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
2018-02-06 09:50:27	ga_ls8c_ard_3-0-0_096067_2018-02-06_final
2018-02-06 11:29:20	ga_ls8c_ard_3-0-0_112067_2018-02-06_final
2018-02-07 10:33:42	ga_ls8c_ard_3-0-0_103067_2018-02-07_final
2018-02-07 10:34:06	ga_ls8c_ard_3-0-0_103068_2018-02-07_final
2018-02-08 09:38:04	ga_ls8c_ard_3-0-0_094067_2018-02-08_final
2018-02-08 11:16:57	ga_ls8c_ard_3-0-0_110067_2018-02-08_final
2018-02-09 10:21:20	ga_ls8c_ard_3-0-0_101067_2018-02-09_final
2018-02-10 09:25:42	ga_ls8c_ard_3-0-0_092067_2018-02-09_final
2018-02-22 09:50:21	ga_ls8c_ard_3-0-0_096067_2018-02-22_final
2018-02-22 11:29:14	ga_ls8c_ard_3-0-0_112067_2018-02-22_final
2018-02-23 10:33:36	ga_ls8c_ard_3-0-0_103067_2018-02-23_final
2018-02-24 09:37:58	ga_ls8c_ard_3-0-0_094067_2018-02-24_final
2018-02-24 11:16:51	ga_ls8c_ard_3-0-0_110067_2018-02-24_final
2018-02-25 10:21:14	ga_ls8c_ard_3-0-0_101067_2018-02-25_final
2018-02-26 09:25:36	ga_ls8c_ard_3-0-0_092067_2018-02-25_final
2018-03-28 09:37:43	ga_ls8c_ard_3-0-0_094067_2018-03-28_final
2018-03-28 11:16:36	ga_ls8c_ard_3-0-0_110067_2018-03-28_final
2018-03-29 10:20:58	ga_ls8c_ard_3-0-0_101067_2018-03-29_final
2018-03-30 09:25:20	ga_ls8c_ard_3-0-0_092067_2018-03-29_final
2018-06-20 10:51:20	ga_ls8c_ard_3-0-0_106067_2018-06-20_final
2018-06-21 09:55:43	ga_ls8c_ard_3-0-0_097067_2018-06-21_final
2018-06-21 09:56:07	ga_ls8c_ard_3-0-0_097068_2018-06-21_final
2018-06-21 11:34:37	ga_ls8c_ard_3-0-0_113067_2018-06-21_final
2018-06-22 10:39:00	ga_ls8c_ard_3-0-0_104067_2018-06-22_final
2018-06-22 10:39:24	ga_ls8c_ard_3-0-0_104068_2018-06-22_final
2018-07-04 11:03:50	ga_ls8c_ard_3-0-0_108067_2018-07-04_final
2018-07-04 11:04:14	ga_ls8c_ard_3-0-0_108068_2018-07-04_final
2018-07-05 10:08:13	ga_ls8c_ard_3-0-0_099067_2018-07-05_final
2018-07-05 10:08:37	ga_ls8c_ard_3-0-0_099068_2018-07-05_final
2018-07-06 10:51:29	ga_ls8c_ard_3-0-0_106067_2018-07-06_final
2018-07-06 10:51:53	ga_ls8c_ard_3-0-0_106068_2018-07-06_final
2018-07-07 09:55:52	ga_ls8c_ard_3-0-0_097067_2018-07-07_final
2018-07-07 09:56:16	ga_ls8c_ard_3-0-0_097068_2018-07-07_final
2018-07-07 11:34:46	ga_ls8c_ard_3-0-0_113067_2018-07-07_final
2018-07-08 10:39:09	ga_ls8c_ard_3-0-0_104067_2018-07-08_final
2018-07-08 10:39:33	ga_ls8c_ard_3-0-0_104068_2018-07-08_final
2018-07-20 11:03:57	ga_ls8c_ard_3-0-0_108067_2018-07-20_final
2018-07-20 11:04:21	ga_ls8c_ard_3-0-0_108068_2018-07-20_final
2018-07-21 10:08:20	ga_ls8c_ard_3-0-0_099067_2018-07-21_final
2018-07-21 10:08:44	ga_ls8c_ard_3-0-0_099068_2018-07-21_final
2018-07-22 10:51:36	ga_ls8c_ard_3-0-0_106067_2018-07-22_final
2018-07-22 10:52:00	ga_ls8c_ard_3-0-0_106068_2018-07-22_final
2018-07-23 09:55:59	ga_ls8c_ard_3-0-0_097067_2018-07-23_final
2018-07-23 09:56:23	ga_ls8c_ard_3-1-0_097068_2018-07-23_final
2018-07-23 11:34:52	ga_ls8c_ard_3-0-0_113067_2018-07-23_final
2018-07-24 10:39:15	ga_ls8c_ard_3-0-0_104067_2018-07-24_final
2018-07-24 10:39:39	ga_ls8c_ard_3-0-0_104068_2018-07-24_final
2018-08-05 11:04:05	ga_ls8c_ard_3-0-0_108067_2018-08-05_final
2018-08-05 11:04:29	ga_ls8c_ard_3-0-0_108068_2018-08-05_final
2018-08-06 10:08:29	ga_ls8c_ard_3-0-0_099067_2018-08-06_final
