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
2013-11-07 09:55:32	ga_ls8c_ard_3-1-0_096075_2013-11-07_final
2016-06-02 10:32:31	ga_ls8c_ard_3-1-0_102080_2016-06-02_final
2019-03-10 09:24:06	ga_ls8c_ard_3-1-0_091079_2019-03-09_final
2019-03-13 09:53:47	ga_ls8c_ard_3-1-0_096076_2019-03-13_final
2019-03-22 09:49:10	ga_ls8c_ard_3-1-0_095080_2019-03-22_final
2019-03-28 10:50:09	ga_ls8c_ard_3-1-0_105078_2019-03-28_final
2019-03-28 10:51:21	ga_ls8c_ard_3-1-0_105081_2019-03-28_final
2019-03-29 09:56:08	ga_ls8c_ard_3-1-0_096082_2019-03-29_final
2019-04-07 09:48:19	ga_ls8c_ard_3-1-0_095078_2019-04-07_final
2019-04-07 09:49:06	ga_ls8c_ard_3-1-0_095080_2019-04-07_final
2019-04-07 09:51:06	ga_ls8c_ard_3-1-0_095085_2019-04-07_final
2019-04-14 11:32:56	ga_ls8c_ard_3-1-0_112077_2019-04-14_final
2019-06-26 09:48:41	ga_ls8c_ard_3-1-0_095078_2019-06-26_final
2019-07-03 09:50:30	ga_ls8c_ard_3-1-0_096067_2019-07-03_final
2019-07-03 11:34:10	ga_ls8c_ard_3-1-0_112079_2019-07-03_final
2019-07-07 11:08:40	ga_ls8c_ard_3-1-0_108077_2019-07-07_final
2019-07-18 10:46:10	ga_ls8c_ard_3-1-0_105067_2019-07-18_final
2019-07-19 09:56:32	ga_ls8c_ard_3-1-0_096082_2019-07-19_final
2019-08-04 11:33:56	ga_ls8c_ard_3-1-0_112078_2019-08-04_final
2019-08-04 11:34:20	ga_ls8c_ard_3-1-0_112079_2019-08-04_final
2019-08-08 11:05:39	ga_ls8c_ard_3-1-0_108069_2019-08-08_final
2019-08-08 11:08:50	ga_ls8c_ard_3-1-0_108077_2019-08-08_final
2019-08-13 11:25:01	ga_ls8c_ard_3-1-0_111071_2019-08-13_final
2019-08-20 09:56:44	ga_ls8c_ard_3-1-0_096082_2019-08-20_final
2019-08-24 11:05:43	ga_ls8c_ard_3-1-0_108069_2019-08-24_final
2019-08-29 09:49:23	ga_ls8c_ard_3-1-0_095079_2019-08-29_final
2019-09-05 11:34:28	ga_ls8c_ard_3-1-0_112079_2019-09-05_final
2019-09-14 09:49:04	ga_ls8c_ard_3-1-0_095078_2019-09-14_final
2019-09-14 09:49:28	ga_ls8c_ard_3-1-0_095079_2019-09-14_final
2019-09-14 11:28:21	ga_ls8c_ard_3-1-0_111079_2019-09-14_final
2019-09-30 09:49:09	ga_ls8c_ard_3-1-0_095078_2019-09-30_final
2019-10-06 10:50:58	ga_ls8c_ard_3-1-0_105078_2019-10-06_final
2019-10-07 11:33:26	ga_ls8c_ard_3-1-0_112076_2019-10-07_final
2019-10-16 09:49:11	ga_ls8c_ard_3-1-0_095078_2019-10-16_final
2019-10-16 11:28:28	ga_ls8c_ard_3-1-0_111079_2019-10-16_final
2019-10-20 09:20:29	ga_ls8c_ard_3-1-0_091068_2019-10-19_final
2019-10-22 10:52:12	ga_ls8c_ard_3-1-0_105081_2019-10-22_final
2019-11-17 09:49:32	ga_ls8c_ard_3-1-0_095079_2019-11-17_final
2019-11-18 10:31:12	ga_ls8c_ard_3-1-0_102075_2019-11-18_final
2019-11-24 09:54:06	ga_ls8c_ard_3-1-0_096075_2019-11-24_final
2019-11-24 09:54:30	ga_ls8c_ard_3-1-0_096076_2019-11-24_final
2019-11-28 11:05:52	ga_ls8c_ard_3-1-0_108069_2019-11-28_final
2019-12-03 11:28:24	ga_ls8c_ard_3-1-0_111079_2019-12-03_final
2019-12-07 09:24:47	ga_ls8c_ard_3-1-0_091079_2019-12-06_final
2019-12-10 09:54:29	ga_ls8c_ard_3-1-0_096076_2019-12-10_final
2020-01-08 09:24:40	ga_ls8c_ard_3-1-0_091079_2020-01-07_final
2020-01-08 09:25:52	ga_ls8c_ard_3-1-0_091082_2020-01-07_final
2020-01-11 09:53:58	ga_ls8c_ard_3-1-0_096075_2020-01-11_final
2020-01-20 11:28:14	ga_ls8c_ard_3-1-0_111079_2020-01-20_final
2020-02-21 09:51:12	ga_ls8c_ard_3-1-0_095084_2020-02-21_final
