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
2022-06-22 10:59:59	ga_ls8c_ard_3-2-1_107070_2022-06-22_final
2022-06-24 10:50:50	ga_ls8c_ard_3-2-1_105078_2022-06-24_final
2022-06-27 09:41:15	ga_ls8c_ard_3-2-1_094074_2022-06-27_final
2022-06-29 09:32:30	ga_ls8c_ard_3-2-1_092083_2022-06-29_final
2022-06-30 10:16:09	ga_ls8c_ard_3-2-1_099084_2022-06-30_final
2022-07-02 11:38:41	ga_ls8c_ard_3-2-1_113074_2022-07-02_final
2022-07-04 09:48:39	ga_ls8c_ard_3-2-1_095077_2022-07-04_final
2022-07-10 10:51:38	ga_ls8c_ard_3-2-1_105080_2022-07-10_final
2022-07-13 11:22:08	ga_ls8c_ard_3-2-1_110079_2022-07-13_final
2022-07-18 10:02:36	ga_ls8c_ard_3-2-1_097081_2022-07-18_final
2022-07-20 11:25:34	ga_ls8c_ard_3-2-1_111072_2022-07-20_final
2022-07-21 10:28:46	ga_ls8c_ard_3-2-1_102069_2022-07-21_final
2022-07-26 10:50:58	ga_ls8c_ard_3-2-1_105078_2022-07-26_final
2022-07-26 10:51:22	ga_ls8c_ard_3-2-1_105079_2022-07-26_final
2022-07-28 10:36:14	ga_ls8c_ard_3-2-1_103072_2022-07-28_final
2022-07-29 11:20:18	ga_ls8c_ard_3-2-1_110074_2022-07-29_final
2022-07-29 11:22:18	ga_ls8c_ard_3-2-1_110079_2022-07-29_final
2022-07-31 11:09:57	ga_ls8c_ard_3-2-1_108079_2022-07-31_final
2022-08-05 11:28:32	ga_ls8c_ard_3-2-1_111079_2022-08-05_final
2022-08-07 09:35:43	ga_ls8c_ard_3-2-1_093075_2022-08-07_final
2022-08-09 11:04:39	ga_ls8c_ard_3-2-1_107081_2022-08-09_final
2022-08-14 09:40:20	ga_ls8c_ard_3-2-1_094071_2022-08-14_final
2022-08-16 09:31:59	ga_ls8c_ard_3-2-1_092081_2022-08-16_final
2022-08-16 11:09:16	ga_ls8c_ard_3-2-1_108077_2022-08-16_final
2022-08-22 10:29:00	ga_ls8c_ard_3-2-1_102069_2022-08-22_final
2022-08-25 11:04:18	ga_ls8c_ard_3-2-1_107080_2022-08-25_final
2022-08-25 11:04:42	ga_ls8c_ard_3-2-1_107081_2022-08-25_final
2022-08-28 09:55:31	ga_ls8c_ard_3-2-1_096078_2022-08-28_final
2022-08-28 09:55:55	ga_ls8c_ard_3-2-1_096079_2022-08-28_final
2022-08-30 09:44:21	ga_ls8c_ard_3-2-1_094081_2022-08-30_final
2022-08-30 11:20:02	ga_ls8c_ard_3-2-1_110073_2022-08-30_final
2022-08-30 11:20:26	ga_ls8c_ard_3-2-1_110074_2022-08-30_final
2022-08-30 11:22:26	ga_ls8c_ard_3-2-1_110079_2022-08-30_final
2022-08-31 10:24:49	ga_ls8c_ard_3-2-1_101074_2022-08-31_final
2022-09-01 11:07:40	ga_ls8c_ard_3-2-1_108073_2022-09-01_final
2022-09-01 11:09:16	ga_ls8c_ard_3-2-1_108077_2022-09-01_final
2022-09-05 10:41:47	ga_ls8c_ard_3-2-1_104070_2022-09-05_final
2022-09-08 11:15:30	ga_ls8c_ard_3-2-1_109077_2022-09-08_final
2022-09-12 10:49:13	ga_ls8c_ard_3-2-1_105073_2022-09-12_final
2022-09-12 10:51:13	ga_ls8c_ard_3-2-1_105078_2022-09-12_final
2022-09-13 09:55:36	ga_ls8c_ard_3-2-1_096078_2022-09-13_final
2022-09-16 10:26:31	ga_ls8c_ard_3-2-1_101078_2022-09-16_final
2022-09-21 10:46:40	ga_ls8c_ard_3-2-1_104082_2022-09-21_final
2022-09-26 11:06:00	ga_ls8c_ard_3-2-1_107084_2022-09-26_final
2022-09-29 09:55:37	ga_ls8c_ard_3-2-1_096078_2022-09-29_final
2022-10-01 11:20:32	ga_ls8c_ard_3-2-1_110074_2022-10-01_final
2022-10-06 10:04:09	ga_ls8c_ard_3-2-1_097084_2022-10-06_final
2022-10-06 10:04:33	ga_ls8c_ard_3-2-1_097085_2022-10-06_final
2022-10-08 09:47:47	ga_ls8c_ard_3-2-1_095074_2022-10-08_final
2022-10-10 09:38:11	ga_ls8c_ard_3-2-1_093081_2022-10-10_final
