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
2019-03-22 09:47:35	ga_ls8c_ard_3-1-0_095076_2019-03-22_final
2019-03-22 09:48:46	ga_ls8c_ard_3-1-0_095079_2019-03-22_final
2019-04-14 09:53:15	ga_ls8c_ard_3-1-0_096075_2019-04-14_final
2019-04-14 09:56:03	ga_ls8c_ard_3-1-0_096082_2019-04-14_final
2019-06-26 09:49:05	ga_ls8c_ard_3-1-0_095079_2019-06-26_final
2019-07-12 09:49:08	ga_ls8c_ard_3-1-0_095079_2019-07-12_final
2019-07-16 09:24:01	ga_ls8c_ard_3-1-0_091078_2019-07-15_final
2019-08-17 09:24:37	ga_ls8c_ard_3-1-0_091079_2019-08-16_final
2019-09-02 09:24:41	ga_ls8c_ard_3-1-0_091079_2019-09-01_final
2019-09-18 09:24:46	ga_ls8c_ard_3-1-0_091079_2019-09-17_final
2019-09-30 09:47:57	ga_ls8c_ard_3-1-0_095075_2019-09-30_final
2019-09-30 09:48:21	ga_ls8c_ard_3-1-0_095076_2019-09-30_final
2019-09-30 09:49:33	ga_ls8c_ard_3-1-0_095079_2019-09-30_final
2019-10-04 09:24:50	ga_ls8c_ard_3-1-0_091079_2019-10-03_final
2019-10-16 09:49:35	ga_ls8c_ard_3-1-0_095079_2019-10-16_final
2019-10-20 09:24:52	ga_ls8c_ard_3-1-0_091079_2019-10-19_final
2019-11-01 09:48:47	ga_ls8c_ard_3-1-0_095077_2019-11-01_final
2019-11-05 09:24:51	ga_ls8c_ard_3-1-0_091079_2019-11-04_final
2019-11-08 09:55:21	ga_ls8c_ard_3-1-0_096078_2019-11-08_final
2019-11-21 09:24:48	ga_ls8c_ard_3-1-0_091079_2019-11-20_final
2019-11-24 09:54:06	ga_ls8c_ard_3-1-0_096075_2019-11-24_final
2019-11-24 09:55:18	ga_ls8c_ard_3-1-0_096078_2019-11-24_final
2019-12-07 09:24:47	ga_ls8c_ard_3-1-0_091079_2019-12-06_final
2019-12-10 09:55:17	ga_ls8c_ard_3-1-0_096078_2019-12-10_final
2020-01-08 09:24:40	ga_ls8c_ard_3-1-0_091079_2020-01-07_final
2020-01-20 09:48:09	ga_ls8c_ard_3-1-0_095076_2020-01-20_final
2020-01-20 09:49:21	ga_ls8c_ard_3-1-0_095079_2020-01-20_final
2020-02-05 09:48:27	ga_ls8c_ard_3-1-0_095077_2020-02-05_final
2020-02-28 09:54:09	ga_ls8c_ard_3-1-0_096076_2020-02-28_final
2020-03-24 09:51:22	ga_ls8c_ard_3-1-0_095085_2020-03-24_final
2020-04-09 09:48:02	ga_ls8c_ard_3-1-0_095077_2020-04-09_final
2020-04-09 09:48:26	ga_ls8c_ard_3-1-0_095078_2020-04-09_final
2022-03-31 10:31:00	ga_ls8c_ard_3-2-1_102076_2022-03-31_final
2022-03-31 10:31:48	ga_ls8c_ard_3-2-1_102078_2022-03-31_final
2022-04-01 09:38:10	ga_ls8c_ard_3-2-1_093083_2022-04-01_final
2022-04-04 10:05:29	ga_ls8c_ard_3-2-1_098074_2022-04-04_final
2022-04-04 10:06:17	ga_ls8c_ard_3-2-1_098076_2022-04-04_final
2022-04-04 10:08:17	ga_ls8c_ard_3-2-1_098081_2022-04-04_final
2022-04-05 10:50:46	ga_ls8c_ard_3-2-1_105079_2022-04-05_final
2022-04-06 09:54:45	ga_ls8c_ard_3-2-1_096078_2022-04-06_final
2022-04-07 10:38:01	ga_ls8c_ard_3-2-1_103078_2022-04-07_final
2022-04-07 10:38:25	ga_ls8c_ard_3-2-1_103079_2022-04-07_final
2022-04-08 11:21:42	ga_ls8c_ard_3-2-1_110079_2022-04-08_final
2022-04-09 10:26:05	ga_ls8c_ard_3-2-1_101079_2022-04-09_final
2022-04-11 10:11:44	ga_ls8c_ard_3-2-1_099074_2022-04-11_final
2022-04-14 10:44:39	ga_ls8c_ard_3-2-1_104079_2022-04-14_final
2022-04-15 11:27:55	ga_ls8c_ard_3-2-1_111079_2022-04-15_final
2022-04-16 10:31:06	ga_ls8c_ard_3-2-1_102076_2022-04-16_final
2022-04-16 10:31:54	ga_ls8c_ard_3-2-1_102078_2022-04-16_final
2022-04-17 09:37:52	ga_ls8c_ard_3-2-1_093082_2022-04-17_final
