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
2014-10-22 09:27:54	ga_ls8c_ard_3-1-0_091087_2014-10-21_final
2019-03-13 09:52:35	ga_ls8c_ard_3-1-0_096073_2019-03-13_final
2019-03-13 09:56:35	ga_ls8c_ard_3-1-0_096083_2019-03-13_final
2019-04-11 09:23:58	ga_ls8c_ard_3-1-0_091079_2019-04-10_final
2019-04-18 11:06:11	ga_ls8c_ard_3-1-0_108072_2019-04-18_final
2019-06-26 09:47:05	ga_ls8c_ard_3-1-0_095074_2019-06-26_final
2019-06-30 09:24:46	ga_ls8c_ard_3-1-0_091080_2019-06-29_final
2019-07-07 11:06:40	ga_ls8c_ard_3-1-0_108072_2019-07-07_final
2019-07-28 09:47:13	ga_ls8c_ard_3-1-0_095074_2019-07-28_final
2019-07-28 09:47:37	ga_ls8c_ard_3-1-0_095075_2019-07-28_final
2019-07-28 09:51:13	ga_ls8c_ard_3-1-0_095084_2019-07-28_final
2019-08-13 09:50:55	ga_ls8c_ard_3-1-0_095083_2019-08-13_final
2019-08-19 10:47:34	ga_ls8c_ard_3-1-0_105070_2019-08-19_final
2019-08-19 10:48:21	ga_ls8c_ard_3-1-0_105072_2019-08-19_final
2019-08-20 09:50:45	ga_ls8c_ard_3-1-0_096067_2019-08-20_final
2019-08-24 11:10:31	ga_ls8c_ard_3-1-0_108081_2019-08-24_final
2019-08-29 09:51:47	ga_ls8c_ard_3-1-0_095085_2019-08-29_final
2019-09-05 09:52:48	ga_ls8c_ard_3-1-0_096072_2019-09-05_final
2019-09-14 09:47:28	ga_ls8c_ard_3-1-0_095074_2019-09-14_final
2019-09-14 09:51:52	ga_ls8c_ard_3-1-0_095085_2019-09-14_final
2019-09-14 09:52:39	ga_ls8c_ard_3-1-0_095087_2019-09-14_final
2019-09-20 10:48:30	ga_ls8c_ard_3-1-0_105072_2019-09-20_final
2019-09-20 10:50:30	ga_ls8c_ard_3-1-0_105077_2019-09-20_final
2019-09-21 09:55:41	ga_ls8c_ard_3-1-0_096079_2019-09-21_final
2019-10-04 09:26:02	ga_ls8c_ard_3-1-0_091082_2019-10-03_final
2019-10-06 10:48:58	ga_ls8c_ard_3-1-0_105073_2019-10-06_final
2019-10-06 10:50:34	ga_ls8c_ard_3-1-0_105077_2019-10-06_final
2019-10-22 10:50:36	ga_ls8c_ard_3-1-0_105077_2019-10-22_final
2019-11-01 09:50:23	ga_ls8c_ard_3-1-0_095081_2019-11-01_final
2019-11-12 11:10:42	ga_ls8c_ard_3-1-0_108081_2019-11-12_final
2019-11-12 11:11:06	ga_ls8c_ard_3-1-0_108082_2019-11-12_final
2019-11-23 10:52:31	ga_ls8c_ard_3-1-0_105082_2019-11-23_final
2019-11-28 11:07:04	ga_ls8c_ard_3-1-0_108072_2019-11-28_final
2019-12-10 09:57:41	ga_ls8c_ard_3-1-0_096084_2019-12-10_final
2019-12-10 09:58:05	ga_ls8c_ard_3-1-0_096085_2019-12-10_final
2019-12-23 09:24:21	ga_ls8c_ard_3-1-0_091078_2019-12-22_final
2020-01-04 09:51:24	ga_ls8c_ard_3-1-0_095084_2020-01-04_final
2020-01-08 09:24:16	ga_ls8c_ard_3-1-0_091078_2020-01-07_final
2020-01-08 09:28:16	ga_ls8c_ard_3-1-0_091088_2020-01-07_final
2020-01-11 09:53:10	ga_ls8c_ard_3-1-0_096073_2020-01-11_final
2020-01-20 09:50:09	ga_ls8c_ard_3-1-0_095081_2020-01-20_final
2020-01-27 09:56:18	ga_ls8c_ard_3-1-0_096081_2020-01-27_final
2020-02-05 09:51:39	ga_ls8c_ard_3-1-0_095085_2020-02-05_final
2020-02-16 11:06:23	ga_ls8c_ard_3-1-0_108071_2020-02-16_final
2020-03-12 09:23:58	ga_ls8c_ard_3-1-0_091078_2020-03-11_final
2020-03-28 09:19:49	ga_ls8c_ard_3-1-0_091068_2020-03-27_final
2020-04-09 09:50:26	ga_ls8c_ard_3-1-0_095083_2020-04-09_final
2020-04-13 09:24:05	ga_ls8c_ard_3-1-0_091079_2020-04-12_final
2020-04-16 09:55:22	ga_ls8c_ard_3-1-0_096080_2020-04-16_final
2020-04-20 11:08:42	ga_ls8c_ard_3-1-0_108078_2020-04-20_final
