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
2018-09-16 10:09:21	ga_ls8c_ard_3-0-0_098084_2018-09-16_final
2018-09-17 09:13:44	ga_ls8c_ard_3-0-0_089084_2018-09-16_final
2019-01-06 10:09:36	ga_ls8c_ard_3-0-0_098084_2019-01-06_final
2019-01-07 09:13:58	ga_ls8c_ard_3-0-0_089084_2019-01-06_final
2022-08-05 11:30:32	ga_ls8c_ard_3-2-1_111084_2022-08-05_final
2022-08-14 09:45:32	ga_ls8c_ard_3-2-1_094084_2022-08-14_final
2022-08-14 11:24:25	ga_ls8c_ard_3-2-1_110084_2022-08-14_final
2022-08-16 09:33:11	ga_ls8c_ard_3-2-1_092084_2022-08-16_final
2022-08-16 11:12:04	ga_ls8c_ard_3-2-1_108084_2022-08-16_final
2022-08-19 10:04:05	ga_ls8c_ard_3-2-1_097084_2022-08-19_final
2022-08-19 11:42:58	ga_ls8c_ard_3-2-1_113084_2022-08-19_final
2022-08-21 09:51:44	ga_ls8c_ard_3-2-1_095084_2022-08-21_final
2022-08-21 11:30:37	ga_ls8c_ard_3-2-1_111084_2022-08-21_final
2022-08-28 09:57:54	ga_ls8c_ard_3-2-1_096084_2022-08-28_final
2022-08-28 11:36:48	ga_ls8c_ard_3-2-1_112084_2022-08-28_final
2022-08-30 09:45:33	ga_ls8c_ard_3-2-1_094084_2022-08-30_final
2022-08-30 11:24:26	ga_ls8c_ard_3-2-1_110084_2022-08-30_final
2022-09-03 09:20:49	ga_ls8c_ard_3-2-1_090084_2022-09-02_final
2022-09-04 10:04:05	ga_ls8c_ard_3-2-1_097084_2022-09-04_final
2022-09-04 11:42:58	ga_ls8c_ard_3-2-1_113084_2022-09-04_final
2022-09-06 09:51:45	ga_ls8c_ard_3-2-1_095084_2022-09-06_final
2022-09-06 11:30:38	ga_ls8c_ard_3-2-1_111084_2022-09-06_final
2022-09-08 09:39:25	ga_ls8c_ard_3-2-1_093084_2022-09-08_final
2022-09-08 11:18:18	ga_ls8c_ard_3-2-1_109084_2022-09-08_final
2022-09-09 10:22:41	ga_ls8c_ard_3-2-1_100084_2022-09-09_final
2022-09-10 09:27:04	ga_ls8c_ard_3-2-1_091084_2022-09-09_final
2022-09-10 11:05:57	ga_ls8c_ard_3-2-1_107084_2022-09-10_final
2022-09-11 10:10:20	ga_ls8c_ard_3-2-1_098084_2022-09-11_final
2022-09-12 09:14:43	ga_ls8c_ard_3-2-1_089084_2022-09-11_final
2022-10-12 09:26:59	ga_ls8c_ard_3-2-1_091084_2022-10-11_final
2022-10-12 11:05:52	ga_ls8c_ard_3-2-1_107084_2022-10-12_final
2022-10-13 10:10:14	ga_ls8c_ard_3-2-1_098084_2022-10-13_final
2022-10-14 09:14:36	ga_ls8c_ard_3-2-1_089084_2022-10-13_final
2022-10-15 09:57:53	ga_ls8c_ard_3-2-1_096084_2022-10-15_final
2022-10-15 11:36:46	ga_ls8c_ard_3-2-1_112084_2022-10-15_final
2022-10-17 09:45:33	ga_ls8c_ard_3-2-1_094084_2022-10-17_final
2022-10-17 11:24:26	ga_ls8c_ard_3-2-1_110084_2022-10-17_final
2022-10-19 09:33:13	ga_ls8c_ard_3-2-1_092084_2022-10-19_final
2022-10-19 11:12:06	ga_ls8c_ard_3-2-1_108084_2022-10-19_final
2022-10-20 10:16:29	ga_ls8c_ard_3-2-1_099084_2022-10-20_final
2022-10-21 09:20:52	ga_ls8c_ard_3-2-1_090084_2022-10-20_final
2022-10-22 10:04:09	ga_ls8c_ard_3-2-1_097084_2022-10-22_final
2022-10-22 11:43:02	ga_ls8c_ard_3-2-1_113084_2022-10-22_final
2022-10-24 09:51:48	ga_ls8c_ard_3-2-1_095084_2022-10-24_final
2022-10-26 11:18:20	ga_ls8c_ard_3-2-1_109084_2022-10-26_final
2022-10-27 10:22:43	ga_ls8c_ard_3-2-1_100084_2022-10-27_final
2022-10-28 09:27:06	ga_ls8c_ard_3-2-1_091084_2022-10-27_final
2022-10-31 09:58:01	ga_ls8c_ard_3-2-1_096084_2022-10-31_final
2022-10-31 11:36:54	ga_ls8c_ard_3-2-1_112084_2022-10-31_final
2022-11-02 09:45:39	ga_ls8c_ard_3-2-1_094084_2022-11-02_final
