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
2019-07-08 10:10:15	ga_ls8c_ard_3-1-0_099070_2019-07-08_final
2019-07-08 10:10:39	ga_ls8c_ard_3-1-0_099071_2019-07-08_final
2019-07-09 10:53:31	ga_ls8c_ard_3-1-0_106070_2019-07-09_final
2019-07-09 10:53:55	ga_ls8c_ard_3-1-0_106071_2019-07-09_final
2019-07-10 09:58:18	ga_ls8c_ard_3-1-0_097071_2019-07-10_final
2019-07-10 11:37:11	ga_ls8c_ard_3-1-0_113071_2019-07-10_final
2019-08-26 10:53:46	ga_ls8c_ard_3-1-0_106070_2019-08-26_final
2019-08-26 10:54:10	ga_ls8c_ard_3-1-0_106071_2019-08-26_final
2019-08-27 09:58:33	ga_ls8c_ard_3-1-0_097071_2019-08-27_final
2019-08-27 11:37:26	ga_ls8c_ard_3-1-0_113071_2019-08-27_final
2019-09-16 09:33:55	ga_ls8c_ard_3-1-0_093071_2019-09-16_final
2019-09-16 11:12:25	ga_ls8c_ard_3-1-0_109070_2019-09-16_final
2019-09-16 11:12:48	ga_ls8c_ard_3-1-0_109071_2019-09-16_final
2019-09-17 10:17:11	ga_ls8c_ard_3-1-0_100071_2019-09-17_final
2019-09-18 11:00:28	ga_ls8c_ard_3-1-0_107071_2019-09-18_final
2019-10-14 09:58:21	ga_ls8c_ard_3-1-0_097070_2019-10-14_final
2019-10-14 09:58:45	ga_ls8c_ard_3-1-0_097071_2019-10-14_final
2019-10-14 11:37:38	ga_ls8c_ard_3-1-0_113071_2019-10-14_final
2019-10-15 10:41:37	ga_ls8c_ard_3-1-0_104070_2019-10-15_final
2019-10-15 10:42:01	ga_ls8c_ard_3-1-0_104071_2019-10-15_final
2019-10-16 09:46:00	ga_ls8c_ard_3-1-0_095070_2019-10-16_final
2019-10-16 09:46:24	ga_ls8c_ard_3-1-0_095071_2019-10-16_final
2019-10-16 11:24:53	ga_ls8c_ard_3-1-0_111070_2019-10-16_final
2019-10-16 11:25:17	ga_ls8c_ard_3-1-0_111071_2019-10-16_final
2019-11-26 09:40:09	ga_ls8c_ard_3-1-0_094071_2019-11-26_final
2019-11-26 11:18:38	ga_ls8c_ard_3-1-0_110070_2019-11-26_final
2019-11-26 11:19:02	ga_ls8c_ard_3-1-0_110071_2019-11-26_final
2019-11-27 10:23:24	ga_ls8c_ard_3-1-0_101071_2019-11-27_final
2019-11-28 09:27:47	ga_ls8c_ard_3-1-0_092071_2019-11-27_final
2019-11-28 11:06:16	ga_ls8c_ard_3-1-0_108070_2019-11-28_final
2019-11-28 11:06:40	ga_ls8c_ard_3-1-0_108071_2019-11-28_final
2019-12-01 09:58:17	ga_ls8c_ard_3-1-0_097070_2019-12-01_final
2019-12-01 09:58:41	ga_ls8c_ard_3-1-0_097071_2019-12-01_final
2019-12-01 11:37:34	ga_ls8c_ard_3-1-0_113071_2019-12-01_final
2019-12-02 10:41:33	ga_ls8c_ard_3-1-0_104070_2019-12-02_final
2019-12-02 10:41:57	ga_ls8c_ard_3-1-0_104071_2019-12-02_final
2019-12-03 09:46:19	ga_ls8c_ard_3-1-0_095071_2019-12-03_final
2019-12-03 11:24:48	ga_ls8c_ard_3-1-0_111070_2019-12-03_final
2019-12-03 11:25:12	ga_ls8c_ard_3-1-0_111071_2019-12-03_final
2021-01-05 10:41:53	ga_ls8c_ard_3-2-0_104071_2021-01-05_final
2021-01-06 09:46:15	ga_ls8c_ard_3-2-0_095071_2021-01-06_final
2021-01-06 11:24:44	ga_ls8c_ard_3-2-0_111070_2021-01-06_final
2021-01-06 11:25:08	ga_ls8c_ard_3-2-0_111071_2021-01-06_final
2021-01-07 10:29:06	ga_ls8c_ard_3-2-0_102070_2021-01-07_final
2021-01-07 10:29:30	ga_ls8c_ard_3-2-0_102071_2021-01-07_final
2021-01-31 11:18:50	ga_ls8c_ard_3-2-0_110071_2021-01-31_final
2021-02-01 10:23:13	ga_ls8c_ard_3-2-0_101071_2021-02-01_final
2021-02-02 09:27:35	ga_ls8c_ard_3-2-0_092071_2021-02-01_final
2021-02-02 11:06:05	ga_ls8c_ard_3-2-0_108070_2021-02-02_final
