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
2016-07-05 09:31:56	ga_ls8c_ard_3-0-0_093067_2016-07-05_final
2016-07-05 09:32:20	ga_ls8c_ard_3-0-0_093068_2016-07-05_final
2016-07-05 09:33:31	ga_ls8c_ard_3-0-0_093071_2016-07-05_final
2016-07-05 09:33:55	ga_ls8c_ard_3-0-0_093072_2016-07-05_final
2016-07-05 09:34:19	ga_ls8c_ard_3-0-0_093073_2016-07-05_final
2016-07-28 09:38:14	ga_ls8c_ard_3-0-0_094067_2016-07-28_final
2016-10-09 09:32:21	ga_ls8c_ard_3-0-0_093067_2016-10-09_final
2016-10-09 09:32:45	ga_ls8c_ard_3-0-0_093068_2016-10-09_final
2017-11-17 09:14:21	ga_ls8c_ard_3-0-0_089084_2017-11-16_final
2017-11-17 09:14:45	ga_ls8c_ard_3-0-0_089085_2017-11-16_final
2017-11-17 09:15:09	ga_ls8c_ard_3-0-0_089086_2017-11-16_final
2017-11-17 09:15:33	ga_ls8c_ard_3-0-0_089087_2017-11-16_final
2017-11-17 09:15:57	ga_ls8c_ard_3-0-0_089088_2017-11-16_final
2017-11-17 09:16:21	ga_ls8c_ard_3-0-0_089089_2017-11-16_final
2017-11-17 09:16:45	ga_ls8c_ard_3-0-0_089090_2017-11-16_final
2018-01-04 09:14:15	ga_ls8c_ard_3-0-0_089084_2018-01-03_final
2018-01-04 09:14:39	ga_ls8c_ard_3-0-0_089085_2018-01-03_final
2018-01-04 09:15:03	ga_ls8c_ard_3-0-0_089086_2018-01-03_final
2018-01-04 09:15:27	ga_ls8c_ard_3-0-0_089087_2018-01-03_final
2018-01-04 09:15:51	ga_ls8c_ard_3-0-0_089088_2018-01-03_final
2018-01-04 09:16:15	ga_ls8c_ard_3-0-0_089089_2018-01-03_final
2018-01-04 09:16:38	ga_ls8c_ard_3-0-0_089090_2018-01-03_final
2018-01-20 09:14:07	ga_ls8c_ard_3-0-0_089084_2018-01-19_final
2018-01-20 09:14:31	ga_ls8c_ard_3-0-0_089085_2018-01-19_final
2018-01-20 09:14:55	ga_ls8c_ard_3-0-0_089086_2018-01-19_final
2018-01-20 09:15:19	ga_ls8c_ard_3-0-0_089087_2018-01-19_final
2018-01-20 09:15:43	ga_ls8c_ard_3-0-0_089088_2018-01-19_final
2018-01-20 09:16:07	ga_ls8c_ard_3-0-0_089089_2018-01-19_final
2018-01-20 09:16:31	ga_ls8c_ard_3-0-0_089090_2018-01-19_final
2018-02-17 09:31:51	ga_ls8c_ard_3-0-0_093067_2018-02-17_final
2018-02-17 09:32:15	ga_ls8c_ard_3-0-0_093068_2018-02-17_final
2018-02-17 09:33:26	ga_ls8c_ard_3-0-0_093071_2018-02-17_final
2018-02-17 09:33:50	ga_ls8c_ard_3-0-0_093072_2018-02-17_final
2018-02-17 09:34:14	ga_ls8c_ard_3-0-0_093073_2018-02-17_final
2018-05-19 09:18:04	ga_ls8c_ard_3-0-0_090081_2018-05-18_final
2018-05-19 09:18:28	ga_ls8c_ard_3-0-0_090082_2018-05-18_final
2018-05-19 09:18:51	ga_ls8c_ard_3-0-0_090083_2018-05-18_final
2018-05-19 09:19:15	ga_ls8c_ard_3-0-0_090084_2018-05-18_final
2018-05-19 09:19:39	ga_ls8c_ard_3-0-0_090085_2018-05-18_final
2018-05-19 09:20:03	ga_ls8c_ard_3-0-0_090086_2018-05-18_final
2018-05-24 09:30:57	ga_ls8c_ard_3-0-0_093067_2018-05-24_final
2018-05-24 09:31:21	ga_ls8c_ard_3-0-0_093068_2018-05-24_final
2018-06-04 09:17:52	ga_ls8c_ard_3-0-0_090081_2018-06-03_final
2018-06-04 09:18:16	ga_ls8c_ard_3-0-0_090082_2018-06-03_final
2018-06-04 09:18:40	ga_ls8c_ard_3-0-0_090083_2018-06-03_final
2018-06-04 09:19:04	ga_ls8c_ard_3-0-0_090084_2018-06-03_final
2018-06-04 09:19:28	ga_ls8c_ard_3-0-0_090085_2018-06-03_final
2018-06-04 09:19:52	ga_ls8c_ard_3-0-0_090086_2018-06-03_final
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
2019-02-24 09:13:49	ga_ls8c_ard_3-0-0_089084_2019-02-23_final
