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
2018-06-20 10:56:31	ga_ls8c_ard_3-0-0_106080_2018-06-20_final
2018-06-20 10:56:55	ga_ls8c_ard_3-0-0_106081_2018-06-20_final
2018-06-20 10:57:19	ga_ls8c_ard_3-0-0_106082_2018-06-20_final
2018-06-20 10:57:43	ga_ls8c_ard_3-0-0_106083_2018-06-20_final
2018-06-20 10:58:07	ga_ls8c_ard_3-0-0_106084_2018-06-20_final
2018-07-06 10:56:41	ga_ls8c_ard_3-0-0_106080_2018-07-06_final
2018-07-06 10:57:04	ga_ls8c_ard_3-0-0_106081_2018-07-06_final
2018-07-06 10:57:28	ga_ls8c_ard_3-0-0_106082_2018-07-06_final
2018-07-06 10:57:52	ga_ls8c_ard_3-0-0_106083_2018-07-06_final
2018-07-06 10:58:16	ga_ls8c_ard_3-0-0_106084_2018-07-06_final
2018-07-20 11:05:33	ga_ls8c_ard_3-0-0_108071_2018-07-20_final
2018-07-20 11:05:57	ga_ls8c_ard_3-0-0_108072_2018-07-20_final
2018-07-20 11:06:21	ga_ls8c_ard_3-0-0_108073_2018-07-20_final
2018-07-20 11:06:45	ga_ls8c_ard_3-0-0_108074_2018-07-20_final
2018-07-20 11:07:09	ga_ls8c_ard_3-0-0_108075_2018-07-20_final
2018-07-20 11:07:33	ga_ls8c_ard_3-0-0_108076_2018-07-20_final
2018-08-05 11:05:41	ga_ls8c_ard_3-0-0_108071_2018-08-05_final
2018-08-05 11:06:05	ga_ls8c_ard_3-0-0_108072_2018-08-05_final
2018-08-05 11:06:29	ga_ls8c_ard_3-0-0_108073_2018-08-05_final
2018-08-05 11:06:53	ga_ls8c_ard_3-0-0_108074_2018-08-05_final
2018-08-05 11:07:17	ga_ls8c_ard_3-0-0_108075_2018-08-05_final
2018-08-05 11:07:41	ga_ls8c_ard_3-0-0_108076_2018-08-05_final
2018-08-21 11:05:50	ga_ls8c_ard_3-0-0_108071_2018-08-21_final
2018-08-21 11:06:13	ga_ls8c_ard_3-0-0_108072_2018-08-21_final
2018-08-21 11:06:37	ga_ls8c_ard_3-0-0_108073_2018-08-21_final
2018-08-21 11:07:01	ga_ls8c_ard_3-0-0_108074_2018-08-21_final
2018-08-21 11:07:25	ga_ls8c_ard_3-0-0_108075_2018-08-21_final
2018-08-21 11:07:49	ga_ls8c_ard_3-0-0_108076_2018-08-21_final
2018-08-23 10:57:04	ga_ls8c_ard_3-0-0_106080_2018-08-23_final
2018-08-23 10:57:28	ga_ls8c_ard_3-0-0_106081_2018-08-23_final
2018-08-23 10:57:52	ga_ls8c_ard_3-0-0_106082_2018-08-23_final
2018-08-23 10:58:16	ga_ls8c_ard_3-0-0_106083_2018-08-23_final
2018-08-23 10:58:40	ga_ls8c_ard_3-0-0_106084_2018-08-23_final
2022-08-16 11:06:52	ga_ls8c_ard_3-2-1_108071_2022-08-16_final
2022-08-16 11:07:16	ga_ls8c_ard_3-2-1_108072_2022-08-16_final
2022-08-16 11:07:40	ga_ls8c_ard_3-2-1_108073_2022-08-16_final
2022-08-16 11:08:04	ga_ls8c_ard_3-2-1_108074_2022-08-16_final
2022-08-16 11:08:28	ga_ls8c_ard_3-2-1_108075_2022-08-16_final
2022-08-16 11:08:52	ga_ls8c_ard_3-2-1_108076_2022-08-16_final
2022-09-08 11:12:19	ga_ls8c_ard_3-2-1_109069_2022-09-08_final
2022-09-08 11:12:43	ga_ls8c_ard_3-2-1_109070_2022-09-08_final
2022-09-08 11:13:06	ga_ls8c_ard_3-2-1_109071_2022-09-08_final
2022-09-08 11:13:30	ga_ls8c_ard_3-2-1_109072_2022-09-08_final
2022-09-10 11:02:22	ga_ls8c_ard_3-2-1_107075_2022-09-10_final
2022-09-10 11:02:46	ga_ls8c_ard_3-2-1_107076_2022-09-10_final
2022-09-10 11:03:09	ga_ls8c_ard_3-2-1_107077_2022-09-10_final
2022-09-10 11:03:33	ga_ls8c_ard_3-2-1_107078_2022-09-10_final
2022-09-10 11:03:57	ga_ls8c_ard_3-2-1_107079_2022-09-10_final
2022-09-10 11:04:21	ga_ls8c_ard_3-2-1_107080_2022-09-10_final
2022-09-10 11:04:45	ga_ls8c_ard_3-2-1_107081_2022-09-10_final
