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
2013-09-04 11:36:42	ga_ls8c_ard_3-0-0_112080_2013-09-04_final
2013-09-04 11:37:06	ga_ls8c_ard_3-0-0_112081_2013-09-04_final
2013-09-04 11:37:30	ga_ls8c_ard_3-0-0_112082_2013-09-04_final
2013-09-04 11:37:54	ga_ls8c_ard_3-0-0_112083_2013-09-04_final
2013-09-04 11:38:18	ga_ls8c_ard_3-0-0_112084_2013-09-04_final
2015-09-03 11:29:53	ga_ls8c_ard_3-0-0_111084_2015-09-03_final
2015-09-03 11:30:17	ga_ls8c_ard_3-0-0_111085_2015-09-03_final
2015-11-04 11:38:58	ga_ls8c_ard_3-0-0_113075_2015-11-04_final
2015-11-04 11:39:22	ga_ls8c_ard_3-0-0_113076_2015-11-04_final
2015-11-04 11:39:45	ga_ls8c_ard_3-0-0_113077_2015-11-04_final
2015-11-04 11:40:09	ga_ls8c_ard_3-0-0_113078_2015-11-04_final
2015-11-04 11:40:33	ga_ls8c_ard_3-0-0_113079_2015-11-04_final
2015-11-04 11:40:57	ga_ls8c_ard_3-0-0_113080_2015-11-04_final
2015-11-04 11:41:21	ga_ls8c_ard_3-0-0_113081_2015-11-04_final
2015-11-06 11:30:11	ga_ls8c_ard_3-0-0_111084_2015-11-06_final
2015-11-06 11:30:35	ga_ls8c_ard_3-0-0_111085_2015-11-06_final
2015-11-20 11:38:59	ga_ls8c_ard_3-0-0_113075_2015-11-20_final
2015-11-20 11:39:23	ga_ls8c_ard_3-0-0_113076_2015-11-20_final
2015-11-20 11:39:47	ga_ls8c_ard_3-0-0_113077_2015-11-20_final
2015-11-20 11:40:11	ga_ls8c_ard_3-0-0_113078_2015-11-20_final
2015-11-20 11:40:35	ga_ls8c_ard_3-0-0_113079_2015-11-20_final
2015-11-20 11:40:59	ga_ls8c_ard_3-0-0_113080_2015-11-20_final
2015-11-20 11:41:23	ga_ls8c_ard_3-0-0_113081_2015-11-20_final
2018-03-03 11:29:46	ga_ls8c_ard_3-0-0_111084_2018-03-03_final
2018-03-03 11:30:10	ga_ls8c_ard_3-0-0_111085_2018-03-03_final
2018-03-17 11:38:24	ga_ls8c_ard_3-0-0_113075_2018-03-17_final
2018-03-17 11:38:48	ga_ls8c_ard_3-0-0_113076_2018-03-17_final
2018-03-17 11:39:12	ga_ls8c_ard_3-0-0_113077_2018-03-17_final
2018-03-17 11:39:36	ga_ls8c_ard_3-0-0_113078_2018-03-17_final
2018-03-17 11:40:00	ga_ls8c_ard_3-0-0_113079_2018-03-17_final
2018-03-17 11:40:23	ga_ls8c_ard_3-0-0_113080_2018-03-17_final
2018-03-17 11:40:47	ga_ls8c_ard_3-0-0_113081_2018-03-17_final
2018-03-19 11:29:37	ga_ls8c_ard_3-0-0_111084_2018-03-19_final
2018-03-19 11:30:01	ga_ls8c_ard_3-0-0_111085_2018-03-19_final
2022-10-15 11:35:10	ga_ls8c_ard_3-2-1_112080_2022-10-15_final
2022-10-15 11:35:34	ga_ls8c_ard_3-2-1_112081_2022-10-15_final
2022-10-15 11:35:58	ga_ls8c_ard_3-2-1_112082_2022-10-15_final
2022-10-15 11:36:22	ga_ls8c_ard_3-2-1_112083_2022-10-15_final
2022-10-15 11:36:46	ga_ls8c_ard_3-2-1_112084_2022-10-15_final
2022-10-22 11:39:26	ga_ls8c_ard_3-2-1_113075_2022-10-22_final
2022-10-22 11:39:50	ga_ls8c_ard_3-2-1_113076_2022-10-22_final
2022-10-22 11:40:14	ga_ls8c_ard_3-2-1_113077_2022-10-22_final
2022-10-22 11:40:38	ga_ls8c_ard_3-2-1_113078_2022-10-22_final
2022-10-22 11:41:02	ga_ls8c_ard_3-2-1_113079_2022-10-22_final
2022-10-22 11:41:26	ga_ls8c_ard_3-2-1_113080_2022-10-22_final
2022-10-22 11:41:50	ga_ls8c_ard_3-2-1_113081_2022-10-22_final
2022-10-24 11:30:17	ga_ls8c_ard_3-2-1_111083_2022-10-24_final
2022-10-24 11:30:41	ga_ls8c_ard_3-2-1_111084_2022-10-24_final
2022-10-29 11:45:16	ga_ls8c_ard_3-2-1_114074_2022-10-29_final
2022-10-29 11:45:40	ga_ls8c_ard_3-2-1_114075_2022-10-29_final