2022-04-17 09:38:16	ga_ls8c_ard_3-2-1_093083_2022-04-17_final
2022-04-20 10:05:10	ga_ls8c_ard_3-2-1_098073_2022-04-20_final
2022-04-20 10:05:34	ga_ls8c_ard_3-2-1_098074_2022-04-20_final
2022-04-20 11:45:15	ga_ls8c_ard_3-2-1_114076_2022-04-20_final
2022-04-21 10:50:25	ga_ls8c_ard_3-2-1_105078_2022-04-21_final
2022-04-22 09:52:24	ga_ls8c_ard_3-2-1_096072_2022-04-22_final
2022-04-22 09:53:35	ga_ls8c_ard_3-2-1_096075_2022-04-22_final
2022-04-22 09:54:23	ga_ls8c_ard_3-2-1_096077_2022-04-22_final
2022-04-22 09:54:47	ga_ls8c_ard_3-2-1_096078_2022-04-22_final
2022-04-22 09:55:35	ga_ls8c_ard_3-2-1_096080_2022-04-22_final
2022-04-22 11:32:52	ga_ls8c_ard_3-2-1_112076_2022-04-22_final
2022-04-24 11:21:18	ga_ls8c_ard_3-2-1_110078_2022-04-24_final
2022-04-24 11:21:42	ga_ls8c_ard_3-2-1_110079_2022-04-24_final
2022-04-29 11:39:48	ga_ls8c_ard_3-2-1_113078_2022-04-29_final
2022-05-01 09:48:11	ga_ls8c_ard_3-2-1_095077_2022-05-01_final
2022-05-01 09:48:35	ga_ls8c_ard_3-2-1_095078_2022-05-01_final
2022-05-01 11:27:52	ga_ls8c_ard_3-2-1_111079_2022-05-01_final
2022-05-02 10:31:51	ga_ls8c_ard_3-2-1_102078_2022-05-02_final
2022-05-02 10:32:15	ga_ls8c_ard_3-2-1_102079_2022-05-02_final
2022-05-03 09:37:51	ga_ls8c_ard_3-2-1_093082_2022-05-03_final
2022-05-03 11:15:32	ga_ls8c_ard_3-2-1_109079_2022-05-03_final
2022-05-06 10:06:23	ga_ls8c_ard_3-2-1_098076_2022-05-06_final
2022-05-06 10:08:23	ga_ls8c_ard_3-2-1_098081_2022-05-06_final
2022-05-07 10:50:04	ga_ls8c_ard_3-2-1_105077_2022-05-07_final
2022-05-07 10:50:28	ga_ls8c_ard_3-2-1_105078_2022-05-07_final
2022-05-07 10:52:27	ga_ls8c_ard_3-2-1_105083_2022-05-07_final
2022-05-08 09:54:51	ga_ls8c_ard_3-2-1_096078_2022-05-08_final
2022-05-08 11:34:32	ga_ls8c_ard_3-2-1_112080_2022-05-08_final
2022-05-09 10:38:31	ga_ls8c_ard_3-2-1_103079_2022-05-09_final
2022-05-10 11:21:47	ga_ls8c_ard_3-2-1_110079_2022-05-10_final
2022-05-11 10:26:11	ga_ls8c_ard_3-2-1_101079_2022-05-11_final
2022-05-11 10:26:35	ga_ls8c_ard_3-2-1_101080_2022-05-11_final
2022-05-13 10:14:38	ga_ls8c_ard_3-2-1_099081_2022-05-13_final
2022-05-15 10:02:41	ga_ls8c_ard_3-2-1_097082_2022-05-15_final
2022-05-15 11:38:46	ga_ls8c_ard_3-2-1_113075_2022-05-15_final
2022-05-15 11:39:34	ga_ls8c_ard_3-2-1_113077_2022-05-15_final
2022-05-15 11:39:58	ga_ls8c_ard_3-2-1_113078_2022-05-15_final
2022-05-19 11:15:40	ga_ls8c_ard_3-2-1_109079_2022-05-19_final
2022-05-19 11:16:04	ga_ls8c_ard_3-2-1_109080_2022-05-19_final
2022-05-24 09:52:31	ga_ls8c_ard_3-2-1_096072_2022-05-24_final
2022-05-24 11:32:36	ga_ls8c_ard_3-2-1_112075_2022-05-24_final
2022-05-24 11:33:00	ga_ls8c_ard_3-2-1_112076_2022-05-24_final
2022-05-25 10:36:59	ga_ls8c_ard_3-2-1_103075_2022-05-25_final
2022-06-02 11:28:05	ga_ls8c_ard_3-2-1_111079_2022-06-02_final
2022-06-04 09:38:28	ga_ls8c_ard_3-2-1_093083_2022-06-04_final
2022-06-04 11:16:09	ga_ls8c_ard_3-2-1_109080_2022-06-04_final
2022-06-05 11:58:38	ga_ls8c_ard_3-2-1_116078_2022-06-05_final
2022-06-13 11:09:17	ga_ls8c_ard_3-2-1_108078_2022-06-13_final
2022-06-15 10:58:57	ga_ls8c_ard_3-2-1_106083_2022-06-15_final
2022-06-20 09:38:14	ga_ls8c_ard_3-2-1_093082_2022-06-20_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