2020-02-27 10:50:35	ga_ls8c_ard_3-1-0_105078_2020-02-27_final
2020-02-27 10:51:46	ga_ls8c_ard_3-1-0_105081_2020-02-27_final
2020-03-14 10:50:28	ga_ls8c_ard_3-1-0_105078_2020-03-14_final
2020-03-15 11:32:55	ga_ls8c_ard_3-1-0_112076_2020-03-15_final
2020-03-15 11:33:19	ga_ls8c_ard_3-1-0_112077_2020-03-15_final
2020-03-31 11:33:58	ga_ls8c_ard_3-1-0_112079_2020-03-31_final
2020-04-09 11:27:43	ga_ls8c_ard_3-1-0_111079_2020-04-09_final
2020-04-10 10:29:18	ga_ls8c_ard_3-1-0_102072_2020-04-10_final
2020-04-16 09:57:22	ga_ls8c_ard_3-1-0_096085_2020-04-16_final
2020-04-16 11:32:39	ga_ls8c_ard_3-1-0_112076_2020-04-16_final
2020-05-02 09:51:38	ga_ls8c_ard_3-1-0_096071_2020-05-02_final
2020-05-02 09:53:38	ga_ls8c_ard_3-1-0_096076_2020-05-02_final
2020-05-02 11:32:31	ga_ls8c_ard_3-1-0_112076_2020-05-02_final
2020-05-02 11:33:43	ga_ls8c_ard_3-1-0_112079_2020-05-02_final
2022-03-30 09:48:32	ga_ls8c_ard_3-2-1_095078_2022-03-30_final
2022-04-05 10:50:46	ga_ls8c_ard_3-2-1_105079_2022-04-05_final
2022-04-07 10:38:49	ga_ls8c_ard_3-2-1_103080_2022-04-07_final
2022-04-08 11:21:42	ga_ls8c_ard_3-2-1_110079_2022-04-08_final
2022-04-12 10:56:12	ga_ls8c_ard_3-2-1_106077_2022-04-12_final
2022-04-13 09:59:48	ga_ls8c_ard_3-2-1_097075_2022-04-13_final
2022-04-15 09:49:02	ga_ls8c_ard_3-2-1_095079_2022-04-15_final
2022-04-15 09:49:26	ga_ls8c_ard_3-2-1_095080_2022-04-15_final
2022-04-15 11:27:55	ga_ls8c_ard_3-2-1_111079_2022-04-15_final
2022-04-17 09:37:28	ga_ls8c_ard_3-2-1_093081_2022-04-17_final
2022-04-17 09:37:52	ga_ls8c_ard_3-2-1_093082_2022-04-17_final
2022-04-19 11:04:23	ga_ls8c_ard_3-2-1_107082_2022-04-19_final
2022-04-22 09:53:59	ga_ls8c_ard_3-2-1_096076_2022-04-22_final
2022-04-24 11:21:42	ga_ls8c_ard_3-2-1_110079_2022-04-24_final
2022-04-26 11:08:07	ga_ls8c_ard_3-2-1_108076_2022-04-26_final
2022-04-28 10:58:32	ga_ls8c_ard_3-2-1_106083_2022-04-28_final
2022-05-01 09:48:11	ga_ls8c_ard_3-2-1_095077_2022-05-01_final
2022-05-03 11:15:56	ga_ls8c_ard_3-2-1_109080_2022-05-03_final
2022-05-04 11:58:01	ga_ls8c_ard_3-2-1_116077_2022-05-04_final
2022-05-07 10:51:15	ga_ls8c_ard_3-2-1_105080_2022-05-07_final
2022-05-08 09:54:51	ga_ls8c_ard_3-2-1_096078_2022-05-08_final
2022-05-08 11:34:08	ga_ls8c_ard_3-2-1_112079_2022-05-08_final
2022-05-10 11:24:11	ga_ls8c_ard_3-2-1_110085_2022-05-10_final
2022-05-12 11:09:51	ga_ls8c_ard_3-2-1_108080_2022-05-12_final
2022-05-14 10:57:06	ga_ls8c_ard_3-2-1_106079_2022-05-14_final
2022-05-16 10:43:57	ga_ls8c_ard_3-2-1_104077_2022-05-16_final
2022-05-17 09:48:44	ga_ls8c_ard_3-2-1_095078_2022-05-17_final
2022-05-19 11:16:04	ga_ls8c_ard_3-2-1_109080_2022-05-19_final
2022-05-24 09:54:31	ga_ls8c_ard_3-2-1_096077_2022-05-24_final
2022-06-02 09:49:12	ga_ls8c_ard_3-2-1_095079_2022-06-02_final
2022-06-08 10:51:29	ga_ls8c_ard_3-2-1_105080_2022-06-08_final
2022-06-16 10:00:08	ga_ls8c_ard_3-2-1_097075_2022-06-16_final
2022-06-17 10:44:36	ga_ls8c_ard_3-2-1_104078_2022-06-17_final
2022-06-18 11:27:29	ga_ls8c_ard_3-2-1_111077_2022-06-18_final
2022-06-18 11:28:17	ga_ls8c_ard_3-2-1_111079_2022-06-18_final
2022-06-20 11:15:56	ga_ls8c_ard_3-2-1_109079_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