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
2022-10-01 09:41:15	ga_ls8c_ard_3-2-1_094073_2022-10-01_final
2022-10-10 11:16:40	ga_ls8c_ard_3-2-1_109080_2022-10-10_final
2022-10-17 09:43:09	ga_ls8c_ard_3-2-1_094078_2022-10-17_final
2022-10-17 11:22:02	ga_ls8c_ard_3-2-1_110078_2022-10-17_final
2022-10-19 11:10:30	ga_ls8c_ard_3-2-1_108080_2022-10-19_final
2022-10-19 11:11:18	ga_ls8c_ard_3-2-1_108082_2022-10-19_final
2022-10-23 10:41:26	ga_ls8c_ard_3-2-1_104069_2022-10-23_final
2022-10-24 11:28:41	ga_ls8c_ard_3-2-1_111079_2022-10-24_final
2022-10-27 10:21:07	ga_ls8c_ard_3-2-1_100080_2022-10-27_final
2022-10-28 11:05:59	ga_ls8c_ard_3-2-1_107084_2022-10-28_final
2022-10-30 10:47:39	ga_ls8c_ard_3-2-1_105069_2022-10-30_final
2022-10-31 11:35:18	ga_ls8c_ard_3-2-1_112080_2022-10-31_final
2022-11-01 10:38:53	ga_ls8c_ard_3-2-1_103078_2022-11-01_final
2022-11-02 09:43:16	ga_ls8c_ard_3-2-1_094078_2022-11-02_final
2022-11-02 11:21:45	ga_ls8c_ard_3-2-1_110077_2022-11-02_final
2022-11-04 09:29:42	ga_ls8c_ard_3-2-1_092075_2022-11-03_final
2022-11-04 09:30:06	ga_ls8c_ard_3-2-1_092076_2022-11-04_final
2022-11-04 09:30:54	ga_ls8c_ard_3-2-1_092078_2022-11-04_final
2022-11-04 11:09:47	ga_ls8c_ard_3-2-1_108078_2022-11-04_final
2022-11-04 11:10:11	ga_ls8c_ard_3-2-1_108079_2022-11-04_final
2022-11-04 11:11:23	ga_ls8c_ard_3-2-1_108082_2022-11-04_final
2022-11-05 10:14:57	ga_ls8c_ard_3-2-1_099080_2022-11-05_final
2022-11-05 10:15:21	ga_ls8c_ard_3-2-1_099081_2022-11-05_final
2022-11-06 10:53:49	ga_ls8c_ard_3-2-1_106069_2022-11-06_final
2022-11-06 10:54:13	ga_ls8c_ard_3-2-1_106070_2022-11-06_final
2022-11-08 10:41:03	ga_ls8c_ard_3-2-1_104068_2022-11-08_final
2022-11-09 11:25:30	ga_ls8c_ard_3-2-1_111071_2022-11-09_final
2022-11-09 11:27:54	ga_ls8c_ard_3-2-1_111077_2022-11-09_final
2022-11-09 11:28:42	ga_ls8c_ard_3-2-1_111079_2022-11-09_final
2022-11-11 09:36:38	ga_ls8c_ard_3-2-1_093077_2022-11-11_final
2022-11-11 11:15:07	ga_ls8c_ard_3-2-1_109076_2022-11-11_final
2022-11-14 10:08:18	ga_ls8c_ard_3-2-1_098079_2022-11-14_final
2022-11-16 09:56:19	ga_ls8c_ard_3-2-1_096080_2022-11-16_final
2022-11-16 11:35:12	ga_ls8c_ard_3-2-1_112080_2022-11-16_final
2022-11-17 10:35:34	ga_ls8c_ard_3-2-1_103070_2022-11-17_final
2022-11-20 09:31:11	ga_ls8c_ard_3-2-1_092079_2022-11-20_final
2022-11-20 11:09:16	ga_ls8c_ard_3-2-1_108077_2022-11-20_final
2022-11-21 10:12:03	ga_ls8c_ard_3-2-1_099073_2022-11-21_final
2022-11-22 09:19:14	ga_ls8c_ard_3-2-1_090080_2022-11-21_final
2022-11-22 09:20:50	ga_ls8c_ard_3-2-1_090084_2022-11-21_final
2022-11-23 10:00:54	ga_ls8c_ard_3-2-1_097076_2022-11-23_final
2022-11-24 10:40:59	ga_ls8c_ard_3-2-1_104068_2022-11-24_final
2022-11-25 09:49:45	ga_ls8c_ard_3-2-1_095079_2022-11-25_final
2022-11-25 09:52:09	ga_ls8c_ard_3-2-1_095085_2022-11-25_final
2022-11-28 10:20:39	ga_ls8c_ard_3-2-1_100079_2022-11-28_final
2022-11-29 09:25:02	ga_ls8c_ard_3-2-1_091079_2022-11-28_final
2022-12-02 09:56:20	ga_ls8c_ard_3-2-1_096080_2022-12-02_final
2022-12-04 09:43:35	ga_ls8c_ard_3-2-1_094079_2022-12-04_final
2022-12-04 09:45:10	ga_ls8c_ard_3-2-1_094083_2022-12-04_final
2022-12-05 10:28:02	ga_ls8c_ard_3-2-1_101082_2022-12-05_final
