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
2019-03-26 09:25:14	ga_ls8c_ard_3-1-0_091082_2019-03-25_final
2019-04-07 09:50:42	ga_ls8c_ard_3-1-0_095084_2019-04-07_final
2019-06-14 09:23:54	ga_ls8c_ard_3-1-0_091078_2019-06-13_final
2019-06-16 10:46:50	ga_ls8c_ard_3-1-0_105069_2019-06-16_final
2019-06-17 09:52:49	ga_ls8c_ard_3-1-0_096073_2019-06-17_final
2019-07-03 09:56:05	ga_ls8c_ard_3-1-0_096081_2019-07-03_final
2019-08-01 09:26:07	ga_ls8c_ard_3-1-0_091083_2019-07-31_final
2019-08-03 10:52:40	ga_ls8c_ard_3-1-0_105083_2019-08-03_final
2019-08-04 09:56:15	ga_ls8c_ard_3-1-0_096081_2019-08-04_final
2019-08-13 09:50:07	ga_ls8c_ard_3-1-0_095081_2019-08-13_final
2019-08-20 09:57:08	ga_ls8c_ard_3-1-0_096083_2019-08-20_final
2019-08-29 09:47:47	ga_ls8c_ard_3-1-0_095075_2019-08-29_final
2019-08-29 09:50:11	ga_ls8c_ard_3-1-0_095081_2019-08-29_final
2019-09-05 09:53:35	ga_ls8c_ard_3-1-0_096074_2019-09-05_final
2019-09-09 11:10:58	ga_ls8c_ard_3-1-0_108082_2019-09-09_final
2019-09-14 09:50:16	ga_ls8c_ard_3-1-0_095081_2019-09-14_final
2019-09-14 09:52:39	ga_ls8c_ard_3-1-0_095087_2019-09-14_final
2019-09-21 09:52:53	ga_ls8c_ard_3-1-0_096072_2019-09-21_final
2019-10-04 09:26:02	ga_ls8c_ard_3-1-0_091082_2019-10-03_final
2019-10-11 11:08:44	ga_ls8c_ard_3-1-0_108076_2019-10-11_final
2019-11-01 09:48:47	ga_ls8c_ard_3-1-0_095077_2019-11-01_final
2019-12-07 09:20:24	ga_ls8c_ard_3-1-0_091068_2019-12-06_final
2019-12-10 09:55:41	ga_ls8c_ard_3-1-0_096079_2019-12-10_final
2019-12-10 09:56:29	ga_ls8c_ard_3-1-0_096081_2019-12-10_final
2019-12-23 09:27:32	ga_ls8c_ard_3-1-0_091086_2019-12-22_final
2019-12-26 09:55:38	ga_ls8c_ard_3-1-0_096079_2019-12-26_final
2020-01-04 09:51:24	ga_ls8c_ard_3-1-0_095084_2020-01-04_final
2020-01-27 09:56:41	ga_ls8c_ard_3-1-0_096082_2020-01-27_final
2020-02-05 09:49:15	ga_ls8c_ard_3-1-0_095079_2020-02-05_final
2020-02-12 09:56:37	ga_ls8c_ard_3-1-0_096082_2020-02-12_final
2020-02-21 09:48:24	ga_ls8c_ard_3-1-0_095077_2020-02-21_final
2020-02-28 09:56:33	ga_ls8c_ard_3-1-0_096082_2020-02-28_final
2020-03-03 11:08:17	ga_ls8c_ard_3-1-0_108076_2020-03-03_final
2020-03-15 09:56:26	ga_ls8c_ard_3-1-0_096082_2020-03-15_final
2020-03-15 09:57:38	ga_ls8c_ard_3-1-0_096085_2020-03-15_final
2020-03-24 09:47:47	ga_ls8c_ard_3-1-0_095076_2020-03-24_final
2020-03-28 09:23:49	ga_ls8c_ard_3-1-0_091078_2020-03-27_final
2020-03-30 10:52:19	ga_ls8c_ard_3-1-0_105083_2020-03-30_final
2020-04-13 09:23:41	ga_ls8c_ard_3-1-0_091078_2020-04-12_final
2020-04-16 09:57:22	ga_ls8c_ard_3-1-0_096085_2020-04-16_final
2022-03-29 10:41:46	ga_ls8c_ard_3-2-1_104072_2022-03-29_final
2022-04-02 10:18:14	ga_ls8c_ard_3-2-1_100075_2022-04-02_final
2022-04-02 10:20:14	ga_ls8c_ard_3-2-1_100080_2022-04-02_final
2022-04-03 09:23:49	ga_ls8c_ard_3-2-1_091078_2022-04-02_final
2022-04-03 11:00:18	ga_ls8c_ard_3-2-1_107072_2022-04-03_final
2022-04-03 11:03:30	ga_ls8c_ard_3-2-1_107080_2022-04-03_final
2022-04-04 10:08:17	ga_ls8c_ard_3-2-1_098081_2022-04-04_final
2022-04-05 10:47:58	ga_ls8c_ard_3-2-1_105072_2022-04-05_final
2022-04-06 09:55:57	ga_ls8c_ard_3-2-1_096081_2022-04-06_final
2022-04-08 11:20:54	ga_ls8c_ard_3-2-1_110077_2022-04-08_final
