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 09:49:34	ga_ls8c_ard_3-1-0_095081_2019-03-22_final
2019-04-07 09:48:43	ga_ls8c_ard_3-1-0_095079_2019-04-07_final
2019-04-07 09:49:06	ga_ls8c_ard_3-1-0_095080_2019-04-07_final
2019-04-07 09:50:42	ga_ls8c_ard_3-1-0_095084_2019-04-07_final
2019-06-26 09:49:29	ga_ls8c_ard_3-1-0_095080_2019-06-26_final
2019-07-12 09:47:56	ga_ls8c_ard_3-1-0_095076_2019-07-12_final
2019-07-12 09:49:08	ga_ls8c_ard_3-1-0_095079_2019-07-12_final
2019-07-28 09:48:49	ga_ls8c_ard_3-1-0_095078_2019-07-28_final
2019-07-28 09:49:13	ga_ls8c_ard_3-1-0_095079_2019-07-28_final
2019-08-13 09:51:43	ga_ls8c_ard_3-1-0_095085_2019-08-13_final
2019-08-29 09:52:11	ga_ls8c_ard_3-1-0_095086_2019-08-29_final
2019-09-14 09:48:40	ga_ls8c_ard_3-1-0_095077_2019-09-14_final
2019-09-14 09:51:28	ga_ls8c_ard_3-1-0_095084_2019-09-14_final
2019-09-30 09:50:21	ga_ls8c_ard_3-1-0_095081_2019-09-30_final
2019-09-30 09:50:45	ga_ls8c_ard_3-1-0_095082_2019-09-30_final
2019-10-16 09:49:35	ga_ls8c_ard_3-1-0_095079_2019-10-16_final
2019-10-16 09:50:23	ga_ls8c_ard_3-1-0_095081_2019-10-16_final
2019-11-01 09:52:47	ga_ls8c_ard_3-1-0_095087_2019-11-01_final
2020-01-04 09:49:00	ga_ls8c_ard_3-1-0_095078_2020-01-04_final
2020-01-04 09:51:00	ga_ls8c_ard_3-1-0_095083_2020-01-04_final
2020-01-20 09:46:33	ga_ls8c_ard_3-1-0_095072_2020-01-20_final
2020-01-20 09:49:21	ga_ls8c_ard_3-1-0_095079_2020-01-20_final
2020-02-05 09:49:39	ga_ls8c_ard_3-1-0_095080_2020-02-05_final
2020-02-21 09:48:48	ga_ls8c_ard_3-1-0_095078_2020-02-21_final
2020-02-21 09:51:36	ga_ls8c_ard_3-1-0_095085_2020-02-21_final
2020-03-08 09:48:43	ga_ls8c_ard_3-1-0_095078_2020-03-08_final
2020-03-08 09:49:07	ga_ls8c_ard_3-1-0_095079_2020-03-08_final
2022-03-29 10:43:46	ga_ls8c_ard_3-2-1_104077_2022-03-29_final
2022-03-30 11:27:49	ga_ls8c_ard_3-2-1_111079_2022-03-30_final
2022-03-31 10:31:00	ga_ls8c_ard_3-2-1_102076_2022-03-31_final
2022-04-01 09:34:11	ga_ls8c_ard_3-2-1_093073_2022-04-01_final
2022-04-01 09:36:10	ga_ls8c_ard_3-2-1_093078_2022-04-01_final
2022-04-02 10:17:26	ga_ls8c_ard_3-2-1_100073_2022-04-02_final
2022-04-03 11:03:06	ga_ls8c_ard_3-2-1_107079_2022-04-03_final
2022-04-05 10:50:46	ga_ls8c_ard_3-2-1_105079_2022-04-05_final
2022-04-06 11:32:02	ga_ls8c_ard_3-2-1_112074_2022-04-06_final
2022-04-06 11:32:50	ga_ls8c_ard_3-2-1_112076_2022-04-06_final
2022-04-06 11:33:38	ga_ls8c_ard_3-2-1_112078_2022-04-06_final
2022-04-06 11:34:26	ga_ls8c_ard_3-2-1_112080_2022-04-06_final
2022-04-07 10:34:50	ga_ls8c_ard_3-2-1_103070_2022-04-07_final
2022-04-07 10:36:50	ga_ls8c_ard_3-2-1_103075_2022-04-07_final
2022-04-08 09:45:36	ga_ls8c_ard_3-2-1_094086_2022-04-08_final
2022-04-09 10:26:29	ga_ls8c_ard_3-2-1_101080_2022-04-09_final
2022-04-09 10:27:41	ga_ls8c_ard_3-2-1_101083_2022-04-09_final
2022-04-11 10:12:08	ga_ls8c_ard_3-2-1_099075_2022-04-11_final
2022-04-12 10:56:36	ga_ls8c_ard_3-2-1_106078_2022-04-12_final
2022-04-14 10:43:27	ga_ls8c_ard_3-2-1_104076_2022-04-14_final
2022-04-16 10:30:18	ga_ls8c_ard_3-2-1_102074_2022-04-16_final
2022-04-18 10:17:32	ga_ls8c_ard_3-2-1_100073_2022-04-18_final
2022-04-19 09:23:54	ga_ls8c_ard_3-2-1_091078_2022-04-18_final
