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
2022-01-04 09:32:06	ga_ls8c_ard_3-2-1_092082_2022-01-04_final
2022-01-04 11:06:12	ga_ls8c_ard_3-2-1_108070_2022-01-04_final
2022-01-05 11:53:27	ga_ls8c_ard_3-2-1_115080_2022-01-05_final
2022-01-12 10:21:56	ga_ls8c_ard_3-2-1_100083_2022-01-12_final
2022-01-13 09:27:06	ga_ls8c_ard_3-2-1_091085_2022-01-12_final
2022-01-13 09:28:42	ga_ls8c_ard_3-2-1_091089_2022-01-12_final
2022-01-19 10:24:53	ga_ls8c_ard_3-2-1_101075_2022-01-19_final
2022-01-22 10:55:46	ga_ls8c_ard_3-2-1_106075_2022-01-22_final
2022-01-28 11:57:55	ga_ls8c_ard_3-2-1_116076_2022-01-28_final
2022-01-29 09:28:12	ga_ls8c_ard_3-2-1_091088_2022-01-28_final
2022-02-01 11:36:00	ga_ls8c_ard_3-2-1_112083_2022-02-01_final
2022-02-05 11:06:53	ga_ls8c_ard_3-2-1_108072_2022-02-05_final
2022-02-16 10:47:28	ga_ls8c_ard_3-2-1_105070_2022-02-16_final
2022-02-16 10:48:40	ga_ls8c_ard_3-2-1_105073_2022-02-16_final
2022-02-24 11:40:52	ga_ls8c_ard_3-2-1_113080_2022-02-24_final
2022-02-24 11:42:04	ga_ls8c_ard_3-2-1_113083_2022-02-24_final
2022-02-26 09:47:14	ga_ls8c_ard_3-2-1_095074_2022-02-26_final
2022-03-02 09:23:42	ga_ls8c_ard_3-2-1_091077_2022-03-01_final
2022-03-02 09:25:17	ga_ls8c_ard_3-2-1_091081_2022-03-01_final
2022-03-02 11:00:11	ga_ls8c_ard_3-2-1_107071_2022-03-02_final
2022-03-07 11:18:42	ga_ls8c_ard_3-2-1_110071_2022-03-07_final
2022-03-07 11:23:06	ga_ls8c_ard_3-2-1_110082_2022-03-07_final
2022-03-12 11:42:00	ga_ls8c_ard_3-2-1_113083_2022-03-12_final
2022-03-19 11:44:55	ga_ls8c_ard_3-2-1_114075_2022-03-19_final
2022-03-23 09:46:03	ga_ls8c_ard_3-2-1_094087_2022-03-23_final
2022-03-30 09:51:44	ga_ls8c_ard_3-2-1_095086_2022-03-30_final
2022-04-03 09:28:12	ga_ls8c_ard_3-2-1_091089_2022-04-02_final
2022-04-03 11:04:41	ga_ls8c_ard_3-2-1_107083_2022-04-03_final
2022-04-16 10:33:30	ga_ls8c_ard_3-2-1_102082_2022-04-16_final
2022-04-21 09:16:19	ga_ls8c_ard_3-2-1_089090_2022-04-20_final
2022-04-28 09:20:51	ga_ls8c_ard_3-2-1_090086_2022-04-27_final
2022-05-05 11:01:12	ga_ls8c_ard_3-2-1_107074_2022-05-05_final
2022-05-06 10:09:59	ga_ls8c_ard_3-2-1_098085_2022-05-06_final
2022-05-17 09:51:32	ga_ls8c_ard_3-2-1_095085_2022-05-17_final
2022-05-18 10:30:24	ga_ls8c_ard_3-2-1_102074_2022-05-18_final
2022-05-22 10:08:05	ga_ls8c_ard_3-2-1_098080_2022-05-22_final
2022-05-22 11:44:58	ga_ls8c_ard_3-2-1_114075_2022-05-22_final
2022-05-24 11:35:48	ga_ls8c_ard_3-2-1_112083_2022-05-24_final
2022-05-28 09:32:58	ga_ls8c_ard_3-2-1_092085_2022-05-28_final
2022-05-30 10:53:33	ga_ls8c_ard_3-2-1_106070_2022-05-30_final
2022-05-30 10:53:57	ga_ls8c_ard_3-2-1_106071_2022-05-30_final
2022-06-02 11:30:05	ga_ls8c_ard_3-2-1_111084_2022-06-02_final
2022-06-13 11:07:18	ga_ls8c_ard_3-2-1_108073_2022-06-13_final
2022-06-15 10:53:46	ga_ls8c_ard_3-2-1_106070_2022-06-15_final
2022-06-22 09:25:30	ga_ls8c_ard_3-2-1_091081_2022-06-21_final
2022-06-22 09:26:41	ga_ls8c_ard_3-2-1_091084_2022-06-21_final
2022-06-24 09:16:20	ga_ls8c_ard_3-2-1_089089_2022-06-23_final
2022-07-03 09:06:35	ga_ls8c_ard_3-2-1_088080_2022-07-02_final
2022-07-13 09:46:02	ga_ls8c_ard_3-2-1_094086_2022-07-13_final
2022-07-26 10:46:58	ga_ls8c_ard_3-2-1_105068_2022-07-26_final
