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
2022-08-21 09:52:08	ga_ls8c_ard_3-2-1_095085_2022-08-21_final
2022-08-22 10:29:00	ga_ls8c_ard_3-2-1_102069_2022-08-22_final
2022-08-23 09:36:11	ga_ls8c_ard_3-2-1_093076_2022-08-23_final
2022-08-23 09:37:22	ga_ls8c_ard_3-2-1_093079_2022-08-23_final
2022-09-03 10:54:55	ga_ls8c_ard_3-2-1_106072_2022-09-03_final
2022-09-15 11:22:56	ga_ls8c_ard_3-2-1_110080_2022-09-15_final
2022-09-19 09:18:09	ga_ls8c_ard_3-2-1_090077_2022-09-18_final
2022-09-20 10:00:13	ga_ls8c_ard_3-2-1_097074_2022-09-20_final
2022-09-27 10:08:47	ga_ls8c_ard_3-2-1_098080_2022-09-27_final
2022-09-28 10:53:14	ga_ls8c_ard_3-2-1_105083_2022-09-28_final
2022-09-30 10:38:53	ga_ls8c_ard_3-2-1_103078_2022-09-30_final
2022-10-04 11:52:13	ga_ls8c_ard_3-2-1_115076_2022-10-04_final
2022-10-05 10:58:11	ga_ls8c_ard_3-2-1_106080_2022-10-05_final
2022-10-06 10:02:33	ga_ls8c_ard_3-2-1_097080_2022-10-06_final
2022-10-14 10:47:54	ga_ls8c_ard_3-2-1_105070_2022-10-14_final
2022-10-14 10:53:05	ga_ls8c_ard_3-2-1_105083_2022-10-14_final
2022-10-17 11:24:50	ga_ls8c_ard_3-2-1_110085_2022-10-17_final
2022-10-20 10:13:17	ga_ls8c_ard_3-2-1_099076_2022-10-20_final
2022-10-22 10:02:33	ga_ls8c_ard_3-2-1_097080_2022-10-22_final
2022-10-26 11:12:21	ga_ls8c_ard_3-2-1_109069_2022-10-26_final
2022-10-27 11:59:13	ga_ls8c_ard_3-2-1_116078_2022-10-27_final
2022-10-28 09:25:54	ga_ls8c_ard_3-2-1_091081_2022-10-27_final
2022-10-30 09:13:09	ga_ls8c_ard_3-2-1_089080_2022-10-29_final
2022-11-03 10:27:43	ga_ls8c_ard_3-2-1_101081_2022-11-03_final
2022-11-05 11:52:39	ga_ls8c_ard_3-2-1_115077_2022-11-05_final
2022-11-08 10:45:51	ga_ls8c_ard_3-2-1_104080_2022-11-08_final
2022-11-14 10:09:06	ga_ls8c_ard_3-2-1_098081_2022-11-14_final
2022-11-14 11:46:23	ga_ls8c_ard_3-2-1_114077_2022-11-14_final
2022-11-16 09:57:07	ga_ls8c_ard_3-2-1_096082_2022-11-16_final
2022-11-24 10:44:34	ga_ls8c_ard_3-2-1_104077_2022-11-24_final
2022-11-25 09:51:21	ga_ls8c_ard_3-2-1_095083_2022-11-25_final
2022-11-29 11:03:07	ga_ls8c_ard_3-2-1_107077_2022-11-29_final
2022-11-29 11:04:43	ga_ls8c_ard_3-2-1_107081_2022-11-29_final
2022-12-03 10:38:24	ga_ls8c_ard_3-2-1_103077_2022-12-03_final
2022-12-04 09:45:10	ga_ls8c_ard_3-2-1_094083_2022-12-04_final
2022-12-06 09:31:13	ga_ls8c_ard_3-2-1_092079_2022-12-06_final
2022-12-07 10:12:04	ga_ls8c_ard_3-2-1_099073_2022-12-07_final
2022-12-08 09:20:50	ga_ls8c_ard_3-2-1_090084_2022-12-07_final
2022-12-11 09:51:43	ga_ls8c_ard_3-2-1_095084_2022-12-11_final
2022-12-13 11:16:14	ga_ls8c_ard_3-2-1_109079_2022-12-13_final
2022-12-14 11:58:41	ga_ls8c_ard_3-2-1_116077_2022-12-14_final
2022-12-16 11:46:42	ga_ls8c_ard_3-2-1_114078_2022-12-16_final
2022-12-17 10:48:16	ga_ls8c_ard_3-2-1_105071_2022-12-17_final
2022-12-18 09:53:50	ga_ls8c_ard_3-2-1_096074_2022-12-18_final
2022-12-24 10:56:46	ga_ls8c_ard_3-2-1_106077_2022-12-24_final
2022-12-25 10:02:45	ga_ls8c_ard_3-2-1_097081_2022-12-25_final
2022-12-25 11:40:26	ga_ls8c_ard_3-2-1_113078_2022-12-25_final
2022-12-26 10:45:37	ga_ls8c_ard_3-2-1_104080_2022-12-26_final
2022-12-29 09:36:51	ga_ls8c_ard_3-2-1_093078_2022-12-29_final
2022-12-31 11:03:47	ga_ls8c_ard_3-2-1_107079_2022-12-31_final
