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
2019-03-10 09:27:18	ga_ls8c_ard_3-1-0_091087_2019-03-09_final
2019-04-18 11:04:59	ga_ls8c_ard_3-1-0_108069_2019-04-18_final
2019-06-21 11:09:00	ga_ls8c_ard_3-1-0_108078_2019-06-21_final
2019-07-02 10:48:31	ga_ls8c_ard_3-1-0_105073_2019-07-02_final
2019-07-03 09:52:30	ga_ls8c_ard_3-1-0_096072_2019-07-03_final
2019-07-03 09:57:41	ga_ls8c_ard_3-1-0_096085_2019-07-03_final
2019-07-16 09:27:13	ga_ls8c_ard_3-1-0_091086_2019-07-15_final
2019-08-03 10:48:40	ga_ls8c_ard_3-1-0_105073_2019-08-03_final
2019-08-03 10:50:16	ga_ls8c_ard_3-1-0_105077_2019-08-03_final
2019-08-08 11:06:27	ga_ls8c_ard_3-1-0_108071_2019-08-08_final
2019-08-19 10:49:09	ga_ls8c_ard_3-1-0_105074_2019-08-19_final
2019-08-19 10:50:21	ga_ls8c_ard_3-1-0_105077_2019-08-19_final
2019-08-19 10:51:33	ga_ls8c_ard_3-1-0_105080_2019-08-19_final
2019-08-20 09:56:44	ga_ls8c_ard_3-1-0_096082_2019-08-20_final
2019-08-29 09:47:00	ga_ls8c_ard_3-1-0_095073_2019-08-29_final
2019-09-09 11:06:35	ga_ls8c_ard_3-1-0_108071_2019-09-09_final
2019-09-18 09:25:10	ga_ls8c_ard_3-1-0_091080_2019-09-17_final
2019-09-20 10:48:54	ga_ls8c_ard_3-1-0_105073_2019-09-20_final
2019-09-21 09:52:53	ga_ls8c_ard_3-1-0_096072_2019-09-21_final
2019-09-21 09:56:53	ga_ls8c_ard_3-1-0_096082_2019-09-21_final
2019-09-30 09:47:57	ga_ls8c_ard_3-1-0_095075_2019-09-30_final
2019-09-30 09:52:20	ga_ls8c_ard_3-1-0_095086_2019-09-30_final
2019-10-16 09:48:23	ga_ls8c_ard_3-1-0_095076_2019-10-16_final
2019-10-22 10:48:36	ga_ls8c_ard_3-1-0_105072_2019-10-22_final
2019-10-22 10:49:00	ga_ls8c_ard_3-1-0_105073_2019-10-22_final
2019-11-01 09:47:11	ga_ls8c_ard_3-1-0_095073_2019-11-01_final
2019-11-01 09:47:59	ga_ls8c_ard_3-1-0_095075_2019-11-01_final
2019-11-07 10:48:59	ga_ls8c_ard_3-1-0_105073_2019-11-07_final
2019-11-08 09:52:33	ga_ls8c_ard_3-1-0_096071_2019-11-08_final
2019-11-12 11:06:42	ga_ls8c_ard_3-1-0_108071_2019-11-12_final
2019-11-21 09:24:00	ga_ls8c_ard_3-1-0_091077_2019-11-20_final
2019-11-21 09:25:12	ga_ls8c_ard_3-1-0_091080_2019-11-20_final
2019-11-23 10:52:55	ga_ls8c_ard_3-1-0_105083_2019-11-23_final
2019-11-24 09:56:53	ga_ls8c_ard_3-1-0_096082_2019-11-24_final
2019-12-07 09:23:35	ga_ls8c_ard_3-1-0_091076_2019-12-06_final
2019-12-09 10:48:31	ga_ls8c_ard_3-1-0_105072_2019-12-09_final
2019-12-23 09:28:20	ga_ls8c_ard_3-1-0_091088_2019-12-22_final
2020-01-04 09:47:48	ga_ls8c_ard_3-1-0_095075_2020-01-04_final
2020-01-04 09:49:48	ga_ls8c_ard_3-1-0_095080_2020-01-04_final
2020-01-08 09:25:52	ga_ls8c_ard_3-1-0_091082_2020-01-07_final
2020-01-27 09:56:41	ga_ls8c_ard_3-1-0_096082_2020-01-27_final
2020-02-16 11:10:46	ga_ls8c_ard_3-1-0_108082_2020-02-16_final
2020-02-21 09:47:13	ga_ls8c_ard_3-1-0_095074_2020-02-21_final
2020-03-28 09:28:12	ga_ls8c_ard_3-1-0_091089_2020-03-27_final
2020-03-30 10:47:07	ga_ls8c_ard_3-1-0_105070_2020-03-30_final
2020-04-09 09:52:02	ga_ls8c_ard_3-1-0_095087_2020-04-09_final
2020-04-15 10:49:48	ga_ls8c_ard_3-1-0_105077_2020-04-15_final
2020-04-20 11:07:54	ga_ls8c_ard_3-1-0_108076_2020-04-20_final
2020-04-29 09:24:46	ga_ls8c_ard_3-1-0_091081_2020-04-28_final
2020-05-02 09:57:14	ga_ls8c_ard_3-1-0_096085_2020-05-02_final