2020-05-01 10:46:28	ga_ls8c_ard_3-1-0_105069_2020-05-01_final
2020-05-02 09:55:14	ga_ls8c_ard_3-1-0_096080_2020-05-02_final
2022-03-30 09:50:32	ga_ls8c_ard_3-2-1_095083_2022-03-30_final
2022-04-04 10:07:53	ga_ls8c_ard_3-2-1_098080_2022-04-04_final
2022-04-05 09:13:28	ga_ls8c_ard_3-2-1_089083_2022-04-04_final
2022-04-05 09:14:40	ga_ls8c_ard_3-2-1_089086_2022-04-04_final
2022-04-07 10:36:02	ga_ls8c_ard_3-2-1_103073_2022-04-07_final
2022-04-07 10:39:37	ga_ls8c_ard_3-2-1_103082_2022-04-07_final
2022-04-11 11:51:25	ga_ls8c_ard_3-2-1_115076_2022-04-11_final
2022-04-12 09:17:43	ga_ls8c_ard_3-2-1_090078_2022-04-11_final
2022-04-13 10:01:23	ga_ls8c_ard_3-2-1_097079_2022-04-13_final
2022-04-14 10:42:16	ga_ls8c_ard_3-2-1_104073_2022-04-14_final
2022-04-16 10:32:42	ga_ls8c_ard_3-2-1_102080_2022-04-16_final
2022-04-16 10:33:30	ga_ls8c_ard_3-2-1_102082_2022-04-16_final
2022-04-23 10:36:03	ga_ls8c_ard_3-2-1_103073_2022-04-23_final
2022-04-24 09:40:49	ga_ls8c_ard_3-2-1_094074_2022-04-24_final
2022-04-26 11:06:08	ga_ls8c_ard_3-2-1_108071_2022-04-26_final
2022-04-28 09:20:27	ga_ls8c_ard_3-2-1_090085_2022-04-27_final
2022-04-29 11:40:36	ga_ls8c_ard_3-2-1_113080_2022-04-29_final
2022-05-01 09:49:47	ga_ls8c_ard_3-2-1_095081_2022-05-01_final
2022-05-02 10:29:28	ga_ls8c_ard_3-2-1_102072_2022-05-02_final
2022-05-03 09:38:15	ga_ls8c_ard_3-2-1_093083_2022-05-03_final
2022-05-03 11:11:33	ga_ls8c_ard_3-2-1_109069_2022-05-03_final
2022-05-03 11:12:44	ga_ls8c_ard_3-2-1_109072_2022-05-03_final
2022-05-05 11:02:24	ga_ls8c_ard_3-2-1_107077_2022-05-05_final
2022-05-06 11:46:28	ga_ls8c_ard_3-2-1_114079_2022-05-06_final
2022-05-07 10:52:27	ga_ls8c_ard_3-2-1_105083_2022-05-07_final
2022-05-08 09:52:27	ga_ls8c_ard_3-2-1_096072_2022-05-08_final
2022-05-09 10:36:07	ga_ls8c_ard_3-2-1_103073_2022-05-09_final
2022-05-13 10:11:50	ga_ls8c_ard_3-2-1_099074_2022-05-13_final
2022-05-15 09:58:18	ga_ls8c_ard_3-2-1_097071_2022-05-15_final
2022-05-15 09:58:41	ga_ls8c_ard_3-2-1_097072_2022-05-15_final
2022-05-15 10:01:29	ga_ls8c_ard_3-2-1_097079_2022-05-15_final
2022-05-17 09:50:20	ga_ls8c_ard_3-2-1_095082_2022-05-17_final
2022-05-19 09:35:11	ga_ls8c_ard_3-2-1_093075_2022-05-19_final
2022-05-21 09:26:49	ga_ls8c_ard_3-2-1_091085_2022-05-20_final
2022-05-26 09:43:21	ga_ls8c_ard_3-2-1_094080_2022-05-26_final
2022-05-26 11:20:38	ga_ls8c_ard_3-2-1_110076_2022-05-26_final
2022-05-30 10:56:20	ga_ls8c_ard_3-2-1_106077_2022-05-30_final
2022-05-31 09:59:08	ga_ls8c_ard_3-2-1_097073_2022-05-31_final
2022-06-02 11:28:53	ga_ls8c_ard_3-2-1_111081_2022-06-02_final
2022-06-03 10:32:05	ga_ls8c_ard_3-2-1_102078_2022-06-03_final
2022-06-05 10:20:57	ga_ls8c_ard_3-2-1_100081_2022-06-05_final
2022-06-07 11:46:18	ga_ls8c_ard_3-2-1_114078_2022-06-07_final
2022-06-07 11:47:30	ga_ls8c_ard_3-2-1_114081_2022-06-07_final
2022-06-08 10:47:06	ga_ls8c_ard_3-2-1_105069_2022-06-08_final
2022-06-08 10:48:18	ga_ls8c_ard_3-2-1_105072_2022-06-08_final
2022-06-13 09:32:24	ga_ls8c_ard_3-2-1_092083_2022-06-13_final
2022-06-16 10:03:44	ga_ls8c_ard_3-2-1_097084_2022-06-16_final
2022-06-17 10:43:25	ga_ls8c_ard_3-2-1_104075_2022-06-17_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