2023-01-05 09:46:13	ga_ls8c_ard_3-2-1_094086_2023-01-05_final
2023-01-05 09:46:37	ga_ls8c_ard_3-2-1_094087_2023-01-05_final
2023-01-06 10:24:41	ga_ls8c_ard_3-2-1_101074_2023-01-06_final
2023-01-06 10:26:41	ga_ls8c_ard_3-2-1_101079_2023-01-06_final
2023-01-07 09:30:40	ga_ls8c_ard_3-2-1_092078_2023-01-07_final
2023-01-09 10:57:34	ga_ls8c_ard_3-2-1_106079_2023-01-09_final
2023-01-12 11:29:14	ga_ls8c_ard_3-2-1_111081_2023-01-12_final
2023-01-17 10:08:01	ga_ls8c_ard_3-2-1_098079_2023-01-17_final
2023-01-20 10:38:09	ga_ls8c_ard_3-2-1_103077_2023-01-20_final
2023-01-25 09:19:27	ga_ls8c_ard_3-2-1_090081_2023-01-24_final
2023-01-26 11:42:00	ga_ls8c_ard_3-2-1_113082_2023-01-26_final
2023-01-30 11:17:18	ga_ls8c_ard_3-2-1_109082_2023-01-30_final
2023-02-05 10:37:01	ga_ls8c_ard_3-2-1_103074_2023-02-05_final
2023-02-15 11:17:35	ga_ls8c_ard_3-2-1_109083_2023-02-15_final
2023-02-18 11:45:38	ga_ls8c_ard_3-2-1_114076_2023-02-18_final
2023-02-18 11:46:26	ga_ls8c_ard_3-2-1_114078_2023-02-18_final
2023-02-19 10:48:24	ga_ls8c_ard_3-2-1_105072_2023-02-19_final
2023-02-20 11:35:38	ga_ls8c_ard_3-2-1_112082_2023-02-20_final
2023-02-23 10:25:59	ga_ls8c_ard_3-2-1_101078_2023-02-23_final
2023-02-24 11:08:25	ga_ls8c_ard_3-2-1_108076_2023-02-24_final
2023-03-01 09:51:15	ga_ls8c_ard_3-2-1_095084_2023-03-01_final
2023-03-03 09:39:41	ga_ls8c_ard_3-2-1_093086_2023-03-03_final
2023-03-10 11:18:41	ga_ls8c_ard_3-2-1_110071_2023-03-10_final
2023-03-10 11:23:04	ga_ls8c_ard_3-2-1_110082_2023-03-10_final
2023-03-14 09:18:16	ga_ls8c_ard_3-2-1_090079_2023-03-13_final
2023-03-14 09:19:52	ga_ls8c_ard_3-2-1_090083_2023-03-13_final
2023-03-15 11:40:48	ga_ls8c_ard_3-2-1_113080_2023-03-15_final
2023-03-15 11:41:36	ga_ls8c_ard_3-2-1_113082_2023-03-15_final
2023-03-17 09:50:44	ga_ls8c_ard_3-2-1_095083_2023-03-17_final
2023-03-22 11:46:29	ga_ls8c_ard_3-2-1_114079_2023-03-22_final
2023-03-27 10:24:30	ga_ls8c_ard_3-2-1_101075_2023-03-27_final
2023-03-29 10:11:20	ga_ls8c_ard_3-2-1_099073_2023-03-29_final
2023-03-29 10:14:55	ga_ls8c_ard_3-2-1_099082_2023-03-29_final
2023-03-31 10:02:09	ga_ls8c_ard_3-2-1_097081_2023-03-31_final
2023-04-07 11:45:53	ga_ls8c_ard_3-2-1_114078_2023-04-07_final
2023-04-08 09:13:21	ga_ls8c_ard_3-2-1_089083_2023-04-07_final
2023-04-11 11:23:03	ga_ls8c_ard_3-2-1_110083_2023-04-11_final
2023-04-16 11:40:47	ga_ls8c_ard_3-2-1_113081_2023-04-16_final
2023-04-18 09:50:43	ga_ls8c_ard_3-2-1_095084_2023-04-18_final
2023-04-19 10:29:59	ga_ls8c_ard_3-2-1_102074_2023-04-19_final
2023-05-01 09:17:22	ga_ls8c_ard_3-2-1_090078_2023-04-30_final
2023-05-04 09:51:02	ga_ls8c_ard_3-2-1_095085_2023-05-04_final
2023-05-04 11:29:31	ga_ls8c_ard_3-2-1_111084_2023-05-04_final
2023-05-10 09:13:51	ga_ls8c_ard_3-2-1_089085_2023-05-09_final
2023-05-13 09:44:18	ga_ls8c_ard_3-2-1_094084_2023-05-13_final
2023-05-13 09:44:42	ga_ls8c_ard_3-2-1_094085_2023-05-13_final
2023-05-17 10:53:38	ga_ls8c_ard_3-2-1_106072_2023-05-17_final
2023-05-23 10:17:00	ga_ls8c_ard_3-2-1_100073_2023-05-23_final
2023-05-23 10:17:24	ga_ls8c_ard_3-2-1_100074_2023-05-23_final
2023-05-24 11:03:52	ga_ls8c_ard_3-2-1_107082_2023-05-24_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