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
2015-08-23 11:45:59	ga_ls8c_ard_3-0-0_114078_2015-08-23_final
2015-08-23 11:46:23	ga_ls8c_ard_3-0-0_114079_2015-08-23_final
2015-08-23 11:46:47	ga_ls8c_ard_3-0-0_114080_2015-08-23_final
2015-08-23 11:47:11	ga_ls8c_ard_3-0-0_114081_2015-08-23_final
2015-08-25 11:36:26	ga_ls8c_ard_3-0-0_112085_2015-08-25_final
2015-09-08 11:46:05	ga_ls8c_ard_3-0-0_114078_2015-09-08_final
2015-09-08 11:46:29	ga_ls8c_ard_3-0-0_114079_2015-09-08_final
2015-09-08 11:46:53	ga_ls8c_ard_3-0-0_114080_2015-09-08_final
2015-09-08 11:47:17	ga_ls8c_ard_3-0-0_114081_2015-09-08_final
2015-09-24 11:46:13	ga_ls8c_ard_3-0-0_114078_2015-09-24_final
2015-09-24 11:46:37	ga_ls8c_ard_3-0-0_114079_2015-09-24_final
2015-09-24 11:47:01	ga_ls8c_ard_3-0-0_114080_2015-09-24_final
2015-09-24 11:47:25	ga_ls8c_ard_3-0-0_114081_2015-09-24_final
2015-10-10 11:46:14	ga_ls8c_ard_3-0-0_114078_2015-10-10_final
2015-10-10 11:46:38	ga_ls8c_ard_3-0-0_114079_2015-10-10_final
2015-10-10 11:47:02	ga_ls8c_ard_3-0-0_114080_2015-10-10_final
2015-10-10 11:47:26	ga_ls8c_ard_3-0-0_114081_2015-10-10_final
2015-11-11 11:46:20	ga_ls8c_ard_3-0-0_114078_2015-11-11_final
2015-11-11 11:46:43	ga_ls8c_ard_3-0-0_114079_2015-11-11_final
2015-11-11 11:47:07	ga_ls8c_ard_3-0-0_114080_2015-11-11_final
2015-11-11 11:47:31	ga_ls8c_ard_3-0-0_114081_2015-11-11_final
2015-12-13 11:46:21	ga_ls8c_ard_3-0-0_114078_2015-12-13_final
2015-12-13 11:46:44	ga_ls8c_ard_3-0-0_114079_2015-12-13_final
2015-12-13 11:47:08	ga_ls8c_ard_3-0-0_114080_2015-12-13_final
2015-12-13 11:47:32	ga_ls8c_ard_3-0-0_114081_2015-12-13_final
2019-06-13 11:56:48	ga_ls8c_ard_3-1-0_116074_2019-06-13_final
2019-06-22 11:50:16	ga_ls8c_ard_3-1-0_115073_2019-06-22_final
2019-06-22 11:50:40	ga_ls8c_ard_3-1-0_115074_2019-06-22_final
2019-06-22 11:51:04	ga_ls8c_ard_3-1-0_115075_2019-06-22_final
2019-06-22 11:51:28	ga_ls8c_ard_3-1-0_115076_2019-06-22_final
2019-06-22 11:51:52	ga_ls8c_ard_3-1-0_115077_2019-06-22_final
2019-06-22 11:52:16	ga_ls8c_ard_3-1-0_115078_2019-06-22_final
2019-06-22 11:52:40	ga_ls8c_ard_3-1-0_115079_2019-06-22_final
2019-06-24 11:41:31	ga_ls8c_ard_3-1-0_113082_2019-06-24_final
2019-06-24 11:41:55	ga_ls8c_ard_3-1-0_113083_2019-06-24_final
2019-06-24 11:42:19	ga_ls8c_ard_3-1-0_113084_2019-06-24_final
2019-06-29 11:56:53	ga_ls8c_ard_3-1-0_116074_2019-06-29_final
2019-07-15 11:56:56	ga_ls8c_ard_3-1-0_116074_2019-07-15_final
2019-08-16 11:57:08	ga_ls8c_ard_3-1-0_116074_2019-08-16_final
2019-08-25 11:50:35	ga_ls8c_ard_3-1-0_115073_2019-08-25_final
2019-08-25 11:50:59	ga_ls8c_ard_3-1-0_115074_2019-08-25_final
2019-08-25 11:51:23	ga_ls8c_ard_3-1-0_115075_2019-08-25_final
2019-08-25 11:51:47	ga_ls8c_ard_3-1-0_115076_2019-08-25_final
2019-08-25 11:52:11	ga_ls8c_ard_3-1-0_115077_2019-08-25_final
2019-08-25 11:52:35	ga_ls8c_ard_3-1-0_115078_2019-08-25_final
2019-08-25 11:52:59	ga_ls8c_ard_3-1-0_115079_2019-08-25_final
2019-08-27 11:41:49	ga_ls8c_ard_3-1-0_113082_2019-08-27_final
2019-08-27 11:42:13	ga_ls8c_ard_3-1-0_113083_2019-08-27_final
2019-08-27 11:42:37	ga_ls8c_ard_3-1-0_113084_2019-08-27_final
2019-09-01 11:57:11	ga_ls8c_ard_3-1-0_116074_2019-09-01_final