2022-04-19 11:03:11	ga_ls8c_ard_3-2-1_107079_2022-04-19_final
2022-04-20 10:08:45	ga_ls8c_ard_3-2-1_098082_2022-04-20_final
2022-04-22 09:56:23	ga_ls8c_ard_3-2-1_096082_2022-04-22_final
2022-04-22 11:33:16	ga_ls8c_ard_3-2-1_112077_2022-04-22_final
2022-04-23 10:36:51	ga_ls8c_ard_3-2-1_103075_2022-04-23_final
2022-04-23 10:37:15	ga_ls8c_ard_3-2-1_103076_2022-04-23_final
2022-04-27 10:12:05	ga_ls8c_ard_3-2-1_099075_2022-04-27_final
2022-04-30 10:43:23	ga_ls8c_ard_3-2-1_104076_2022-04-30_final
2022-04-30 10:43:47	ga_ls8c_ard_3-2-1_104077_2022-04-30_final
2022-04-30 10:45:23	ga_ls8c_ard_3-2-1_104081_2022-04-30_final
2022-05-02 10:28:40	ga_ls8c_ard_3-2-1_102070_2022-05-02_final
2022-05-04 10:18:44	ga_ls8c_ard_3-2-1_100076_2022-05-04_final
2022-05-06 10:05:59	ga_ls8c_ard_3-2-1_098075_2022-05-06_final
2022-05-06 10:08:47	ga_ls8c_ard_3-2-1_098082_2022-05-06_final
2022-05-08 09:52:27	ga_ls8c_ard_3-2-1_096072_2022-05-08_final
2022-05-08 09:53:39	ga_ls8c_ard_3-2-1_096075_2022-05-08_final
2022-05-08 11:32:56	ga_ls8c_ard_3-2-1_112076_2022-05-08_final
2022-05-09 10:38:07	ga_ls8c_ard_3-2-1_103078_2022-05-09_final
2022-05-10 11:22:11	ga_ls8c_ard_3-2-1_110080_2022-05-10_final
2022-05-10 11:22:35	ga_ls8c_ard_3-2-1_110081_2022-05-10_final
2022-05-11 10:26:35	ga_ls8c_ard_3-2-1_101080_2022-05-11_final
2022-05-12 11:06:39	ga_ls8c_ard_3-2-1_108072_2022-05-12_final
2022-05-13 10:14:14	ga_ls8c_ard_3-2-1_099080_2022-05-13_final
2022-05-13 10:14:38	ga_ls8c_ard_3-2-1_099081_2022-05-13_final
2022-05-13 10:15:02	ga_ls8c_ard_3-2-1_099082_2022-05-13_final
2022-05-14 10:53:54	ga_ls8c_ard_3-2-1_106071_2022-05-14_final
2022-05-15 10:01:53	ga_ls8c_ard_3-2-1_097080_2022-05-15_final
2022-05-19 09:36:23	ga_ls8c_ard_3-2-1_093078_2022-05-19_final
2022-05-19 11:16:28	ga_ls8c_ard_3-2-1_109081_2022-05-19_final
2022-05-20 10:20:50	ga_ls8c_ard_3-2-1_100081_2022-05-20_final
2022-05-24 11:32:36	ga_ls8c_ard_3-2-1_112075_2022-05-24_final
2022-05-24 11:33:48	ga_ls8c_ard_3-2-1_112078_2022-05-24_final
2022-05-24 11:35:48	ga_ls8c_ard_3-2-1_112083_2022-05-24_final
2022-05-25 10:34:59	ga_ls8c_ard_3-2-1_103070_2022-05-25_final
2022-05-25 10:38:10	ga_ls8c_ard_3-2-1_103078_2022-05-25_final
2022-05-30 10:58:20	ga_ls8c_ard_3-2-1_106082_2022-05-30_final
2022-05-31 10:00:20	ga_ls8c_ard_3-2-1_097076_2022-05-31_final
2022-06-02 09:50:48	ga_ls8c_ard_3-2-1_095083_2022-06-02_final
2022-06-06 09:24:08	ga_ls8c_ard_3-2-1_091078_2022-06-05_final
2022-06-06 09:25:44	ga_ls8c_ard_3-2-1_091082_2022-06-05_final
2022-06-17 10:41:01	ga_ls8c_ard_3-2-1_104069_2022-06-17_final
2022-06-17 10:43:49	ga_ls8c_ard_3-2-1_104076_2022-06-17_final
2022-06-18 09:49:47	ga_ls8c_ard_3-2-1_095080_2022-06-18_final
2022-06-19 10:28:40	ga_ls8c_ard_3-2-1_102069_2022-06-19_final
2022-06-19 10:31:28	ga_ls8c_ard_3-2-1_102076_2022-06-19_final
2022-06-20 09:37:51	ga_ls8c_ard_3-2-1_093081_2022-06-20_final
2022-06-20 11:17:32	ga_ls8c_ard_3-2-1_109083_2022-06-20_final
2022-06-21 10:21:07	ga_ls8c_ard_3-2-1_100081_2022-06-21_final
2022-06-22 09:24:18	ga_ls8c_ard_3-2-1_091078_2022-06-21_final
2022-06-22 09:25:54	ga_ls8c_ard_3-2-1_091082_2022-06-21_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