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
2020-10-21 08:42:45	ga_ls8c_ard_3-2-1_084082_2020-10-20_final
2022-04-20 11:44:51	ga_ls8c_ard_3-2-1_114075_2022-04-20_final
2022-04-29 11:41:48	ga_ls8c_ard_3-2-1_113083_2022-04-29_final
2022-05-20 10:21:14	ga_ls8c_ard_3-2-1_100082_2022-05-20_final
2022-05-25 10:34:59	ga_ls8c_ard_3-2-1_103070_2022-05-25_final
2022-06-18 11:26:41	ga_ls8c_ard_3-2-1_111075_2022-06-18_final
2022-07-16 11:51:49	ga_ls8c_ard_3-2-1_115076_2022-07-16_final
2022-07-18 10:03:24	ga_ls8c_ard_3-2-1_097083_2022-07-18_final
2022-07-20 09:47:29	ga_ls8c_ard_3-2-1_095074_2022-07-20_final
2022-07-25 10:04:06	ga_ls8c_ard_3-2-1_098069_2022-07-25_final
2022-08-02 10:57:37	ga_ls8c_ard_3-2-1_106079_2022-08-02_final
2022-08-05 09:47:40	ga_ls8c_ard_3-2-1_095074_2022-08-05_final
2022-08-07 11:17:00	ga_ls8c_ard_3-2-1_109081_2022-08-07_final
2022-08-12 11:36:22	ga_ls8c_ard_3-2-1_112083_2022-08-12_final
2022-08-15 10:24:24	ga_ls8c_ard_3-2-1_101073_2022-08-15_final
2022-08-17 10:15:15	ga_ls8c_ard_3-2-1_099081_2022-08-17_final
2022-08-19 11:41:22	ga_ls8c_ard_3-2-1_113080_2022-08-19_final
2022-08-21 11:29:49	ga_ls8c_ard_3-2-1_111082_2022-08-21_final
2022-09-01 11:07:16	ga_ls8c_ard_3-2-1_108072_2022-09-01_final
2022-09-08 11:13:06	ga_ls8c_ard_3-2-1_109071_2022-09-08_final
2022-09-24 09:39:53	ga_ls8c_ard_3-2-1_093085_2022-09-24_final
2022-10-01 09:42:51	ga_ls8c_ard_3-2-1_094077_2022-10-01_final
2022-10-03 11:06:58	ga_ls8c_ard_3-2-1_108071_2022-10-03_final
2022-10-10 11:13:29	ga_ls8c_ard_3-2-1_109072_2022-10-10_final
2022-10-14 10:50:42	ga_ls8c_ard_3-2-1_105077_2022-10-14_final
2022-10-17 09:44:21	ga_ls8c_ard_3-2-1_094081_2022-10-17_final
2022-10-21 10:57:22	ga_ls8c_ard_3-2-1_106078_2022-10-21_final
2022-10-28 09:26:18	ga_ls8c_ard_3-2-1_091082_2022-10-27_final
2022-10-30 10:53:14	ga_ls8c_ard_3-2-1_105083_2022-10-30_final
2022-11-13 09:25:03	ga_ls8c_ard_3-2-1_091079_2022-11-12_final
2022-11-14 11:46:23	ga_ls8c_ard_3-2-1_114077_2022-11-14_final
2022-11-27 11:17:29	ga_ls8c_ard_3-2-1_109082_2022-11-27_final
2022-11-30 10:06:18	ga_ls8c_ard_3-2-1_098074_2022-11-30_final
2022-11-30 11:45:59	ga_ls8c_ard_3-2-1_114076_2022-11-30_final
2022-12-03 10:36:48	ga_ls8c_ard_3-2-1_103073_2022-12-03_final
2022-12-04 11:18:52	ga_ls8c_ard_3-2-1_110070_2022-12-04_final
2022-12-16 10:07:25	ga_ls8c_ard_3-2-1_098077_2022-12-16_final
2022-12-17 10:48:16	ga_ls8c_ard_3-2-1_105071_2022-12-17_final
2022-12-26 09:07:56	ga_ls8c_ard_3-2-1_088083_2022-12-25_final
2022-12-28 10:33:40	ga_ls8c_ard_3-2-1_102081_2022-12-28_final
2023-01-06 10:25:29	ga_ls8c_ard_3-2-1_101076_2023-01-06_final
2023-01-14 09:40:22	ga_ls8c_ard_3-2-1_093087_2023-01-14_final
2023-01-23 11:10:41	ga_ls8c_ard_3-2-1_108081_2023-01-23_final
2023-01-24 10:16:40	ga_ls8c_ard_3-2-1_099085_2023-01-24_final
2023-02-03 09:14:30	ga_ls8c_ard_3-2-1_089084_2023-02-02_final
2023-02-03 10:50:35	ga_ls8c_ard_3-2-1_105077_2023-02-03_final
2023-02-09 10:15:04	ga_ls8c_ard_3-2-1_099081_2023-02-09_final
2023-02-13 09:51:53	ga_ls8c_ard_3-2-1_095085_2023-02-13_final
2023-02-23 10:25:11	ga_ls8c_ard_3-2-1_101076_2023-02-23_final
2023-02-27 11:40:30	ga_ls8c_ard_3-2-1_113079_2023-02-27_final
