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
2022-03-09 11:08:20	ga_ls8c_ard_3-2-1_108076_2022-03-09_final
2022-03-11 09:19:28	ga_ls8c_ard_3-2-1_090082_2022-03-10_final
2022-03-16 09:38:21	ga_ls8c_ard_3-2-1_093083_2022-03-16_final
2022-03-19 10:06:50	ga_ls8c_ard_3-2-1_098077_2022-03-19_final
2022-03-21 09:52:03	ga_ls8c_ard_3-2-1_096071_2022-03-21_final
2022-03-22 10:36:06	ga_ls8c_ard_3-2-1_103073_2022-03-22_final
2022-03-22 10:38:05	ga_ls8c_ard_3-2-1_103078_2022-03-22_final
2022-03-23 09:42:51	ga_ls8c_ard_3-2-1_094079_2022-03-23_final
2022-03-24 10:26:06	ga_ls8c_ard_3-2-1_101079_2022-03-24_final
2022-04-06 09:56:45	ga_ls8c_ard_3-2-1_096083_2022-04-06_final
2022-04-10 09:29:16	ga_ls8c_ard_3-2-1_092076_2022-04-09_final
2022-04-11 11:51:25	ga_ls8c_ard_3-2-1_115076_2022-04-11_final
2022-04-15 11:26:43	ga_ls8c_ard_3-2-1_111076_2022-04-15_final
2022-04-19 11:02:23	ga_ls8c_ard_3-2-1_107077_2022-04-19_final
2022-04-24 11:23:42	ga_ls8c_ard_3-2-1_110084_2022-04-24_final
2022-05-10 11:22:35	ga_ls8c_ard_3-2-1_110081_2022-05-10_final
2022-06-11 09:44:20	ga_ls8c_ard_3-2-1_094082_2022-06-11_final
2022-06-17 10:44:12	ga_ls8c_ard_3-2-1_104077_2022-06-17_final
2022-06-19 10:31:52	ga_ls8c_ard_3-2-1_102077_2022-06-19_final
2022-07-11 09:52:49	ga_ls8c_ard_3-2-1_096072_2022-07-11_final
2022-07-15 09:32:52	ga_ls8c_ard_3-2-1_092084_2022-07-15_final
2022-07-19 10:45:29	ga_ls8c_ard_3-2-1_104080_2022-07-19_final
2022-07-23 10:22:25	ga_ls8c_ard_3-2-1_100084_2022-07-23_final
2022-08-03 09:59:36	ga_ls8c_ard_3-2-1_097073_2022-08-03_final
2022-08-04 10:42:05	ga_ls8c_ard_3-2-1_104071_2022-08-04_final
2022-08-05 09:48:27	ga_ls8c_ard_3-2-1_095076_2022-08-05_final
2022-08-14 11:24:01	ga_ls8c_ard_3-2-1_110083_2022-08-14_final
2022-08-15 10:24:48	ga_ls8c_ard_3-2-1_101074_2022-08-15_final
2022-08-16 11:06:52	ga_ls8c_ard_3-2-1_108071_2022-08-16_final
2022-08-18 09:20:01	ga_ls8c_ard_3-2-1_090082_2022-08-17_final
2022-08-21 09:52:08	ga_ls8c_ard_3-2-1_095085_2022-08-21_final
2022-08-23 11:15:28	ga_ls8c_ard_3-2-1_109077_2022-08-23_final
2022-08-25 11:05:30	ga_ls8c_ard_3-2-1_107083_2022-08-25_final
2022-08-27 10:47:57	ga_ls8c_ard_3-2-1_105070_2022-08-27_final
2022-09-01 11:06:52	ga_ls8c_ard_3-2-1_108071_2022-09-01_final
2022-09-09 10:19:05	ga_ls8c_ard_3-2-1_100075_2022-09-09_final
2022-09-09 10:20:41	ga_ls8c_ard_3-2-1_100079_2022-09-09_final
2022-09-12 10:48:49	ga_ls8c_ard_3-2-1_105072_2022-09-12_final
2022-09-21 10:44:16	ga_ls8c_ard_3-2-1_104076_2022-09-21_final
2022-09-28 10:52:50	ga_ls8c_ard_3-2-1_105082_2022-09-28_final
2022-10-14 09:14:12	ga_ls8c_ard_3-2-1_089083_2022-10-13_final
2022-10-14 10:47:54	ga_ls8c_ard_3-2-1_105070_2022-10-14_final
2022-10-16 10:38:46	ga_ls8c_ard_3-2-1_103078_2022-10-16_final
2022-10-19 11:10:30	ga_ls8c_ard_3-2-1_108080_2022-10-19_final
2022-10-22 09:59:45	ga_ls8c_ard_3-2-1_097073_2022-10-22_final
2022-10-22 10:00:09	ga_ls8c_ard_3-2-1_097074_2022-10-22_final
2022-10-23 10:45:49	ga_ls8c_ard_3-2-1_104080_2022-10-23_final
2022-10-28 11:04:23	ga_ls8c_ard_3-2-1_107080_2022-10-28_final
2022-10-29 11:48:03	ga_ls8c_ard_3-2-1_114081_2022-10-29_final
2022-10-30 10:50:50	ga_ls8c_ard_3-2-1_105077_2022-10-30_final
