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
2018-06-09 09:30:52	ga_ls8c_ard_3-0-0_093067_2018-06-09_final
2018-06-09 09:31:16	ga_ls8c_ard_3-0-0_093068_2018-06-09_final
2018-06-18 09:25:11	ga_ls8c_ard_3-0-0_092068_2018-06-17_final
2018-07-04 09:25:21	ga_ls8c_ard_3-0-0_092068_2018-07-03_final
2018-07-13 09:21:14	ga_ls8c_ard_3-0-0_091073_2018-07-12_final
2018-07-13 09:21:38	ga_ls8c_ard_3-0-0_091074_2018-07-12_final
2018-07-13 09:22:02	ga_ls8c_ard_3-0-0_091075_2018-07-12_final
2018-07-13 09:22:26	ga_ls8c_ard_3-0-0_091076_2018-07-12_final
2018-07-13 09:22:50	ga_ls8c_ard_3-0-0_091077_2018-07-12_final
2018-07-13 09:23:14	ga_ls8c_ard_3-0-0_091078_2018-07-12_final
2018-07-13 09:23:38	ga_ls8c_ard_3-0-0_091079_2018-07-12_final
2018-08-12 09:31:27	ga_ls8c_ard_3-0-0_093067_2018-08-12_final
2018-08-12 09:31:51	ga_ls8c_ard_3-0-0_093068_2018-08-12_final
2018-08-14 09:21:30	ga_ls8c_ard_3-0-0_091073_2018-08-13_final
2018-08-14 09:21:54	ga_ls8c_ard_3-0-0_091074_2018-08-13_final
2018-08-14 09:22:18	ga_ls8c_ard_3-0-0_091075_2018-08-13_final
2018-08-14 09:22:42	ga_ls8c_ard_3-0-0_091076_2018-08-13_final
2018-08-14 09:23:06	ga_ls8c_ard_3-0-0_091077_2018-08-13_final
2018-08-14 09:23:30	ga_ls8c_ard_3-0-0_091078_2018-08-13_final
2018-08-14 09:23:54	ga_ls8c_ard_3-0-0_091079_2018-08-13_final
2018-08-21 09:25:45	ga_ls8c_ard_3-0-0_092068_2018-08-20_final
2018-08-28 09:31:35	ga_ls8c_ard_3-0-0_093067_2018-08-28_final
2018-08-28 09:31:59	ga_ls8c_ard_3-0-0_093068_2018-08-28_final
2018-10-03 09:13:04	ga_ls8c_ard_3-0-0_089082_2018-10-02_final
2018-10-03 09:13:28	ga_ls8c_ard_3-0-0_089083_2018-10-02_final
2018-10-03 09:13:52	ga_ls8c_ard_3-0-0_089084_2018-10-02_final
2018-10-03 09:14:16	ga_ls8c_ard_3-0-0_089085_2018-10-02_final
2018-10-03 09:14:40	ga_ls8c_ard_3-0-0_089086_2018-10-02_final
2018-10-03 09:15:04	ga_ls8c_ard_3-0-0_089087_2018-10-02_final
2018-10-19 09:13:10	ga_ls8c_ard_3-0-0_089082_2018-10-18_final
2018-10-19 09:13:34	ga_ls8c_ard_3-0-0_089083_2018-10-18_final
2018-10-19 09:13:58	ga_ls8c_ard_3-0-0_089084_2018-10-18_final
2018-10-19 09:14:22	ga_ls8c_ard_3-0-0_089085_2018-10-18_final
2018-10-19 09:14:46	ga_ls8c_ard_3-0-0_089086_2018-10-18_final
2018-10-19 09:15:10	ga_ls8c_ard_3-0-0_089087_2018-10-18_final
2020-03-14 09:13:11	ga_ls8c_ard_3-1-0_089082_2020-03-13_final
2020-03-14 09:13:35	ga_ls8c_ard_3-1-0_089083_2020-03-13_final
2020-03-14 09:13:59	ga_ls8c_ard_3-1-0_089084_2020-03-13_final
2020-03-14 09:14:23	ga_ls8c_ard_3-1-0_089085_2020-03-13_final
2020-03-14 09:14:47	ga_ls8c_ard_3-1-0_089086_2020-03-13_final
2020-03-14 09:15:11	ga_ls8c_ard_3-1-0_089087_2020-03-13_final
2020-04-13 09:21:42	ga_ls8c_ard_3-1-0_091073_2020-04-12_final
2020-04-13 09:22:06	ga_ls8c_ard_3-1-0_091074_2020-04-12_final
2020-04-13 09:22:30	ga_ls8c_ard_3-1-0_091075_2020-04-12_final
2020-04-13 09:22:54	ga_ls8c_ard_3-1-0_091076_2020-04-12_final
2020-04-13 09:23:17	ga_ls8c_ard_3-1-0_091077_2020-04-12_final
2020-04-13 09:23:41	ga_ls8c_ard_3-1-0_091078_2020-04-12_final
2020-04-13 09:24:05	ga_ls8c_ard_3-1-0_091079_2020-04-12_final
2020-04-15 09:12:55	ga_ls8c_ard_3-1-0_089082_2020-04-14_final
2020-04-15 09:13:19	ga_ls8c_ard_3-1-0_089083_2020-04-14_final
