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
2018-06-15 10:32:44	ga_ls8c_ard_3-0-0_103067_2018-06-15_final
2018-06-15 10:33:08	ga_ls8c_ard_3-0-0_103068_2018-06-15_final
2018-06-17 10:22:24	ga_ls8c_ard_3-0-0_101072_2018-06-17_final
2018-06-17 10:22:48	ga_ls8c_ard_3-0-0_101073_2018-06-17_final
2018-06-17 10:23:12	ga_ls8c_ard_3-0-0_101074_2018-06-17_final
2018-06-17 10:23:36	ga_ls8c_ard_3-0-0_101075_2018-06-17_final
2018-06-17 10:24:00	ga_ls8c_ard_3-0-0_101076_2018-06-17_final
2018-06-17 10:24:23	ga_ls8c_ard_3-0-0_101077_2018-06-17_final
2018-07-01 10:32:54	ga_ls8c_ard_3-0-0_103067_2018-07-01_final
2018-07-01 10:33:18	ga_ls8c_ard_3-0-0_103068_2018-07-01_final
2018-07-03 10:22:33	ga_ls8c_ard_3-0-0_101072_2018-07-03_final
2018-07-03 10:22:57	ga_ls8c_ard_3-0-0_101073_2018-07-03_final
2018-07-03 10:23:21	ga_ls8c_ard_3-0-0_101074_2018-07-03_final
2018-07-03 10:23:45	ga_ls8c_ard_3-0-0_101075_2018-07-03_final
2018-07-03 10:24:09	ga_ls8c_ard_3-0-0_101076_2018-07-03_final
2018-07-03 10:24:33	ga_ls8c_ard_3-0-0_101077_2018-07-03_final
2018-08-18 10:33:18	ga_ls8c_ard_3-0-0_103067_2018-08-18_final
2018-08-18 10:33:42	ga_ls8c_ard_3-0-0_103068_2018-08-18_final
2018-08-20 10:22:57	ga_ls8c_ard_3-0-0_101072_2018-08-20_final
2018-08-20 10:23:21	ga_ls8c_ard_3-0-0_101073_2018-08-20_final
2018-08-20 10:23:45	ga_ls8c_ard_3-0-0_101074_2018-08-20_final
2018-08-20 10:24:09	ga_ls8c_ard_3-0-0_101075_2018-08-20_final
2018-08-20 10:24:33	ga_ls8c_ard_3-0-0_101076_2018-08-20_final
2018-08-20 10:24:57	ga_ls8c_ard_3-0-0_101077_2018-08-20_final
2018-09-05 10:23:04	ga_ls8c_ard_3-0-0_101072_2018-09-05_final
2018-09-05 10:23:28	ga_ls8c_ard_3-0-0_101073_2018-09-05_final
2018-09-05 10:23:51	ga_ls8c_ard_3-0-0_101074_2018-09-05_final
2018-09-05 10:24:15	ga_ls8c_ard_3-0-0_101075_2018-09-05_final
2018-09-05 10:24:39	ga_ls8c_ard_3-0-0_101076_2018-09-05_final
2018-09-05 10:25:03	ga_ls8c_ard_3-0-0_101077_2018-09-05_final
2018-09-16 10:09:21	ga_ls8c_ard_3-0-0_098084_2018-09-16_final
2018-09-16 10:09:45	ga_ls8c_ard_3-0-0_098085_2018-09-16_final
2018-09-16 10:10:09	ga_ls8c_ard_3-0-0_098086_2018-09-16_final
2018-10-16 10:18:45	ga_ls8c_ard_3-0-0_100076_2018-10-16_final
2018-10-16 10:19:09	ga_ls8c_ard_3-0-0_100077_2018-10-16_final
2018-10-16 10:19:33	ga_ls8c_ard_3-0-0_100078_2018-10-16_final
2018-10-16 10:19:56	ga_ls8c_ard_3-0-0_100079_2018-10-16_final
2018-10-16 10:20:20	ga_ls8c_ard_3-0-0_100080_2018-10-16_final
2018-10-21 10:33:43	ga_ls8c_ard_3-0-0_103067_2018-10-21_final
2018-10-21 10:34:07	ga_ls8c_ard_3-0-0_103068_2018-10-21_final
2018-10-23 10:23:22	ga_ls8c_ard_3-0-0_101072_2018-10-23_final
2018-10-23 10:23:46	ga_ls8c_ard_3-0-0_101073_2018-10-23_final
2018-10-23 10:24:10	ga_ls8c_ard_3-0-0_101074_2018-10-23_final
2018-10-23 10:24:34	ga_ls8c_ard_3-0-0_101075_2018-10-23_final
2018-10-23 10:24:58	ga_ls8c_ard_3-0-0_101076_2018-10-23_final
2018-10-23 10:25:22	ga_ls8c_ard_3-0-0_101077_2018-10-23_final
2018-11-08 10:23:25	ga_ls8c_ard_3-0-0_101072_2018-11-08_final
2018-11-08 10:23:49	ga_ls8c_ard_3-0-0_101073_2018-11-08_final
2018-11-08 10:24:13	ga_ls8c_ard_3-0-0_101074_2018-11-08_final
2018-11-08 10:24:37	ga_ls8c_ard_3-0-0_101075_2018-11-08_final