2022-10-19 11:08:06	ga_ls8c_ard_3-2-1_108074_2022-10-19_final
2022-10-23 10:41:50	ga_ls8c_ard_3-2-1_104070_2022-10-23_final
2022-10-26 09:38:15	ga_ls8c_ard_3-2-1_093081_2022-10-26_final
2022-10-29 10:05:35	ga_ls8c_ard_3-2-1_098072_2022-10-29_final
2022-10-30 10:50:50	ga_ls8c_ard_3-2-1_105077_2022-10-30_final
2022-11-02 11:22:33	ga_ls8c_ard_3-2-1_110079_2022-11-02_final
2022-11-08 10:46:14	ga_ls8c_ard_3-2-1_104081_2022-11-08_final
2022-11-11 11:17:31	ga_ls8c_ard_3-2-1_109082_2022-11-11_final
2022-11-15 10:49:09	ga_ls8c_ard_3-2-1_105073_2022-11-15_final
2022-11-18 11:21:13	ga_ls8c_ard_3-2-1_110076_2022-11-18_final
2022-11-21 10:12:03	ga_ls8c_ard_3-2-1_099073_2022-11-21_final
2022-11-21 10:15:15	ga_ls8c_ard_3-2-1_099081_2022-11-21_final
2022-11-25 11:27:50	ga_ls8c_ard_3-2-1_111077_2022-11-25_final
2022-11-27 11:14:17	ga_ls8c_ard_3-2-1_109074_2022-11-27_final
2022-11-27 11:16:41	ga_ls8c_ard_3-2-1_109080_2022-11-27_final
2022-11-29 11:05:31	ga_ls8c_ard_3-2-1_107083_2022-11-29_final
2022-12-01 10:49:58	ga_ls8c_ard_3-2-1_105075_2022-12-01_final
2022-12-04 09:41:11	ga_ls8c_ard_3-2-1_094073_2022-12-04_final
2022-12-04 09:45:58	ga_ls8c_ard_3-2-1_094085_2022-12-04_final
2022-12-05 10:28:02	ga_ls8c_ard_3-2-1_101082_2022-12-05_final
2022-12-06 09:33:12	ga_ls8c_ard_3-2-1_092084_2022-12-06_final
2022-12-06 11:10:30	ga_ls8c_ard_3-2-1_108080_2022-12-06_final
2022-12-13 11:12:14	ga_ls8c_ard_3-2-1_109069_2022-12-13_final
2022-12-13 11:16:38	ga_ls8c_ard_3-2-1_109080_2022-12-13_final
2022-12-25 10:01:57	ga_ls8c_ard_3-2-1_097079_2022-12-25_final
2022-12-26 10:46:01	ga_ls8c_ard_3-2-1_104081_2022-12-26_final
2022-12-27 09:52:00	ga_ls8c_ard_3-2-1_095085_2022-12-27_final
2023-01-04 10:40:15	ga_ls8c_ard_3-2-1_103082_2023-01-04_final
2023-01-07 11:07:09	ga_ls8c_ard_3-2-1_108072_2023-01-07_final
2023-01-09 09:19:05	ga_ls8c_ard_3-2-1_090080_2023-01-08_final
2023-01-13 10:31:37	ga_ls8c_ard_3-2-1_102076_2023-01-13_final
2023-01-14 09:36:22	ga_ls8c_ard_3-2-1_093077_2023-01-14_final
2023-01-14 11:14:03	ga_ls8c_ard_3-2-1_109074_2023-01-14_final
2023-01-16 11:00:28	ga_ls8c_ard_3-2-1_107071_2023-01-16_final
2023-01-19 09:58:04	ga_ls8c_ard_3-2-1_096085_2023-01-19_final
2023-01-22 10:24:13	ga_ls8c_ard_3-2-1_101073_2023-01-22_final
2023-01-23 11:11:29	ga_ls8c_ard_3-2-1_108083_2023-01-23_final
2023-01-24 10:15:04	ga_ls8c_ard_3-2-1_099081_2023-01-24_final
2023-01-24 10:15:52	ga_ls8c_ard_3-2-1_099083_2023-01-24_final
2023-01-26 10:01:56	ga_ls8c_ard_3-2-1_097079_2023-01-26_final
2023-01-26 11:38:01	ga_ls8c_ard_3-2-1_113072_2023-01-26_final
2023-02-10 10:56:19	ga_ls8c_ard_3-2-1_106076_2023-02-10_final
2023-02-10 10:57:55	ga_ls8c_ard_3-2-1_106080_2023-02-10_final
2023-02-13 09:47:29	ga_ls8c_ard_3-2-1_095074_2023-02-13_final
2023-02-16 11:58:50	ga_ls8c_ard_3-2-1_116078_2023-02-16_final
2023-02-19 10:51:59	ga_ls8c_ard_3-2-1_105081_2023-02-19_final
2023-02-24 09:32:20	ga_ls8c_ard_3-2-1_092083_2023-02-24_final
2023-03-01 09:51:39	ga_ls8c_ard_3-2-1_095085_2023-03-01_final
2023-03-10 09:40:36	ga_ls8c_ard_3-2-1_094073_2023-03-10_final
2023-03-10 09:45:23	ga_ls8c_ard_3-2-1_094085_2023-03-10_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