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
2019-01-24 09:53:59	ga_ls8c_ard_3-0-0_096076_2019-01-24_final
2019-01-24 09:54:22	ga_ls8c_ard_3-0-0_096077_2019-01-24_final
2019-01-24 09:54:46	ga_ls8c_ard_3-0-0_096078_2019-01-24_final
2019-01-24 09:55:10	ga_ls8c_ard_3-0-0_096079_2019-01-24_final
2019-01-24 09:55:34	ga_ls8c_ard_3-0-0_096080_2019-01-24_final
2019-01-24 09:55:58	ga_ls8c_ard_3-0-0_096081_2019-01-24_final
2019-02-02 09:49:22	ga_ls8c_ard_3-0-0_095080_2019-02-02_final
2019-02-02 09:49:46	ga_ls8c_ard_3-0-0_095081_2019-02-02_final
2019-02-02 09:50:10	ga_ls8c_ard_3-0-0_095082_2019-02-02_final
2019-02-02 09:50:34	ga_ls8c_ard_3-0-0_095083_2019-02-02_final
2019-02-02 09:50:58	ga_ls8c_ard_3-0-0_095084_2019-02-02_final
2019-02-02 09:51:21	ga_ls8c_ard_3-0-0_095085_2019-02-02_final
2019-02-07 10:02:43	ga_ls8c_ard_3-0-0_098067_2019-02-07_final
2019-02-07 10:03:07	ga_ls8c_ard_3-0-0_098068_2019-02-07_final
2019-02-07 10:03:30	ga_ls8c_ard_3-0-0_098069_2019-02-07_final
2019-02-07 10:03:54	ga_ls8c_ard_3-0-0_098070_2019-02-07_final
2019-02-07 10:04:18	ga_ls8c_ard_3-0-0_098071_2019-02-07_final
2019-02-07 10:04:42	ga_ls8c_ard_3-0-0_098072_2019-02-07_final
2019-03-11 10:02:34	ga_ls8c_ard_3-1-0_098067_2019-03-11_final
2019-03-11 10:02:58	ga_ls8c_ard_3-1-0_098068_2019-03-11_final
2019-03-11 10:03:22	ga_ls8c_ard_3-1-0_098069_2019-03-11_final
2019-03-11 10:03:46	ga_ls8c_ard_3-1-0_098070_2019-03-11_final
2019-03-11 10:04:10	ga_ls8c_ard_3-1-0_098071_2019-03-11_final
2019-03-11 10:04:34	ga_ls8c_ard_3-1-0_098072_2019-03-11_final
2019-03-13 09:53:47	ga_ls8c_ard_3-1-0_096076_2019-03-13_final
2019-03-13 09:54:11	ga_ls8c_ard_3-1-0_096077_2019-03-13_final
2019-03-13 09:54:35	ga_ls8c_ard_3-1-0_096078_2019-03-13_final
2019-03-13 09:54:59	ga_ls8c_ard_3-1-0_096079_2019-03-13_final
2019-03-13 09:55:23	ga_ls8c_ard_3-1-0_096080_2019-03-13_final
2019-03-13 09:55:47	ga_ls8c_ard_3-1-0_096081_2019-03-13_final
2019-04-28 10:02:21	ga_ls8c_ard_3-0-0_098067_2019-04-28_final
2019-04-28 10:02:45	ga_ls8c_ard_3-0-0_098068_2019-04-28_final
2019-04-28 10:03:09	ga_ls8c_ard_3-0-0_098069_2019-04-28_final
2019-04-28 10:03:33	ga_ls8c_ard_3-0-0_098070_2019-04-28_final
2019-04-28 10:03:57	ga_ls8c_ard_3-0-0_098071_2019-04-28_final
2019-04-28 10:04:21	ga_ls8c_ard_3-0-0_098072_2019-04-28_final
2019-05-09 09:49:06	ga_ls8c_ard_3-0-0_095080_2019-05-09_final
2019-05-09 09:49:30	ga_ls8c_ard_3-0-0_095081_2019-05-09_final
2019-05-09 09:49:54	ga_ls8c_ard_3-0-0_095082_2019-05-09_final
2019-05-09 09:50:18	ga_ls8c_ard_3-0-0_095083_2019-05-09_final
2019-05-09 09:50:42	ga_ls8c_ard_3-0-0_095084_2019-05-09_final
2019-05-09 09:51:06	ga_ls8c_ard_3-0-0_095085_2019-05-09_final
2019-05-11 09:39:33	ga_ls8c_ard_3-0-0_093087_2019-05-11_final
2019-05-11 09:39:57	ga_ls8c_ard_3-0-0_093088_2019-05-11_final
2021-12-17 09:45:21	ga_ls8c_ard_3-2-1_094084_2021-12-17_final
2021-12-17 09:45:45	ga_ls8c_ard_3-2-1_094085_2021-12-17_final
2021-12-19 09:35:23	ga_ls8c_ard_3-2-1_092090_2021-12-19_final
2022-01-18 09:45:13	ga_ls8c_ard_3-2-1_094084_2022-01-18_final
2022-01-18 09:45:37	ga_ls8c_ard_3-2-1_094085_2022-01-18_final
2022-01-18 09:46:01	ga_ls8c_ard_3-2-1_094086_2022-01-18_final