2022-04-08 11:22:06	ga_ls8c_ard_3-2-1_110080_2022-04-08_final
2022-04-10 09:31:16	ga_ls8c_ard_3-2-1_092081_2022-04-10_final
2022-04-13 11:39:28	ga_ls8c_ard_3-2-1_113077_2022-04-13_final
2022-04-13 11:39:52	ga_ls8c_ard_3-2-1_113078_2022-04-13_final
2022-04-15 09:47:26	ga_ls8c_ard_3-2-1_095075_2022-04-15_final
2022-04-16 10:31:30	ga_ls8c_ard_3-2-1_102077_2022-04-16_final
2022-04-19 11:00:48	ga_ls8c_ard_3-2-1_107073_2022-04-19_final
2022-04-19 11:03:35	ga_ls8c_ard_3-2-1_107080_2022-04-19_final
2022-04-20 10:06:22	ga_ls8c_ard_3-2-1_098076_2022-04-20_final
2022-04-22 11:34:52	ga_ls8c_ard_3-2-1_112081_2022-04-22_final
2022-04-23 10:34:51	ga_ls8c_ard_3-2-1_103070_2022-04-23_final
2022-04-24 09:44:25	ga_ls8c_ard_3-2-1_094083_2022-04-24_final
2022-04-26 11:10:31	ga_ls8c_ard_3-2-1_108082_2022-04-26_final
2022-04-28 09:18:27	ga_ls8c_ard_3-2-1_090080_2022-04-27_final
2022-04-29 10:00:31	ga_ls8c_ard_3-2-1_097077_2022-04-29_final
2022-04-29 11:39:48	ga_ls8c_ard_3-2-1_113078_2022-04-29_final
2022-05-03 11:14:44	ga_ls8c_ard_3-2-1_109077_2022-05-03_final
2022-05-04 10:17:32	ga_ls8c_ard_3-2-1_100073_2022-05-04_final
2022-05-04 11:58:25	ga_ls8c_ard_3-2-1_116078_2022-05-04_final
2022-05-05 11:02:00	ga_ls8c_ard_3-2-1_107076_2022-05-05_final
2022-05-07 10:47:16	ga_ls8c_ard_3-2-1_105070_2022-05-07_final
2022-05-07 10:47:40	ga_ls8c_ard_3-2-1_105071_2022-05-07_final
2022-05-08 09:56:03	ga_ls8c_ard_3-2-1_096081_2022-05-08_final
2022-05-09 10:34:56	ga_ls8c_ard_3-2-1_103070_2022-05-09_final
2022-05-09 10:39:43	ga_ls8c_ard_3-2-1_103082_2022-05-09_final
2022-05-10 11:24:11	ga_ls8c_ard_3-2-1_110085_2022-05-10_final
2022-05-11 10:24:35	ga_ls8c_ard_3-2-1_101075_2022-05-11_final
2022-05-13 10:11:50	ga_ls8c_ard_3-2-1_099074_2022-05-13_final
2022-05-13 10:15:02	ga_ls8c_ard_3-2-1_099082_2022-05-13_final
2022-05-14 10:57:54	ga_ls8c_ard_3-2-1_106081_2022-05-14_final
2022-05-15 11:39:34	ga_ls8c_ard_3-2-1_113077_2022-05-15_final
2022-05-16 10:42:45	ga_ls8c_ard_3-2-1_104074_2022-05-16_final
2022-05-17 09:49:32	ga_ls8c_ard_3-2-1_095080_2022-05-17_final
2022-05-20 10:17:39	ga_ls8c_ard_3-2-1_100073_2022-05-20_final
2022-05-20 10:18:27	ga_ls8c_ard_3-2-1_100075_2022-05-20_final
2022-05-24 09:54:55	ga_ls8c_ard_3-2-1_096078_2022-05-24_final
2022-05-24 09:55:43	ga_ls8c_ard_3-2-1_096080_2022-05-24_final
2022-05-25 10:34:59	ga_ls8c_ard_3-2-1_103070_2022-05-25_final
2022-05-26 09:41:21	ga_ls8c_ard_3-2-1_094075_2022-05-26_final
2022-05-26 11:21:26	ga_ls8c_ard_3-2-1_110078_2022-05-26_final
2022-06-02 11:27:41	ga_ls8c_ard_3-2-1_111078_2022-06-02_final
2022-06-03 10:29:41	ga_ls8c_ard_3-2-1_102072_2022-06-03_final
2022-06-04 09:38:28	ga_ls8c_ard_3-2-1_093083_2022-06-04_final
2022-06-08 10:47:30	ga_ls8c_ard_3-2-1_105070_2022-06-08_final
2022-06-08 10:50:41	ga_ls8c_ard_3-2-1_105078_2022-06-08_final
2022-06-13 09:30:24	ga_ls8c_ard_3-2-1_092078_2022-06-13_final
2022-06-15 10:57:45	ga_ls8c_ard_3-2-1_106080_2022-06-15_final
2022-06-16 11:39:02	ga_ls8c_ard_3-2-1_113075_2022-06-16_final
2022-06-19 10:29:52	ga_ls8c_ard_3-2-1_102072_2022-06-19_final
2022-06-20 09:37:51	ga_ls8c_ard_3-2-1_093081_2022-06-20_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