2022-10-30 10:53:14	ga_ls8c_ard_3-2-1_105083_2022-10-30_final
2022-10-31 09:56:01	ga_ls8c_ard_3-2-1_096079_2022-10-31_final
2022-11-07 11:41:28	ga_ls8c_ard_3-2-1_113080_2022-11-07_final
2022-11-09 11:25:30	ga_ls8c_ard_3-2-1_111071_2022-11-09_final
2022-11-14 10:08:18	ga_ls8c_ard_3-2-1_098079_2022-11-14_final
2022-12-20 11:23:55	ga_ls8c_ard_3-2-1_110083_2022-12-20_final
2022-12-24 09:20:40	ga_ls8c_ard_3-2-1_090084_2022-12-23_final
2022-12-26 10:42:01	ga_ls8c_ard_3-2-1_104071_2022-12-26_final
2023-01-26 11:39:13	ga_ls8c_ard_3-2-1_113075_2023-01-26_final
2023-02-11 11:41:33	ga_ls8c_ard_3-2-1_113081_2023-02-11_final
2023-02-17 09:24:43	ga_ls8c_ard_3-2-1_091079_2023-02-16_final
2023-02-21 10:38:23	ga_ls8c_ard_3-2-1_103078_2023-02-21_final
2023-03-02 10:31:43	ga_ls8c_ard_3-2-1_102077_2023-03-02_final
2023-03-05 11:03:47	ga_ls8c_ard_3-2-1_107080_2023-03-05_final
2023-03-17 11:26:49	ga_ls8c_ard_3-2-1_111076_2023-03-17_final
2023-03-19 09:35:33	ga_ls8c_ard_3-2-1_093076_2023-03-19_final
2023-03-19 09:37:33	ga_ls8c_ard_3-2-1_093081_2023-03-19_final
2023-03-23 10:48:27	ga_ls8c_ard_3-2-1_105073_2023-03-23_final
2023-03-23 10:51:14	ga_ls8c_ard_3-2-1_105080_2023-03-23_final
2023-03-25 10:38:04	ga_ls8c_ard_3-2-1_103078_2023-03-25_final
2023-03-28 11:09:45	ga_ls8c_ard_3-2-1_108080_2023-03-28_final
2023-03-29 10:11:20	ga_ls8c_ard_3-2-1_099073_2023-03-29_final
2023-04-04 09:39:21	ga_ls8c_ard_3-2-1_093086_2023-04-04_final
2023-05-04 11:29:31	ga_ls8c_ard_3-2-1_111084_2023-05-04_final
2023-05-13 09:42:18	ga_ls8c_ard_3-2-1_094079_2023-05-13_final
2023-05-22 09:32:56	ga_ls8c_ard_3-2-1_093071_2023-05-22_final
2023-05-27 11:31:11	ga_ls8c_ard_3-2-1_112073_2023-05-27_final
2023-05-31 11:04:52	ga_ls8c_ard_3-2-1_108069_2023-05-31_final
2023-06-02 09:17:12	ga_ls8c_ard_3-2-1_090078_2023-06-01_final
2023-06-02 10:53:42	ga_ls8c_ard_3-2-1_106072_2023-06-02_final
2023-06-08 10:19:30	ga_ls8c_ard_3-2-1_100079_2023-06-08_final
2023-06-09 10:59:59	ga_ls8c_ard_3-2-1_107072_2023-06-09_final
2023-06-12 09:54:49	ga_ls8c_ard_3-2-1_096079_2023-06-12_final
2023-06-12 09:55:37	ga_ls8c_ard_3-2-1_096081_2023-06-12_final
2023-06-16 09:30:07	ga_ls8c_ard_3-2-1_092079_2023-06-16_final
2023-06-16 09:32:31	ga_ls8c_ard_3-2-1_092085_2023-06-16_final
2023-06-16 11:09:00	ga_ls8c_ard_3-2-1_108079_2023-06-16_final
2023-06-18 09:19:22	ga_ls8c_ard_3-2-1_090083_2023-06-17_final
2023-06-21 09:45:28	ga_ls8c_ard_3-2-1_095071_2023-06-21_final
2023-06-30 11:22:41	ga_ls8c_ard_3-2-1_110082_2023-06-30_final
2023-07-13 10:48:18	ga_ls8c_ard_3-2-1_105073_2023-07-13_final
2023-07-14 09:53:05	ga_ls8c_ard_3-2-1_096074_2023-07-14_final
2023-07-20 09:18:47	ga_ls8c_ard_3-2-1_090081_2023-07-19_final
2023-07-29 09:12:20	ga_ls8c_ard_3-2-1_089080_2023-07-28_final
2023-08-02 10:23:44	ga_ls8c_ard_3-2-1_101073_2023-08-02_final
2023-08-03 09:30:30	ga_ls8c_ard_3-2-1_092079_2023-08-03_final
2023-08-08 09:49:03	ga_ls8c_ard_3-2-1_095079_2023-08-08_final
2023-08-08 09:49:51	ga_ls8c_ard_3-2-1_095081_2023-08-08_final
2023-08-24 11:26:29	ga_ls8c_ard_3-2-1_111075_2023-08-24_final
2023-09-08 10:43:12	ga_ls8c_ard_3-2-1_104075_2023-09-08_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