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
2020-07-23 11:17:01	ga_ls8c_ard_3-1-0_110067_2020-07-23_final
2020-07-23 11:17:25	ga_ls8c_ard_3-1-0_110068_2020-07-23_final
2020-07-23 11:17:49	ga_ls8c_ard_3-1-0_110069_2020-07-23_final
2020-07-23 11:18:13	ga_ls8c_ard_3-1-0_110070_2020-07-23_final
2020-07-25 11:07:28	ga_ls8c_ard_3-1-0_108074_2020-07-25_final
2020-07-25 11:07:52	ga_ls8c_ard_3-1-0_108075_2020-07-25_final
2020-07-25 11:08:16	ga_ls8c_ard_3-1-0_108076_2020-07-25_final
2020-07-25 11:08:40	ga_ls8c_ard_3-1-0_108077_2020-07-25_final
2020-07-25 11:09:04	ga_ls8c_ard_3-1-0_108078_2020-07-25_final
2020-07-25 11:09:28	ga_ls8c_ard_3-1-0_108079_2020-07-25_final
2020-07-25 11:09:52	ga_ls8c_ard_3-1-0_108080_2020-07-25_final
2020-08-01 11:12:05	ga_ls8c_ard_3-1-0_109070_2020-08-01_final
2020-08-01 11:12:28	ga_ls8c_ard_3-1-0_109071_2020-08-01_final
2020-08-01 11:12:52	ga_ls8c_ard_3-1-0_109072_2020-08-01_final
2020-08-01 11:13:16	ga_ls8c_ard_3-1-0_109073_2020-08-01_final
2020-08-01 11:13:40	ga_ls8c_ard_3-1-0_109074_2020-08-01_final
2020-08-01 11:14:04	ga_ls8c_ard_3-1-0_109075_2020-08-01_final
2020-08-03 11:02:55	ga_ls8c_ard_3-1-0_107078_2020-08-03_final
2020-08-03 11:03:19	ga_ls8c_ard_3-1-0_107079_2020-08-03_final
2020-08-03 11:03:43	ga_ls8c_ard_3-1-0_107080_2020-08-03_final
2020-08-03 11:04:07	ga_ls8c_ard_3-1-0_107081_2020-08-03_final
2020-08-03 11:04:31	ga_ls8c_ard_3-1-0_107082_2020-08-03_final
2020-08-03 11:04:55	ga_ls8c_ard_3-1-0_107083_2020-08-03_final
2020-08-03 11:05:19	ga_ls8c_ard_3-1-0_107084_2020-08-03_final
2020-08-12 10:58:21	ga_ls8c_ard_3-1-0_106082_2020-08-12_final
2020-08-12 10:58:45	ga_ls8c_ard_3-1-0_106083_2020-08-12_final
2020-08-12 10:59:09	ga_ls8c_ard_3-1-0_106084_2020-08-12_final
2020-08-28 10:58:30	ga_ls8c_ard_3-1-0_106082_2020-08-28_final
2020-08-28 10:58:54	ga_ls8c_ard_3-1-0_106083_2020-08-28_final
2020-08-28 10:59:18	ga_ls8c_ard_3-1-0_106084_2020-08-28_final
2020-11-21 11:12:27	ga_ls8c_ard_3-1-0_109070_2020-11-21_final
2020-11-21 11:12:51	ga_ls8c_ard_3-1-0_109071_2020-11-21_final
2020-11-21 11:13:14	ga_ls8c_ard_3-1-0_109072_2020-11-21_final
2020-11-21 11:13:38	ga_ls8c_ard_3-1-0_109073_2020-11-21_final
2020-11-21 11:14:02	ga_ls8c_ard_3-1-0_109074_2020-11-21_final
2020-11-21 11:14:26	ga_ls8c_ard_3-1-0_109075_2020-11-21_final
2020-12-09 11:04:31	ga_ls8c_ard_3-1-0_107081_2020-12-09_final
2020-12-09 11:04:55	ga_ls8c_ard_3-1-0_107082_2020-12-09_final
2020-12-09 11:05:19	ga_ls8c_ard_3-1-0_107083_2020-12-09_final
2021-10-23 11:12:10	ga_ls8c_ard_3-2-0_109069_2021-10-23_final
2021-10-23 11:12:34	ga_ls8c_ard_3-2-0_109070_2021-10-23_final
2021-10-23 11:12:58	ga_ls8c_ard_3-2-0_109071_2021-10-23_final
2021-10-23 11:13:22	ga_ls8c_ard_3-2-0_109072_2021-10-23_final
2021-10-23 11:13:46	ga_ls8c_ard_3-2-0_109073_2021-10-23_final
2021-10-23 11:14:09	ga_ls8c_ard_3-2-0_109074_2021-10-23_final
2021-10-23 11:14:33	ga_ls8c_ard_3-2-0_109075_2021-10-23_final
2021-11-24 11:12:29	ga_ls8c_ard_3-2-0_109070_2021-11-24_final
2021-11-24 11:12:53	ga_ls8c_ard_3-2-0_109071_2021-11-24_final
2021-11-24 11:13:17	ga_ls8c_ard_3-2-0_109072_2021-11-24_final
2021-11-24 11:13:40	ga_ls8c_ard_3-2-0_109073_2021-11-24_final
