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
2018-06-08 10:26:28	ga_ls8c_ard_3-0-0_102067_2018-06-08_final
2018-06-08 10:26:52	ga_ls8c_ard_3-0-0_102068_2018-06-08_final
2018-06-08 10:27:16	ga_ls8c_ard_3-0-0_102069_2018-06-08_final
2018-06-08 10:27:40	ga_ls8c_ard_3-0-0_102070_2018-06-08_final
2018-06-08 10:28:04	ga_ls8c_ard_3-0-0_102071_2018-06-08_final
2018-06-10 10:17:20	ga_ls8c_ard_3-0-0_100075_2018-06-10_final
2018-06-10 10:17:44	ga_ls8c_ard_3-0-0_100076_2018-06-10_final
2018-06-10 10:18:08	ga_ls8c_ard_3-0-0_100077_2018-06-10_final
2018-06-10 10:18:32	ga_ls8c_ard_3-0-0_100078_2018-06-10_final
2018-06-10 10:18:56	ga_ls8c_ard_3-0-0_100079_2018-06-10_final
2018-06-10 10:19:19	ga_ls8c_ard_3-0-0_100080_2018-06-10_final
2018-07-12 10:17:15	ga_ls8c_ard_3-0-0_100074_2018-07-12_final
2018-07-12 10:17:39	ga_ls8c_ard_3-0-0_100075_2018-07-12_final
2018-09-16 10:08:58	ga_ls8c_ard_3-0-0_098083_2018-09-16_final
2018-09-16 10:09:21	ga_ls8c_ard_3-0-0_098084_2018-09-16_final
2018-09-16 10:09:45	ga_ls8c_ard_3-0-0_098085_2018-09-16_final
2018-09-16 10:10:09	ga_ls8c_ard_3-0-0_098086_2018-09-16_final
2018-10-07 10:22:28	ga_ls8c_ard_3-0-0_101070_2018-10-07_final
2018-10-07 10:22:52	ga_ls8c_ard_3-0-0_101071_2018-10-07_final
2018-10-07 10:23:16	ga_ls8c_ard_3-1-0_101072_2018-10-07_final
2018-10-07 10:23:40	ga_ls8c_ard_3-0-0_101073_2018-10-07_final
2018-10-07 10:24:04	ga_ls8c_ard_3-0-0_101074_2018-10-07_final
2018-10-07 10:24:28	ga_ls8c_ard_3-0-0_101075_2018-10-07_final
2018-12-26 10:22:34	ga_ls8c_ard_3-0-0_101070_2018-12-26_final
2018-12-26 10:22:58	ga_ls8c_ard_3-0-0_101071_2018-12-26_final
2018-12-26 10:23:22	ga_ls8c_ard_3-1-0_101072_2018-12-26_final
2018-12-26 10:23:46	ga_ls8c_ard_3-0-0_101073_2018-12-26_final
2018-12-26 10:24:10	ga_ls8c_ard_3-0-0_101074_2018-12-26_final
2018-12-26 10:24:33	ga_ls8c_ard_3-0-0_101075_2018-12-26_final
2018-12-26 10:24:57	ga_ls8c_ard_3-0-0_101076_2018-12-26_final
2019-01-06 10:09:12	ga_ls8c_ard_3-0-0_098083_2019-01-06_final
2019-01-06 10:09:36	ga_ls8c_ard_3-0-0_098084_2019-01-06_final
2019-01-06 10:10:00	ga_ls8c_ard_3-0-0_098085_2019-01-06_final
2019-01-06 10:10:24	ga_ls8c_ard_3-0-0_098086_2019-01-06_final
2019-07-06 10:22:36	ga_ls8c_ard_3-1-0_101070_2019-07-06_final
2019-07-06 10:23:00	ga_ls8c_ard_3-1-0_101071_2019-07-06_final
2019-07-06 10:23:24	ga_ls8c_ard_3-1-0_101072_2019-07-06_final
2019-07-06 10:23:48	ga_ls8c_ard_3-1-0_101073_2019-07-06_final
2019-07-06 10:24:12	ga_ls8c_ard_3-1-0_101074_2019-07-06_final
2019-07-06 10:24:36	ga_ls8c_ard_3-1-0_101075_2019-07-06_final
2019-07-17 10:09:17	ga_ls8c_ard_3-1-0_098083_2019-07-17_final
2019-07-17 10:09:41	ga_ls8c_ard_3-1-0_098084_2019-07-17_final
2019-07-17 10:10:05	ga_ls8c_ard_3-1-0_098085_2019-07-17_final
2019-07-17 10:10:29	ga_ls8c_ard_3-1-0_098086_2019-07-17_final
2019-07-24 10:13:55	ga_ls8c_ard_3-1-0_099079_2019-07-24_final
2019-07-24 10:14:19	ga_ls8c_ard_3-1-0_099080_2019-07-24_final
2019-07-24 10:14:43	ga_ls8c_ard_3-1-0_099081_2019-07-24_final
2019-07-24 10:15:06	ga_ls8c_ard_3-1-0_099082_2019-07-24_final
2019-07-24 10:15:30	ga_ls8c_ard_3-1-0_099083_2019-07-24_final
2019-07-24 10:15:54	ga_ls8c_ard_3-1-0_099084_2019-07-24_final
