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
2022-03-04 09:10:08	ga_ls8c_ard_3-2-1_089074_2022-03-03_final
2022-03-04 10:48:13	ga_ls8c_ard_3-2-1_105072_2022-03-04_final
2022-03-04 10:49:25	ga_ls8c_ard_3-2-1_105075_2022-03-04_final
2022-03-04 10:49:49	ga_ls8c_ard_3-2-1_105076_2022-03-04_final
2022-03-04 10:50:37	ga_ls8c_ard_3-2-1_105078_2022-03-04_final
2022-03-04 10:51:48	ga_ls8c_ard_3-2-1_105081_2022-03-04_final
2022-03-04 10:52:12	ga_ls8c_ard_3-2-1_105082_2022-03-04_final
2022-03-05 09:54:35	ga_ls8c_ard_3-2-1_096077_2022-03-05_final
2022-03-05 09:54:59	ga_ls8c_ard_3-2-1_096078_2022-03-05_final
2022-03-05 09:55:23	ga_ls8c_ard_3-2-1_096079_2022-03-05_final
2022-03-05 09:57:23	ga_ls8c_ard_3-2-1_096084_2022-03-05_final
2022-03-05 11:32:40	ga_ls8c_ard_3-2-1_112075_2022-03-05_final
2022-03-05 11:35:28	ga_ls8c_ard_3-2-1_112082_2022-03-05_final
2022-03-06 10:35:51	ga_ls8c_ard_3-2-1_103072_2022-03-06_final
2022-03-07 09:41:49	ga_ls8c_ard_3-2-1_094076_2022-03-07_final
2022-03-07 09:42:37	ga_ls8c_ard_3-2-1_094078_2022-03-07_final
2022-03-07 09:45:24	ga_ls8c_ard_3-2-1_094085_2022-03-07_final
2022-03-07 11:17:54	ga_ls8c_ard_3-2-1_110069_2022-03-07_final
2022-03-07 11:18:18	ga_ls8c_ard_3-2-1_110070_2022-03-07_final
2022-03-07 11:19:54	ga_ls8c_ard_3-2-1_110074_2022-03-07_final
2022-03-07 11:21:54	ga_ls8c_ard_3-2-1_110079_2022-03-07_final
2022-03-07 11:23:30	ga_ls8c_ard_3-2-1_110083_2022-03-07_final
2022-03-08 10:25:28	ga_ls8c_ard_3-2-1_101077_2022-03-08_final
2022-03-08 10:26:16	ga_ls8c_ard_3-2-1_101079_2022-03-08_final
2022-03-08 10:26:40	ga_ls8c_ard_3-2-1_101080_2022-03-08_final
2022-03-08 10:27:04	ga_ls8c_ard_3-2-1_101081_2022-03-08_final
2022-03-09 09:27:27	ga_ls8c_ard_3-2-1_092071_2022-03-08_final
2022-03-09 09:33:26	ga_ls8c_ard_3-2-1_092086_2022-03-09_final
2022-03-09 11:07:08	ga_ls8c_ard_3-2-1_108073_2022-03-09_final
2022-03-09 11:08:44	ga_ls8c_ard_3-2-1_108077_2022-03-09_final
2022-03-09 11:09:55	ga_ls8c_ard_3-2-1_108080_2022-03-09_final
2022-03-10 10:09:06	ga_ls8c_ard_3-2-1_099067_2022-03-10_final
2022-03-10 10:10:18	ga_ls8c_ard_3-2-1_099070_2022-03-10_final
2022-03-10 11:51:11	ga_ls8c_ard_3-2-1_115075_2022-03-10_final
2022-03-11 09:19:52	ga_ls8c_ard_3-2-1_090083_2022-03-10_final
2022-03-11 09:21:28	ga_ls8c_ard_3-2-1_090087_2022-03-10_final
2022-03-11 10:53:10	ga_ls8c_ard_3-2-1_106069_2022-03-11_final
2022-03-11 10:54:45	ga_ls8c_ard_3-2-1_106073_2022-03-11_final
2022-03-11 10:55:09	ga_ls8c_ard_3-2-1_106074_2022-03-11_final
2022-03-11 10:56:21	ga_ls8c_ard_3-2-1_106077_2022-03-11_final
2022-03-11 10:57:33	ga_ls8c_ard_3-2-1_106080_2022-03-11_final
2022-03-12 09:56:44	ga_ls8c_ard_3-2-1_097067_2022-03-12_final
2022-03-12 09:57:32	ga_ls8c_ard_3-2-1_097069_2022-03-12_final
2022-03-12 09:57:56	ga_ls8c_ard_3-2-1_097070_2022-03-12_final
2022-03-12 09:59:31	ga_ls8c_ard_3-2-1_097074_2022-03-12_final
2022-03-12 10:03:07	ga_ls8c_ard_3-2-1_097083_2022-03-12_final
2022-03-12 11:37:37	ga_ls8c_ard_3-2-1_113072_2022-03-12_final
2022-03-12 11:38:01	ga_ls8c_ard_3-2-1_113073_2022-03-12_final
2022-03-12 11:38:48	ga_ls8c_ard_3-2-1_113075_2022-03-12_final
2022-03-12 11:40:00	ga_ls8c_ard_3-2-1_113078_2022-03-12_final
