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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

67 results

Time (local)	Label
2013-04-26 09:23:50	ga_ls8c_ard_3-0-0_091073_2013-04-25_final
2013-05-20 10:11:57	ga_ls8c_ard_3-0-0_099069_2013-05-20_final
2014-02-02 10:01:49	ga_ls8c_ard_3-0-0_097077_2014-02-02_final
2014-05-23 10:09:49	ga_ls8c_ard_3-0-0_099070_2014-05-23_final
2015-02-14 11:30:04	ga_ls8c_ard_3-0-0_112069_2015-02-14_final
2015-02-19 10:09:44	ga_ls8c_ard_3-0-0_099069_2015-02-19_final
2015-06-19 09:28:10	ga_ls8c_ard_3-0-0_091090_2015-06-18_final
2015-07-21 09:28:27	ga_ls8c_ard_3-0-0_091090_2015-07-20_final
2016-02-12 09:32:01	ga_ls8c_ard_3-0-0_093067_2016-02-12_final
2016-05-21 10:07:44	ga_ls8c_ard_3-0-0_098080_2016-05-21_final
2016-06-29 10:13:21	ga_ls8c_ard_3-0-0_099078_2016-06-29_final
2016-12-10 11:24:47	ga_ls8c_ard_3-0-0_111070_2016-12-10_final
2016-12-24 11:35:53	ga_ls8c_ard_3-0-0_113067_2016-12-24_final
2017-01-16 10:03:30	ga_ls8c_ard_3-0-0_098068_2017-01-16_final
2017-05-31 10:09:07	ga_ls8c_ard_3-0-0_099068_2017-05-31_final
2017-06-22 09:33:23	ga_ls8c_ard_3-0-0_093071_2017-06-22_final
2017-09-20 10:13:16	ga_ls8c_ard_3-0-0_099077_2017-09-20_final
2018-02-07 10:35:42	ga_ls8c_ard_3-0-0_103072_2018-02-07_final
2018-03-08 10:06:59	ga_ls8c_ard_3-0-0_098078_2018-03-08_final
2018-09-14 10:19:19	ga_ls8c_ard_3-0-0_100078_2018-09-14_final
2019-03-11 10:08:57	ga_ls8c_ard_3-1-0_098083_2019-03-11_final
2019-05-21 10:08:46	ga_ls8c_ard_3-0-0_099067_2019-05-21_final
2019-05-27 11:13:49	ga_ls8c_ard_3-0-0_109075_2019-05-27_final
2019-07-10 11:41:58	ga_ls8c_ard_3-1-0_113083_2019-07-10_final
2019-07-27 09:06:45	ga_ls8c_ard_3-1-0_088081_2019-07-26_final
2019-08-04 11:29:57	ga_ls8c_ard_3-1-0_112068_2019-08-04_final
2019-08-25 10:10:06	ga_ls8c_ard_3-1-0_099069_2019-08-25_final
2019-09-10 10:10:34	ga_ls8c_ard_3-1-0_099070_2019-09-10_final
2020-02-29 10:39:24	ga_ls8c_ard_3-1-0_103081_2020-02-29_final
2020-03-26 11:13:53	ga_ls8c_ard_3-1-0_109075_2020-03-26_final
2020-07-10 10:10:10	ga_ls8c_ard_3-1-0_099070_2020-07-10_final
2020-07-26 10:09:51	ga_ls8c_ard_3-1-0_099069_2020-07-26_final
2020-12-11 10:46:58	ga_ls8c_ard_3-1-0_105068_2020-12-11_final
2021-01-23 10:33:48	ga_ls8c_ard_3-2-0_102082_2021-01-23_final
2021-04-03 11:31:14	ga_ls8c_ard_3-2-0_112072_2021-04-03_final
2021-06-08 09:40:01	ga_ls8c_ard_3-2-0_094072_2021-06-08_final
2021-07-28 09:29:05	ga_ls8c_ard_3-2-0_092075_2021-07-27_final
2021-08-11 09:46:20	ga_ls8c_ard_3-2-0_094087_2021-08-11_final
2021-08-14 10:08:52	ga_ls8c_ard_3-2-1_099066_2021-08-14_final
2021-09-03 09:51:50	ga_ls8c_ard_3-2-0_095085_2021-09-03_final
2021-09-30 09:34:36	ga_ls8c_ard_3-2-0_092088_2021-09-30_final
2021-11-17 11:06:17	ga_ls8c_ard_3-2-0_108070_2021-11-17_final
2021-12-04 10:10:17	ga_ls8c_ard_3-2-0_099069_2021-12-04_final
2022-01-22 09:18:05	ga_ls8c_ard_3-2-1_090078_2022-01-21_final
2022-01-22 10:54:10	ga_ls8c_ard_3-2-1_106071_2022-01-22_final
2022-02-16 09:11:47	ga_ls8c_ard_3-2-1_089078_2022-02-15_final
2022-02-28 11:14:09	ga_ls8c_ard_3-2-1_109075_2022-02-28_final
2022-03-04 09:11:20	ga_ls8c_ard_3-2-1_089077_2022-03-03_final
2022-04-25 10:25:40	ga_ls8c_ard_3-2-1_101078_2022-04-25_final
2022-05-18 10:28:48	ga_ls8c_ard_3-2-1_102070_2022-05-18_final
2022-05-29 10:09:28	ga_ls8c_ard_3-2-1_099068_2022-05-29_final
2022-07-16 10:10:33	ga_ls8c_ard_3-2-1_099070_2022-07-16_final
2022-10-13 10:03:03	ga_ls8c_ard_3-2-1_098066_2022-10-13_final
2023-03-12 09:31:02	ga_ls8c_ard_3-2-1_092080_2023-03-12_final
2023-03-21 09:27:33	ga_ls8c_ard_3-2-1_091087_2023-03-20_final
2023-03-29 10:08:32	ga_ls8c_ard_3-2-1_099066_2023-03-29_final
2023-04-15 09:21:26	ga_ls8c_ard_3-2-1_090088_2023-04-14_final
2023-04-24 09:11:38	ga_ls8c_ard_3-2-1_089079_2023-04-23_final
2023-07-07 11:25:45	ga_ls8c_ard_3-2-1_111074_2023-07-07_final
2023-11-12 11:24:39	ga_ls8c_ard_3-2-1_111070_2023-11-12_final
2023-12-08 10:27:58	ga_ls8c_ard_3-2-1_101083_2023-12-08_final
2023-12-10 10:15:15	ga_ls8c_ard_3-2-1_099082_2023-12-10_final
2023-12-27 09:20:53	ga_ls8c_ard_3-2-1_090085_2023-12-26_final
2024-01-17 09:39:21	ga_ls8c_ard_3-2-1_093085_2024-01-17_final
2024-03-01 09:57:08	ga_ls8c_ard_3-2-1_097068_2024-03-01_final
2024-03-16 09:17:19	ga_ls8c_ard_3-2-1_090077_2024-03-15_final
2024-04-16 10:10:15	ga_ls8c_ard_3-2-1_099071_2024-04-16_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