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
2018-02-03 10:59:38	ga_ls8c_ard_3-0-0_107070_2018-02-03_final
2018-03-07 10:59:25	ga_ls8c_ard_3-0-0_107070_2018-03-07_final
2018-03-24 10:03:39	ga_ls8c_ard_3-0-0_098070_2018-03-24_final
2018-03-25 10:46:55	ga_ls8c_ard_3-0-0_105070_2018-03-25_final
2018-04-09 10:03:31	ga_ls8c_ard_3-0-0_098070_2018-04-09_final
2018-04-10 10:46:46	ga_ls8c_ard_3-0-0_105070_2018-04-10_final
2018-05-12 10:46:28	ga_ls8c_ard_3-0-0_105070_2018-05-12_final
2018-05-13 09:50:50	ga_ls8c_ard_3-0-0_096070_2018-05-13_final
2018-05-13 11:29:43	ga_ls8c_ard_3-0-0_112070_2018-05-13_final
2018-05-14 10:34:05	ga_ls8c_ard_3-0-0_103070_2018-05-14_final
2018-05-15 11:17:19	ga_ls8c_ard_3-0-0_110070_2018-05-15_final
2018-05-16 10:21:41	ga_ls8c_ard_3-0-0_101070_2018-05-16_final
2018-05-17 11:04:56	ga_ls8c_ard_3-0-0_108070_2018-05-17_final
2018-06-07 09:44:24	ga_ls8c_ard_3-0-0_095070_2018-06-07_final
2018-06-07 09:44:48	ga_ls8c_ard_3-0-0_095071_2018-06-07_final
2018-06-07 11:23:17	ga_ls8c_ard_3-0-0_111070_2018-06-07_final
2018-06-07 11:23:41	ga_ls8c_ard_3-0-0_111071_2018-06-07_final
2018-06-08 10:27:40	ga_ls8c_ard_3-0-0_102070_2018-06-08_final
2018-06-08 10:28:04	ga_ls8c_ard_3-0-0_102071_2018-06-08_final
2018-06-09 09:32:28	ga_ls8c_ard_3-0-0_093071_2018-06-09_final
2018-06-09 11:10:57	ga_ls8c_ard_3-0-0_109070_2018-06-09_final
2018-06-09 11:11:21	ga_ls8c_ard_3-0-0_109071_2018-06-09_final
2018-06-10 10:15:20	ga_ls8c_ard_3-1-0_100070_2018-06-10_final
2018-06-10 10:15:44	ga_ls8c_ard_3-0-0_100071_2018-06-10_final
2018-06-11 10:58:37	ga_ls8c_ard_3-0-0_107070_2018-06-11_final
2018-07-13 10:58:55	ga_ls8c_ard_3-0-0_107070_2018-07-13_final
2018-07-13 10:59:19	ga_ls8c_ard_3-0-0_107071_2018-07-13_final
2018-07-16 09:50:58	ga_ls8c_ard_3-0-0_096070_2018-07-16_final
2018-07-16 09:51:21	ga_ls8c_ard_3-0-0_096071_2018-07-16_final
2018-07-16 11:29:51	ga_ls8c_ard_3-0-0_112070_2018-07-16_final
2018-07-16 11:30:15	ga_ls8c_ard_3-0-0_112071_2018-07-16_final
2018-07-17 10:34:14	ga_ls8c_ard_3-0-0_103070_2018-07-17_final
2018-07-17 10:34:38	ga_ls8c_ard_3-0-0_103071_2018-07-17_final
2018-07-18 09:39:01	ga_ls8c_ard_3-0-0_094071_2018-07-18_final
2018-07-18 11:17:30	ga_ls8c_ard_3-0-0_110070_2018-07-18_final
2018-07-18 11:17:54	ga_ls8c_ard_3-0-0_110071_2018-07-18_final
2018-07-19 10:21:53	ga_ls8c_ard_3-0-0_101070_2018-07-19_final
2018-08-10 09:44:59	ga_ls8c_ard_3-0-0_095070_2018-08-10_final
2018-08-10 09:45:23	ga_ls8c_ard_3-0-0_095071_2018-08-10_final
2018-08-10 11:23:52	ga_ls8c_ard_3-0-0_111070_2018-08-10_final
2018-08-10 11:24:16	ga_ls8c_ard_3-0-0_111071_2018-08-10_final
2018-08-11 10:28:16	ga_ls8c_ard_3-0-0_102070_2018-08-11_final
2018-08-11 10:28:40	ga_ls8c_ard_3-0-0_102071_2018-08-11_final
2018-08-12 09:33:03	ga_ls8c_ard_3-0-0_093071_2018-08-12_final
2018-08-12 11:11:32	ga_ls8c_ard_3-0-0_109070_2018-08-12_final
2018-08-13 10:15:55	ga_ls8c_ard_3-0-0_100070_2018-08-13_final
2018-08-14 10:59:11	ga_ls8c_ard_3-0-0_107070_2018-08-14_final
2018-08-28 11:11:39	ga_ls8c_ard_3-0-0_109070_2018-08-28_final
2018-08-29 10:16:02	ga_ls8c_ard_3-0-0_100070_2018-08-29_final
2018-08-29 10:16:26	ga_ls8c_ard_3-0-0_100071_2018-08-29_final