2022-08-04 09:06:47	ga_ls8c_ard_3-2-1_088080_2022-08-03_final
2022-08-05 11:25:45	ga_ls8c_ard_3-2-1_111072_2022-08-05_final
2022-08-10 10:08:14	ga_ls8c_ard_3-2-1_098079_2022-08-10_final
2022-08-11 09:12:37	ga_ls8c_ard_3-2-1_089079_2022-08-10_final
2022-08-21 11:25:49	ga_ls8c_ard_3-2-1_111072_2022-08-21_final
2022-08-21 11:26:37	ga_ls8c_ard_3-2-1_111074_2022-08-21_final
2022-08-30 11:20:26	ga_ls8c_ard_3-2-1_110074_2022-08-30_final
2022-09-01 11:07:40	ga_ls8c_ard_3-2-1_108073_2022-09-01_final
2022-09-07 10:29:50	ga_ls8c_ard_3-2-1_102071_2022-09-07_final
2022-09-15 11:20:08	ga_ls8c_ard_3-2-1_110073_2022-09-15_final
2022-09-17 11:06:59	ga_ls8c_ard_3-2-1_108071_2022-09-17_final
2022-09-23 10:29:31	ga_ls8c_ard_3-2-1_102070_2022-09-23_final
2022-09-23 10:29:55	ga_ls8c_ard_3-2-1_102071_2022-09-23_final
2022-10-01 09:46:03	ga_ls8c_ard_3-2-1_094085_2022-10-01_final
2022-10-01 09:46:27	ga_ls8c_ard_3-2-1_094086_2022-10-01_final
2022-10-21 10:54:34	ga_ls8c_ard_3-2-1_106071_2022-10-21_final
2022-10-21 10:54:58	ga_ls8c_ard_3-2-1_106072_2022-10-21_final
2022-11-02 09:41:40	ga_ls8c_ard_3-2-1_094074_2022-11-02_final
2022-11-05 11:52:15	ga_ls8c_ard_3-2-1_115076_2022-11-05_final
2022-11-08 10:45:03	ga_ls8c_ard_3-2-1_104078_2022-11-08_final
2022-11-09 09:47:49	ga_ls8c_ard_3-2-1_095074_2022-11-09_final
2022-11-13 09:23:51	ga_ls8c_ard_3-2-1_091076_2022-11-12_final
2022-11-14 10:04:19	ga_ls8c_ard_3-2-1_098069_2022-11-14_final
2022-11-16 09:52:43	ga_ls8c_ard_3-2-1_096071_2022-11-16_final
2022-11-19 10:26:00	ga_ls8c_ard_3-2-1_101077_2022-11-19_final
2022-11-20 09:31:59	ga_ls8c_ard_3-2-1_092081_2022-11-20_final
2022-11-30 10:05:54	ga_ls8c_ard_3-2-1_098073_2022-11-30_final
2022-12-02 11:36:25	ga_ls8c_ard_3-2-1_112083_2022-12-02_final
2022-12-06 09:34:48	ga_ls8c_ard_3-2-1_092088_2022-12-06_final
2022-12-06 11:06:30	ga_ls8c_ard_3-2-1_108070_2022-12-06_final
2022-12-15 09:26:34	ga_ls8c_ard_3-2-1_091083_2022-12-14_final
2022-12-20 09:45:50	ga_ls8c_ard_3-2-1_094085_2022-12-20_final
2023-01-09 09:19:53	ga_ls8c_ard_3-2-1_090082_2023-01-08_final
2023-01-11 10:44:00	ga_ls8c_ard_3-2-1_104076_2023-01-11_final
2023-01-26 09:58:44	ga_ls8c_ard_3-2-1_097071_2023-01-26_final
2023-01-31 10:20:05	ga_ls8c_ard_3-2-1_100078_2023-01-31_final
2023-02-06 11:19:05	ga_ls8c_ard_3-2-1_110071_2023-02-06_final
2023-02-07 10:27:50	ga_ls8c_ard_3-2-1_101082_2023-02-07_final
2023-02-17 09:28:18	ga_ls8c_ard_3-2-1_091088_2023-02-16_final
2023-02-17 11:02:24	ga_ls8c_ard_3-2-1_107076_2023-02-17_final
2023-02-20 09:52:22	ga_ls8c_ard_3-2-1_096071_2023-02-20_final
2023-03-14 09:22:15	ga_ls8c_ard_3-2-1_090089_2023-03-13_final
2023-04-06 11:04:38	ga_ls8c_ard_3-2-1_107083_2023-04-06_final
2023-04-13 09:32:13	ga_ls8c_ard_3-2-1_092084_2023-04-13_final
2023-04-24 10:51:43	ga_ls8c_ard_3-2-1_105082_2023-04-24_final
2023-04-26 10:37:45	ga_ls8c_ard_3-2-1_103078_2023-04-26_final
2023-05-04 11:29:07	ga_ls8c_ard_3-2-1_111083_2023-05-04_final
2023-05-08 09:25:51	ga_ls8c_ard_3-2-1_091084_2023-05-07_final
2023-05-09 11:46:23	ga_ls8c_ard_3-2-1_114080_2023-05-09_final
2023-05-16 11:50:52	ga_ls8c_ard_3-2-1_115076_2023-05-16_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