2019-09-17 11:57:16	ga_ls8c_ard_3-1-0_116074_2019-09-17_final
2019-09-26 11:50:44	ga_ls8c_ard_3-1-0_115073_2019-09-26_final
2019-09-26 11:51:08	ga_ls8c_ard_3-1-0_115074_2019-09-26_final
2019-09-26 11:51:32	ga_ls8c_ard_3-1-0_115075_2019-09-26_final
2019-09-26 11:51:56	ga_ls8c_ard_3-1-0_115076_2019-09-26_final
2019-09-26 11:52:20	ga_ls8c_ard_3-1-0_115077_2019-09-26_final
2019-09-26 11:52:44	ga_ls8c_ard_3-1-0_115078_2019-09-26_final
2019-09-26 11:53:08	ga_ls8c_ard_3-1-0_115079_2019-09-26_final
2019-09-28 11:41:59	ga_ls8c_ard_3-1-0_113082_2019-09-28_final
2019-09-28 11:42:23	ga_ls8c_ard_3-1-0_113083_2019-09-28_final
2019-09-28 11:42:47	ga_ls8c_ard_3-1-0_113084_2019-09-28_final
2019-10-03 11:57:21	ga_ls8c_ard_3-1-0_116074_2019-10-03_final
2019-10-14 11:42:02	ga_ls8c_ard_3-1-0_113082_2019-10-14_final
2019-10-14 11:42:26	ga_ls8c_ard_3-1-0_113083_2019-10-14_final
2019-10-14 11:42:50	ga_ls8c_ard_3-1-0_113084_2019-10-14_final
2019-10-23 11:37:03	ga_ls8c_ard_3-1-0_112085_2019-10-23_final
2022-02-06 11:50:56	ga_ls8c_ard_3-2-1_115074_2022-02-06_final
2022-02-06 11:51:20	ga_ls8c_ard_3-2-1_115075_2022-02-06_final
2022-02-06 11:51:44	ga_ls8c_ard_3-2-1_115076_2022-02-06_final
2022-02-06 11:52:08	ga_ls8c_ard_3-2-1_115077_2022-02-06_final
2022-02-06 11:52:32	ga_ls8c_ard_3-2-1_115078_2022-02-06_final
2022-02-06 11:52:56	ga_ls8c_ard_3-2-1_115079_2022-02-06_final
2022-02-08 11:41:45	ga_ls8c_ard_3-2-1_113082_2022-02-08_final
2022-02-08 11:42:09	ga_ls8c_ard_3-2-1_113083_2022-02-08_final
2022-02-08 11:42:33	ga_ls8c_ard_3-2-1_113084_2022-02-08_final
2022-03-28 11:41:24	ga_ls8c_ard_3-2-1_113082_2022-03-28_final
2022-03-28 11:41:48	ga_ls8c_ard_3-2-1_113083_2022-03-28_final
2022-03-28 11:42:12	ga_ls8c_ard_3-2-1_113084_2022-03-28_final
2022-04-04 11:45:58	ga_ls8c_ard_3-2-1_114078_2022-04-04_final
2022-04-04 11:46:22	ga_ls8c_ard_3-2-1_114079_2022-04-04_final
2022-04-04 11:46:46	ga_ls8c_ard_3-2-1_114080_2022-04-04_final
2022-04-04 11:47:10	ga_ls8c_ard_3-2-1_114081_2022-04-04_final
2022-04-13 11:41:28	ga_ls8c_ard_3-2-1_113082_2022-04-13_final
2022-04-13 11:41:52	ga_ls8c_ard_3-2-1_113083_2022-04-13_final
2022-04-13 11:42:16	ga_ls8c_ard_3-2-1_113084_2022-04-13_final
2022-04-29 11:41:24	ga_ls8c_ard_3-2-1_113082_2022-04-29_final
2022-04-29 11:41:48	ga_ls8c_ard_3-2-1_113083_2022-04-29_final
2022-04-29 11:42:11	ga_ls8c_ard_3-2-1_113084_2022-04-29_final
2022-05-06 11:46:04	ga_ls8c_ard_3-2-1_114078_2022-05-06_final
2022-05-06 11:46:28	ga_ls8c_ard_3-2-1_114079_2022-05-06_final
2022-05-06 11:46:52	ga_ls8c_ard_3-2-1_114080_2022-05-06_final
2022-05-06 11:47:16	ga_ls8c_ard_3-2-1_114081_2022-05-06_final
2022-05-13 11:50:43	ga_ls8c_ard_3-2-1_115074_2022-05-13_final
2022-05-13 11:51:07	ga_ls8c_ard_3-2-1_115075_2022-05-13_final
2022-05-13 11:51:31	ga_ls8c_ard_3-2-1_115076_2022-05-13_final
2022-05-13 11:51:55	ga_ls8c_ard_3-2-1_115077_2022-05-13_final
2022-05-13 11:52:19	ga_ls8c_ard_3-2-1_115078_2022-05-13_final
2022-05-13 11:52:43	ga_ls8c_ard_3-2-1_115079_2022-05-13_final
2022-08-03 11:42:05	ga_ls8c_ard_3-2-1_113082_2022-08-03_final
2022-08-03 11:42:29	ga_ls8c_ard_3-2-1_113083_2022-08-03_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