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
2018-03-08 10:09:46	ga_ls8c_ard_3-0-0_098085_2018-03-08_final
2018-03-09 09:14:08	ga_ls8c_ard_3-0-0_089085_2018-03-08_final
2018-03-24 10:09:38	ga_ls8c_ard_3-0-0_098085_2018-03-24_final
2018-03-25 09:14:01	ga_ls8c_ard_3-0-0_089085_2018-03-24_final
2018-04-09 10:09:30	ga_ls8c_ard_3-0-0_098085_2018-04-09_final
2018-04-10 09:13:53	ga_ls8c_ard_3-0-0_089085_2018-04-09_final
2018-04-29 09:44:36	ga_ls8c_ard_3-0-0_094085_2018-04-29_final
2018-04-29 11:23:29	ga_ls8c_ard_3-0-0_110085_2018-04-29_final
2018-05-01 09:32:13	ga_ls8c_ard_3-0-0_092085_2018-05-01_final
2018-05-01 11:11:06	ga_ls8c_ard_3-0-0_108085_2018-05-01_final
2018-05-10 09:25:57	ga_ls8c_ard_3-0-0_091085_2018-05-09_final
2018-05-10 11:04:50	ga_ls8c_ard_3-0-0_107085_2018-05-10_final
2018-05-11 10:09:12	ga_ls8c_ard_3-0-0_098085_2018-05-11_final
2018-05-12 09:13:34	ga_ls8c_ard_3-0-0_089085_2018-05-11_final
2018-05-13 09:56:49	ga_ls8c_ard_3-0-0_096085_2018-05-13_final
2018-05-13 11:35:42	ga_ls8c_ard_3-0-0_112085_2018-05-13_final
2018-05-15 09:44:26	ga_ls8c_ard_3-0-0_094085_2018-05-15_final
2018-05-15 11:23:19	ga_ls8c_ard_3-0-0_110085_2018-05-15_final
2018-05-17 09:32:03	ga_ls8c_ard_3-0-0_092085_2018-05-17_final
2018-05-17 11:10:55	ga_ls8c_ard_3-0-0_108085_2018-05-17_final
2018-06-30 09:56:49	ga_ls8c_ard_3-0-0_096085_2018-06-30_final
2018-06-30 11:35:18	ga_ls8c_ard_3-0-0_112084_2018-06-30_final
2018-06-30 11:35:42	ga_ls8c_ard_3-0-0_112085_2018-06-30_final
2018-07-02 09:44:05	ga_ls8c_ard_3-1-0_094084_2018-07-02_final
2018-07-02 09:44:28	ga_ls8c_ard_3-0-0_094085_2018-07-02_final
2018-07-02 11:22:58	ga_ls8c_ard_3-0-0_110084_2018-07-02_final
2018-07-02 11:23:22	ga_ls8c_ard_3-0-0_110085_2018-07-02_final
2018-07-03 10:27:21	ga_ls8c_ard_3-0-0_101084_2018-07-03_final
2018-09-11 09:51:12	ga_ls8c_ard_3-0-0_095085_2018-09-11_final
2018-09-11 11:29:41	ga_ls8c_ard_3-0-0_111084_2018-09-11_final
2018-09-11 11:30:05	ga_ls8c_ard_3-0-0_111085_2018-09-11_final
2018-09-13 09:38:27	ga_ls8c_ard_3-0-0_093084_2018-09-13_final
2018-09-13 09:38:51	ga_ls8c_ard_3-0-0_093085_2018-09-13_final
2018-09-13 11:17:44	ga_ls8c_ard_3-0-0_109085_2018-09-13_final
2018-09-14 10:21:43	ga_ls8c_ard_3-0-0_100084_2018-09-14_final
2018-09-14 10:22:07	ga_ls8c_ard_3-0-0_100085_2018-09-14_final
2018-09-16 10:09:45	ga_ls8c_ard_3-0-0_098085_2018-09-16_final
2018-09-17 09:13:44	ga_ls8c_ard_3-0-0_089084_2018-09-16_final
2018-09-17 09:14:08	ga_ls8c_ard_3-0-0_089085_2018-09-16_final
2018-11-14 09:51:32	ga_ls8c_ard_3-0-0_095085_2018-11-14_final
2018-11-14 11:30:25	ga_ls8c_ard_3-0-0_111085_2018-11-14_final
2018-11-16 09:39:10	ga_ls8c_ard_3-0-0_093085_2018-11-16_final
2018-11-16 11:18:03	ga_ls8c_ard_3-0-0_109085_2018-11-16_final
2018-11-17 10:22:26	ga_ls8c_ard_3-0-0_100085_2018-11-17_final
2018-11-30 09:51:07	ga_ls8c_ard_3-0-0_095084_2018-11-30_final
2018-11-30 09:51:31	ga_ls8c_ard_3-0-0_095085_2018-11-30_final
2018-11-30 11:30:00	ga_ls8c_ard_3-0-0_111084_2018-11-30_final
2018-11-30 11:30:24	ga_ls8c_ard_3-0-0_111085_2018-11-30_final
2018-12-02 09:39:09	ga_ls8c_ard_3-0-0_093085_2018-12-02_final
2018-12-02 11:17:38	ga_ls8c_ard_3-0-0_109084_2018-12-02_final