2022-10-19 11:06:54	ga_ls8c_ard_3-2-1_108071_2022-10-19_final
2022-10-19 11:07:18	ga_ls8c_ard_3-2-1_108072_2022-10-19_final
2022-10-19 11:07:42	ga_ls8c_ard_3-2-1_108073_2022-10-19_final
2022-10-19 11:08:06	ga_ls8c_ard_3-2-1_108074_2022-10-19_final
2022-10-19 11:08:30	ga_ls8c_ard_3-2-1_108075_2022-10-19_final
2022-10-19 11:08:54	ga_ls8c_ard_3-2-1_108076_2022-10-19_final
2022-10-21 10:58:09	ga_ls8c_ard_3-2-1_106080_2022-10-21_final
2022-10-21 10:58:33	ga_ls8c_ard_3-2-1_106081_2022-10-21_final
2022-10-21 10:58:57	ga_ls8c_ard_3-2-1_106082_2022-10-21_final
2022-10-21 10:59:21	ga_ls8c_ard_3-2-1_106083_2022-10-21_final
2022-11-04 11:06:59	ga_ls8c_ard_3-2-1_108071_2022-11-04_final
2022-11-04 11:07:23	ga_ls8c_ard_3-2-1_108072_2022-11-04_final
2022-11-04 11:07:47	ga_ls8c_ard_3-2-1_108073_2022-11-04_final
2022-11-04 11:08:11	ga_ls8c_ard_3-2-1_108074_2022-11-04_final
2022-11-04 11:08:35	ga_ls8c_ard_3-2-1_108075_2022-11-04_final
2022-11-04 11:08:59	ga_ls8c_ard_3-2-1_108076_2022-11-04_final
2022-11-06 10:58:13	ga_ls8c_ard_3-2-1_106080_2022-11-06_final
2022-11-06 10:58:37	ga_ls8c_ard_3-2-1_106081_2022-11-06_final
2022-11-06 10:59:01	ga_ls8c_ard_3-2-1_106082_2022-11-06_final
2022-11-06 10:59:25	ga_ls8c_ard_3-2-1_106083_2022-11-06_final
2022-11-20 11:06:52	ga_ls8c_ard_3-2-1_108071_2022-11-20_final
2022-11-20 11:07:16	ga_ls8c_ard_3-2-1_108072_2022-11-20_final
2022-11-20 11:07:40	ga_ls8c_ard_3-2-1_108073_2022-11-20_final
2022-11-20 11:08:04	ga_ls8c_ard_3-2-1_108074_2022-11-20_final
2022-11-20 11:08:28	ga_ls8c_ard_3-2-1_108075_2022-11-20_final
2022-11-20 11:08:52	ga_ls8c_ard_3-2-1_108076_2022-11-20_final
2022-11-22 10:58:07	ga_ls8c_ard_3-2-1_106080_2022-11-22_final
2022-11-22 10:58:31	ga_ls8c_ard_3-2-1_106081_2022-11-22_final
2022-11-22 10:58:55	ga_ls8c_ard_3-2-1_106082_2022-11-22_final
2022-11-22 10:59:19	ga_ls8c_ard_3-2-1_106083_2022-11-22_final
2022-11-27 11:12:17	ga_ls8c_ard_3-2-1_109069_2022-11-27_final
2022-11-27 11:12:41	ga_ls8c_ard_3-2-1_109070_2022-11-27_final
2022-11-27 11:13:05	ga_ls8c_ard_3-2-1_109071_2022-11-27_final
2022-11-27 11:13:29	ga_ls8c_ard_3-2-1_109072_2022-11-27_final
2022-11-29 11:02:19	ga_ls8c_ard_3-2-1_107075_2022-11-29_final
2022-11-29 11:02:43	ga_ls8c_ard_3-2-1_107076_2022-11-29_final
2022-11-29 11:03:07	ga_ls8c_ard_3-2-1_107077_2022-11-29_final
2022-11-29 11:03:31	ga_ls8c_ard_3-2-1_107078_2022-11-29_final
2022-11-29 11:03:55	ga_ls8c_ard_3-2-1_107079_2022-11-29_final
2022-11-29 11:04:19	ga_ls8c_ard_3-2-1_107080_2022-11-29_final
2022-11-29 11:04:43	ga_ls8c_ard_3-2-1_107081_2022-11-29_final
2022-12-06 11:06:54	ga_ls8c_ard_3-2-1_108071_2022-12-06_final
2022-12-06 11:07:18	ga_ls8c_ard_3-2-1_108072_2022-12-06_final
2022-12-06 11:07:42	ga_ls8c_ard_3-2-1_108073_2022-12-06_final
2022-12-06 11:08:06	ga_ls8c_ard_3-2-1_108074_2022-12-06_final
2022-12-06 11:08:30	ga_ls8c_ard_3-2-1_108075_2022-12-06_final
2022-12-06 11:08:54	ga_ls8c_ard_3-2-1_108076_2022-12-06_final
2022-12-29 11:12:08	ga_ls8c_ard_3-2-1_109069_2022-12-29_final
2022-12-29 11:12:32	ga_ls8c_ard_3-2-1_109070_2022-12-29_final
2022-12-29 11:12:56	ga_ls8c_ard_3-2-1_109071_2022-12-29_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