2022-12-06 09:30:25	ga_ls8c_ard_3-2-1_092077_2022-12-06_final
2022-12-07 10:16:28	ga_ls8c_ard_3-2-1_099084_2022-12-07_final
2022-12-11 11:27:48	ga_ls8c_ard_3-2-1_111077_2022-12-11_final
2022-12-16 10:09:25	ga_ls8c_ard_3-2-1_098082_2022-12-16_final
2022-12-18 11:33:07	ga_ls8c_ard_3-2-1_112075_2022-12-18_final
2022-12-20 09:42:38	ga_ls8c_ard_3-2-1_094077_2022-12-20_final
2022-12-20 09:43:02	ga_ls8c_ard_3-2-1_094078_2022-12-20_final
2022-12-22 11:09:07	ga_ls8c_ard_3-2-1_108077_2022-12-22_final
2022-12-22 11:10:19	ga_ls8c_ard_3-2-1_108080_2022-12-22_final
2022-12-23 10:15:05	ga_ls8c_ard_3-2-1_099081_2022-12-23_final
2022-12-24 10:58:45	ga_ls8c_ard_3-2-1_106082_2022-12-24_final
2022-12-31 09:24:30	ga_ls8c_ard_3-2-1_091078_2022-12-30_final
2022-12-31 11:02:35	ga_ls8c_ard_3-2-1_107076_2022-12-31_final
2023-01-03 09:55:00	ga_ls8c_ard_3-2-1_096077_2023-01-03_final
2023-01-03 11:33:53	ga_ls8c_ard_3-2-1_112077_2023-01-03_final
2023-01-06 10:26:17	ga_ls8c_ard_3-2-1_101078_2023-01-06_final
2023-01-09 10:53:59	ga_ls8c_ard_3-2-1_106070_2023-01-09_final
2023-01-09 10:54:23	ga_ls8c_ard_3-2-1_106071_2023-01-09_final
2023-01-11 10:44:47	ga_ls8c_ard_3-2-1_104078_2023-01-11_final
2023-01-11 10:45:59	ga_ls8c_ard_3-2-1_104081_2023-01-11_final
2023-01-12 11:28:26	ga_ls8c_ard_3-2-1_111079_2023-01-12_final
2023-01-13 10:28:49	ga_ls8c_ard_3-2-1_102069_2023-01-13_final
2023-01-16 11:02:52	ga_ls8c_ard_3-2-1_107077_2023-01-16_final
2023-01-19 11:34:57	ga_ls8c_ard_3-2-1_112080_2023-01-19_final
2023-01-20 10:38:33	ga_ls8c_ard_3-2-1_103078_2023-01-20_final
2023-01-20 10:39:21	ga_ls8c_ard_3-2-1_103080_2023-01-20_final
2023-01-21 09:42:32	ga_ls8c_ard_3-2-1_094077_2023-01-21_final
2023-01-22 10:27:49	ga_ls8c_ard_3-2-1_101082_2023-01-22_final
2023-01-23 11:11:05	ga_ls8c_ard_3-2-1_108082_2023-01-23_final
2023-01-24 10:13:28	ga_ls8c_ard_3-2-1_099077_2023-01-24_final
2023-01-26 10:04:19	ga_ls8c_ard_3-2-1_097085_2023-01-26_final
2023-02-09 10:12:16	ga_ls8c_ard_3-2-1_099074_2023-02-09_final
2023-02-15 11:16:23	ga_ls8c_ard_3-2-1_109080_2023-02-15_final
2023-02-17 09:24:19	ga_ls8c_ard_3-2-1_091078_2023-02-16_final
2023-02-18 11:47:14	ga_ls8c_ard_3-2-1_114080_2023-02-18_final
2023-02-20 09:55:33	ga_ls8c_ard_3-2-1_096079_2023-02-20_final
2023-02-20 11:34:50	ga_ls8c_ard_3-2-1_112080_2023-02-20_final
2023-02-22 09:42:45	ga_ls8c_ard_3-2-1_094078_2023-02-22_final
2023-02-22 09:43:57	ga_ls8c_ard_3-2-1_094081_2023-02-22_final
2023-02-22 11:21:38	ga_ls8c_ard_3-2-1_110078_2023-02-22_final
2023-02-23 10:27:35	ga_ls8c_ard_3-2-1_101082_2023-02-23_final
2023-02-24 09:29:08	ga_ls8c_ard_3-2-1_092075_2023-02-23_final
2023-02-24 09:29:56	ga_ls8c_ard_3-2-1_092077_2023-02-23_final
2023-03-01 09:49:15	ga_ls8c_ard_3-2-1_095079_2023-03-01_final
2023-03-03 11:15:46	ga_ls8c_ard_3-2-1_109079_2023-03-03_final
2023-03-03 11:16:10	ga_ls8c_ard_3-2-1_109080_2023-03-03_final
2023-03-04 10:22:08	ga_ls8c_ard_3-2-1_100084_2023-03-04_final
2023-03-05 11:02:35	ga_ls8c_ard_3-2-1_107077_2023-03-05_final
2023-03-07 10:50:36	ga_ls8c_ard_3-2-1_105078_2023-03-07_final
2023-03-08 09:55:45	ga_ls8c_ard_3-2-1_096080_2023-03-08_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