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
2023-07-27 11:03:09	ga_ls8c_ard_3-2-1_107079_2023-07-27_final
2023-07-30 09:54:48	ga_ls8c_ard_3-2-1_096078_2023-07-30_final
2023-07-30 11:31:41	ga_ls8c_ard_3-2-1_112073_2023-07-30_final
2023-07-31 10:36:53	ga_ls8c_ard_3-2-1_103075_2023-07-31_final
2023-08-01 09:42:03	ga_ls8c_ard_3-2-1_094077_2023-08-01_final
2023-08-01 09:42:27	ga_ls8c_ard_3-2-1_094078_2023-08-01_final
2023-08-01 09:43:15	ga_ls8c_ard_3-2-1_094080_2023-08-01_final
2023-08-01 11:18:57	ga_ls8c_ard_3-2-1_110072_2023-08-01_final
2023-08-01 11:21:21	ga_ls8c_ard_3-2-1_110078_2023-08-01_final
2023-08-01 11:21:44	ga_ls8c_ard_3-2-1_110079_2023-08-01_final
2023-08-03 09:30:30	ga_ls8c_ard_3-2-1_092079_2023-08-03_final
2023-08-05 09:18:09	ga_ls8c_ard_3-2-1_090079_2023-08-04_final
2023-08-08 09:51:03	ga_ls8c_ard_3-2-1_095084_2023-08-08_final
2023-08-08 11:27:32	ga_ls8c_ard_3-2-1_111078_2023-08-08_final
2023-08-08 11:27:56	ga_ls8c_ard_3-2-1_111079_2023-08-08_final
2023-08-11 10:18:21	ga_ls8c_ard_3-2-1_100075_2023-08-11_final
2023-08-11 10:20:45	ga_ls8c_ard_3-2-1_100081_2023-08-11_final
2023-08-14 10:46:55	ga_ls8c_ard_3-2-1_105069_2023-08-14_final
2023-08-15 09:55:41	ga_ls8c_ard_3-2-1_096080_2023-08-15_final
2023-08-16 10:36:58	ga_ls8c_ard_3-2-1_103075_2023-08-16_final
2023-08-17 09:42:33	ga_ls8c_ard_3-2-1_094078_2023-08-17_final
2023-08-17 11:19:03	ga_ls8c_ard_3-2-1_110072_2023-08-17_final
2023-08-17 11:21:26	ga_ls8c_ard_3-2-1_110078_2023-08-17_final
2023-08-19 11:06:42	ga_ls8c_ard_3-2-1_108072_2023-08-19_final
2023-08-19 11:08:42	ga_ls8c_ard_3-2-1_108077_2023-08-19_final
2023-08-21 09:18:40	ga_ls8c_ard_3-2-1_090080_2023-08-20_final
2023-08-22 09:57:57	ga_ls8c_ard_3-2-1_097070_2023-08-22_final
2023-08-22 11:39:14	ga_ls8c_ard_3-2-1_113076_2023-08-22_final
2023-08-23 10:42:49	ga_ls8c_ard_3-2-1_104074_2023-08-23_final
2023-08-24 09:48:47	ga_ls8c_ard_3-2-1_095078_2023-08-24_final
2023-08-24 11:28:04	ga_ls8c_ard_3-2-1_111079_2023-08-24_final
2023-08-26 11:12:56	ga_ls8c_ard_3-2-1_109072_2023-08-26_final
2023-08-26 11:15:43	ga_ls8c_ard_3-2-1_109079_2023-08-26_final
2023-08-28 09:24:29	ga_ls8c_ard_3-2-1_091079_2023-08-27_final
2023-08-28 11:00:10	ga_ls8c_ard_3-2-1_107071_2023-08-28_final
2023-08-31 11:32:40	ga_ls8c_ard_3-2-1_112075_2023-08-31_final
2023-08-31 11:33:52	ga_ls8c_ard_3-2-1_112078_2023-08-31_final
2023-08-31 11:34:39	ga_ls8c_ard_3-2-1_112080_2023-08-31_final
2023-09-03 10:24:40	ga_ls8c_ard_3-2-1_101075_2023-09-03_final
2023-09-03 10:26:16	ga_ls8c_ard_3-2-1_101079_2023-09-03_final
2023-09-04 09:30:38	ga_ls8c_ard_3-2-1_092079_2023-09-04_final
2023-09-04 09:35:02	ga_ls8c_ard_3-2-1_092090_2023-09-04_final
2023-09-06 09:17:52	ga_ls8c_ard_3-2-1_090078_2023-09-05_final
2023-09-06 10:58:44	ga_ls8c_ard_3-2-1_106083_2023-09-06_final
2023-09-08 10:45:36	ga_ls8c_ard_3-2-1_104081_2023-09-08_final
2023-09-09 09:46:48	ga_ls8c_ard_3-2-1_095073_2023-09-09_final
2023-09-09 09:48:47	ga_ls8c_ard_3-2-1_095078_2023-09-09_final
2023-09-09 09:49:59	ga_ls8c_ard_3-2-1_095081_2023-09-09_final
2023-09-11 11:15:20	ga_ls8c_ard_3-2-1_109078_2023-09-11_final
2023-09-11 11:15:44	ga_ls8c_ard_3-2-1_109079_2023-09-11_final
