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
2015-03-17 10:47:48	ga_ls8c_ard_3-1-0_105072_2015-03-17_final
2015-11-28 10:51:09	ga_ls8c_ard_3-1-0_105079_2015-11-28_final
2016-11-08 11:28:01	ga_ls8c_ard_3-1-0_111078_2016-11-08_final
2019-03-10 09:24:06	ga_ls8c_ard_3-1-0_091079_2019-03-09_final
2019-03-13 09:54:35	ga_ls8c_ard_3-1-0_096078_2019-03-13_final
2019-03-23 10:30:50	ga_ls8c_ard_3-1-0_102076_2019-03-23_final
2019-03-23 10:32:26	ga_ls8c_ard_3-1-0_102080_2019-03-23_final
2019-03-28 10:50:09	ga_ls8c_ard_3-1-0_105078_2019-03-28_final
2019-03-29 11:33:25	ga_ls8c_ard_3-1-0_112078_2019-03-29_final
2019-04-02 11:08:41	ga_ls8c_ard_3-1-0_108078_2019-04-02_final
2019-04-07 09:48:43	ga_ls8c_ard_3-1-0_095079_2019-04-07_final
2019-04-07 11:27:59	ga_ls8c_ard_3-1-0_111080_2019-04-07_final
2019-04-14 11:32:32	ga_ls8c_ard_3-1-0_112076_2019-04-14_final
2019-04-18 11:08:35	ga_ls8c_ard_3-1-0_108078_2019-04-18_final
2019-06-17 11:32:54	ga_ls8c_ard_3-1-0_112076_2019-06-17_final
2019-06-26 09:49:05	ga_ls8c_ard_3-1-0_095079_2019-06-26_final
2019-07-03 09:54:29	ga_ls8c_ard_3-1-0_096077_2019-07-03_final
2019-07-19 09:54:56	ga_ls8c_ard_3-1-0_096078_2019-07-19_final
2019-07-19 11:33:01	ga_ls8c_ard_3-1-0_112076_2019-07-19_final
2019-07-28 09:49:13	ga_ls8c_ard_3-1-0_095079_2019-07-28_final
2019-07-28 11:27:18	ga_ls8c_ard_3-1-0_111077_2019-07-28_final
2019-07-28 11:28:30	ga_ls8c_ard_3-1-0_111080_2019-07-28_final
2019-07-29 10:32:29	ga_ls8c_ard_3-1-0_102079_2019-07-29_final
2019-07-31 11:58:14	ga_ls8c_ard_3-1-0_116077_2019-07-31_final
2019-08-04 09:53:51	ga_ls8c_ard_3-1-0_096075_2019-08-04_final
2019-08-04 11:33:08	ga_ls8c_ard_3-1-0_112076_2019-08-04_final
2019-08-13 09:49:19	ga_ls8c_ard_3-1-0_095079_2019-08-13_final
2019-08-16 11:58:19	ga_ls8c_ard_3-1-0_116077_2019-08-16_final
2019-08-20 09:55:08	ga_ls8c_ard_3-1-0_096078_2019-08-20_final
2019-08-20 11:33:13	ga_ls8c_ard_3-1-0_112076_2019-08-20_final
2019-08-30 10:32:15	ga_ls8c_ard_3-1-0_102078_2019-08-30_final
2019-09-04 10:50:48	ga_ls8c_ard_3-1-0_105078_2019-09-04_final
2019-09-05 09:53:59	ga_ls8c_ard_3-1-0_096075_2019-09-05_final
2019-09-09 11:09:22	ga_ls8c_ard_3-1-0_108078_2019-09-09_final
2019-09-14 11:27:33	ga_ls8c_ard_3-1-0_111077_2019-09-14_final
2019-09-15 10:31:32	ga_ls8c_ard_3-1-0_102076_2019-09-15_final
2019-09-21 09:54:05	ga_ls8c_ard_3-1-0_096075_2019-09-21_final
2019-09-21 11:34:10	ga_ls8c_ard_3-1-0_112078_2019-09-21_final
2019-09-30 09:48:21	ga_ls8c_ard_3-1-0_095076_2019-09-30_final
2019-10-01 10:33:13	ga_ls8c_ard_3-1-0_102080_2019-10-01_final
2019-10-06 10:50:58	ga_ls8c_ard_3-1-0_105078_2019-10-06_final
2019-10-07 09:54:09	ga_ls8c_ard_3-1-0_096075_2019-10-07_final
2019-10-07 09:55:21	ga_ls8c_ard_3-1-0_096078_2019-10-07_final
2019-10-07 11:33:26	ga_ls8c_ard_3-1-0_112076_2019-10-07_final
2019-10-11 11:09:31	ga_ls8c_ard_3-1-0_108078_2019-10-11_final
2019-10-22 10:51:00	ga_ls8c_ard_3-1-0_105078_2019-10-22_final
2019-10-23 09:54:58	ga_ls8c_ard_3-1-0_096077_2019-10-23_final
2019-11-01 11:28:28	ga_ls8c_ard_3-1-0_111079_2019-11-01_final
