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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

69 results

Time (local)	Label
2013-10-09 10:29:22	ga_ls8c_ard_3-0-0_101082_2013-10-09_final
2014-07-05 11:29:41	ga_ls8c_ard_3-0-0_112068_2014-07-05_final
2014-07-09 09:33:18	ga_ls8c_ard_3-0-0_092086_2014-07-09_final
2014-08-08 11:23:55	ga_ls8c_ard_3-0-0_110084_2014-08-08_final
2014-10-14 10:14:09	ga_ls8c_ard_3-0-0_099079_2014-10-14_final
2014-12-21 11:25:25	ga_ls8c_ard_3-0-0_111072_2014-12-21_final
2015-01-29 11:29:26	ga_ls8c_ard_3-0-0_112067_2015-01-29_final
2015-06-25 10:26:48	ga_ls8c_ard_3-0-0_101082_2015-06-25_final
2015-08-23 10:03:07	ga_ls8c_ard_3-0-0_098068_2015-08-23_final
2015-11-02 10:13:14	ga_ls8c_ard_3-0-0_099077_2015-11-02_final
2016-03-08 09:28:32	ga_ls8c_ard_3-0-0_092074_2016-03-07_final
2016-05-17 10:32:49	ga_ls8c_ard_3-0-0_102081_2016-05-17_final
2016-07-23 11:04:57	ga_ls8c_ard_3-0-0_107083_2016-07-23_final
2016-08-18 09:57:39	ga_ls8c_ard_3-0-0_097069_2016-08-18_final
2016-08-20 11:25:24	ga_ls8c_ard_3-0-0_111072_2016-08-20_final
2016-11-11 10:20:01	ga_ls8c_ard_3-0-0_100078_2016-11-11_final
2016-11-13 10:09:40	ga_ls8c_ard_3-0-0_098083_2016-11-13_final
2016-11-29 10:02:53	ga_ls8c_ard_3-2-1_098066_2016-11-29_final
2016-12-22 10:08:58	ga_ls8c_ard_3-2-1_099066_2016-12-22_final
2017-04-13 10:12:36	ga_ls8c_ard_3-0-0_099077_2017-04-13_final
2017-05-02 09:06:00	ga_ls8c_ard_3-1-0_088081_2017-05-01_final
2017-10-06 10:09:47	ga_ls8c_ard_3-0-0_099068_2017-10-06_final
2017-11-07 10:13:48	ga_ls8c_ard_3-0-0_099078_2017-11-07_final
2017-11-14 10:19:57	ga_ls8c_ard_3-0-0_100078_2017-11-14_final
2017-12-14 10:28:14	ga_ls8c_ard_3-1-0_102068_2017-12-14_final
2018-04-04 11:23:55	ga_ls8c_ard_3-0-0_111070_2018-04-04_final
2018-06-12 10:06:11	ga_ls8c_ard_3-0-0_098078_2018-06-12_final
2018-08-14 09:21:30	ga_ls8c_ard_3-0-0_091073_2018-08-13_final
2018-10-13 11:23:55	ga_ls8c_ard_3-0-0_111069_2018-10-13_final
2019-03-19 10:52:23	ga_ls8c_ard_3-1-0_106068_2019-03-19_final
2019-04-27 09:27:04	ga_ls8c_ard_3-0-0_091087_2019-04-26_final
2019-05-11 09:39:57	ga_ls8c_ard_3-0-0_093088_2019-05-11_final
2019-08-03 10:49:04	ga_ls8c_ard_3-1-0_105074_2019-08-03_final
2019-10-13 09:17:53	ga_ls8c_ard_3-1-0_090077_2019-10-12_final
2020-05-21 10:26:55	ga_ls8c_ard_3-1-0_101082_2020-05-21_final
2020-06-22 10:27:35	ga_ls8c_ard_3-1-0_101083_2020-06-22_final
2020-07-02 09:28:15	ga_ls8c_ard_3-1-0_091089_2020-07-01_final
2020-07-17 11:57:16	ga_ls8c_ard_3-1-0_116075_2020-07-17_final
2020-08-11 10:16:17	ga_ls8c_ard_3-1-0_099085_2020-08-11_final
2020-08-17 11:14:09	ga_ls8c_ard_3-1-0_109075_2020-08-17_final
2020-09-12 10:14:09	ga_ls8c_ard_3-1-0_099079_2020-09-12_final
2020-09-13 09:16:56	ga_ls8c_ard_3-1-0_090075_2020-09-12_final
2020-09-21 10:07:37	ga_ls8c_ard_3-1-0_098078_2020-09-21_final
2020-12-17 10:13:28	ga_ls8c_ard_3-2-0_099077_2020-12-17_final
2021-01-31 11:18:26	ga_ls8c_ard_3-2-0_110070_2021-01-31_final
2021-02-03 10:13:15	ga_ls8c_ard_3-2-0_099077_2021-02-03_final
2021-04-25 09:17:06	ga_ls8c_ard_3-2-0_090077_2021-04-24_final
2021-07-22 10:07:19	ga_ls8c_ard_3-2-0_098078_2021-07-22_final
2021-09-01 09:57:24	ga_ls8c_ard_3-2-0_097068_2021-09-01_final
2021-11-18 10:16:14	ga_ls8c_ard_3-2-0_099084_2021-11-18_final
2021-11-20 11:38:47	ga_ls8c_ard_3-2-0_113074_2021-11-20_final
2021-12-20 10:13:27	ga_ls8c_ard_3-2-1_099077_2021-12-20_final
2022-02-17 09:58:14	ga_ls8c_ard_3-2-1_096086_2022-02-17_final
2022-05-21 09:22:25	ga_ls8c_ard_3-2-1_091074_2022-05-20_final
2022-06-07 10:03:26	ga_ls8c_ard_3-2-1_098068_2022-06-07_final
2022-07-15 09:34:28	ga_ls8c_ard_3-2-1_092088_2022-07-15_final
2022-09-18 10:10:34	ga_ls8c_ard_3-2-1_099069_2022-09-18_final
2023-04-02 09:46:34	ga_ls8c_ard_3-2-1_095073_2023-04-02_final
2023-04-15 09:21:50	ga_ls8c_ard_3-2-1_090089_2023-04-14_final
2023-05-22 09:33:44	ga_ls8c_ard_3-2-1_093073_2023-05-22_final
2023-10-17 09:10:40	ga_ls8c_ard_3-2-1_089075_2023-10-16_final
2023-12-09 11:08:03	ga_ls8c_ard_3-2-1_108075_2023-12-09_final
2023-12-27 10:52:59	ga_ls8c_ard_3-2-1_106068_2023-12-27_final
2024-01-20 10:03:51	ga_ls8c_ard_3-2-1_098069_2024-01-20_final
2024-01-31 11:24:33	ga_ls8c_ard_3-2-1_111070_2024-01-31_final
2024-02-07 11:32:22	ga_ls8c_ard_3-2-1_112074_2024-02-07_final
2024-02-09 09:40:44	ga_ls8c_ard_3-2-1_094073_2024-02-09_final
2024-02-14 09:57:39	ga_ls8c_ard_3-2-1_097069_2024-02-14_final
2024-04-10 09:12:54	ga_ls8c_ard_3-2-1_089082_2024-04-09_nrt

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