2018-08-30 10:59:19	ga_ls8c_ard_3-0-0_107070_2018-08-30_final
2018-08-30 10:59:42	ga_ls8c_ard_3-0-0_107071_2018-08-30_final
2018-09-16 10:03:46	ga_ls8c_ard_3-0-0_098070_2018-09-16_final
2018-09-17 10:47:02	ga_ls8c_ard_3-0-0_105070_2018-09-17_final
2018-09-17 10:47:26	ga_ls8c_ard_3-0-0_105071_2018-09-17_final
2019-01-06 10:04:01	ga_ls8c_ard_3-0-0_098070_2019-01-06_final
2019-01-06 10:04:25	ga_ls8c_ard_3-0-0_098071_2019-01-06_final
2019-01-07 10:47:16	ga_ls8c_ard_3-0-0_105070_2019-01-07_final
2023-01-13 10:29:13	ga_ls8c_ard_3-2-1_102070_2023-01-13_final
2023-01-14 11:12:28	ga_ls8c_ard_3-2-1_109070_2023-01-14_final
2023-01-20 10:35:21	ga_ls8c_ard_3-2-1_103070_2023-01-20_final
2023-01-29 10:29:15	ga_ls8c_ard_3-2-1_102070_2023-01-29_final
2023-01-30 11:12:31	ga_ls8c_ard_3-2-1_109070_2023-01-30_final
2023-02-01 11:00:09	ga_ls8c_ard_3-2-1_107070_2023-02-01_final
2023-02-02 10:04:32	ga_ls8c_ard_3-2-1_098070_2023-02-02_final
2023-02-02 10:04:56	ga_ls8c_ard_3-2-1_098071_2023-02-02_final
2023-02-03 10:47:47	ga_ls8c_ard_3-2-1_105070_2023-02-03_final
2023-02-04 09:52:10	ga_ls8c_ard_3-2-1_096070_2023-02-04_final
2023-02-05 10:35:25	ga_ls8c_ard_3-2-1_103070_2023-02-05_final
2023-02-09 10:10:40	ga_ls8c_ard_3-2-1_099070_2023-02-09_final
2023-02-15 11:12:24	ga_ls8c_ard_3-2-1_109070_2023-02-15_final
2023-02-17 11:00:00	ga_ls8c_ard_3-2-1_107070_2023-02-17_final
2023-02-18 10:04:22	ga_ls8c_ard_3-2-1_098070_2023-02-18_final
2023-02-22 11:18:26	ga_ls8c_ard_3-2-1_110070_2023-02-22_final
2023-02-26 10:53:39	ga_ls8c_ard_3-2-1_106070_2023-02-26_final
2023-02-27 09:58:01	ga_ls8c_ard_3-2-1_097070_2023-02-27_final
2023-03-10 11:18:17	ga_ls8c_ard_3-2-1_110070_2023-03-10_final
2023-03-11 10:22:40	ga_ls8c_ard_3-2-1_101070_2023-03-11_final
2023-03-14 10:53:33	ga_ls8c_ard_3-2-1_106070_2023-03-14_final
2023-03-15 09:57:56	ga_ls8c_ard_3-2-1_097070_2023-03-15_final
2023-03-16 10:41:11	ga_ls8c_ard_3-2-1_104070_2023-03-16_final
2023-03-17 11:24:26	ga_ls8c_ard_3-2-1_111070_2023-03-17_final
2023-03-18 10:28:48	ga_ls8c_ard_3-2-1_102070_2023-03-18_final
2023-03-19 11:12:03	ga_ls8c_ard_3-2-1_109070_2023-03-19_final
2023-03-21 10:59:39	ga_ls8c_ard_3-2-1_107070_2023-03-21_final
2023-03-22 10:04:01	ga_ls8c_ard_3-2-1_098070_2023-03-22_final
2023-03-24 09:51:37	ga_ls8c_ard_3-2-1_096070_2023-03-24_final
2023-03-25 10:34:53	ga_ls8c_ard_3-2-1_103070_2023-03-25_final
2023-03-30 10:53:23	ga_ls8c_ard_3-2-1_106070_2023-03-30_final
2023-03-31 09:57:45	ga_ls8c_ard_3-2-1_097070_2023-03-31_final
2023-04-01 10:41:00	ga_ls8c_ard_3-2-1_104070_2023-04-01_final
2023-04-08 10:47:02	ga_ls8c_ard_3-2-1_105070_2023-04-08_final
2023-04-09 09:51:24	ga_ls8c_ard_3-2-1_096070_2023-04-09_final
2023-04-14 10:09:53	ga_ls8c_ard_3-2-1_099070_2023-04-14_final
2023-04-15 10:53:08	ga_ls8c_ard_3-2-1_106070_2023-04-15_final
2023-09-04 11:06:20	ga_ls8c_ard_3-2-1_108071_2023-09-04_final
2023-09-05 10:10:18	ga_ls8c_ard_3-2-1_099070_2023-09-05_final
2023-09-06 10:53:33	ga_ls8c_ard_3-2-1_106070_2023-09-06_final
2023-09-06 10:53:57	ga_ls8c_ard_3-2-1_106071_2023-09-06_final
2023-09-08 10:41:12	ga_ls8c_ard_3-2-1_104070_2023-09-08_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