2019-02-24 09:14:13	ga_ls8c_ard_3-0-0_089085_2019-02-23_final
2019-02-24 09:14:37	ga_ls8c_ard_3-0-0_089086_2019-02-23_final
2019-02-24 09:15:01	ga_ls8c_ard_3-0-0_089087_2019-02-23_final
2019-02-24 09:15:25	ga_ls8c_ard_3-0-0_089088_2019-02-23_final
2019-02-24 09:15:49	ga_ls8c_ard_3-0-0_089089_2019-02-23_final
2019-02-24 09:16:13	ga_ls8c_ard_3-0-0_089090_2019-02-23_final
2019-03-24 09:31:37	ga_ls8c_ard_3-1-0_093067_2019-03-24_final
2019-03-24 09:32:01	ga_ls8c_ard_3-1-0_093068_2019-03-24_final
2019-04-13 09:13:35	ga_ls8c_ard_3-1-0_089084_2019-04-12_final
2019-04-13 09:13:59	ga_ls8c_ard_3-1-0_089085_2019-04-12_final
2019-04-13 09:14:23	ga_ls8c_ard_3-1-0_089086_2019-04-12_final
2019-04-13 09:14:47	ga_ls8c_ard_3-1-0_089087_2019-04-12_final
2019-04-13 09:15:11	ga_ls8c_ard_3-1-0_089088_2019-04-12_final
2019-04-13 09:15:35	ga_ls8c_ard_3-1-0_089089_2019-04-12_final
2019-04-13 09:15:59	ga_ls8c_ard_3-1-0_089090_2019-04-12_final
2019-08-03 09:14:11	ga_ls8c_ard_3-1-0_089084_2019-08-02_final
2019-08-03 09:14:34	ga_ls8c_ard_3-1-0_089085_2019-08-02_final
2019-08-03 09:14:58	ga_ls8c_ard_3-1-0_089086_2019-08-02_final
2019-08-03 09:15:22	ga_ls8c_ard_3-1-0_089087_2019-08-02_final
2019-08-03 09:15:46	ga_ls8c_ard_3-1-0_089088_2019-08-02_final
2019-08-03 09:16:10	ga_ls8c_ard_3-1-0_089089_2019-08-02_final
2019-08-03 09:16:34	ga_ls8c_ard_3-1-0_089090_2019-08-02_final
2019-08-22 09:38:24	ga_ls8c_ard_3-1-0_094067_2019-08-22_final
2019-08-24 09:28:02	ga_ls8c_ard_3-1-0_092072_2019-08-23_final
2019-08-24 09:28:26	ga_ls8c_ard_3-1-0_092073_2019-08-23_final
2019-08-24 09:28:50	ga_ls8c_ard_3-1-0_092074_2019-08-23_final
2019-08-24 09:29:14	ga_ls8c_ard_3-1-0_092075_2019-08-23_final
2019-08-24 09:29:38	ga_ls8c_ard_3-1-0_092076_2019-08-23_final
2019-08-24 09:30:02	ga_ls8c_ard_3-1-0_092077_2019-08-24_final
2019-08-24 09:30:26	ga_ls8c_ard_3-1-0_092078_2019-08-24_final
2019-09-16 09:32:20	ga_ls8c_ard_3-1-0_093067_2019-09-16_final
2019-09-16 09:32:44	ga_ls8c_ard_3-1-0_093068_2019-09-16_final
2019-09-25 09:28:11	ga_ls8c_ard_3-1-0_092072_2019-09-24_final
2019-09-25 09:28:35	ga_ls8c_ard_3-1-0_092073_2019-09-24_final
2019-09-25 09:28:59	ga_ls8c_ard_3-1-0_092074_2019-09-24_final
2019-09-25 09:29:23	ga_ls8c_ard_3-1-0_092075_2019-09-24_final
2019-09-25 09:29:47	ga_ls8c_ard_3-1-0_092076_2019-09-24_final
2019-09-25 09:30:11	ga_ls8c_ard_3-1-0_092077_2019-09-25_final
2019-09-25 09:30:35	ga_ls8c_ard_3-1-0_092078_2019-09-25_final
2019-11-23 09:14:26	ga_ls8c_ard_3-1-0_089084_2019-11-22_final
2019-11-23 09:14:50	ga_ls8c_ard_3-1-0_089085_2019-11-22_final
2019-11-23 09:15:14	ga_ls8c_ard_3-1-0_089086_2019-11-22_final
2019-11-23 09:15:38	ga_ls8c_ard_3-1-0_089087_2019-11-22_final
2019-11-23 09:16:01	ga_ls8c_ard_3-1-0_089088_2019-11-22_final
2019-11-23 09:16:25	ga_ls8c_ard_3-1-0_089089_2019-11-22_final
2019-11-23 09:16:49	ga_ls8c_ard_3-1-0_089090_2019-11-22_final
2019-11-26 09:38:33	ga_ls8c_ard_3-1-0_094067_2019-11-26_final
2022-10-26 09:34:16	ga_ls8c_ard_3-2-1_093071_2022-10-26_final
2022-10-26 09:34:40	ga_ls8c_ard_3-2-1_093072_2022-10-26_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years