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
2022-09-15 09:41:15	ga_ls8c_ard_3-2-1_094073_2022-09-15_final
2022-09-28 10:46:51	ga_ls8c_ard_3-2-1_105067_2022-09-28_final
2022-10-03 11:06:34	ga_ls8c_ard_3-2-1_108070_2022-10-03_final
2022-10-04 11:51:49	ga_ls8c_ard_3-2-1_115075_2022-10-04_final
2022-10-12 09:28:59	ga_ls8c_ard_3-2-1_091089_2022-10-11_final
2022-10-13 10:03:27	ga_ls8c_ard_3-2-1_098067_2022-10-13_final
2022-10-17 11:20:50	ga_ls8c_ard_3-2-1_110075_2022-10-17_final
2022-10-18 10:23:38	ga_ls8c_ard_3-2-1_101071_2022-10-18_final
2022-10-21 10:53:46	ga_ls8c_ard_3-2-1_106069_2022-10-21_final
2022-10-21 10:54:10	ga_ls8c_ard_3-2-1_106070_2022-10-21_final
2022-10-22 09:58:33	ga_ls8c_ard_3-2-1_097070_2022-10-22_final
2022-10-22 09:58:57	ga_ls8c_ard_3-2-1_097071_2022-10-22_final
2022-10-24 11:25:30	ga_ls8c_ard_3-2-1_111071_2022-10-24_final
2022-10-25 10:29:53	ga_ls8c_ard_3-2-1_102071_2022-10-25_final
2022-10-29 10:10:46	ga_ls8c_ard_3-2-1_098085_2022-10-29_final
2022-10-30 10:47:39	ga_ls8c_ard_3-2-1_105069_2022-10-30_final
2022-11-04 11:11:47	ga_ls8c_ard_3-2-1_108083_2022-11-04_final
2022-11-09 09:53:00	ga_ls8c_ard_3-2-1_095087_2022-11-09_final
2022-11-13 11:00:21	ga_ls8c_ard_3-2-1_107070_2022-11-13_final
2022-11-15 09:14:40	ga_ls8c_ard_3-2-1_089084_2022-11-14_final
2022-11-17 10:37:10	ga_ls8c_ard_3-2-1_103074_2022-11-17_final
2022-11-19 10:24:00	ga_ls8c_ard_3-2-1_101072_2022-11-19_final
2022-11-24 10:40:59	ga_ls8c_ard_3-2-1_104068_2022-11-24_final
2022-11-26 10:29:49	ga_ls8c_ard_3-2-1_102071_2022-11-26_final
2022-11-27 11:15:05	ga_ls8c_ard_3-2-1_109076_2022-11-27_final
2022-12-04 09:44:46	ga_ls8c_ard_3-2-1_094082_2022-12-04_final
2022-12-04 09:46:46	ga_ls8c_ard_3-2-1_094087_2022-12-04_final
2022-12-05 10:28:02	ga_ls8c_ard_3-2-1_101082_2022-12-05_final
2022-12-08 10:54:32	ga_ls8c_ard_3-2-1_106071_2022-12-08_final
2022-12-08 10:55:20	ga_ls8c_ard_3-2-1_106073_2022-12-08_final
2022-12-10 10:40:58	ga_ls8c_ard_3-2-1_104068_2022-12-10_final
2022-12-11 11:24:37	ga_ls8c_ard_3-2-1_111069_2022-12-11_final
2022-12-13 09:38:56	ga_ls8c_ard_3-2-1_093083_2022-12-13_final
2022-12-15 11:04:15	ga_ls8c_ard_3-2-1_107080_2022-12-15_final
2022-12-22 11:08:19	ga_ls8c_ard_3-2-1_108075_2022-12-22_final
2022-12-28 10:32:04	ga_ls8c_ard_3-2-1_102077_2022-12-28_final
2023-01-03 09:53:00	ga_ls8c_ard_3-2-1_096072_2023-01-03_final
2023-01-06 10:28:17	ga_ls8c_ard_3-2-1_101083_2023-01-06_final
2023-01-09 09:19:53	ga_ls8c_ard_3-2-1_090082_2023-01-08_final
2023-01-19 09:58:28	ga_ls8c_ard_3-2-1_096086_2023-01-19_final
2023-01-21 11:19:02	ga_ls8c_ard_3-2-1_110071_2023-01-21_final
2023-01-22 10:27:49	ga_ls8c_ard_3-2-1_101082_2023-01-22_final
2023-01-25 10:59:08	ga_ls8c_ard_3-2-1_106083_2023-01-25_final
2023-01-26 11:41:13	ga_ls8c_ard_3-2-1_113080_2023-01-26_final
2023-02-03 09:13:18	ga_ls8c_ard_3-2-1_089081_2023-02-02_final
2023-02-06 11:19:53	ga_ls8c_ard_3-2-1_110073_2023-02-06_final
2023-02-09 11:53:09	ga_ls8c_ard_3-2-1_115079_2023-02-09_final
2023-02-10 09:21:01	ga_ls8c_ard_3-2-1_090085_2023-02-09_final
2023-02-11 10:03:52	ga_ls8c_ard_3-2-1_097084_2023-02-11_final
2023-02-11 11:42:21	ga_ls8c_ard_3-2-1_113083_2023-02-11_final