2018-12-02 11:18:02	ga_ls8c_ard_3-0-0_109085_2018-12-02_final
2018-12-03 10:22:00	ga_ls8c_ard_3-0-0_100084_2018-12-03_final
2018-12-03 10:22:24	ga_ls8c_ard_3-0-0_100085_2018-12-03_final
2018-12-18 11:17:59	ga_ls8c_ard_3-0-0_109085_2018-12-18_final
2018-12-19 10:22:22	ga_ls8c_ard_3-0-0_100085_2018-12-19_final
2018-12-23 09:57:39	ga_ls8c_ard_3-0-0_096085_2018-12-23_final
2018-12-23 11:36:32	ga_ls8c_ard_3-0-0_112085_2018-12-23_final
2018-12-25 09:44:53	ga_ls8c_ard_3-0-0_094084_2018-12-25_final
2018-12-25 09:45:17	ga_ls8c_ard_3-0-0_094085_2018-12-25_final
2018-12-25 11:24:10	ga_ls8c_ard_3-0-0_110085_2018-12-25_final
2019-01-01 09:51:28	ga_ls8c_ard_3-0-0_095085_2019-01-01_final
2019-01-01 11:29:57	ga_ls8c_ard_3-0-0_111084_2019-01-01_final
2019-01-01 11:30:21	ga_ls8c_ard_3-0-0_111085_2019-01-01_final
2019-01-03 09:39:06	ga_ls8c_ard_3-0-0_093085_2019-01-03_final
2019-01-03 11:17:59	ga_ls8c_ard_3-0-0_109085_2019-01-03_final
2019-01-04 10:22:22	ga_ls8c_ard_3-0-0_100085_2019-01-04_final
2019-01-06 10:09:36	ga_ls8c_ard_3-0-0_098084_2019-01-06_final
2019-01-06 10:10:00	ga_ls8c_ard_3-0-0_098085_2019-01-06_final
2019-01-07 09:13:58	ga_ls8c_ard_3-0-0_089084_2019-01-06_final
2019-01-07 09:14:22	ga_ls8c_ard_3-0-0_089085_2019-01-06_final
2019-01-17 09:51:25	ga_ls8c_ard_3-0-0_095085_2019-01-17_final
2019-01-17 11:29:54	ga_ls8c_ard_3-0-0_111084_2019-01-17_final
2019-01-17 11:30:18	ga_ls8c_ard_3-0-0_111085_2019-01-17_final
2019-01-19 09:39:03	ga_ls8c_ard_3-0-0_093085_2019-01-19_final
2019-01-19 11:17:56	ga_ls8c_ard_3-0-0_109085_2019-01-19_final
2019-01-20 10:22:18	ga_ls8c_ard_3-0-0_100085_2019-01-20_final
2022-07-27 09:57:45	ga_ls8c_ard_3-2-1_096084_2022-07-27_final
2022-07-27 09:58:09	ga_ls8c_ard_3-2-1_096085_2022-07-27_final
2023-01-14 09:39:34	ga_ls8c_ard_3-2-1_093085_2023-01-14_final
2023-01-21 09:45:44	ga_ls8c_ard_3-2-1_094085_2023-01-21_final
2023-01-30 09:39:37	ga_ls8c_ard_3-2-1_093085_2023-01-30_final
2023-06-21 11:29:33	ga_ls8c_ard_3-2-1_111084_2023-06-21_final
2023-06-23 09:38:18	ga_ls8c_ard_3-2-1_093084_2023-06-23_final
2023-06-23 09:38:42	ga_ls8c_ard_3-2-1_093085_2023-06-23_final
2023-06-23 11:17:11	ga_ls8c_ard_3-2-1_109084_2023-06-23_final
2023-06-24 10:21:35	ga_ls8c_ard_3-2-1_100084_2023-06-24_final
2023-06-25 09:26:23	ga_ls8c_ard_3-2-1_091085_2023-06-24_final
2023-06-26 10:09:16	ga_ls8c_ard_3-2-1_098084_2023-06-26_final
2023-06-26 10:09:40	ga_ls8c_ard_3-2-1_098085_2023-06-26_final
2023-06-27 09:13:39	ga_ls8c_ard_3-2-1_089084_2023-06-26_final
2023-06-27 09:14:03	ga_ls8c_ard_3-2-1_089085_2023-06-26_final
2023-06-28 09:56:56	ga_ls8c_ard_3-2-1_096084_2023-06-28_final
2023-06-28 09:57:20	ga_ls8c_ard_3-2-1_096085_2023-06-28_final
2023-06-30 09:44:36	ga_ls8c_ard_3-2-1_094084_2023-06-30_final
2023-06-30 09:45:00	ga_ls8c_ard_3-2-1_094085_2023-06-30_final
2023-06-30 11:23:29	ga_ls8c_ard_3-2-1_110084_2023-06-30_final
2023-06-30 11:23:53	ga_ls8c_ard_3-2-1_110085_2023-06-30_final
2023-07-16 09:44:43	ga_ls8c_ard_3-2-1_094084_2023-07-16_final
2023-07-16 09:45:07	ga_ls8c_ard_3-2-1_094085_2023-07-16_final
2023-07-16 11:23:36	ga_ls8c_ard_3-2-1_110084_2023-07-16_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