2022-11-02 11:24:32	ga_ls8c_ard_3-2-1_110084_2022-11-02_final
2022-11-04 09:33:18	ga_ls8c_ard_3-2-1_092084_2022-11-04_final
2022-11-04 11:12:11	ga_ls8c_ard_3-2-1_108084_2022-11-04_final
2022-11-05 10:16:33	ga_ls8c_ard_3-2-1_099084_2022-11-05_final
2022-11-06 09:20:56	ga_ls8c_ard_3-2-1_090084_2022-11-05_final
2022-11-07 10:04:11	ga_ls8c_ard_3-2-1_097084_2022-11-07_final
2022-11-07 11:43:04	ga_ls8c_ard_3-2-1_113084_2022-11-07_final
2022-12-07 10:16:28	ga_ls8c_ard_3-2-1_099084_2022-12-07_final
2022-12-08 09:20:50	ga_ls8c_ard_3-2-1_090084_2022-12-07_final
2022-12-09 10:04:06	ga_ls8c_ard_3-2-1_097084_2022-12-09_final
2022-12-09 11:42:59	ga_ls8c_ard_3-2-1_113084_2022-12-09_final
2023-04-29 11:11:02	ga_ls8c_ard_3-2-1_108084_2023-04-29_final
2023-04-30 10:15:24	ga_ls8c_ard_3-2-1_099084_2023-04-30_final
2023-05-01 09:19:46	ga_ls8c_ard_3-2-1_090084_2023-04-30_final
2023-05-02 10:03:01	ga_ls8c_ard_3-2-1_097084_2023-05-02_final
2023-05-02 11:41:54	ga_ls8c_ard_3-2-1_113084_2023-05-02_final
2023-05-22 09:38:07	ga_ls8c_ard_3-2-1_093084_2023-05-22_final
2023-05-24 11:04:39	ga_ls8c_ard_3-2-1_107084_2023-05-24_final
2023-05-25 10:09:02	ga_ls8c_ard_3-2-1_098084_2023-05-25_final
2023-05-26 09:13:25	ga_ls8c_ard_3-2-1_089084_2023-05-25_final
2023-05-27 09:56:41	ga_ls8c_ard_3-2-1_096084_2023-05-27_final
2023-05-27 11:35:34	ga_ls8c_ard_3-2-1_112084_2023-05-27_final
2023-05-29 09:44:19	ga_ls8c_ard_3-2-1_094084_2023-05-29_final
2023-05-29 11:23:12	ga_ls8c_ard_3-2-1_110084_2023-05-29_final
2023-06-14 11:23:21	ga_ls8c_ard_3-2-1_110084_2023-06-14_final
2023-06-16 09:32:07	ga_ls8c_ard_3-2-1_092084_2023-06-16_final
2023-06-16 11:11:00	ga_ls8c_ard_3-2-1_108084_2023-06-16_final
2023-06-17 10:14:59	ga_ls8c_ard_3-2-1_099083_2023-06-17_final
2023-06-17 10:15:23	ga_ls8c_ard_3-2-1_099084_2023-06-17_final
2023-07-18 11:11:14	ga_ls8c_ard_3-2-1_108084_2023-07-18_final
2023-07-19 10:15:37	ga_ls8c_ard_3-2-1_099084_2023-07-19_final
2023-09-27 11:17:50	ga_ls8c_ard_3-2-1_109084_2023-09-27_final
2023-09-28 10:22:13	ga_ls8c_ard_3-2-1_100084_2023-09-28_final
2023-09-29 09:26:36	ga_ls8c_ard_3-2-1_091084_2023-09-28_final
2023-10-01 09:14:14	ga_ls8c_ard_3-2-1_089084_2023-09-30_final
2023-10-02 09:57:30	ga_ls8c_ard_3-2-1_096084_2023-10-02_final
2023-10-02 11:36:23	ga_ls8c_ard_3-2-1_112084_2023-10-02_final
2023-10-04 09:45:08	ga_ls8c_ard_3-2-1_094084_2023-10-04_final
2023-10-04 11:24:01	ga_ls8c_ard_3-2-1_110084_2023-10-04_final
2023-10-06 09:32:46	ga_ls8c_ard_3-2-1_092084_2023-10-06_final
2023-10-06 11:11:39	ga_ls8c_ard_3-2-1_108084_2023-10-06_final
2023-10-07 10:16:02	ga_ls8c_ard_3-2-1_099084_2023-10-07_final
2023-10-08 09:20:26	ga_ls8c_ard_3-2-1_090084_2023-10-07_final
2023-10-09 10:03:42	ga_ls8c_ard_3-2-1_097084_2023-10-09_final
2023-10-09 11:42:35	ga_ls8c_ard_3-2-1_113084_2023-10-09_final
2023-10-11 09:51:21	ga_ls8c_ard_3-2-1_095084_2023-10-11_final
2023-10-11 11:30:14	ga_ls8c_ard_3-2-1_111084_2023-10-11_final
2023-10-13 09:39:00	ga_ls8c_ard_3-2-1_093084_2023-10-13_final
2023-10-13 11:17:53	ga_ls8c_ard_3-2-1_109084_2023-10-13_final
2023-10-15 09:26:38	ga_ls8c_ard_3-2-1_091084_2023-10-14_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