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 09:52:02	ga_ls8c_ard_3-0-0_096071_2018-02-06_final
2018-02-06 11:30:55	ga_ls8c_ard_3-0-0_112071_2018-02-06_final
2018-02-06 11:31:19	ga_ls8c_ard_3-0-0_112072_2018-02-06_final
2018-02-07 10:35:18	ga_ls8c_ard_3-0-0_103071_2018-02-07_final
2018-02-08 09:39:40	ga_ls8c_ard_3-0-0_094071_2018-02-08_final
2018-02-08 11:18:33	ga_ls8c_ard_3-0-0_110071_2018-02-08_final
2018-02-09 10:22:56	ga_ls8c_ard_3-0-0_101071_2018-02-09_final
2018-02-22 09:51:57	ga_ls8c_ard_3-0-0_096071_2018-02-22_final
2018-02-22 11:30:50	ga_ls8c_ard_3-0-0_112071_2018-02-22_final
2018-02-22 11:31:14	ga_ls8c_ard_3-0-0_112072_2018-02-22_final
2018-02-23 10:35:12	ga_ls8c_ard_3-0-0_103071_2018-02-23_final
2018-02-24 09:39:34	ga_ls8c_ard_3-0-0_094071_2018-02-24_final
2018-02-24 11:18:27	ga_ls8c_ard_3-0-0_110071_2018-02-24_final
2018-02-24 11:18:51	ga_ls8c_ard_3-0-0_110072_2018-02-24_final
2018-02-25 10:22:49	ga_ls8c_ard_3-0-0_101071_2018-02-25_final
2018-03-26 09:51:41	ga_ls8c_ard_3-0-0_096071_2018-03-26_final
2018-03-26 11:30:34	ga_ls8c_ard_3-0-0_112071_2018-03-26_final
2018-03-27 10:34:56	ga_ls8c_ard_3-0-0_103071_2018-03-27_final
2018-03-28 09:39:18	ga_ls8c_ard_3-0-0_094071_2018-03-28_final
2018-03-28 11:18:11	ga_ls8c_ard_3-0-0_110071_2018-03-28_final
2018-03-29 10:22:33	ga_ls8c_ard_3-0-0_101071_2018-03-29_final
2018-09-16 10:04:10	ga_ls8c_ard_3-0-0_098071_2018-09-16_final
2018-09-16 10:04:34	ga_ls8c_ard_3-0-0_098072_2018-09-16_final
2018-09-17 10:47:26	ga_ls8c_ard_3-0-0_105071_2018-09-17_final
2018-09-17 10:47:50	ga_ls8c_ard_3-0-0_105072_2018-09-17_final
2019-01-06 10:04:25	ga_ls8c_ard_3-0-0_098071_2019-01-06_final
2019-01-06 10:04:48	ga_ls8c_ard_3-0-0_098072_2019-01-06_final
2019-01-07 10:47:40	ga_ls8c_ard_3-0-0_105071_2019-01-07_final
2019-01-07 10:48:04	ga_ls8c_ard_3-0-0_105072_2019-01-07_final
2023-02-01 11:00:33	ga_ls8c_ard_3-2-1_107071_2023-02-01_final
2023-02-02 10:04:56	ga_ls8c_ard_3-2-1_098071_2023-02-02_final
2023-02-03 10:48:11	ga_ls8c_ard_3-2-1_105071_2023-02-03_final
2023-02-04 09:52:34	ga_ls8c_ard_3-2-1_096071_2023-02-04_final
2023-02-15 11:12:48	ga_ls8c_ard_3-2-1_109071_2023-02-15_final
2023-02-16 10:17:09	ga_ls8c_ard_3-2-1_100071_2023-02-16_final
2023-02-19 10:48:00	ga_ls8c_ard_3-2-1_105071_2023-02-19_final
2023-02-20 09:52:22	ga_ls8c_ard_3-2-1_096071_2023-02-20_final
2023-02-25 10:10:47	ga_ls8c_ard_3-2-1_099071_2023-02-25_final
2023-02-26 10:54:03	ga_ls8c_ard_3-2-1_106071_2023-02-26_final
2023-02-27 09:58:25	ga_ls8c_ard_3-2-1_097071_2023-02-27_final
2023-02-27 09:58:49	ga_ls8c_ard_3-2-1_097072_2023-02-27_final
2023-02-28 10:41:41	ga_ls8c_ard_3-2-1_104071_2023-02-28_final
2023-04-25 09:51:42	ga_ls8c_ard_3-2-1_096071_2023-04-25_final
2023-04-27 09:39:20	ga_ls8c_ard_3-2-1_094071_2023-04-27_final
2023-04-27 11:18:13	ga_ls8c_ard_3-2-1_110071_2023-04-27_final
2023-04-28 10:22:35	ga_ls8c_ard_3-2-1_101071_2023-04-28_final
2023-05-04 11:24:20	ga_ls8c_ard_3-2-1_111071_2023-05-04_final
2023-05-05 10:28:42	ga_ls8c_ard_3-2-1_102071_2023-05-05_final
2023-05-06 09:33:03	ga_ls8c_ard_3-2-1_093071_2023-05-06_final
2023-05-10 10:47:09	ga_ls8c_ard_3-2-1_105071_2023-05-10_final
