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
2019-03-22 09:47:35	ga_ls8c_ard_3-1-0_095076_2019-03-22_final
2019-06-26 09:47:53	ga_ls8c_ard_3-1-0_095076_2019-06-26_final
2019-07-28 09:51:37	ga_ls8c_ard_3-1-0_095085_2019-07-28_final
2019-08-13 09:48:07	ga_ls8c_ard_3-1-0_095076_2019-08-13_final
2019-08-29 09:48:11	ga_ls8c_ard_3-1-0_095076_2019-08-29_final
2019-08-29 09:50:11	ga_ls8c_ard_3-1-0_095081_2019-08-29_final
2019-10-16 09:50:23	ga_ls8c_ard_3-1-0_095081_2019-10-16_final
2019-11-01 09:49:35	ga_ls8c_ard_3-1-0_095079_2019-11-01_final
2020-01-04 09:49:24	ga_ls8c_ard_3-1-0_095079_2020-01-04_final
2020-01-04 09:50:12	ga_ls8c_ard_3-1-0_095081_2020-01-04_final
2020-02-05 09:48:04	ga_ls8c_ard_3-1-0_095076_2020-02-05_final
2020-02-21 09:51:36	ga_ls8c_ard_3-1-0_095085_2020-02-21_final
2020-03-08 09:49:07	ga_ls8c_ard_3-1-0_095079_2020-03-08_final
2022-03-29 10:40:35	ga_ls8c_ard_3-2-1_104069_2022-03-29_final
2022-03-30 09:47:44	ga_ls8c_ard_3-2-1_095076_2022-03-30_final
2022-03-30 11:27:49	ga_ls8c_ard_3-2-1_111079_2022-03-30_final
2022-03-31 10:31:24	ga_ls8c_ard_3-2-1_102077_2022-03-31_final
2022-04-02 10:20:38	ga_ls8c_ard_3-2-1_100081_2022-04-02_final
2022-04-03 11:00:18	ga_ls8c_ard_3-2-1_107072_2022-04-03_final
2022-04-05 09:13:28	ga_ls8c_ard_3-2-1_089083_2022-04-04_final
2022-04-05 09:13:52	ga_ls8c_ard_3-2-1_089084_2022-04-04_final
2022-04-05 10:47:10	ga_ls8c_ard_3-2-1_105070_2022-04-05_final
2022-04-06 09:53:09	ga_ls8c_ard_3-2-1_096074_2022-04-06_final
2022-04-06 09:55:57	ga_ls8c_ard_3-2-1_096081_2022-04-06_final
2022-04-07 10:35:14	ga_ls8c_ard_3-2-1_103071_2022-04-07_final
2022-04-10 11:05:46	ga_ls8c_ard_3-2-1_108070_2022-04-10_final
2022-04-11 11:51:25	ga_ls8c_ard_3-2-1_115076_2022-04-11_final
2022-04-12 09:18:31	ga_ls8c_ard_3-2-1_090080_2022-04-11_final
2022-04-12 09:18:55	ga_ls8c_ard_3-2-1_090081_2022-04-11_final
2022-04-12 10:57:00	ga_ls8c_ard_3-2-1_106079_2022-04-12_final
2022-04-13 10:00:59	ga_ls8c_ard_3-2-1_097078_2022-04-13_final
2022-04-13 10:01:23	ga_ls8c_ard_3-2-1_097079_2022-04-13_final
2022-04-13 10:02:11	ga_ls8c_ard_3-2-1_097081_2022-04-13_final
2022-04-13 10:02:59	ga_ls8c_ard_3-2-1_097083_2022-04-13_final
2022-04-15 11:26:43	ga_ls8c_ard_3-2-1_111076_2022-04-15_final
2022-04-17 09:37:28	ga_ls8c_ard_3-2-1_093081_2022-04-17_final
2022-04-17 09:37:52	ga_ls8c_ard_3-2-1_093082_2022-04-17_final
2022-04-17 11:14:21	ga_ls8c_ard_3-2-1_109076_2022-04-17_final
2022-04-19 09:23:54	ga_ls8c_ard_3-2-1_091078_2022-04-18_final
2022-04-20 10:07:34	ga_ls8c_ard_3-2-1_098079_2022-04-20_final
2022-04-20 11:46:27	ga_ls8c_ard_3-2-1_114079_2022-04-20_final
2022-04-21 10:50:01	ga_ls8c_ard_3-2-1_105077_2022-04-21_final
2022-04-21 10:50:49	ga_ls8c_ard_3-2-1_105079_2022-04-21_final
2022-04-22 09:55:11	ga_ls8c_ard_3-2-1_096079_2022-04-22_final
2022-04-22 11:34:52	ga_ls8c_ard_3-2-1_112081_2022-04-22_final
2022-04-24 11:18:30	ga_ls8c_ard_3-2-1_110071_2022-04-24_final
2022-04-24 11:22:54	ga_ls8c_ard_3-2-1_110082_2022-04-24_final
2022-04-25 10:26:04	ga_ls8c_ard_3-2-1_101079_2022-04-25_final
2022-04-26 11:08:07	ga_ls8c_ard_3-2-1_108076_2022-04-26_final
2022-04-27 10:12:05	ga_ls8c_ard_3-2-1_099075_2022-04-27_final