2023-02-28 10:41:17	ga_ls8c_ard_3-2-1_104070_2023-02-28_final
2023-03-13 11:53:10	ga_ls8c_ard_3-2-1_115080_2023-03-13_final
2023-03-15 11:41:36	ga_ls8c_ard_3-2-1_113082_2023-03-15_final
2023-03-30 09:19:18	ga_ls8c_ard_3-2-1_090082_2023-03-29_final
2023-04-20 11:16:01	ga_ls8c_ard_3-2-1_109081_2023-04-20_final
2023-05-08 09:23:03	ga_ls8c_ard_3-2-1_091077_2023-05-07_final
2023-05-12 10:35:56	ga_ls8c_ard_3-2-1_103074_2023-05-12_final
2023-05-23 10:20:36	ga_ls8c_ard_3-2-1_100082_2023-05-23_final
2023-05-26 09:13:49	ga_ls8c_ard_3-2-1_089085_2023-05-25_final
2023-05-27 11:33:58	ga_ls8c_ard_3-2-1_112080_2023-05-27_final
2023-05-28 10:33:58	ga_ls8c_ard_3-2-1_103069_2023-05-28_final
2023-06-08 10:17:06	ga_ls8c_ard_3-2-1_100073_2023-06-08_final
2023-06-13 10:36:05	ga_ls8c_ard_3-2-1_103074_2023-06-13_final
2023-06-14 11:22:09	ga_ls8c_ard_3-2-1_110081_2023-06-14_final
2023-06-24 10:19:59	ga_ls8c_ard_3-2-1_100080_2023-06-24_final
2023-07-12 11:46:43	ga_ls8c_ard_3-2-1_114080_2023-07-12_final
2023-07-13 10:48:18	ga_ls8c_ard_3-2-1_105073_2023-07-13_final
2023-07-25 11:12:18	ga_ls8c_ard_3-2-1_109071_2023-07-25_final
2023-08-09 10:29:07	ga_ls8c_ard_3-2-1_102071_2023-08-09_final
2023-08-12 11:00:50	ga_ls8c_ard_3-2-1_107073_2023-08-12_final
2023-08-24 09:47:12	ga_ls8c_ard_3-2-1_095074_2023-08-24_final
2023-09-15 10:51:51	ga_ls8c_ard_3-2-1_105081_2023-09-15_final
2023-09-22 09:19:34	ga_ls8c_ard_3-2-1_090082_2023-09-21_final
2023-09-27 11:16:38	ga_ls8c_ard_3-2-1_109081_2023-09-27_final
2023-10-01 10:47:32	ga_ls8c_ard_3-2-1_105070_2023-10-01_final
2023-10-07 10:12:03	ga_ls8c_ard_3-2-1_099074_2023-10-07_final
2023-10-11 11:25:03	ga_ls8c_ard_3-2-1_111071_2023-10-11_final
2023-10-15 11:03:31	ga_ls8c_ard_3-2-1_107079_2023-10-15_final
2023-10-16 11:47:11	ga_ls8c_ard_3-2-1_114080_2023-10-16_final
2023-10-20 09:45:09	ga_ls8c_ard_3-2-1_094084_2023-10-20_final
2023-10-22 11:06:55	ga_ls8c_ard_3-2-1_108072_2023-10-22_final
2023-10-25 11:41:26	ga_ls8c_ard_3-2-1_113081_2023-10-25_final
2023-10-29 11:13:09	ga_ls8c_ard_3-2-1_109072_2023-10-29_final
2023-11-04 10:38:03	ga_ls8c_ard_3-2-1_103077_2023-11-04_final
2023-11-14 11:16:42	ga_ls8c_ard_3-2-1_109081_2023-11-14_final
2023-11-20 10:39:16	ga_ls8c_ard_3-2-1_103080_2023-11-20_final
2023-11-21 11:22:08	ga_ls8c_ard_3-2-1_110079_2023-11-21_final
2023-11-29 10:32:41	ga_ls8c_ard_3-2-1_102079_2023-11-29_final
2023-12-01 10:18:42	ga_ls8c_ard_3-2-1_100075_2023-12-01_final
2024-01-02 10:18:37	ga_ls8c_ard_3-2-1_100075_2024-01-02_final
2024-01-19 11:03:52	ga_ls8c_ard_3-2-1_107080_2024-01-19_final
2024-01-28 10:57:12	ga_ls8c_ard_3-2-1_106079_2024-01-28_final
2024-02-01 10:31:19	ga_ls8c_ard_3-2-1_102076_2024-02-01_final
2024-02-05 10:06:14	ga_ls8c_ard_3-2-1_098075_2024-02-05_final
2024-02-07 11:34:46	ga_ls8c_ard_3-2-1_112080_2024-02-07_final
2024-03-05 09:35:08	ga_ls8c_ard_3-2-1_093075_2024-03-05_final
2024-03-10 09:54:50	ga_ls8c_ard_3-2-1_096078_2024-03-10_final
2024-03-10 11:34:07	ga_ls8c_ard_3-2-1_112079_2024-03-10_final
2024-03-13 10:24:07	ga_ls8c_ard_3-2-1_101074_2024-03-13_final
2024-03-26 11:34:17	ga_ls8c_ard_3-2-1_112080_2024-03-26_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