2018-08-06 10:08:52	ga_ls8c_ard_3-0-0_099068_2018-08-06_final
2018-08-21 11:04:14	ga_ls8c_ard_3-0-0_108067_2018-08-21_final
2018-08-21 11:04:38	ga_ls8c_ard_3-0-0_108068_2018-08-21_final
2018-08-22 10:08:37	ga_ls8c_ard_3-0-0_099067_2018-08-22_final
2018-08-23 10:51:53	ga_ls8c_ard_3-0-0_106067_2018-08-23_final
2018-08-23 10:52:17	ga_ls8c_ard_3-0-0_106068_2018-08-23_final
2018-08-24 09:56:16	ga_ls8c_ard_3-0-0_097067_2018-08-24_final
2018-08-24 09:56:40	ga_ls8c_ard_3-0-0_097068_2018-08-24_final
2018-08-24 11:35:09	ga_ls8c_ard_3-0-0_113067_2018-08-24_final
2018-08-25 10:39:32	ga_ls8c_ard_3-0-0_104067_2018-08-25_final
2018-08-25 10:39:56	ga_ls8c_ard_3-1-0_104068_2018-08-25_final
2018-09-16 10:02:34	ga_ls8c_ard_3-0-0_098067_2018-09-16_final
2018-09-16 10:02:58	ga_ls8c_ard_3-0-0_098068_2018-09-16_final
2018-09-16 11:41:28	ga_ls8c_ard_3-0-0_114067_2018-09-16_final
2018-09-17 10:45:50	ga_ls8c_ard_3-0-0_105067_2018-09-17_final
2018-09-17 10:46:14	ga_ls8c_ard_3-0-0_105068_2018-09-17_final
2019-01-06 10:02:49	ga_ls8c_ard_3-0-0_098067_2019-01-06_final
2019-01-06 11:41:42	ga_ls8c_ard_3-0-0_114067_2019-01-06_final
2019-01-07 10:46:04	ga_ls8c_ard_3-0-0_105067_2019-01-07_final
2022-08-19 09:57:18	ga_ls8c_ard_3-2-1_097067_2022-08-19_final
2022-08-20 10:40:34	ga_ls8c_ard_3-2-1_104067_2022-08-20_final
2022-08-21 11:24:14	ga_ls8c_ard_3-2-1_111068_2022-08-21_final
2022-08-22 10:28:12	ga_ls8c_ard_3-2-1_102067_2022-08-22_final
2022-08-22 10:28:36	ga_ls8c_ard_3-2-1_102068_2022-08-22_final
2022-08-25 12:38:00	ga_ls8c_ard_3-2-1_123067_2022-08-25_final
2022-08-26 10:03:29	ga_ls8c_ard_3-2-1_098067_2022-08-26_final
2022-08-26 10:03:53	ga_ls8c_ard_3-2-1_098068_2022-08-26_final
2022-09-04 09:57:42	ga_ls8c_ard_3-2-1_097068_2022-09-04_final
2022-09-14 10:34:52	ga_ls8c_ard_3-2-1_103068_2022-09-14_final
2022-09-18 10:09:46	ga_ls8c_ard_3-2-1_099067_2022-09-18_final
2022-09-27 10:03:36	ga_ls8c_ard_3-2-1_098067_2022-09-27_final
2022-09-27 10:04:00	ga_ls8c_ard_3-2-1_098068_2022-09-27_final
2022-09-28 10:46:51	ga_ls8c_ard_3-2-1_105067_2022-09-28_final
2022-09-28 10:47:15	ga_ls8c_ard_3-2-1_105068_2022-09-28_final
2022-10-04 10:09:45	ga_ls8c_ard_3-2-1_099067_2022-10-04_final
2022-10-04 10:10:09	ga_ls8c_ard_3-2-1_099068_2022-10-04_final
2022-10-23 10:40:38	ga_ls8c_ard_3-2-1_104067_2022-10-23_final
2022-10-23 10:41:02	ga_ls8c_ard_3-2-1_104068_2022-10-23_final
2022-10-25 10:28:17	ga_ls8c_ard_3-2-1_102067_2022-10-25_final
2022-10-28 12:38:05	ga_ls8c_ard_3-2-1_123067_2022-10-28_final
2022-10-29 10:03:35	ga_ls8c_ard_3-2-1_098067_2022-10-29_final
2022-10-30 10:46:51	ga_ls8c_ard_3-2-1_105067_2022-10-30_final
2022-10-30 10:47:15	ga_ls8c_ard_3-2-1_105068_2022-10-30_final
2022-11-05 10:09:46	ga_ls8c_ard_3-2-1_099067_2022-11-05_final
2022-11-05 10:10:10	ga_ls8c_ard_3-2-1_099068_2022-11-05_final
2022-11-06 10:53:02	ga_ls8c_ard_3-2-1_106067_2022-11-06_final
2022-11-06 10:53:26	ga_ls8c_ard_3-2-1_106068_2022-11-06_final
2022-11-06 12:31:55	ga_ls8c_ard_3-2-1_122067_2022-11-06_final
2022-11-07 09:57:24	ga_ls8c_ard_3-2-1_097067_2022-11-07_final
2022-11-07 09:57:48	ga_ls8c_ard_3-2-1_097068_2022-11-07_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