2021-02-02 11:06:28	ga_ls8c_ard_3-2-0_108071_2021-02-02_final
2021-02-03 10:10:51	ga_ls8c_ard_3-2-0_099071_2021-02-03_final
2021-04-07 09:27:12	ga_ls8c_ard_3-2-0_092071_2021-04-06_final
2021-04-07 11:06:05	ga_ls8c_ard_3-2-0_108071_2021-04-07_final
2021-04-08 10:10:28	ga_ls8c_ard_3-2-0_099071_2021-04-08_final
2021-04-09 10:53:43	ga_ls8c_ard_3-2-0_106071_2021-04-09_final
2021-04-10 09:58:05	ga_ls8c_ard_3-2-0_097071_2021-04-10_final
2021-08-21 10:16:41	ga_ls8c_ard_3-2-0_100070_2021-08-21_final
2021-08-21 10:17:05	ga_ls8c_ard_3-2-0_100071_2021-08-21_final
2021-08-22 10:59:57	ga_ls8c_ard_3-2-0_107070_2021-08-22_final
2021-08-22 11:00:21	ga_ls8c_ard_3-2-0_107071_2021-08-22_final
2021-08-23 10:04:20	ga_ls8c_ard_3-2-0_098070_2021-08-23_final
2021-08-23 10:04:44	ga_ls8c_ard_3-2-0_098071_2021-08-23_final
2021-08-28 10:23:17	ga_ls8c_ard_3-2-0_101071_2021-08-28_final
2021-08-29 09:27:40	ga_ls8c_ard_3-2-0_092071_2021-08-28_final
2021-08-29 11:06:09	ga_ls8c_ard_3-2-0_108070_2021-08-29_final
2021-08-29 11:06:33	ga_ls8c_ard_3-2-0_108071_2021-08-29_final
2021-08-30 10:10:32	ga_ls8c_ard_3-2-0_099070_2021-08-30_final
2021-08-30 10:10:56	ga_ls8c_ard_3-2-0_099071_2021-08-30_final
2023-02-09 10:11:04	ga_ls8c_ard_3-2-1_099071_2023-02-09_final
2023-02-10 10:54:19	ga_ls8c_ard_3-2-1_106071_2023-02-10_final
2023-02-11 09:58:41	ga_ls8c_ard_3-2-1_097071_2023-02-11_final
2023-02-12 10:41:56	ga_ls8c_ard_3-2-1_104071_2023-02-12_final
2023-02-13 09:46:18	ga_ls8c_ard_3-2-1_095071_2023-02-13_final
2023-02-13 11:25:11	ga_ls8c_ard_3-2-1_111071_2023-02-13_final
2023-02-14 10:29:33	ga_ls8c_ard_3-2-1_102071_2023-02-14_final
2023-02-15 09:33:55	ga_ls8c_ard_3-2-1_093071_2023-02-15_final
2023-02-18 10:04:46	ga_ls8c_ard_3-2-1_098071_2023-02-18_final
2023-02-19 10:47:36	ga_ls8c_ard_3-2-1_105070_2023-02-19_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
2023-02-27 09:58:25	ga_ls8c_ard_3-2-1_097071_2023-02-27_final
2023-02-28 10:41:41	ga_ls8c_ard_3-2-1_104071_2023-02-28_final
2023-03-01 09:46:04	ga_ls8c_ard_3-2-1_095071_2023-03-01_final
2023-03-01 11:24:57	ga_ls8c_ard_3-2-1_111071_2023-03-01_final
2023-03-02 10:29:19	ga_ls8c_ard_3-2-1_102071_2023-03-02_final
2023-03-03 09:33:41	ga_ls8c_ard_3-2-1_093071_2023-03-03_final
2023-03-03 11:12:34	ga_ls8c_ard_3-2-1_109071_2023-03-03_final
2023-03-04 10:16:57	ga_ls8c_ard_3-2-1_100071_2023-03-04_final
2023-03-05 11:00:12	ga_ls8c_ard_3-2-1_107071_2023-03-05_final
2023-03-06 10:04:34	ga_ls8c_ard_3-2-1_098071_2023-03-06_final
2023-05-26 10:46:43	ga_ls8c_ard_3-2-1_105070_2023-05-26_final
2023-05-26 10:47:07	ga_ls8c_ard_3-2-1_105071_2023-05-26_final
2023-05-27 09:51:06	ga_ls8c_ard_3-2-1_096070_2023-05-27_final
2023-05-27 09:51:30	ga_ls8c_ard_3-2-1_096071_2023-05-27_final
2023-05-28 10:34:45	ga_ls8c_ard_3-2-1_103071_2023-05-28_final
2023-05-29 11:17:37	ga_ls8c_ard_3-2-1_110070_2023-05-29_final
2023-05-30 10:22:00	ga_ls8c_ard_3-2-1_101070_2023-05-30_final
2023-05-30 10:22:24	ga_ls8c_ard_3-2-1_101071_2023-05-30_final
2023-05-31 09:26:46	ga_ls8c_ard_3-2-1_092071_2023-05-30_final
2023-05-31 11:05:15	ga_ls8c_ard_3-2-1_108070_2023-05-31_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years