2023-09-15 09:12:58	ga_ls8c_ard_3-2-1_089081_2023-09-14_final
2023-09-18 11:19:11	ga_ls8c_ard_3-2-1_110072_2023-09-18_final
2023-09-20 09:30:44	ga_ls8c_ard_3-2-1_092079_2023-09-20_final
2023-09-20 11:06:25	ga_ls8c_ard_3-2-1_108071_2023-09-20_final
2023-09-20 11:08:49	ga_ls8c_ard_3-2-1_108077_2023-09-20_final
2023-09-24 10:46:06	ga_ls8c_ard_3-2-1_104082_2023-09-24_final
2023-09-27 11:15:50	ga_ls8c_ard_3-2-1_109079_2023-09-27_final
2023-09-30 11:45:33	ga_ls8c_ard_3-2-1_114076_2023-09-30_final
2023-10-02 11:32:47	ga_ls8c_ard_3-2-1_112075_2023-10-02_final
2023-10-03 10:38:46	ga_ls8c_ard_3-2-1_103079_2023-10-03_final
2023-10-04 11:22:01	ga_ls8c_ard_3-2-1_110079_2023-10-04_final
2023-10-04 11:23:37	ga_ls8c_ard_3-2-1_110083_2023-10-04_final
2023-10-05 10:22:48	ga_ls8c_ard_3-2-1_101070_2023-10-05_final
2023-10-06 11:09:15	ga_ls8c_ard_3-2-1_108078_2023-10-06_final
2023-10-07 11:52:56	ga_ls8c_ard_3-2-1_115079_2023-10-07_final
2023-10-08 09:18:50	ga_ls8c_ard_3-2-1_090080_2023-10-07_final
2023-10-09 11:38:36	ga_ls8c_ard_3-2-1_113074_2023-10-09_final
2023-10-09 11:39:24	ga_ls8c_ard_3-2-1_113076_2023-10-09_final
2023-10-09 11:40:11	ga_ls8c_ard_3-2-1_113078_2023-10-09_final
2023-10-10 10:45:46	ga_ls8c_ard_3-2-1_104081_2023-10-10_final
2023-10-11 11:29:02	ga_ls8c_ard_3-2-1_111081_2023-10-11_final
2023-10-12 10:33:01	ga_ls8c_ard_3-2-1_102080_2023-10-12_final
2023-10-14 10:21:28	ga_ls8c_ard_3-2-1_100082_2023-10-14_final
2023-10-15 09:24:38	ga_ls8c_ard_3-2-1_091079_2023-10-14_final
2023-10-15 11:00:20	ga_ls8c_ard_3-2-1_107071_2023-10-15_final
2023-10-16 11:47:11	ga_ls8c_ard_3-2-1_114080_2023-10-16_final
2023-10-17 10:48:46	ga_ls8c_ard_3-2-1_105073_2023-10-17_final
2023-10-19 10:37:11	ga_ls8c_ard_3-2-1_103075_2023-10-19_final
2023-10-22 11:08:54	ga_ls8c_ard_3-2-1_108077_2023-10-22_final
2023-10-28 10:31:28	ga_ls8c_ard_3-2-1_102076_2023-10-28_final
2023-10-28 10:31:52	ga_ls8c_ard_3-2-1_102077_2023-10-28_final
2023-10-28 10:33:04	ga_ls8c_ard_3-2-1_102080_2023-10-28_final
2023-10-29 11:13:33	ga_ls8c_ard_3-2-1_109073_2023-10-29_final
2023-10-29 11:15:56	ga_ls8c_ard_3-2-1_109079_2023-10-29_final
2023-10-31 09:24:42	ga_ls8c_ard_3-2-1_091079_2023-10-30_final
2023-11-01 10:03:34	ga_ls8c_ard_3-2-1_098068_2023-11-01_final
2023-11-01 11:47:14	ga_ls8c_ard_3-2-1_114080_2023-11-01_final
2023-11-02 10:50:25	ga_ls8c_ard_3-2-1_105077_2023-11-02_final
2023-11-05 11:21:42	ga_ls8c_ard_3-2-1_110078_2023-11-05_final
2023-11-10 10:02:04	ga_ls8c_ard_3-2-1_097080_2023-11-10_final
2023-11-12 11:28:14	ga_ls8c_ard_3-2-1_111079_2023-11-12_final
2023-11-15 10:22:17	ga_ls8c_ard_3-2-1_100084_2023-11-15_final
2023-11-18 10:50:49	ga_ls8c_ard_3-2-1_105078_2023-11-18_final
2023-11-19 11:33:18	ga_ls8c_ard_3-2-1_112076_2023-11-19_final
2023-11-19 11:34:29	ga_ls8c_ard_3-2-1_112079_2023-11-19_final
2023-11-21 09:43:39	ga_ls8c_ard_3-2-1_094080_2023-11-21_final
2023-11-21 11:18:57	ga_ls8c_ard_3-2-1_110071_2023-11-21_final
2023-11-21 11:22:56	ga_ls8c_ard_3-2-1_110081_2023-11-21_final
2023-11-22 10:26:31	ga_ls8c_ard_3-2-1_101079_2023-11-22_final
2023-11-23 09:33:18	ga_ls8c_ard_3-2-1_092085_2023-11-23_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