2022-01-18 09:46:25	ga_ls8c_ard_3-2-1_094087_2022-01-18_final
2022-01-20 09:35:15	ga_ls8c_ard_3-2-1_092090_2022-01-20_final
2022-01-21 10:08:55	ga_ls8c_ard_3-2-1_099066_2022-01-21_final
2022-01-21 10:09:19	ga_ls8c_ard_3-2-1_099067_2022-01-21_final
2022-01-23 09:58:32	ga_ls8c_ard_3-2-1_097071_2022-01-23_final
2022-01-23 09:58:56	ga_ls8c_ard_3-2-1_097072_2022-01-23_final
2022-01-23 09:59:20	ga_ls8c_ard_3-2-1_097073_2022-01-23_final
2022-01-23 09:59:44	ga_ls8c_ard_3-2-1_097074_2022-01-23_final
2022-01-23 10:00:08	ga_ls8c_ard_3-2-1_097075_2022-01-23_final
2022-01-23 10:00:32	ga_ls8c_ard_3-2-1_097076_2022-01-23_final
2022-01-23 10:00:56	ga_ls8c_ard_3-2-1_097077_2022-01-23_final
2022-01-25 09:49:45	ga_ls8c_ard_3-2-1_095080_2022-01-25_final
2022-01-25 09:50:09	ga_ls8c_ard_3-2-1_095081_2022-01-25_final
2022-01-25 09:50:33	ga_ls8c_ard_3-2-1_095082_2022-01-25_final
2022-01-25 09:50:57	ga_ls8c_ard_3-2-1_095083_2022-01-25_final
2022-01-25 09:51:21	ga_ls8c_ard_3-2-1_095084_2022-01-25_final
2022-01-25 09:51:45	ga_ls8c_ard_3-2-1_095085_2022-01-25_final
2022-01-30 10:02:41	ga_ls8c_ard_3-2-1_098066_2022-01-30_final
2022-01-30 10:03:05	ga_ls8c_ard_3-2-1_098067_2022-01-30_final
2022-01-30 10:03:29	ga_ls8c_ard_3-2-1_098068_2022-01-30_final
2022-01-30 10:03:53	ga_ls8c_ard_3-2-1_098069_2022-01-30_final
2022-01-30 10:04:17	ga_ls8c_ard_3-2-1_098070_2022-01-30_final
2022-01-30 10:04:41	ga_ls8c_ard_3-2-1_098071_2022-01-30_final
2022-01-30 10:05:05	ga_ls8c_ard_3-2-1_098072_2022-01-30_final
2022-02-01 09:54:19	ga_ls8c_ard_3-2-1_096076_2022-02-01_final
2022-02-01 09:54:43	ga_ls8c_ard_3-2-1_096077_2022-02-01_final
2022-02-01 09:55:07	ga_ls8c_ard_3-2-1_096078_2022-02-01_final
2022-02-01 09:55:31	ga_ls8c_ard_3-2-1_096079_2022-02-01_final
2022-02-01 09:55:55	ga_ls8c_ard_3-2-1_096080_2022-02-01_final
2022-02-01 09:56:19	ga_ls8c_ard_3-2-1_096081_2022-02-01_final
2022-02-03 09:45:09	ga_ls8c_ard_3-2-1_094084_2022-02-03_final
2022-02-03 09:45:33	ga_ls8c_ard_3-2-1_094085_2022-02-03_final
2022-02-03 09:45:57	ga_ls8c_ard_3-2-1_094086_2022-02-03_final
2022-02-03 09:46:21	ga_ls8c_ard_3-2-1_094087_2022-02-03_final
2022-02-05 09:35:11	ga_ls8c_ard_3-2-1_092090_2022-02-05_final
2022-03-09 09:35:02	ga_ls8c_ard_3-2-1_092090_2022-03-09_final
2022-03-10 10:08:43	ga_ls8c_ard_3-2-1_099066_2022-03-10_final
2022-03-10 10:09:06	ga_ls8c_ard_3-2-1_099067_2022-03-10_final
2022-03-12 09:58:20	ga_ls8c_ard_3-2-1_097071_2022-03-12_final
2022-03-12 09:58:44	ga_ls8c_ard_3-2-1_097072_2022-03-12_final
2022-03-12 09:59:08	ga_ls8c_ard_3-2-1_097073_2022-03-12_final
2022-03-12 09:59:31	ga_ls8c_ard_3-2-1_097074_2022-03-12_final
2022-03-12 09:59:55	ga_ls8c_ard_3-2-1_097075_2022-03-12_final
2022-03-12 10:00:19	ga_ls8c_ard_3-2-1_097076_2022-03-12_final
2022-03-12 10:00:43	ga_ls8c_ard_3-2-1_097077_2022-03-12_final
2022-03-14 09:49:32	ga_ls8c_ard_3-2-1_095080_2022-03-14_final
2022-03-14 09:49:56	ga_ls8c_ard_3-2-1_095081_2022-03-14_final
2022-03-14 09:50:20	ga_ls8c_ard_3-2-1_095082_2022-03-14_final
2022-03-14 09:50:44	ga_ls8c_ard_3-2-1_095083_2022-03-14_final
2022-03-14 09:51:08	ga_ls8c_ard_3-2-1_095084_2022-03-14_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