2020-04-15 09:13:43	ga_ls8c_ard_3-1-0_089084_2020-04-14_final
2020-04-15 09:14:07	ga_ls8c_ard_3-1-0_089085_2020-04-14_final
2020-04-15 09:14:31	ga_ls8c_ard_3-1-0_089086_2020-04-14_final
2020-04-15 09:14:55	ga_ls8c_ard_3-1-0_089087_2020-04-14_final
2020-05-22 09:26:54	ga_ls8c_ard_3-1-0_092071_2020-05-21_final
2020-05-22 09:27:18	ga_ls8c_ard_3-1-0_092072_2020-05-21_final
2020-05-22 09:27:42	ga_ls8c_ard_3-1-0_092073_2020-05-21_final
2020-05-22 09:28:06	ga_ls8c_ard_3-1-0_092074_2020-05-21_final
2020-05-24 09:17:21	ga_ls8c_ard_3-1-0_090078_2020-05-23_final
2020-05-24 09:17:45	ga_ls8c_ard_3-1-0_090079_2020-05-23_final
2020-05-24 09:18:09	ga_ls8c_ard_3-1-0_090080_2020-05-23_final
2020-05-24 09:18:33	ga_ls8c_ard_3-1-0_090081_2020-05-23_final
2020-05-24 09:18:56	ga_ls8c_ard_3-1-0_090082_2020-05-23_final
2020-05-24 09:19:20	ga_ls8c_ard_3-1-0_090083_2020-05-23_final
2020-06-25 09:17:38	ga_ls8c_ard_3-1-0_090078_2020-06-24_final
2020-06-25 09:18:02	ga_ls8c_ard_3-1-0_090079_2020-06-24_final
2020-06-25 09:18:26	ga_ls8c_ard_3-1-0_090080_2020-06-24_final
2020-06-25 09:18:50	ga_ls8c_ard_3-1-0_090081_2020-06-24_final
2020-06-25 09:19:13	ga_ls8c_ard_3-1-0_090082_2020-06-24_final
2020-06-25 09:19:37	ga_ls8c_ard_3-1-0_090083_2020-06-24_final
2020-08-03 09:22:02	ga_ls8c_ard_3-1-0_091073_2020-08-02_final
2020-08-03 09:22:26	ga_ls8c_ard_3-1-0_091074_2020-08-02_final
2020-08-03 09:22:50	ga_ls8c_ard_3-1-0_091075_2020-08-02_final
2020-08-03 09:23:14	ga_ls8c_ard_3-1-0_091076_2020-08-02_final
2020-08-03 09:23:38	ga_ls8c_ard_3-1-0_091077_2020-08-02_final
2020-08-03 09:24:02	ga_ls8c_ard_3-1-0_091078_2020-08-02_final
2020-08-03 09:24:26	ga_ls8c_ard_3-1-0_091079_2020-08-02_final
2020-08-17 09:32:05	ga_ls8c_ard_3-1-0_093067_2020-08-17_final
2020-08-17 09:32:28	ga_ls8c_ard_3-1-0_093068_2020-08-17_final
2020-08-28 09:20:01	ga_ls8c_ard_3-1-0_090083_2020-08-27_final
2020-11-16 09:18:11	ga_ls8c_ard_3-1-0_090078_2020-11-15_final
2020-11-16 09:18:35	ga_ls8c_ard_3-1-0_090079_2020-11-15_final
2020-11-16 09:18:59	ga_ls8c_ard_3-1-0_090080_2020-11-15_final
2020-11-16 09:19:23	ga_ls8c_ard_3-1-0_090081_2020-11-15_final
2020-11-16 09:19:47	ga_ls8c_ard_3-1-0_090082_2020-11-15_final
2020-11-16 09:20:11	ga_ls8c_ard_3-1-0_090083_2020-11-15_final
2020-12-23 09:32:22	ga_ls8c_ard_3-2-0_093067_2020-12-23_final
2020-12-23 09:32:46	ga_ls8c_ard_3-2-0_093068_2020-12-23_final
2020-12-25 09:22:24	ga_ls8c_ard_3-2-0_091073_2020-12-24_final
2020-12-25 09:22:48	ga_ls8c_ard_3-2-0_091074_2020-12-24_final
2020-12-25 09:23:12	ga_ls8c_ard_3-2-0_091075_2020-12-24_final
2020-12-25 09:23:36	ga_ls8c_ard_3-2-0_091076_2020-12-24_final
2020-12-25 09:24:00	ga_ls8c_ard_3-2-0_091077_2020-12-24_final
2020-12-25 09:24:24	ga_ls8c_ard_3-2-0_091078_2020-12-24_final
2020-12-25 09:24:47	ga_ls8c_ard_3-2-0_091079_2020-12-24_final
2020-12-27 09:13:37	ga_ls8c_ard_3-2-0_089082_2020-12-26_final
2020-12-27 09:14:01	ga_ls8c_ard_3-2-0_089083_2020-12-26_final
2020-12-27 09:14:25	ga_ls8c_ard_3-2-0_089084_2020-12-26_final
2020-12-27 09:14:49	ga_ls8c_ard_3-2-0_089085_2020-12-26_final
2020-12-27 09:15:13	ga_ls8c_ard_3-2-0_089086_2020-12-26_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