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
2014-05-09 11:37:16	ga_ls8c_ard_3-0-0_113072_2014-05-09_final
2014-10-06 11:05:09	ga_ls8c_ard_3-0-0_107083_2014-10-06_final
2014-11-28 11:18:30	ga_ls8c_ard_3-0-0_110070_2014-11-28_final
2015-01-08 11:11:47	ga_ls8c_ard_3-0-0_109069_2015-01-08_final
2015-02-07 11:24:24	ga_ls8c_ard_3-0-0_111070_2015-02-07_final
2015-06-06 11:30:40	ga_ls8c_ard_3-0-0_112072_2015-06-06_final
2015-12-31 11:30:47	ga_ls8c_ard_3-0-0_112070_2015-12-31_final
2016-02-12 11:11:42	ga_ls8c_ard_3-0-0_109069_2016-02-12_final
2016-07-24 11:47:25	ga_ls8c_ard_3-0-0_114081_2016-07-24_final
2016-08-24 11:05:29	ga_ls8c_ard_3-0-0_107084_2016-08-24_final
2016-10-23 11:24:50	ga_ls8c_ard_3-0-0_111070_2016-10-23_final
2017-03-14 11:37:23	ga_ls8c_ard_3-0-0_113072_2017-03-14_final
2017-04-26 11:17:38	ga_ls8c_ard_3-0-0_110070_2017-04-26_final
2017-05-12 11:17:42	ga_ls8c_ard_3-0-0_110070_2017-05-12_final
2017-09-27 11:58:00	ga_ls8c_ard_3-0-0_116076_2017-09-27_final
2017-10-26 11:25:12	ga_ls8c_ard_3-0-0_111071_2017-10-26_final
2017-11-14 11:57:38	ga_ls8c_ard_3-0-0_116075_2017-11-14_final
2017-11-20 11:18:08	ga_ls8c_ard_3-0-0_110069_2017-11-20_final
2018-02-24 11:23:38	ga_ls8c_ard_3-0-0_110084_2018-02-24_final
2018-03-28 11:17:47	ga_ls8c_ard_3-0-0_110070_2018-03-28_final
2018-04-13 11:17:39	ga_ls8c_ard_3-0-0_110070_2018-04-13_final
2018-07-25 11:25:19	ga_ls8c_ard_3-0-0_111074_2018-07-25_final
2018-10-22 11:18:11	ga_ls8c_ard_3-0-0_110070_2018-10-22_final
2018-11-19 11:47:21	ga_ls8c_ard_3-0-0_114081_2018-11-19_final
2018-12-18 11:17:35	ga_ls8c_ard_3-0-0_109084_2018-12-18_final
2019-01-04 11:57:39	ga_ls8c_ard_3-0-0_116076_2019-01-04_final
2019-02-04 11:11:30	ga_ls8c_ard_3-0-0_109069_2019-02-04_final
2019-02-16 11:37:23	ga_ls8c_ard_3-0-0_113072_2019-02-16_final
2019-03-13 11:30:17	ga_ls8c_ard_3-1-0_112070_2019-03-13_final
2019-04-16 11:17:46	ga_ls8c_ard_3-1-0_110070_2019-04-16_final
2019-06-08 11:40:13	ga_ls8c_ard_3-0-0_113079_2019-06-08_final
2019-10-12 11:53:35	ga_ls8c_ard_3-1-0_115080_2019-10-12_final
2019-11-01 11:24:29	ga_ls8c_ard_3-1-0_111069_2019-11-01_final
2019-11-14 12:31:38	ga_ls8c_ard_3-2-1_122067_2019-11-14_final
2019-12-05 11:12:03	ga_ls8c_ard_3-1-0_109069_2019-12-05_final
2020-04-18 11:17:53	ga_ls8c_ard_3-1-0_110070_2020-04-18_final
2020-04-23 11:37:11	ga_ls8c_ard_3-1-0_113072_2020-04-23_final
