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
2018-02-20 10:02:43	ga_ls8c_ard_3-0-0_098067_2018-02-20_final
2018-02-20 10:03:07	ga_ls8c_ard_3-0-0_098068_2018-02-20_final
2018-02-20 10:03:31	ga_ls8c_ard_3-0-0_098069_2018-02-20_final
2018-02-20 10:03:55	ga_ls8c_ard_3-0-0_098070_2018-02-20_final
2018-04-09 10:02:20	ga_ls8c_ard_3-0-0_098067_2018-04-09_final
2018-04-09 10:02:44	ga_ls8c_ard_3-0-0_098068_2018-04-09_final
2018-04-09 10:03:07	ga_ls8c_ard_3-0-0_098069_2018-04-09_final
2018-04-09 10:03:31	ga_ls8c_ard_3-0-0_098070_2018-04-09_final
2018-05-13 09:52:25	ga_ls8c_ard_3-0-0_096074_2018-05-13_final
2018-05-13 09:52:49	ga_ls8c_ard_3-0-0_096075_2018-05-13_final
2018-05-13 09:53:13	ga_ls8c_ard_3-0-0_096076_2018-05-13_final
2018-05-13 09:53:37	ga_ls8c_ard_3-0-0_096077_2018-05-13_final
2018-05-13 09:54:01	ga_ls8c_ard_3-0-0_096078_2018-05-13_final
2018-05-13 09:54:25	ga_ls8c_ard_3-0-0_096079_2018-05-13_final
2018-05-13 09:54:49	ga_ls8c_ard_3-0-0_096080_2018-05-13_final
2019-01-06 10:02:49	ga_ls8c_ard_3-0-0_098067_2019-01-06_final
2019-01-06 10:03:13	ga_ls8c_ard_3-0-0_098068_2019-01-06_final
2019-01-06 10:03:37	ga_ls8c_ard_3-0-0_098069_2019-01-06_final
2019-01-06 10:04:01	ga_ls8c_ard_3-0-0_098070_2019-01-06_final
2022-04-15 09:48:38	ga_ls8c_ard_3-2-1_095078_2022-04-15_final
2022-04-15 09:49:02	ga_ls8c_ard_3-2-1_095079_2022-04-15_final
2022-04-15 09:49:26	ga_ls8c_ard_3-2-1_095080_2022-04-15_final
2022-04-15 09:49:50	ga_ls8c_ard_3-2-1_095081_2022-04-15_final
2022-04-15 09:50:14	ga_ls8c_ard_3-2-1_095082_2022-04-15_final
2022-04-15 09:50:38	ga_ls8c_ard_3-2-1_095083_2022-04-15_final
2022-04-15 09:51:02	ga_ls8c_ard_3-2-1_095084_2022-04-15_final
2022-04-17 09:39:28	ga_ls8c_ard_3-2-1_093086_2022-04-17_final
2022-04-17 09:39:52	ga_ls8c_ard_3-2-1_093087_2022-04-17_final
2022-04-17 09:40:16	ga_ls8c_ard_3-2-1_093088_2022-04-17_final
2022-04-20 10:02:22	ga_ls8c_ard_3-2-1_098066_2022-04-20_final
2022-04-20 10:02:46	ga_ls8c_ard_3-2-1_098067_2022-04-20_final
2022-04-20 10:03:10	ga_ls8c_ard_3-2-1_098068_2022-04-20_final
2022-04-20 10:03:34	ga_ls8c_ard_3-2-1_098069_2022-04-20_final
2022-04-20 10:03:58	ga_ls8c_ard_3-2-1_098070_2022-04-20_final
2022-04-26 09:34:26	ga_ls8c_ard_3-2-1_092089_2022-04-26_final
2022-04-26 09:34:50	ga_ls8c_ard_3-2-1_092090_2022-04-26_final
2022-04-29 09:57:43	ga_ls8c_ard_3-2-1_097070_2022-04-29_final
2022-04-29 09:58:07	ga_ls8c_ard_3-2-1_097071_2022-04-29_final
2022-04-29 09:58:31	ga_ls8c_ard_3-2-1_097072_2022-04-29_final
2022-04-29 09:58:55	ga_ls8c_ard_3-2-1_097073_2022-04-29_final
2022-04-29 09:59:19	ga_ls8c_ard_3-2-1_097074_2022-04-29_final
2022-04-29 09:59:43	ga_ls8c_ard_3-2-1_097075_2022-04-29_final
2022-05-08 09:53:15	ga_ls8c_ard_3-2-1_096074_2022-05-08_final
2022-05-08 09:53:39	ga_ls8c_ard_3-2-1_096075_2022-05-08_final
2022-05-08 09:54:03	ga_ls8c_ard_3-2-1_096076_2022-05-08_final
2022-05-08 09:54:27	ga_ls8c_ard_3-2-1_096077_2022-05-08_final
2022-05-08 09:54:51	ga_ls8c_ard_3-2-1_096078_2022-05-08_final
2022-05-08 09:55:15	ga_ls8c_ard_3-2-1_096079_2022-05-08_final
2022-05-08 09:55:39	ga_ls8c_ard_3-2-1_096080_2022-05-08_final
2022-05-10 09:44:06	ga_ls8c_ard_3-2-1_094082_2022-05-10_final
