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
2018-06-14 11:28:21	ga_ls8c_ard_3-0-0_112067_2018-06-14_final
2018-06-14 11:28:45	ga_ls8c_ard_3-0-0_112068_2018-06-14_final
2018-06-14 11:29:09	ga_ls8c_ard_3-0-0_112069_2018-06-14_final
2018-06-16 11:18:24	ga_ls8c_ard_3-0-0_110073_2018-06-16_final
2018-06-16 11:18:48	ga_ls8c_ard_3-0-0_110074_2018-06-16_final
2018-06-16 11:19:12	ga_ls8c_ard_3-0-0_110075_2018-06-16_final
2018-06-16 11:19:36	ga_ls8c_ard_3-0-0_110076_2018-06-16_final
2018-06-16 11:20:00	ga_ls8c_ard_3-0-0_110077_2018-06-16_final
2018-06-16 11:20:24	ga_ls8c_ard_3-0-0_110078_2018-06-16_final
2018-06-16 11:20:48	ga_ls8c_ard_3-0-0_110079_2018-06-16_final
2018-06-30 11:28:31	ga_ls8c_ard_3-0-0_112067_2018-06-30_final
2018-06-30 11:28:55	ga_ls8c_ard_3-0-0_112068_2018-06-30_final
2018-06-30 11:29:19	ga_ls8c_ard_3-0-0_112069_2018-06-30_final
2018-07-02 11:18:34	ga_ls8c_ard_3-0-0_110073_2018-07-02_final
2018-07-02 11:18:58	ga_ls8c_ard_3-0-0_110074_2018-07-02_final
2018-07-02 11:19:22	ga_ls8c_ard_3-0-0_110075_2018-07-02_final
2018-07-02 11:19:46	ga_ls8c_ard_3-0-0_110076_2018-07-02_final
2018-07-02 11:20:10	ga_ls8c_ard_3-0-0_110077_2018-07-02_final
2018-07-02 11:20:34	ga_ls8c_ard_3-0-0_110078_2018-07-02_final
2018-07-02 11:20:58	ga_ls8c_ard_3-0-0_110079_2018-07-02_final
2018-08-17 11:28:55	ga_ls8c_ard_3-0-0_112067_2018-08-17_final
2018-08-17 11:29:19	ga_ls8c_ard_3-0-0_112068_2018-08-17_final
2018-08-17 11:29:43	ga_ls8c_ard_3-0-0_112069_2018-08-17_final
2018-08-17 11:30:07	ga_ls8c_ard_3-0-0_112070_2018-08-17_final
2018-08-19 11:18:58	ga_ls8c_ard_3-0-0_110073_2018-08-19_final
2018-08-19 11:19:22	ga_ls8c_ard_3-0-0_110074_2018-08-19_final
2018-08-19 11:19:46	ga_ls8c_ard_3-0-0_110075_2018-08-19_final
2018-08-19 11:20:10	ga_ls8c_ard_3-0-0_110076_2018-08-19_final
2018-08-19 11:20:34	ga_ls8c_ard_3-0-0_110077_2018-08-19_final
2018-08-19 11:20:58	ga_ls8c_ard_3-0-0_110078_2018-08-19_final
2018-08-19 11:21:22	ga_ls8c_ard_3-0-0_110079_2018-08-19_final
2018-09-02 11:29:02	ga_ls8c_ard_3-0-0_112067_2018-09-02_final
2018-09-02 11:29:26	ga_ls8c_ard_3-0-0_112068_2018-09-02_final
2018-09-02 11:29:50	ga_ls8c_ard_3-0-0_112069_2018-09-02_final
2018-09-02 11:30:14	ga_ls8c_ard_3-0-0_112070_2018-09-02_final
2018-09-04 11:19:05	ga_ls8c_ard_3-0-0_110073_2018-09-04_final
2018-09-04 11:19:28	ga_ls8c_ard_3-0-0_110074_2018-09-04_final
2018-09-04 11:19:52	ga_ls8c_ard_3-0-0_110075_2018-09-04_final
2018-09-04 11:20:16	ga_ls8c_ard_3-0-0_110076_2018-09-04_final
2018-09-04 11:20:40	ga_ls8c_ard_3-0-0_110077_2018-09-04_final
2018-09-04 11:21:04	ga_ls8c_ard_3-0-0_110078_2018-09-04_final
2018-09-04 11:21:28	ga_ls8c_ard_3-0-0_110079_2018-09-04_final
2020-04-27 11:14:49	ga_ls8c_ard_3-1-0_109078_2020-04-27_final
2020-04-27 11:15:13	ga_ls8c_ard_3-1-0_109079_2020-04-27_final
2020-04-27 11:15:37	ga_ls8c_ard_3-1-0_109080_2020-04-27_final
2020-04-27 11:16:01	ga_ls8c_ard_3-1-0_109081_2020-04-27_final
2020-04-27 11:16:25	ga_ls8c_ard_3-1-0_109082_2020-04-27_final
2020-12-25 11:06:04	ga_ls8c_ard_3-2-0_107085_2020-12-25_final
2020-12-28 11:29:46	ga_ls8c_ard_3-2-0_112067_2020-12-28_final
2020-12-28 11:30:10	ga_ls8c_ard_3-2-0_112068_2020-12-28_final