2023-02-12 10:42:44	ga_ls8c_ard_3-2-1_104073_2023-02-12_final
2023-02-16 10:21:57	ga_ls8c_ard_3-2-1_100083_2023-02-16_final
2023-02-18 11:47:14	ga_ls8c_ard_3-2-1_114080_2023-02-18_final
2023-02-19 09:14:18	ga_ls8c_ard_3-2-1_089084_2023-02-18_final
2023-02-20 09:52:22	ga_ls8c_ard_3-2-1_096071_2023-02-20_final
2023-02-25 10:15:34	ga_ls8c_ard_3-2-1_099083_2023-02-25_final
2023-03-03 11:12:10	ga_ls8c_ard_3-2-1_109070_2023-03-03_final
2023-03-12 09:34:14	ga_ls8c_ard_3-2-1_092088_2023-03-12_final
2023-03-18 10:30:00	ga_ls8c_ard_3-2-1_102073_2023-03-18_final
2023-03-21 09:26:45	ga_ls8c_ard_3-2-1_091085_2023-03-20_final
2023-03-21 09:27:57	ga_ls8c_ard_3-2-1_091088_2023-03-20_final
2023-03-22 11:46:53	ga_ls8c_ard_3-2-1_114080_2023-03-22_final
2023-03-28 11:10:57	ga_ls8c_ard_3-2-1_108083_2023-03-28_final
2023-03-30 09:20:29	ga_ls8c_ard_3-2-1_090085_2023-03-29_final
2023-04-06 11:01:03	ga_ls8c_ard_3-2-1_107074_2023-04-06_final
2023-04-06 11:01:27	ga_ls8c_ard_3-2-1_107075_2023-04-06_final
2023-04-09 11:35:04	ga_ls8c_ard_3-2-1_112082_2023-04-09_final
2023-04-12 10:27:26	ga_ls8c_ard_3-2-1_101083_2023-04-12_final
2023-04-14 10:10:41	ga_ls8c_ard_3-2-1_099072_2023-04-14_final
2023-04-14 11:52:45	ga_ls8c_ard_3-2-1_115080_2023-04-14_final
2023-04-15 10:54:44	ga_ls8c_ard_3-2-1_106074_2023-04-15_final
2023-04-16 10:03:30	ga_ls8c_ard_3-2-1_097085_2023-04-16_final
2023-04-24 10:48:31	ga_ls8c_ard_3-2-1_105074_2023-04-24_final
2023-05-10 09:15:27	ga_ls8c_ard_3-2-1_089089_2023-05-09_final
2023-05-16 10:08:24	ga_ls8c_ard_3-2-1_099067_2023-05-16_final
2023-05-22 09:38:31	ga_ls8c_ard_3-2-1_093085_2023-05-22_final
2023-05-24 11:01:28	ga_ls8c_ard_3-2-1_107076_2023-05-24_final
2023-05-29 11:18:49	ga_ls8c_ard_3-2-1_110073_2023-05-29_final
2023-06-14 11:23:21	ga_ls8c_ard_3-2-1_110084_2023-06-14_final
2023-06-17 10:13:47	ga_ls8c_ard_3-2-1_099080_2023-06-17_final
2023-06-20 09:07:00	ga_ls8c_ard_3-2-1_088083_2023-06-19_final
2023-06-23 09:38:18	ga_ls8c_ard_3-2-1_093084_2023-06-23_final
2023-06-23 11:16:47	ga_ls8c_ard_3-2-1_109083_2023-06-23_final
2023-06-28 09:57:20	ga_ls8c_ard_3-2-1_096085_2023-06-28_final
2023-07-02 11:06:22	ga_ls8c_ard_3-2-1_108072_2023-07-02_final
2023-07-13 10:46:43	ga_ls8c_ard_3-2-1_105069_2023-07-13_final
2023-07-13 10:51:30	ga_ls8c_ard_3-2-1_105081_2023-07-13_final
2023-07-15 10:33:57	ga_ls8c_ard_3-2-1_103068_2023-07-15_final
2023-07-19 10:14:01	ga_ls8c_ard_3-2-1_099080_2023-07-19_final
2023-07-23 09:46:08	ga_ls8c_ard_3-2-1_095072_2023-07-23_final
2023-07-24 10:33:00	ga_ls8c_ard_3-2-1_102081_2023-07-24_final
2023-08-03 11:05:24	ga_ls8c_ard_3-2-1_108069_2023-08-03_final
2023-08-04 10:08:59	ga_ls8c_ard_3-2-1_099067_2023-08-04_final
2023-08-04 10:09:47	ga_ls8c_ard_3-2-1_099069_2023-08-04_final
2023-08-07 09:06:36	ga_ls8c_ard_3-2-1_088081_2023-08-06_final
2023-08-17 09:44:33	ga_ls8c_ard_3-2-1_094083_2023-08-17_final
2023-08-20 10:09:30	ga_ls8c_ard_3-2-1_099068_2023-08-20_final
2023-08-20 10:12:41	ga_ls8c_ard_3-2-1_099076_2023-08-20_final
2023-08-22 09:57:33	ga_ls8c_ard_3-2-1_097069_2023-08-22_final
2023-09-05 10:09:06	ga_ls8c_ard_3-2-1_099067_2023-09-05_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