2021-11-24 11:14:04	ga_ls8c_ard_3-2-0_109074_2021-11-24_final
2021-11-24 11:14:28	ga_ls8c_ard_3-2-0_109075_2021-11-24_final
2023-02-01 11:03:21	ga_ls8c_ard_3-2-1_107078_2023-02-01_final
2023-02-01 11:03:45	ga_ls8c_ard_3-2-1_107079_2023-02-01_final
2023-02-01 11:04:08	ga_ls8c_ard_3-2-1_107080_2023-02-01_final
2023-02-01 11:04:32	ga_ls8c_ard_3-2-1_107081_2023-02-01_final
2023-02-01 11:04:56	ga_ls8c_ard_3-2-1_107082_2023-02-01_final
2023-02-01 11:05:20	ga_ls8c_ard_3-2-1_107083_2023-02-01_final
2023-02-01 11:05:44	ga_ls8c_ard_3-2-1_107084_2023-02-01_final
2023-03-21 11:02:50	ga_ls8c_ard_3-2-1_107078_2023-03-21_final
2023-03-21 11:03:14	ga_ls8c_ard_3-2-1_107079_2023-03-21_final
2023-03-21 11:03:38	ga_ls8c_ard_3-2-1_107080_2023-03-21_final
2023-03-21 11:04:02	ga_ls8c_ard_3-2-1_107081_2023-03-21_final
2023-03-21 11:04:26	ga_ls8c_ard_3-2-1_107082_2023-03-21_final
2023-03-21 11:04:50	ga_ls8c_ard_3-2-1_107083_2023-03-21_final
2023-03-21 11:05:14	ga_ls8c_ard_3-2-1_107084_2023-03-21_final
2023-04-13 11:07:06	ga_ls8c_ard_3-2-1_108074_2023-04-13_final
2023-04-13 11:07:30	ga_ls8c_ard_3-2-1_108075_2023-04-13_final
2023-04-13 11:07:54	ga_ls8c_ard_3-2-1_108076_2023-04-13_final
2023-04-13 11:08:18	ga_ls8c_ard_3-2-1_108077_2023-04-13_final
2023-04-13 11:08:42	ga_ls8c_ard_3-2-1_108078_2023-04-13_final
2023-04-13 11:09:06	ga_ls8c_ard_3-2-1_108079_2023-04-13_final
2023-04-13 11:09:30	ga_ls8c_ard_3-2-1_108080_2023-04-13_final
2023-04-15 10:58:20	ga_ls8c_ard_3-2-1_106083_2023-04-15_final
2023-04-20 11:11:38	ga_ls8c_ard_3-2-1_109070_2023-04-20_final
2023-04-20 11:12:02	ga_ls8c_ard_3-2-1_109071_2023-04-20_final
2023-04-20 11:12:26	ga_ls8c_ard_3-2-1_109072_2023-04-20_final
2023-04-20 11:12:50	ga_ls8c_ard_3-2-1_109073_2023-04-20_final
2023-04-20 11:13:14	ga_ls8c_ard_3-2-1_109074_2023-04-20_final
2023-04-20 11:13:38	ga_ls8c_ard_3-2-1_109075_2023-04-20_final
2023-10-13 11:11:54	ga_ls8c_ard_3-2-1_109069_2023-10-13_final
2023-10-13 11:12:18	ga_ls8c_ard_3-2-1_109070_2023-10-13_final
2023-10-13 11:12:42	ga_ls8c_ard_3-2-1_109071_2023-10-13_final
2023-10-13 11:13:06	ga_ls8c_ard_3-2-1_109072_2023-10-13_final
2023-10-13 11:13:30	ga_ls8c_ard_3-2-1_109073_2023-10-13_final
2023-10-13 11:13:54	ga_ls8c_ard_3-2-1_109074_2023-10-13_final
2023-10-13 11:14:17	ga_ls8c_ard_3-2-1_109075_2023-10-13_final
2023-10-15 11:03:07	ga_ls8c_ard_3-2-1_107078_2023-10-15_final
2023-10-15 11:03:07	ga_ls8c_ard_3-2-1_107078_2023-10-15_nrt
2023-10-15 11:03:31	ga_ls8c_ard_3-2-1_107079_2023-10-15_final
2023-10-15 11:03:31	ga_ls8c_ard_3-2-1_107079_2023-10-15_nrt
2023-10-15 11:03:55	ga_ls8c_ard_3-2-1_107080_2023-10-15_final
2023-10-15 11:03:55	ga_ls8c_ard_3-2-1_107080_2023-10-15_nrt
2023-10-15 11:04:19	ga_ls8c_ard_3-2-1_107081_2023-10-15_final
2023-10-15 11:04:19	ga_ls8c_ard_3-2-1_107081_2023-10-15_nrt
2023-10-15 11:04:43	ga_ls8c_ard_3-2-1_107082_2023-10-15_final
2023-10-15 11:04:43	ga_ls8c_ard_3-2-1_107082_2023-10-15_nrt
2023-10-15 11:05:07	ga_ls8c_ard_3-2-1_107083_2023-10-15_final
2023-10-15 11:05:07	ga_ls8c_ard_3-2-1_107083_2023-10-15_nrt
2023-10-15 11:05:31	ga_ls8c_ard_3-2-1_107084_2023-10-15_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years