2022-10-29 11:46:04	ga_ls8c_ard_3-2-1_114076_2022-10-29_final
2022-10-31 11:35:18	ga_ls8c_ard_3-2-1_112080_2022-10-31_final
2022-10-31 11:35:42	ga_ls8c_ard_3-2-1_112081_2022-10-31_final
2022-10-31 11:36:06	ga_ls8c_ard_3-2-1_112082_2022-10-31_final
2022-10-31 11:36:30	ga_ls8c_ard_3-2-1_112083_2022-10-31_final
2022-10-31 11:36:54	ga_ls8c_ard_3-2-1_112084_2022-10-31_final
2022-11-09 11:30:18	ga_ls8c_ard_3-2-1_111083_2022-11-09_final
2022-11-09 11:30:42	ga_ls8c_ard_3-2-1_111084_2022-11-09_final
2023-05-02 11:38:19	ga_ls8c_ard_3-2-1_113075_2023-05-02_final
2023-05-02 11:38:42	ga_ls8c_ard_3-2-1_113076_2023-05-02_final
2023-05-02 11:39:06	ga_ls8c_ard_3-2-1_113077_2023-05-02_final
2023-05-02 11:39:30	ga_ls8c_ard_3-2-1_113078_2023-05-02_final
2023-05-02 11:39:54	ga_ls8c_ard_3-2-1_113079_2023-05-02_final
2023-05-02 11:40:18	ga_ls8c_ard_3-2-1_113080_2023-05-02_final
2023-05-02 11:40:42	ga_ls8c_ard_3-2-1_113081_2023-05-02_final
2023-05-04 11:29:31	ga_ls8c_ard_3-2-1_111084_2023-05-04_final
2023-05-09 11:43:59	ga_ls8c_ard_3-2-1_114074_2023-05-09_final
2023-05-09 11:44:23	ga_ls8c_ard_3-2-1_114075_2023-05-09_final
2023-05-09 11:44:47	ga_ls8c_ard_3-2-1_114076_2023-05-09_final
2023-05-18 11:38:06	ga_ls8c_ard_3-2-1_113075_2023-05-18_final
2023-05-18 11:38:30	ga_ls8c_ard_3-2-1_113076_2023-05-18_final
2023-05-18 11:38:54	ga_ls8c_ard_3-2-1_113077_2023-05-18_final
2023-05-18 11:39:18	ga_ls8c_ard_3-2-1_113078_2023-05-18_final
2023-05-18 11:39:42	ga_ls8c_ard_3-2-1_113079_2023-05-18_final
2023-05-18 11:40:06	ga_ls8c_ard_3-2-1_113080_2023-05-18_final
2023-05-18 11:40:30	ga_ls8c_ard_3-2-1_113081_2023-05-18_final
2023-05-20 11:28:57	ga_ls8c_ard_3-2-1_111083_2023-05-20_final
2023-05-20 11:29:21	ga_ls8c_ard_3-2-1_111084_2023-05-20_final
2023-05-25 11:43:56	ga_ls8c_ard_3-2-1_114074_2023-05-25_final
2023-05-25 11:44:20	ga_ls8c_ard_3-2-1_114075_2023-05-25_final
2023-05-25 11:44:44	ga_ls8c_ard_3-2-1_114076_2023-05-25_final
2023-05-27 11:33:58	ga_ls8c_ard_3-2-1_112080_2023-05-27_final
2023-05-27 11:34:22	ga_ls8c_ard_3-2-1_112081_2023-05-27_final
2023-05-27 11:34:46	ga_ls8c_ard_3-2-1_112082_2023-05-27_final
2023-05-27 11:35:10	ga_ls8c_ard_3-2-1_112083_2023-05-27_final
2023-05-27 11:35:34	ga_ls8c_ard_3-2-1_112084_2023-05-27_final
2023-07-12 11:44:20	ga_ls8c_ard_3-2-1_114074_2023-07-12_final
2023-07-12 11:44:43	ga_ls8c_ard_3-2-1_114075_2023-07-12_final
2023-07-12 11:45:07	ga_ls8c_ard_3-2-1_114076_2023-07-12_final
2023-07-14 11:34:22	ga_ls8c_ard_3-2-1_112080_2023-07-14_final
2023-07-14 11:34:46	ga_ls8c_ard_3-2-1_112081_2023-07-14_final
2023-07-14 11:35:10	ga_ls8c_ard_3-2-1_112082_2023-07-14_final
2023-07-14 11:35:34	ga_ls8c_ard_3-2-1_112083_2023-07-14_final
2023-07-14 11:35:58	ga_ls8c_ard_3-2-1_112084_2023-07-14_final
2023-08-06 11:38:42	ga_ls8c_ard_3-2-1_113075_2023-08-06_final
2023-08-06 11:39:06	ga_ls8c_ard_3-2-1_113076_2023-08-06_final
2023-08-06 11:39:30	ga_ls8c_ard_3-2-1_113077_2023-08-06_final
2023-08-06 11:39:54	ga_ls8c_ard_3-2-1_113078_2023-08-06_final
2023-08-06 11:40:18	ga_ls8c_ard_3-2-1_113079_2023-08-06_final
2023-08-06 11:40:42	ga_ls8c_ard_3-2-1_113080_2023-08-06_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years