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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

50 results

Time (local)	Label
2014-02-16 10:16:21	ga_ls8c_ard_3-0-0_099083_2014-02-16_final
2014-04-16 11:29:25	ga_ls8c_ard_3-0-0_112067_2014-04-16_final
2014-06-24 10:13:14	ga_ls8c_ard_3-0-0_099078_2014-06-24_final
2015-02-24 10:27:52	ga_ls8c_ard_3-0-0_102068_2015-02-24_final
2015-04-19 11:29:39	ga_ls8c_ard_3-0-0_112069_2015-04-19_final
2015-04-26 11:37:45	ga_ls8c_ard_3-0-0_113074_2015-04-26_final
2015-06-11 11:50:27	ga_ls8c_ard_3-0-0_115075_2015-06-11_final
2015-10-17 10:10:20	ga_ls8c_ard_3-0-0_099070_2015-10-17_final
2015-10-28 11:29:34	ga_ls8c_ard_3-0-0_112067_2015-10-28_final
2016-01-15 09:10:12	ga_ls8c_ard_3-0-0_089074_2016-01-14_final
2016-02-17 09:50:30	ga_ls8c_ard_3-0-0_096067_2016-02-17_final
2016-03-31 09:33:42	ga_ls8c_ard_3-0-0_093072_2016-03-31_final
2016-05-20 09:21:40	ga_ls8c_ard_3-0-0_091073_2016-05-19_final
2016-06-10 11:23:35	ga_ls8c_ard_3-0-0_110084_2016-06-10_final
2016-11-05 09:17:26	ga_ls8c_ard_3-0-0_090076_2016-11-04_final
2016-12-19 09:38:29	ga_ls8c_ard_3-0-0_094067_2016-12-19_final
2017-03-09 11:22:29	ga_ls8c_ard_3-0-0_110081_2017-03-09_final
2017-09-14 09:11:49	ga_ls8c_ard_3-0-0_089078_2017-09-13_final
2018-02-28 10:58:05	ga_ls8c_ard_3-0-0_106082_2018-02-28_final
2018-04-18 09:56:03	ga_ls8c_ard_3-0-0_097067_2018-04-18_final
2018-06-29 09:15:09	ga_ls8c_ard_3-0-0_089089_2018-06-28_final
2018-09-13 11:13:20	ga_ls8c_ard_3-0-0_109074_2018-09-13_final
2019-09-20 09:10:25	ga_ls8c_ard_3-1-0_089074_2019-09-19_final
2020-04-20 11:07:30	ga_ls8c_ard_3-1-0_108075_2020-04-20_final
2020-09-06 09:10:43	ga_ls8c_ard_3-1-0_089075_2020-09-05_final
2020-09-30 11:42:45	ga_ls8c_ard_3-1-0_113084_2020-09-30_final
2021-04-08 10:10:28	ga_ls8c_ard_3-2-0_099071_2021-04-08_final
2021-04-17 10:09:25	ga_ls8c_ard_3-2-0_098084_2021-04-17_final
2021-06-15 11:25:55	ga_ls8c_ard_3-2-0_111074_2021-06-15_final
2021-08-03 10:33:44	ga_ls8c_ard_3-2-0_102082_2021-08-03_final
2021-08-11 09:40:21	ga_ls8c_ard_3-2-0_094072_2021-08-11_final
2021-11-09 10:21:41	ga_ls8c_ard_3-2-0_100082_2021-11-09_final
2021-12-27 10:19:59	ga_ls8c_ard_3-2-1_100078_2021-12-27_final
2022-01-11 11:13:58	ga_ls8c_ard_3-2-1_109074_2022-01-11_final
2022-02-21 09:28:41	ga_ls8c_ard_3-2-1_092074_2022-02-20_final
2022-10-12 11:05:28	ga_ls8c_ard_3-2-1_107083_2022-10-12_final
2023-01-09 09:17:29	ga_ls8c_ard_3-2-1_090076_2023-01-08_final
2023-01-14 11:12:04	ga_ls8c_ard_3-2-1_109069_2023-01-14_final
2023-01-15 10:17:37	ga_ls8c_ard_3-2-1_100072_2023-01-15_final
2023-05-02 09:56:38	ga_ls8c_ard_3-2-1_097068_2023-05-02_final
2023-06-01 10:14:49	ga_ls8c_ard_3-2-1_099083_2023-06-01_final
2023-07-10 10:19:23	ga_ls8c_ard_3-2-1_100078_2023-07-10_final
2023-07-15 10:39:32	ga_ls8c_ard_3-2-1_103082_2023-07-15_final
2023-08-28 09:27:16	ga_ls8c_ard_3-2-1_091086_2023-08-27_final
2023-08-31 09:56:58	ga_ls8c_ard_3-2-1_096083_2023-08-31_final
2023-10-18 09:52:20	ga_ls8c_ard_3-2-1_096071_2023-10-18_final
2023-12-25 11:07:45	ga_ls8c_ard_3-2-1_108074_2023-12-25_final
2023-12-25 11:08:09	ga_ls8c_ard_3-2-1_108075_2023-12-25_final
2023-12-30 11:24:15	ga_ls8c_ard_3-2-1_111069_2023-12-30_final
2024-03-16 10:53:00	ga_ls8c_ard_3-2-1_106069_2024-03-16_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