2019-11-07 10:50:58	ga_ls8c_ard_3-1-0_105078_2019-11-07_final
2019-11-08 09:54:57	ga_ls8c_ard_3-1-0_096077_2019-11-08_final
2019-11-17 09:49:32	ga_ls8c_ard_3-1-0_095079_2019-11-17_final
2019-11-24 09:54:54	ga_ls8c_ard_3-1-0_096077_2019-11-24_final
2019-12-07 09:24:47	ga_ls8c_ard_3-1-0_091079_2019-12-06_final
2019-12-10 09:54:53	ga_ls8c_ard_3-1-0_096077_2019-12-10_final
2019-12-25 10:50:51	ga_ls8c_ard_3-1-0_105078_2019-12-25_final
2020-01-26 10:50:43	ga_ls8c_ard_3-1-0_105078_2020-01-26_final
2020-03-08 11:28:00	ga_ls8c_ard_3-1-0_111079_2020-03-08_final
2020-03-14 10:50:28	ga_ls8c_ard_3-1-0_105078_2020-03-14_final
2020-03-15 09:54:02	ga_ls8c_ard_3-1-0_096076_2020-03-15_final
2020-03-24 11:27:51	ga_ls8c_ard_3-1-0_111079_2020-03-24_final
2020-03-25 10:31:50	ga_ls8c_ard_3-1-0_102078_2020-03-25_final
2020-03-31 09:54:17	ga_ls8c_ard_3-1-0_096077_2020-03-31_final
2020-03-31 11:32:46	ga_ls8c_ard_3-1-0_112076_2020-03-31_final
2020-04-09 11:27:19	ga_ls8c_ard_3-1-0_111078_2020-04-09_final
2020-04-09 11:27:43	ga_ls8c_ard_3-1-0_111079_2020-04-09_final
2020-04-10 10:31:42	ga_ls8c_ard_3-1-0_102078_2020-04-10_final
2020-04-16 11:32:39	ga_ls8c_ard_3-1-0_112076_2020-04-16_final
2020-04-16 11:33:03	ga_ls8c_ard_3-1-0_112077_2020-04-16_final
2020-04-25 09:48:43	ga_ls8c_ard_3-1-0_095079_2020-04-25_final
2020-05-02 09:51:38	ga_ls8c_ard_3-1-0_096071_2020-05-02_final
2020-05-06 11:08:33	ga_ls8c_ard_3-1-0_108078_2020-05-06_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
2022-04-08 09:42:25	ga_ls8c_ard_3-2-1_094078_2022-04-08_final
2022-04-12 10:56:12	ga_ls8c_ard_3-2-1_106077_2022-04-12_final
2022-04-13 11:39:05	ga_ls8c_ard_3-2-1_113076_2022-04-13_final
2022-04-14 10:44:15	ga_ls8c_ard_3-2-1_104078_2022-04-14_final
2022-04-15 09:49:26	ga_ls8c_ard_3-2-1_095080_2022-04-15_final
2022-04-15 11:28:19	ga_ls8c_ard_3-2-1_111080_2022-04-15_final
2022-04-16 10:31:06	ga_ls8c_ard_3-2-1_102076_2022-04-16_final
2022-04-17 09:37:52	ga_ls8c_ard_3-2-1_093082_2022-04-17_final
2022-04-19 11:02:47	ga_ls8c_ard_3-2-1_107078_2022-04-19_final
2022-04-22 09:53:35	ga_ls8c_ard_3-2-1_096075_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
2022-04-22 11:34:28	ga_ls8c_ard_3-2-1_112080_2022-04-22_final
2022-05-02 10:31:04	ga_ls8c_ard_3-2-1_102076_2022-05-02_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 09:36:39	ga_ls8c_ard_3-2-1_093079_2022-05-03_final
2022-05-03 11:15:56	ga_ls8c_ard_3-2-1_109080_2022-05-03_final
2022-05-08 09:54:03	ga_ls8c_ard_3-2-1_096076_2022-05-08_final
2022-05-08 09:54:51	ga_ls8c_ard_3-2-1_096078_2022-05-08_final
2022-05-11 10:26:35	ga_ls8c_ard_3-2-1_101080_2022-05-11_final
2022-05-16 10:44:21	ga_ls8c_ard_3-2-1_104078_2022-05-16_final
2022-05-19 11:16:04	ga_ls8c_ard_3-2-1_109080_2022-05-19_final
2022-05-25 10:36:59	ga_ls8c_ard_3-2-1_103075_2022-05-25_final
2022-05-26 09:42:33	ga_ls8c_ard_3-2-1_094078_2022-05-26_final
2022-06-02 09:48:24	ga_ls8c_ard_3-2-1_095077_2022-06-02_final
2022-06-02 09:48:48	ga_ls8c_ard_3-2-1_095078_2022-06-02_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