2022-04-03 09:23:25	ga_ls8c_ard_3-2-1_091077_2022-04-02_final
2022-04-03 10:59:54	ga_ls8c_ard_3-2-1_107071_2022-04-03_final
2022-04-04 10:05:05	ga_ls8c_ard_3-2-1_098073_2022-04-04_final
2022-04-04 10:07:05	ga_ls8c_ard_3-2-1_098078_2022-04-04_final
2022-04-05 10:47:58	ga_ls8c_ard_3-2-1_105072_2022-04-05_final
2022-04-06 09:51:57	ga_ls8c_ard_3-2-1_096071_2022-04-06_final
2022-04-06 09:52:21	ga_ls8c_ard_3-2-1_096072_2022-04-06_final
2022-04-06 11:34:50	ga_ls8c_ard_3-2-1_112081_2022-04-06_final
2022-04-07 10:34:26	ga_ls8c_ard_3-2-1_103069_2022-04-07_final
2022-04-10 09:30:52	ga_ls8c_ard_3-2-1_092080_2022-04-10_final
2022-04-14 10:41:04	ga_ls8c_ard_3-2-1_104070_2022-04-14_final
2022-04-16 10:30:42	ga_ls8c_ard_3-2-1_102075_2022-04-16_final
2022-04-18 10:19:32	ga_ls8c_ard_3-2-1_100078_2022-04-18_final
2022-04-20 10:06:46	ga_ls8c_ard_3-2-1_098077_2022-04-20_final
2022-04-21 09:12:44	ga_ls8c_ard_3-2-1_089081_2022-04-20_final
2022-04-21 10:46:26	ga_ls8c_ard_3-2-1_105068_2022-04-21_final
2022-04-24 11:20:06	ga_ls8c_ard_3-2-1_110075_2022-04-24_final
2022-04-26 11:06:55	ga_ls8c_ard_3-2-1_108073_2022-04-26_final
2022-04-27 10:14:53	ga_ls8c_ard_3-2-1_099082_2022-04-27_final
2022-04-28 10:53:45	ga_ls8c_ard_3-2-1_106071_2022-04-28_final
2022-04-29 11:41:00	ga_ls8c_ard_3-2-1_113081_2022-04-29_final
2022-04-30 10:41:48	ga_ls8c_ard_3-2-1_104072_2022-04-30_final
2022-05-02 10:30:16	ga_ls8c_ard_3-2-1_102074_2022-05-02_final
2022-05-03 09:38:15	ga_ls8c_ard_3-2-1_093083_2022-05-03_final
2022-05-05 09:28:18	ga_ls8c_ard_3-2-1_091089_2022-05-04_final
2022-05-06 10:06:47	ga_ls8c_ard_3-2-1_098077_2022-05-06_final
2022-05-06 10:09:59	ga_ls8c_ard_3-2-1_098085_2022-05-06_final
2022-05-10 11:19:00	ga_ls8c_ard_3-2-1_110072_2022-05-10_final
2022-05-13 10:13:02	ga_ls8c_ard_3-2-1_099077_2022-05-13_final
2022-05-16 09:06:16	ga_ls8c_ard_3-2-1_088080_2022-05-15_final
2022-05-16 10:41:10	ga_ls8c_ard_3-2-1_104070_2022-05-16_final
2022-05-19 09:38:23	ga_ls8c_ard_3-2-1_093083_2022-05-19_final
2022-05-19 09:38:46	ga_ls8c_ard_3-2-1_093084_2022-05-19_final
2022-05-20 10:18:03	ga_ls8c_ard_3-2-1_100074_2022-05-20_final
2022-05-23 09:14:03	ga_ls8c_ard_3-2-1_089084_2022-05-22_final
2022-05-24 09:52:55	ga_ls8c_ard_3-2-1_096073_2022-05-24_final
2022-05-26 09:44:09	ga_ls8c_ard_3-2-1_094082_2022-05-26_final
2022-05-31 10:01:32	ga_ls8c_ard_3-2-1_097079_2022-05-31_final
2022-05-31 10:02:44	ga_ls8c_ard_3-2-1_097082_2022-05-31_final
2022-06-04 09:34:53	ga_ls8c_ard_3-2-1_093074_2022-06-04_final
2022-06-04 09:38:28	ga_ls8c_ard_3-2-1_093083_2022-06-04_final
2022-06-05 10:17:21	ga_ls8c_ard_3-2-1_100072_2022-06-05_final
2022-06-06 11:00:38	ga_ls8c_ard_3-2-1_107072_2022-06-06_final
2022-06-07 10:05:01	ga_ls8c_ard_3-2-1_098072_2022-06-07_final
2022-06-07 10:05:25	ga_ls8c_ard_3-2-1_098073_2022-06-07_final
2022-06-13 09:31:36	ga_ls8c_ard_3-2-1_092081_2022-06-13_final
2022-06-13 11:06:54	ga_ls8c_ard_3-2-1_108072_2022-06-13_final
2022-06-15 10:58:57	ga_ls8c_ard_3-2-1_106083_2022-06-15_final
2022-06-16 09:59:21	ga_ls8c_ard_3-2-1_097073_2022-06-16_final
2022-06-16 10:01:20	ga_ls8c_ard_3-2-1_097078_2022-06-16_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