2019-07-26 10:04:22	ga_ls8c_ard_3-1-0_097086_2019-07-26_final
2019-08-07 10:22:47	ga_ls8c_ard_3-1-0_101070_2019-08-07_final
2019-08-07 10:23:11	ga_ls8c_ard_3-1-0_101071_2019-08-07_final
2019-08-07 10:23:34	ga_ls8c_ard_3-1-0_101072_2019-08-07_final
2019-08-07 10:23:58	ga_ls8c_ard_3-1-0_101073_2019-08-07_final
2019-08-07 10:24:22	ga_ls8c_ard_3-1-0_101074_2019-08-07_final
2019-08-07 10:24:46	ga_ls8c_ard_3-1-0_101075_2019-08-07_final
2019-08-18 10:09:29	ga_ls8c_ard_3-1-0_098083_2019-08-18_final
2019-08-18 10:09:53	ga_ls8c_ard_3-1-0_098084_2019-08-18_final
2019-08-18 10:10:17	ga_ls8c_ard_3-1-0_098085_2019-08-18_final
2019-08-18 10:10:41	ga_ls8c_ard_3-1-0_098086_2019-08-18_final
2019-08-23 10:22:51	ga_ls8c_ard_3-1-0_101070_2019-08-23_final
2019-08-23 10:23:15	ga_ls8c_ard_3-1-0_101071_2019-08-23_final
2019-08-23 10:23:39	ga_ls8c_ard_3-1-0_101072_2019-08-23_final
2019-08-23 10:24:03	ga_ls8c_ard_3-1-0_101073_2019-08-23_final
2019-08-23 10:24:27	ga_ls8c_ard_3-1-0_101074_2019-08-23_final
2019-08-23 10:24:51	ga_ls8c_ard_3-1-0_101075_2019-08-23_final
2019-09-03 10:09:32	ga_ls8c_ard_3-1-0_098083_2019-09-03_final
2019-09-03 10:09:56	ga_ls8c_ard_3-1-0_098084_2019-09-03_final
2019-09-03 10:10:20	ga_ls8c_ard_3-1-0_098085_2019-09-03_final
2019-09-03 10:10:44	ga_ls8c_ard_3-1-0_098086_2019-09-03_final
2019-09-24 10:23:01	ga_ls8c_ard_3-1-0_101070_2019-09-24_final
2019-09-24 10:23:25	ga_ls8c_ard_3-1-0_101071_2019-09-24_final
2019-09-24 10:23:48	ga_ls8c_ard_3-1-0_101072_2019-09-24_final
2019-09-24 10:24:12	ga_ls8c_ard_3-1-0_101073_2019-09-24_final
2019-09-24 10:24:36	ga_ls8c_ard_3-1-0_101074_2019-09-24_final
2019-09-24 10:25:00	ga_ls8c_ard_3-1-0_101075_2019-09-24_final
2019-10-05 10:09:42	ga_ls8c_ard_3-1-0_098083_2019-10-05_final
2019-10-05 10:10:06	ga_ls8c_ard_3-1-0_098084_2019-10-05_final
2019-10-05 10:10:30	ga_ls8c_ard_3-1-0_098085_2019-10-05_final
2019-10-05 10:10:54	ga_ls8c_ard_3-1-0_098086_2019-10-05_final
2019-10-21 10:09:44	ga_ls8c_ard_3-1-0_098083_2019-10-21_final
2019-10-21 10:10:08	ga_ls8c_ard_3-1-0_098084_2019-10-21_final
2019-10-21 10:10:32	ga_ls8c_ard_3-1-0_098085_2019-10-21_final
2019-10-21 10:10:56	ga_ls8c_ard_3-1-0_098086_2019-10-21_final
2023-07-10 10:17:48	ga_ls8c_ard_3-2-1_100074_2023-07-10_final
2023-07-10 10:18:11	ga_ls8c_ard_3-2-1_100075_2023-07-10_final
2023-07-10 10:18:35	ga_ls8c_ard_3-2-1_100076_2023-07-10_final
2023-07-10 10:18:59	ga_ls8c_ard_3-2-1_100077_2023-07-10_final
2023-07-10 10:19:23	ga_ls8c_ard_3-2-1_100078_2023-07-10_final
2023-07-10 10:19:47	ga_ls8c_ard_3-2-1_100079_2023-07-10_final
2023-07-10 10:20:11	ga_ls8c_ard_3-2-1_100080_2023-07-10_final
2023-07-12 10:09:02	ga_ls8c_ard_3-2-1_098083_2023-07-12_final
2023-07-12 10:09:26	ga_ls8c_ard_3-2-1_098084_2023-07-12_final
2023-07-12 10:09:50	ga_ls8c_ard_3-2-1_098085_2023-07-12_final
2023-07-17 10:22:24	ga_ls8c_ard_3-2-1_101070_2023-07-17_final
2023-07-17 10:22:47	ga_ls8c_ard_3-2-1_101071_2023-07-17_final
2023-07-17 10:23:11	ga_ls8c_ard_3-2-1_101072_2023-07-17_final
2023-07-17 10:23:35	ga_ls8c_ard_3-2-1_101073_2023-07-17_final
2023-07-17 10:23:59	ga_ls8c_ard_3-2-1_101074_2023-07-17_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