2020-12-28 11:30:34	ga_ls8c_ard_3-2-0_112069_2020-12-28_final
2023-10-29 11:15:32	ga_ls8c_ard_3-2-1_109078_2023-10-29_final
2023-10-29 11:15:56	ga_ls8c_ard_3-2-1_109079_2023-10-29_final
2023-10-29 11:16:20	ga_ls8c_ard_3-2-1_109080_2023-10-29_final
2023-10-29 11:16:44	ga_ls8c_ard_3-2-1_109081_2023-10-29_final
2023-10-29 11:17:08	ga_ls8c_ard_3-2-1_109082_2023-10-29_final
2023-10-29 11:17:32	ga_ls8c_ard_3-2-1_109083_2023-10-29_final
2023-11-05 11:19:42	ga_ls8c_ard_3-2-1_110073_2023-11-05_final
2023-11-05 11:20:06	ga_ls8c_ard_3-2-1_110074_2023-11-05_final
2023-11-05 11:20:30	ga_ls8c_ard_3-2-1_110075_2023-11-05_final
2023-11-05 11:20:54	ga_ls8c_ard_3-2-1_110076_2023-11-05_final
2023-11-05 11:21:18	ga_ls8c_ard_3-2-1_110077_2023-11-05_final
2023-11-05 11:21:42	ga_ls8c_ard_3-2-1_110078_2023-11-05_final
2023-11-05 11:22:06	ga_ls8c_ard_3-2-1_110079_2023-11-05_final
2023-11-07 11:10:54	ga_ls8c_ard_3-2-1_108082_2023-11-07_final
2023-11-07 11:11:18	ga_ls8c_ard_3-2-1_108083_2023-11-07_final
2023-11-07 11:11:42	ga_ls8c_ard_3-2-1_108084_2023-11-07_final
2023-11-12 11:24:15	ga_ls8c_ard_3-2-1_111069_2023-11-12_final
2023-11-12 11:24:39	ga_ls8c_ard_3-2-1_111070_2023-11-12_final
2023-11-12 11:25:02	ga_ls8c_ard_3-2-1_111071_2023-11-12_final
2023-11-12 11:25:26	ga_ls8c_ard_3-2-1_111072_2023-11-12_final
2023-11-12 11:25:50	ga_ls8c_ard_3-2-1_111073_2023-11-12_final
2023-11-12 11:26:14	ga_ls8c_ard_3-2-1_111074_2023-11-12_final
2023-11-14 11:15:30	ga_ls8c_ard_3-2-1_109078_2023-11-14_final
2023-11-14 11:15:54	ga_ls8c_ard_3-2-1_109079_2023-11-14_final
2023-11-14 11:16:18	ga_ls8c_ard_3-2-1_109080_2023-11-14_final
2023-11-14 11:16:42	ga_ls8c_ard_3-2-1_109081_2023-11-14_final
2023-11-14 11:17:06	ga_ls8c_ard_3-2-1_109082_2023-11-14_final
2023-11-14 11:17:30	ga_ls8c_ard_3-2-1_109083_2023-11-14_final
2023-11-21 11:19:45	ga_ls8c_ard_3-2-1_110073_2023-11-21_final
2023-11-21 11:20:09	ga_ls8c_ard_3-2-1_110074_2023-11-21_final
2023-11-21 11:20:33	ga_ls8c_ard_3-2-1_110075_2023-11-21_final
2023-11-21 11:20:57	ga_ls8c_ard_3-2-1_110076_2023-11-21_final
2023-11-21 11:21:21	ga_ls8c_ard_3-2-1_110077_2023-11-21_final
2023-11-21 11:21:45	ga_ls8c_ard_3-2-1_110078_2023-11-21_final
2023-11-21 11:22:08	ga_ls8c_ard_3-2-1_110079_2023-11-21_final
2023-11-23 11:10:59	ga_ls8c_ard_3-2-1_108082_2023-11-23_final
2023-11-23 11:11:23	ga_ls8c_ard_3-2-1_108083_2023-11-23_final
2023-11-23 11:11:47	ga_ls8c_ard_3-2-1_108084_2023-11-23_final
2023-11-28 11:24:19	ga_ls8c_ard_3-2-1_111069_2023-11-28_final
2023-11-28 11:24:43	ga_ls8c_ard_3-2-1_111070_2023-11-28_final
2023-11-28 11:25:07	ga_ls8c_ard_3-2-1_111071_2023-11-28_final
2023-11-28 11:25:31	ga_ls8c_ard_3-2-1_111072_2023-11-28_final
2023-11-28 11:25:55	ga_ls8c_ard_3-2-1_111073_2023-11-28_final
2023-11-28 11:26:19	ga_ls8c_ard_3-2-1_111074_2023-11-28_final
2023-11-30 11:15:32	ga_ls8c_ard_3-2-1_109078_2023-11-30_final
2023-11-30 11:15:56	ga_ls8c_ard_3-2-1_109079_2023-11-30_final
2023-11-30 11:16:20	ga_ls8c_ard_3-2-1_109080_2023-11-30_final
2023-11-30 11:16:44	ga_ls8c_ard_3-2-1_109081_2023-11-30_final
2023-11-30 11:17:08	ga_ls8c_ard_3-2-1_109082_2023-11-30_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