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
2018-02-17 11:14:43	ga_ls8c_ard_3-0-0_109077_2018-02-17_final
2018-02-17 11:15:07	ga_ls8c_ard_3-0-0_109078_2018-02-17_final
2018-02-17 11:15:31	ga_ls8c_ard_3-0-0_109079_2018-02-17_final
2018-02-17 11:15:55	ga_ls8c_ard_3-0-0_109080_2018-02-17_final
2018-02-17 11:16:19	ga_ls8c_ard_3-0-0_109081_2018-02-17_final
2018-02-17 11:16:43	ga_ls8c_ard_3-0-0_109082_2018-02-17_final
2018-02-17 11:17:07	ga_ls8c_ard_3-0-0_109083_2018-02-17_final
2018-02-19 11:05:32	ga_ls8c_ard_3-0-0_107085_2018-02-19_final
2018-03-05 11:14:59	ga_ls8c_ard_3-0-0_109078_2018-03-05_final
2018-03-05 11:15:23	ga_ls8c_ard_3-0-0_109079_2018-03-05_final
2018-03-05 11:15:47	ga_ls8c_ard_3-0-0_109080_2018-03-05_final
2018-03-05 11:16:11	ga_ls8c_ard_3-0-0_109081_2018-03-05_final
2018-03-05 11:16:35	ga_ls8c_ard_3-0-0_109082_2018-03-05_final
2018-03-05 11:16:59	ga_ls8c_ard_3-0-0_109083_2018-03-05_final
2018-03-07 11:05:24	ga_ls8c_ard_3-0-0_107085_2018-03-07_final
2018-03-23 11:05:16	ga_ls8c_ard_3-0-0_107085_2018-03-23_final
2018-04-08 11:05:08	ga_ls8c_ard_3-0-0_107085_2018-04-08_final
2018-04-11 11:28:50	ga_ls8c_ard_3-0-0_112067_2018-04-11_final
2018-04-11 11:29:14	ga_ls8c_ard_3-0-0_112068_2018-04-11_final
2018-04-11 11:29:38	ga_ls8c_ard_3-0-0_112069_2018-04-11_final
2018-04-13 11:18:51	ga_ls8c_ard_3-0-0_110073_2018-04-13_final
2018-04-13 11:19:14	ga_ls8c_ard_3-0-0_110074_2018-04-13_final
2018-04-13 11:19:38	ga_ls8c_ard_3-0-0_110075_2018-04-13_final
2018-04-13 11:20:02	ga_ls8c_ard_3-0-0_110076_2018-04-13_final
2018-04-13 11:20:26	ga_ls8c_ard_3-0-0_110077_2018-04-13_final
2018-04-13 11:20:50	ga_ls8c_ard_3-0-0_110078_2018-04-13_final
2018-04-13 11:21:14	ga_ls8c_ard_3-0-0_110079_2018-04-13_final
2018-04-20 11:22:57	ga_ls8c_ard_3-0-0_111068_2018-04-20_final
2018-04-20 11:23:21	ga_ls8c_ard_3-0-0_111069_2018-04-20_final
2018-04-20 11:23:45	ga_ls8c_ard_3-0-0_111070_2018-04-20_final
2018-04-20 11:24:09	ga_ls8c_ard_3-0-0_111071_2018-04-20_final
2018-04-20 11:24:33	ga_ls8c_ard_3-0-0_111072_2018-04-20_final
2018-04-20 11:24:57	ga_ls8c_ard_3-0-0_111073_2018-04-20_final
2018-04-20 11:25:21	ga_ls8c_ard_3-0-0_111074_2018-04-20_final
2018-04-22 11:14:10	ga_ls8c_ard_3-0-0_109077_2018-04-22_final
2018-04-22 11:14:34	ga_ls8c_ard_3-0-0_109078_2018-04-22_final
2018-04-22 11:14:58	ga_ls8c_ard_3-0-0_109079_2018-04-22_final
2018-04-22 11:15:22	ga_ls8c_ard_3-0-0_109080_2018-04-22_final
2018-04-22 11:15:46	ga_ls8c_ard_3-0-0_109081_2018-04-22_final
2018-04-22 11:16:10	ga_ls8c_ard_3-0-0_109082_2018-04-22_final
2018-04-22 11:16:34	ga_ls8c_ard_3-0-0_109083_2018-04-22_final
2018-04-24 11:04:59	ga_ls8c_ard_3-0-0_107085_2018-04-24_final
2018-04-27 11:28:41	ga_ls8c_ard_3-0-0_112067_2018-04-27_final
2018-04-27 11:29:05	ga_ls8c_ard_3-0-0_112068_2018-04-27_final
2018-04-27 11:29:28	ga_ls8c_ard_3-0-0_112069_2018-04-27_final
2018-05-26 11:04:37	ga_ls8c_ard_3-0-0_107085_2018-05-26_final
2022-11-02 11:20:09	ga_ls8c_ard_3-2-1_110073_2022-11-02_final
2022-11-02 11:20:33	ga_ls8c_ard_3-2-1_110074_2022-11-02_final
2022-11-02 11:20:57	ga_ls8c_ard_3-2-1_110075_2022-11-02_final
2022-11-02 11:21:21	ga_ls8c_ard_3-2-1_110076_2022-11-02_final
