3-2-1_108069_2023-02-08_final
2023-02-09 10:13:04	ga_ls8c_ard_3-2-1_099076_2023-02-09_final
2023-02-11 10:01:29	ga_ls8c_ard_3-2-1_097078_2023-02-11_final
2023-02-11 11:41:33	ga_ls8c_ard_3-2-1_113081_2023-02-11_final
2023-02-15 09:40:18	ga_ls8c_ard_3-2-1_093087_2023-02-15_final
2023-02-18 10:08:21	ga_ls8c_ard_3-2-1_098080_2023-02-18_final
2023-03-03 09:35:17	ga_ls8c_ard_3-2-1_093075_2023-03-03_final
2023-03-05 10:59:48	ga_ls8c_ard_3-2-1_107070_2023-03-05_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