2022-03-12 11:41:12	ga_ls8c_ard_3-2-1_113081_2022-03-12_final
2022-03-13 10:43:35	ga_ls8c_ard_3-2-1_104076_2022-03-13_final
2022-03-13 10:44:22	ga_ls8c_ard_3-2-1_104078_2022-03-13_final
2022-03-13 10:45:34	ga_ls8c_ard_3-2-1_104081_2022-03-13_final
2022-03-14 09:45:57	ga_ls8c_ard_3-2-1_095071_2022-03-14_final
2022-03-14 11:24:02	ga_ls8c_ard_3-2-1_111069_2022-03-14_final
2022-03-14 11:25:38	ga_ls8c_ard_3-2-1_111073_2022-03-14_final
2022-03-14 11:27:38	ga_ls8c_ard_3-2-1_111078_2022-03-14_final
2022-03-14 11:30:01	ga_ls8c_ard_3-2-1_111084_2022-03-14_final
2022-03-15 10:28:00	ga_ls8c_ard_3-2-1_102068_2022-03-15_final
2022-03-15 10:29:36	ga_ls8c_ard_3-2-1_102072_2022-03-15_final
2022-03-15 10:30:24	ga_ls8c_ard_3-2-1_102074_2022-03-15_final
2022-03-15 10:30:48	ga_ls8c_ard_3-2-1_102075_2022-03-15_final
2022-03-15 10:31:12	ga_ls8c_ard_3-2-1_102076_2022-03-15_final
2022-03-15 10:32:00	ga_ls8c_ard_3-2-1_102078_2022-03-15_final
2022-03-16 09:34:46	ga_ls8c_ard_3-2-1_093074_2022-03-16_final
2022-03-16 09:35:34	ga_ls8c_ard_3-2-1_093076_2022-03-16_final
2022-03-16 09:36:22	ga_ls8c_ard_3-2-1_093078_2022-03-16_final
2022-03-16 09:36:46	ga_ls8c_ard_3-2-1_093079_2022-03-16_final
2022-03-16 09:37:34	ga_ls8c_ard_3-2-1_093081_2022-03-16_final
2022-03-16 09:39:33	ga_ls8c_ard_3-2-1_093086_2022-03-16_final
2022-03-16 11:11:39	ga_ls8c_ard_3-2-1_109069_2022-03-16_final
2022-03-16 11:13:15	ga_ls8c_ard_3-2-1_109073_2022-03-16_final
2022-03-16 11:13:39	ga_ls8c_ard_3-2-1_109074_2022-03-16_final
2022-03-16 11:15:39	ga_ls8c_ard_3-2-1_109079_2022-03-16_final
2022-03-16 11:16:03	ga_ls8c_ard_3-2-1_109080_2022-03-16_final
2022-03-16 11:17:14	ga_ls8c_ard_3-2-1_109083_2022-03-16_final
2022-03-17 10:18:01	ga_ls8c_ard_3-2-1_100074_2022-03-17_final
2022-03-17 10:19:37	ga_ls8c_ard_3-2-1_100078_2022-03-17_final
2022-03-17 10:20:25	ga_ls8c_ard_3-2-1_100080_2022-03-17_final
2022-03-17 10:20:49	ga_ls8c_ard_3-2-1_100081_2022-03-17_final
2022-03-17 10:21:13	ga_ls8c_ard_3-2-1_100082_2022-03-17_final
2022-03-17 10:21:36	ga_ls8c_ard_3-2-1_100083_2022-03-17_final
2022-03-17 11:57:42	ga_ls8c_ard_3-2-1_116076_2022-03-17_final
2022-03-17 11:58:06	ga_ls8c_ard_3-2-1_116077_2022-03-17_final
2022-03-17 11:58:30	ga_ls8c_ard_3-2-1_116078_2022-03-17_final
2022-03-18 09:21:35	ga_ls8c_ard_3-2-1_091072_2022-03-17_final
2022-03-18 09:21:59	ga_ls8c_ard_3-2-1_091073_2022-03-17_final
2022-03-18 09:22:23	ga_ls8c_ard_3-2-1_091074_2022-03-17_final
2022-03-18 09:22:47	ga_ls8c_ard_3-2-1_091075_2022-03-17_final
2022-03-18 09:23:11	ga_ls8c_ard_3-2-1_091076_2022-03-17_final
2022-03-18 09:23:35	ga_ls8c_ard_3-2-1_091077_2022-03-17_final
2022-03-18 09:24:23	ga_ls8c_ard_3-2-1_091079_2022-03-17_final
2022-03-18 09:24:47	ga_ls8c_ard_3-2-1_091080_2022-03-17_final
2022-03-18 09:28:46	ga_ls8c_ard_3-2-1_091090_2022-03-17_final
2022-03-18 10:59:40	ga_ls8c_ard_3-2-1_107070_2022-03-18_final
2022-03-18 11:00:04	ga_ls8c_ard_3-2-1_107071_2022-03-18_final
2022-03-18 11:01:16	ga_ls8c_ard_3-2-1_107074_2022-03-18_final
2022-03-18 11:02:04	ga_ls8c_ard_3-2-1_107076_2022-03-18_final
2022-03-18 11:03:40	ga_ls8c_ard_3-2-1_107080_2022-03-18_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years