2022-05-10 09:44:30	ga_ls8c_ard_3-2-1_094083_2022-05-10_final
2022-05-10 09:44:54	ga_ls8c_ard_3-2-1_094084_2022-05-10_final
2022-05-10 09:45:18	ga_ls8c_ard_3-2-1_094085_2022-05-10_final
2022-05-10 09:45:42	ga_ls8c_ard_3-2-1_094086_2022-05-10_final
2022-05-10 09:46:06	ga_ls8c_ard_3-2-1_094087_2022-05-10_final
2022-05-22 10:02:30	ga_ls8c_ard_3-2-1_098066_2022-05-22_final
2022-05-22 10:02:54	ga_ls8c_ard_3-2-1_098067_2022-05-22_final
2022-05-22 10:03:17	ga_ls8c_ard_3-2-1_098068_2022-05-22_final
2022-05-22 10:03:41	ga_ls8c_ard_3-2-1_098069_2022-05-22_final
2022-05-22 10:04:05	ga_ls8c_ard_3-2-1_098070_2022-05-22_final
2022-06-02 09:48:48	ga_ls8c_ard_3-2-1_095078_2022-06-02_final
2022-06-02 09:49:12	ga_ls8c_ard_3-2-1_095079_2022-06-02_final
2022-06-02 09:49:36	ga_ls8c_ard_3-2-1_095080_2022-06-02_final
2022-06-02 09:50:00	ga_ls8c_ard_3-2-1_095081_2022-06-02_final
2022-06-02 09:50:24	ga_ls8c_ard_3-2-1_095082_2022-06-02_final
2022-06-02 09:50:48	ga_ls8c_ard_3-2-1_095083_2022-06-02_final
2022-06-02 09:51:12	ga_ls8c_ard_3-2-1_095084_2022-06-02_final
2022-06-04 09:39:40	ga_ls8c_ard_3-2-1_093086_2022-06-04_final
2022-06-04 09:40:04	ga_ls8c_ard_3-2-1_093087_2022-06-04_final
2022-06-04 09:40:28	ga_ls8c_ard_3-2-1_093088_2022-06-04_final
2022-06-07 10:02:38	ga_ls8c_ard_3-2-1_098066_2022-06-07_final
2022-06-07 10:03:02	ga_ls8c_ard_3-2-1_098067_2022-06-07_final
2022-06-07 10:03:26	ga_ls8c_ard_3-2-1_098068_2022-06-07_final
2022-06-07 10:03:50	ga_ls8c_ard_3-2-1_098069_2022-06-07_final
2022-06-07 10:04:13	ga_ls8c_ard_3-2-1_098070_2022-06-07_final
2023-07-25 09:39:24	ga_ls8c_ard_3-2-1_093086_2023-07-25_final
2023-07-25 09:39:48	ga_ls8c_ard_3-2-1_093087_2023-07-25_final
2023-07-25 09:40:12	ga_ls8c_ard_3-2-1_093088_2023-07-25_final
2023-07-28 10:02:21	ga_ls8c_ard_3-2-1_098066_2023-07-28_final
2023-07-28 10:02:45	ga_ls8c_ard_3-2-1_098067_2023-07-28_final
2023-07-28 10:03:09	ga_ls8c_ard_3-2-1_098068_2023-07-28_final
2023-07-28 10:03:33	ga_ls8c_ard_3-2-1_098069_2023-07-28_final
2023-07-28 10:03:57	ga_ls8c_ard_3-2-1_098070_2023-07-28_final
2023-08-01 09:44:03	ga_ls8c_ard_3-2-1_094082_2023-08-01_final
2023-08-01 09:44:27	ga_ls8c_ard_3-2-1_094083_2023-08-01_final
2023-08-01 09:44:51	ga_ls8c_ard_3-2-1_094084_2023-08-01_final
2023-08-01 09:45:15	ga_ls8c_ard_3-2-1_094085_2023-08-01_final
2023-08-01 09:45:39	ga_ls8c_ard_3-2-1_094086_2023-08-01_final
2023-08-01 09:46:03	ga_ls8c_ard_3-2-1_094087_2023-08-01_final
2023-08-03 09:34:30	ga_ls8c_ard_3-2-1_092089_2023-08-03_final
2023-08-03 09:34:54	ga_ls8c_ard_3-2-1_092090_2023-08-03_final
2023-08-10 09:39:29	ga_ls8c_ard_3-2-1_093086_2023-08-10_final
2023-08-10 09:39:53	ga_ls8c_ard_3-2-1_093087_2023-08-10_final
2023-08-10 09:40:17	ga_ls8c_ard_3-2-1_093088_2023-08-10_final
2023-08-15 09:53:18	ga_ls8c_ard_3-2-1_096074_2023-08-15_final
2023-08-15 09:53:42	ga_ls8c_ard_3-2-1_096075_2023-08-15_final
2023-08-15 09:54:06	ga_ls8c_ard_3-2-1_096076_2023-08-15_final
2023-08-15 09:54:30	ga_ls8c_ard_3-2-1_096077_2023-08-15_final
2023-08-15 09:54:53	ga_ls8c_ard_3-2-1_096078_2023-08-15_final
2023-08-15 09:55:17	ga_ls8c_ard_3-2-1_096079_2023-08-15_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