2022-11-02 11:21:45	ga_ls8c_ard_3-2-1_110077_2022-11-02_final
2022-11-02 11:22:09	ga_ls8c_ard_3-2-1_110078_2022-11-02_final
2022-11-04 11:10:59	ga_ls8c_ard_3-2-1_108081_2022-11-04_final
2022-11-04 11:11:23	ga_ls8c_ard_3-2-1_108082_2022-11-04_final
2022-11-04 11:11:47	ga_ls8c_ard_3-2-1_108083_2022-11-04_final
2022-11-04 11:12:11	ga_ls8c_ard_3-2-1_108084_2022-11-04_final
2022-11-18 11:20:01	ga_ls8c_ard_3-2-1_110073_2022-11-18_final
2022-11-18 11:20:25	ga_ls8c_ard_3-2-1_110074_2022-11-18_final
2022-11-18 11:20:49	ga_ls8c_ard_3-2-1_110075_2022-11-18_final
2022-11-18 11:21:13	ga_ls8c_ard_3-2-1_110076_2022-11-18_final
2022-11-18 11:21:37	ga_ls8c_ard_3-2-1_110077_2022-11-18_final
2022-11-18 11:22:01	ga_ls8c_ard_3-2-1_110078_2022-11-18_final
2022-11-18 11:22:25	ga_ls8c_ard_3-2-1_110079_2022-11-18_final
2022-11-20 11:11:16	ga_ls8c_ard_3-2-1_108082_2022-11-20_final
2022-11-20 11:11:40	ga_ls8c_ard_3-2-1_108083_2022-11-20_final
2022-11-20 11:12:04	ga_ls8c_ard_3-2-1_108084_2022-11-20_final
2022-12-04 11:20:04	ga_ls8c_ard_3-2-1_110073_2022-12-04_final
2022-12-04 11:20:28	ga_ls8c_ard_3-2-1_110074_2022-12-04_final
2022-12-04 11:20:52	ga_ls8c_ard_3-2-1_110075_2022-12-04_final
2022-12-04 11:21:16	ga_ls8c_ard_3-2-1_110076_2022-12-04_final
2022-12-04 11:21:40	ga_ls8c_ard_3-2-1_110077_2022-12-04_final
2022-12-04 11:22:04	ga_ls8c_ard_3-2-1_110078_2022-12-04_final
2022-12-04 11:22:28	ga_ls8c_ard_3-2-1_110079_2022-12-04_final
2022-12-13 11:17:02	ga_ls8c_ard_3-2-1_109081_2022-12-13_final
2022-12-13 11:17:25	ga_ls8c_ard_3-2-1_109082_2022-12-13_final
2022-12-13 11:17:49	ga_ls8c_ard_3-2-1_109083_2022-12-13_final
2022-12-27 11:24:06	ga_ls8c_ard_3-2-1_111068_2022-12-27_final
2022-12-27 11:24:30	ga_ls8c_ard_3-2-1_111069_2022-12-27_final
2022-12-27 11:24:54	ga_ls8c_ard_3-2-1_111070_2022-12-27_final
2022-12-27 11:25:17	ga_ls8c_ard_3-2-1_111071_2022-12-27_final
2022-12-27 11:25:41	ga_ls8c_ard_3-2-1_111072_2022-12-27_final
2022-12-27 11:26:05	ga_ls8c_ard_3-2-1_111073_2022-12-27_final
2022-12-27 11:26:29	ga_ls8c_ard_3-2-1_111074_2022-12-27_final
2023-01-21 11:19:50	ga_ls8c_ard_3-2-1_110073_2023-01-21_final
2023-01-21 11:20:14	ga_ls8c_ard_3-2-1_110074_2023-01-21_final
2023-01-21 11:20:38	ga_ls8c_ard_3-2-1_110075_2023-01-21_final
2023-01-23 11:10:41	ga_ls8c_ard_3-2-1_108081_2023-01-23_final
2023-01-23 11:11:05	ga_ls8c_ard_3-2-1_108082_2023-01-23_final
2023-01-23 11:11:29	ga_ls8c_ard_3-2-1_108083_2023-01-23_final
2023-01-23 11:11:53	ga_ls8c_ard_3-2-1_108084_2023-01-23_final
2023-02-13 11:23:59	ga_ls8c_ard_3-2-1_111068_2023-02-13_final
2023-02-13 11:24:23	ga_ls8c_ard_3-2-1_111069_2023-02-13_final
2023-02-13 11:24:47	ga_ls8c_ard_3-2-1_111070_2023-02-13_final
2023-02-13 11:25:11	ga_ls8c_ard_3-2-1_111071_2023-02-13_final
2023-02-13 11:25:35	ga_ls8c_ard_3-2-1_111072_2023-02-13_final
2023-02-13 11:25:58	ga_ls8c_ard_3-2-1_111073_2023-02-13_final
2023-02-13 11:26:22	ga_ls8c_ard_3-2-1_111074_2023-02-13_final
2023-02-22 11:19:38	ga_ls8c_ard_3-2-1_110073_2023-02-22_final
2023-02-22 11:20:02	ga_ls8c_ard_3-2-1_110074_2023-02-22_final
2023-02-22 11:20:26	ga_ls8c_ard_3-2-1_110075_2023-02-22_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