2023-05-11 09:51:30	ga_ls8c_ard_3-2-1_096071_2023-05-11_final
2023-05-12 10:34:45	ga_ls8c_ard_3-2-1_103071_2023-05-12_final
2023-05-13 09:39:07	ga_ls8c_ard_3-2-1_094071_2023-05-13_final
2023-05-14 10:22:22	ga_ls8c_ard_3-2-1_101071_2023-05-14_final
2023-05-15 09:26:44	ga_ls8c_ard_3-2-1_092071_2023-05-14_final
2023-05-17 10:53:15	ga_ls8c_ard_3-2-1_106071_2023-05-17_final
2023-05-18 09:57:37	ga_ls8c_ard_3-2-1_097071_2023-05-18_final
2023-05-18 09:58:01	ga_ls8c_ard_3-2-1_097072_2023-05-18_final
2023-05-18 11:36:54	ga_ls8c_ard_3-2-1_113072_2023-05-18_final
2023-05-31 09:26:46	ga_ls8c_ard_3-2-1_092071_2023-05-30_final
2023-05-31 09:27:10	ga_ls8c_ard_3-2-1_092072_2023-05-30_final
2023-05-31 11:05:39	ga_ls8c_ard_3-2-1_108071_2023-05-31_final
2023-05-31 11:06:03	ga_ls8c_ard_3-2-1_108072_2023-05-31_final
2023-06-01 10:10:02	ga_ls8c_ard_3-2-1_099071_2023-06-01_final
2023-06-01 10:10:26	ga_ls8c_ard_3-2-1_099072_2023-06-01_final
2023-06-02 10:53:18	ga_ls8c_ard_3-2-1_106071_2023-06-02_final
2023-06-02 10:53:42	ga_ls8c_ard_3-2-1_106072_2023-06-02_final
2023-06-03 09:57:41	ga_ls8c_ard_3-2-1_097071_2023-06-03_final
2023-06-03 09:58:05	ga_ls8c_ard_3-2-1_097072_2023-06-03_final
2023-06-03 11:36:58	ga_ls8c_ard_3-2-1_113072_2023-06-03_final
2023-06-04 10:40:58	ga_ls8c_ard_3-2-1_104071_2023-06-04_final
2023-06-04 10:41:22	ga_ls8c_ard_3-2-1_104072_2023-06-04_final
2023-06-05 09:45:22	ga_ls8c_ard_3-2-1_095071_2023-06-05_final
2023-06-05 09:45:46	ga_ls8c_ard_3-2-1_095072_2023-06-05_final
2023-06-05 11:24:15	ga_ls8c_ard_3-2-1_111071_2023-06-05_final
2023-06-05 11:24:39	ga_ls8c_ard_3-2-1_111072_2023-06-05_final
2023-06-21 11:24:21	ga_ls8c_ard_3-2-1_111071_2023-06-21_final
2023-06-21 11:24:45	ga_ls8c_ard_3-2-1_111072_2023-06-21_final
2023-06-22 10:28:44	ga_ls8c_ard_3-2-1_102071_2023-06-22_final
2023-06-22 10:29:08	ga_ls8c_ard_3-2-1_102072_2023-06-22_final
2023-06-23 09:33:07	ga_ls8c_ard_3-2-1_093071_2023-06-23_final
2023-06-23 09:33:31	ga_ls8c_ard_3-2-1_093072_2023-06-23_final
2023-06-23 11:12:00	ga_ls8c_ard_3-2-1_109071_2023-06-23_final
2023-06-23 11:12:24	ga_ls8c_ard_3-2-1_109072_2023-06-23_final
2023-06-24 10:16:24	ga_ls8c_ard_3-2-1_100071_2023-06-24_final
2023-06-24 10:16:48	ga_ls8c_ard_3-2-1_100072_2023-06-24_final
2023-06-25 09:21:12	ga_ls8c_ard_3-2-1_091072_2023-06-24_final
2023-06-27 10:47:21	ga_ls8c_ard_3-2-1_105071_2023-06-27_final
2023-06-28 11:31:02	ga_ls8c_ard_3-2-1_112072_2023-06-28_final
2023-06-29 10:35:01	ga_ls8c_ard_3-2-1_103071_2023-06-29_final
2023-06-29 10:35:25	ga_ls8c_ard_3-2-1_103072_2023-06-29_final
2023-06-30 09:39:25	ga_ls8c_ard_3-2-1_094071_2023-06-30_final
2023-06-30 09:39:49	ga_ls8c_ard_3-2-1_094072_2023-06-30_final
2023-07-04 10:53:38	ga_ls8c_ard_3-2-1_106071_2023-07-04_final
2023-07-04 10:54:02	ga_ls8c_ard_3-2-1_106072_2023-07-04_final
2023-07-05 09:58:01	ga_ls8c_ard_3-2-1_097071_2023-07-05_final
2023-07-05 09:58:25	ga_ls8c_ard_3-2-1_097072_2023-07-05_final
2023-07-09 11:12:13	ga_ls8c_ard_3-2-1_109071_2023-07-09_final
2023-07-09 11:12:37	ga_ls8c_ard_3-2-1_109072_2023-07-09_final
2023-07-10 10:16:36	ga_ls8c_ard_3-2-1_100071_2023-07-10_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