2022-04-28 09:18:51	ga_ls8c_ard_3-2-1_090081_2022-04-27_final
2022-04-28 09:20:03	ga_ls8c_ard_3-2-1_090084_2022-04-27_final
2022-04-29 09:59:43	ga_ls8c_ard_3-2-1_097075_2022-04-29_final
2022-04-29 10:00:07	ga_ls8c_ard_3-2-1_097076_2022-04-29_final
2022-04-29 11:40:12	ga_ls8c_ard_3-2-1_113079_2022-04-29_final
2022-05-01 11:28:40	ga_ls8c_ard_3-2-1_111081_2022-05-01_final
2022-05-03 09:35:51	ga_ls8c_ard_3-2-1_093077_2022-05-03_final
2022-05-04 10:17:56	ga_ls8c_ard_3-2-1_100074_2022-05-04_final
2022-05-06 10:08:47	ga_ls8c_ard_3-2-1_098082_2022-05-06_final
2022-05-07 10:48:28	ga_ls8c_ard_3-2-1_105073_2022-05-07_final
2022-05-07 10:50:52	ga_ls8c_ard_3-2-1_105079_2022-05-07_final
2022-05-08 09:55:15	ga_ls8c_ard_3-2-1_096079_2022-05-08_final
2022-05-08 11:32:56	ga_ls8c_ard_3-2-1_112076_2022-05-08_final
2022-05-13 10:11:26	ga_ls8c_ard_3-2-1_099073_2022-05-13_final
2022-05-13 10:15:02	ga_ls8c_ard_3-2-1_099082_2022-05-13_final
2022-05-14 09:19:01	ga_ls8c_ard_3-2-1_090081_2022-05-13_final
2022-05-15 09:59:53	ga_ls8c_ard_3-2-1_097075_2022-05-15_final
2022-05-17 09:49:08	ga_ls8c_ard_3-2-1_095079_2022-05-17_final
2022-05-19 09:35:59	ga_ls8c_ard_3-2-1_093077_2022-05-19_final
2022-05-19 09:36:47	ga_ls8c_ard_3-2-1_093079_2022-05-19_final
2022-05-19 11:15:16	ga_ls8c_ard_3-2-1_109078_2022-05-19_final
2022-05-20 10:18:27	ga_ls8c_ard_3-2-1_100075_2022-05-20_final
2022-05-20 10:18:51	ga_ls8c_ard_3-2-1_100076_2022-05-20_final
2022-05-24 09:54:55	ga_ls8c_ard_3-2-1_096078_2022-05-24_final
2022-05-24 09:56:07	ga_ls8c_ard_3-2-1_096081_2022-05-24_final
2022-05-24 11:34:12	ga_ls8c_ard_3-2-1_112079_2022-05-24_final
2022-05-25 10:36:35	ga_ls8c_ard_3-2-1_103074_2022-05-25_final
2022-05-25 10:37:22	ga_ls8c_ard_3-2-1_103076_2022-05-25_final
2022-05-25 10:38:10	ga_ls8c_ard_3-2-1_103078_2022-05-25_final
2022-05-26 09:43:45	ga_ls8c_ard_3-2-1_094081_2022-05-26_final
2022-05-26 09:44:32	ga_ls8c_ard_3-2-1_094083_2022-05-26_final
2022-05-26 11:21:50	ga_ls8c_ard_3-2-1_110079_2022-05-26_final
2022-05-31 10:00:20	ga_ls8c_ard_3-2-1_097076_2022-05-31_final
2022-05-31 10:00:44	ga_ls8c_ard_3-2-1_097077_2022-05-31_final
2022-06-02 09:49:12	ga_ls8c_ard_3-2-1_095079_2022-06-02_final
2022-06-05 10:20:57	ga_ls8c_ard_3-2-1_100081_2022-06-05_final
2022-06-07 11:45:54	ga_ls8c_ard_3-2-1_114077_2022-06-07_final
2022-06-07 11:46:18	ga_ls8c_ard_3-2-1_114078_2022-06-07_final
2022-06-07 11:47:06	ga_ls8c_ard_3-2-1_114080_2022-06-07_final
2022-06-08 09:13:00	ga_ls8c_ard_3-2-1_089081_2022-06-07_final
2022-06-08 10:47:54	ga_ls8c_ard_3-2-1_105071_2022-06-08_final
2022-06-08 10:51:05	ga_ls8c_ard_3-2-1_105079_2022-06-08_final
2022-06-13 09:30:00	ga_ls8c_ard_3-2-1_092077_2022-06-13_final
2022-06-13 09:30:24	ga_ls8c_ard_3-2-1_092078_2022-06-13_final
2022-06-17 10:43:25	ga_ls8c_ard_3-2-1_104075_2022-06-17_final
2022-06-18 09:49:47	ga_ls8c_ard_3-2-1_095080_2022-06-18_final
2022-06-18 09:50:11	ga_ls8c_ard_3-2-1_095081_2022-06-18_final
2022-06-18 11:28:17	ga_ls8c_ard_3-2-1_111079_2022-06-18_final
2022-06-19 10:31:52	ga_ls8c_ard_3-2-1_102077_2022-06-19_final
2022-06-22 09:24:42	ga_ls8c_ard_3-2-1_091079_2022-06-21_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