2018-11-08 10:25:01	ga_ls8c_ard_3-0-0_101076_2018-11-08_final
2018-11-08 10:25:25	ga_ls8c_ard_3-0-0_101077_2018-11-08_final
2018-12-24 10:33:44	ga_ls8c_ard_3-0-0_103067_2018-12-24_final
2018-12-24 10:34:08	ga_ls8c_ard_3-0-0_103068_2018-12-24_final
2018-12-26 10:23:22	ga_ls8c_ard_3-1-0_101072_2018-12-26_final
2018-12-26 10:23:46	ga_ls8c_ard_3-0-0_101073_2018-12-26_final
2018-12-26 10:24:10	ga_ls8c_ard_3-0-0_101074_2018-12-26_final
2018-12-26 10:24:33	ga_ls8c_ard_3-0-0_101075_2018-12-26_final
2018-12-26 10:24:57	ga_ls8c_ard_3-0-0_101076_2018-12-26_final
2018-12-26 10:25:21	ga_ls8c_ard_3-0-0_101077_2018-12-26_final
2018-12-26 10:25:45	ga_ls8c_ard_3-0-0_101078_2018-12-26_final
2019-01-06 10:09:36	ga_ls8c_ard_3-0-0_098084_2019-01-06_final
2019-01-06 10:10:00	ga_ls8c_ard_3-0-0_098085_2019-01-06_final
2019-01-06 10:10:24	ga_ls8c_ard_3-0-0_098086_2019-01-06_final
2023-08-25 10:27:40	ga_ls8c_ard_3-2-1_102067_2023-08-25_final
2023-08-25 10:28:04	ga_ls8c_ard_3-2-1_102068_2023-08-25_final
2023-08-25 10:28:28	ga_ls8c_ard_3-2-1_102069_2023-08-25_final
2023-08-25 10:28:52	ga_ls8c_ard_3-2-1_102070_2023-08-25_final
2023-08-25 10:29:16	ga_ls8c_ard_3-2-1_102071_2023-08-25_final
2023-08-25 10:29:40	ga_ls8c_ard_3-2-1_102072_2023-08-25_final
2023-08-25 10:30:04	ga_ls8c_ard_3-2-1_102073_2023-08-25_final
2023-08-27 10:18:54	ga_ls8c_ard_3-2-1_100076_2023-08-27_final
2023-08-27 10:19:18	ga_ls8c_ard_3-2-1_100077_2023-08-27_final
2023-08-27 10:19:42	ga_ls8c_ard_3-2-1_100078_2023-08-27_final
2023-08-27 10:20:06	ga_ls8c_ard_3-2-1_100079_2023-08-27_final
2023-08-27 10:20:30	ga_ls8c_ard_3-2-1_100080_2023-08-27_final
2023-08-27 10:20:54	ga_ls8c_ard_3-2-1_100081_2023-08-27_final
2023-08-27 10:21:18	ga_ls8c_ard_3-2-1_100082_2023-08-27_final
2023-08-29 10:09:44	ga_ls8c_ard_3-2-1_098084_2023-08-29_final
2023-08-29 10:10:08	ga_ls8c_ard_3-2-1_098085_2023-08-29_final
2023-09-01 10:34:15	ga_ls8c_ard_3-2-1_103068_2023-09-01_final
2023-09-03 10:23:28	ga_ls8c_ard_3-2-1_101072_2023-09-03_final
2023-09-03 10:23:52	ga_ls8c_ard_3-2-1_101073_2023-09-03_final
2023-09-03 10:24:16	ga_ls8c_ard_3-2-1_101074_2023-09-03_final
2023-09-03 10:24:40	ga_ls8c_ard_3-2-1_101075_2023-09-03_final
2023-09-03 10:25:04	ga_ls8c_ard_3-2-1_101076_2023-09-03_final
2023-09-03 10:25:28	ga_ls8c_ard_3-2-1_101077_2023-09-03_final
2023-09-10 10:27:41	ga_ls8c_ard_3-2-1_102067_2023-09-10_final
2023-09-10 10:28:05	ga_ls8c_ard_3-2-1_102068_2023-09-10_final
2023-09-10 10:28:28	ga_ls8c_ard_3-2-1_102069_2023-09-10_final
2023-09-10 10:28:52	ga_ls8c_ard_3-2-1_102070_2023-09-10_final
2023-09-10 10:29:16	ga_ls8c_ard_3-2-1_102071_2023-09-10_final
2023-09-10 10:29:40	ga_ls8c_ard_3-2-1_102072_2023-09-10_final
2023-09-10 10:30:04	ga_ls8c_ard_3-2-1_102073_2023-09-10_final
2023-09-12 10:18:56	ga_ls8c_ard_3-2-1_100076_2023-09-12_final
2023-09-12 10:19:20	ga_ls8c_ard_3-2-1_100077_2023-09-12_final
2023-09-12 10:19:44	ga_ls8c_ard_3-2-1_100078_2023-09-12_final
2023-09-12 10:20:08	ga_ls8c_ard_3-2-1_100079_2023-09-12_final
2023-09-12 10:20:32	ga_ls8c_ard_3-2-1_100080_2023-09-12_final
2023-09-12 10:20:56	ga_ls8c_ard_3-2-1_100081_2023-09-12_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