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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

63 results

Time (local)	Label
2013-06-01 10:36:18	ga_ls8c_ard_3-0-0_103068_2013-06-01_final
2013-07-13 11:15:43	ga_ls8c_ard_3-0-0_109074_2013-07-13_final
2013-11-23 09:59:45	ga_ls8c_ard_3-0-0_096086_2013-11-23_final
2013-12-06 09:28:29	ga_ls8c_ard_3-0-0_091085_2013-12-05_final
2014-02-18 10:04:46	ga_ls8c_ard_3-0-0_097085_2014-02-18_final
2014-03-04 10:14:05	ga_ls8c_ard_3-0-0_099078_2014-03-04_final
2014-04-14 11:47:01	ga_ls8c_ard_3-0-0_114080_2014-04-14_final
2014-05-20 09:39:44	ga_ls8c_ard_3-0-0_094072_2014-05-20_final
2014-08-17 09:39:18	ga_ls8c_ard_3-1-0_093085_2014-08-17_final
2015-02-04 09:17:26	ga_ls8c_ard_3-0-0_090077_2015-02-03_final
2015-09-25 09:13:18	ga_ls8c_ard_3-0-0_089082_2015-09-24_final
2015-11-24 11:14:16	ga_ls8c_ard_3-1-0_109075_2015-11-24_final
2016-01-15 09:14:36	ga_ls8c_ard_3-0-0_089085_2016-01-14_final
2016-02-10 11:25:41	ga_ls8c_ard_3-0-0_111073_2016-02-10_final
2016-02-13 10:17:16	ga_ls8c_ard_3-0-0_100072_2016-02-13_final
2016-08-16 10:10:00	ga_ls8c_ard_3-0-0_099069_2016-08-16_final
2016-09-10 10:07:33	ga_ls8c_ard_3-0-0_098078_2016-09-10_final
2016-11-24 09:44:45	ga_ls8c_ard_3-0-0_095067_2016-11-24_final
2016-12-05 09:34:34	ga_ls8c_ard_3-0-0_092088_2016-12-05_final
2017-01-11 11:26:40	ga_ls8c_ard_3-0-0_111075_2017-01-11_final
2017-02-12 11:23:15	ga_ls8c_ard_3-0-0_111067_2017-02-12_final
2017-05-09 09:11:28	ga_ls8c_ard_3-0-0_089079_2017-05-08_final
2017-10-31 11:46:07	ga_ls8c_ard_3-0-0_114077_2017-10-31_final
2017-11-18 11:32:30	ga_ls8c_ard_3-0-0_112074_2017-11-18_final
2017-11-23 10:10:55	ga_ls8c_ard_3-0-0_099071_2017-11-23_final
2017-12-02 11:45:10	ga_ls8c_ard_3-0-0_114075_2017-12-02_final
2017-12-04 09:58:19	ga_ls8c_ard_3-0-0_096086_2017-12-04_final
2018-04-13 11:16:27	ga_ls8c_ard_3-0-0_110067_2018-04-13_final
2018-06-02 11:07:08	ga_ls8c_ard_3-0-0_108076_2018-06-02_final
2018-06-19 10:14:27	ga_ls8c_ard_3-0-0_099083_2018-06-19_final
2018-06-30 11:31:19	ga_ls8c_ard_3-0-0_112074_2018-06-30_final
2018-07-06 09:17:24	ga_ls8c_ard_3-0-0_090079_2018-07-05_final
2018-10-06 11:23:40	ga_ls8c_ard_3-0-0_110084_2018-10-06_final
2018-12-11 11:11:01	ga_ls8c_ard_3-0-0_108083_2018-12-11_final
2019-01-07 09:14:22	ga_ls8c_ard_3-0-0_089085_2019-01-06_final
2019-04-10 10:16:24	ga_ls8c_ard_3-1-0_100071_2019-04-10_final
2019-05-04 11:09:47	ga_ls8c_ard_3-0-0_108081_2019-05-04_final
2019-09-18 11:00:04	ga_ls8c_ard_3-1-0_107070_2019-09-18_final
2019-09-20 09:14:25	ga_ls8c_ard_3-1-0_089084_2019-09-19_final
2019-11-24 11:30:59	ga_ls8c_ard_3-1-0_112070_2019-11-24_final
2020-01-23 10:17:51	ga_ls8c_ard_3-1-0_100073_2020-01-23_final
2020-02-10 10:04:36	ga_ls8c_ard_3-1-0_098071_2020-02-10_final
2020-07-17 11:58:28	ga_ls8c_ard_3-1-0_116078_2020-07-17_final
2020-07-21 11:29:23	ga_ls8c_ard_3-1-0_112067_2020-07-21_final
2020-07-30 09:46:45	ga_ls8c_ard_3-1-0_095073_2020-07-30_final
2020-08-13 09:57:33	ga_ls8c_ard_3-1-0_097069_2020-08-13_final
2020-10-02 11:24:24	ga_ls8c_ard_3-1-0_111069_2020-10-02_final
2020-10-11 09:46:32	ga_ls8c_ard_3-1-0_094087_2020-10-11_final
2020-12-23 11:18:02	ga_ls8c_ard_3-2-0_109084_2020-12-23_final
2021-01-18 10:16:04	ga_ls8c_ard_3-2-0_099084_2021-01-18_final
2021-08-14 10:10:04	ga_ls8c_ard_3-2-0_099069_2021-08-14_final
2021-08-15 10:52:56	ga_ls8c_ard_3-2-0_106068_2021-08-15_final
2021-11-29 09:57:44	ga_ls8c_ard_3-2-0_096084_2021-11-29_final
2021-12-30 10:49:15	ga_ls8c_ard_3-2-1_105074_2021-12-30_final
2022-01-23 09:58:08	ga_ls8c_ard_3-2-1_097070_2022-01-23_final
2022-01-25 11:27:02	ga_ls8c_ard_3-2-1_111076_2022-01-25_final
2022-04-14 09:07:22	ga_ls8c_ard_3-2-1_088083_2022-04-13_final
2022-05-15 11:41:58	ga_ls8c_ard_3-2-1_113083_2022-05-15_final
2022-06-05 10:16:57	ga_ls8c_ard_3-2-1_100071_2022-06-05_final
2022-12-04 09:40:47	ga_ls8c_ard_3-2-1_094072_2022-12-04_final
2023-01-16 11:00:28	ga_ls8c_ard_3-2-1_107071_2023-01-16_final
2023-09-02 11:19:30	ga_ls8c_ard_3-2-1_110073_2023-09-02_final
2023-10-09 11:38:36	ga_ls8c_ard_3-2-1_113074_2023-10-09_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