2020-05-11 11:23:29	ga_ls8c_ard_3-1-0_111069_2020-05-11_final
2020-05-18 11:30:54	ga_ls8c_ard_3-1-0_112072_2020-05-18_final
2020-06-28 11:24:39	ga_ls8c_ard_3-1-0_111071_2020-06-28_final
2020-07-07 11:18:08	ga_ls8c_ard_3-1-0_110070_2020-07-07_final
2020-07-30 11:24:26	ga_ls8c_ard_3-1-0_111070_2020-07-30_final
2020-08-19 09:21:44	ga_ls8c_ard_3-1-0_091072_2020-08-18_final
2020-09-20 11:05:14	ga_ls8c_ard_3-1-0_107083_2020-09-20_final
2020-09-30 11:37:57	ga_ls8c_ard_3-1-0_113072_2020-09-30_final
2020-10-16 11:37:59	ga_ls8c_ard_3-1-0_113072_2020-10-16_final
2020-11-21 11:12:51	ga_ls8c_ard_3-1-0_109071_2020-11-21_final
2021-01-08 09:34:17	ga_ls8c_ard_3-2-0_093072_2021-01-08_final
2021-01-20 11:37:47	ga_ls8c_ard_3-2-0_113072_2021-01-20_final
2021-02-11 09:22:11	ga_ls8c_ard_3-2-0_091073_2021-02-10_final
2021-03-17 09:15:56	ga_ls8c_ard_3-2-0_089089_2021-03-16_final
2021-04-18 10:49:28	ga_ls8c_ard_3-2-0_105076_2021-04-18_final
2021-05-07 11:20:11	ga_ls8c_ard_3-2-0_110076_2021-05-07_final
2021-07-18 10:33:11	ga_ls8c_ard_3-2-0_102081_2021-07-18_final
2021-08-29 11:10:57	ga_ls8c_ard_3-2-0_108082_2021-08-29_final
2021-10-11 10:49:25	ga_ls8c_ard_3-2-0_105074_2021-10-11_final
2021-11-15 11:18:40	ga_ls8c_ard_3-2-0_110070_2021-11-15_final
2021-12-01 09:46:34	ga_ls8c_ard_3-2-0_094087_2021-12-01_final
2021-12-08 11:24:51	ga_ls8c_ard_3-2-1_111070_2021-12-08_final
2021-12-10 09:34:00	ga_ls8c_ard_3-2-1_093071_2021-12-10_final
2021-12-14 10:49:21	ga_ls8c_ard_3-2-1_105074_2021-12-14_final
2022-01-30 10:08:16	ga_ls8c_ard_3-2-1_098080_2022-01-30_final
2022-02-12 09:39:20	ga_ls8c_ard_3-2-1_093085_2022-02-12_final
2022-02-12 09:40:32	ga_ls8c_ard_3-2-1_093088_2022-02-12_final
2022-02-14 09:28:57	ga_ls8c_ard_3-2-1_091090_2022-02-13_final
2022-03-09 09:27:51	ga_ls8c_ard_3-2-1_092072_2022-03-08_final
2022-03-17 11:57:42	ga_ls8c_ard_3-2-1_116076_2022-03-17_final
2022-03-20 10:49:41	ga_ls8c_ard_3-2-1_105076_2022-03-20_final
2022-03-27 09:22:52	ga_ls8c_ard_3-2-1_090091_2022-03-26_final
2022-04-16 10:33:06	ga_ls8c_ard_3-2-1_102081_2022-04-16_final
2022-04-21 10:49:13	ga_ls8c_ard_3-2-1_105075_2022-04-21_final
2022-05-23 10:49:21	ga_ls8c_ard_3-2-1_105075_2022-05-23_final
2022-06-07 11:47:30	ga_ls8c_ard_3-2-1_114081_2022-06-07_final
2022-06-24 10:49:14	ga_ls8c_ard_3-2-1_105074_2022-06-24_final
2022-08-05 09:52:51	ga_ls8c_ard_3-2-1_095087_2022-08-05_final
2022-08-14 09:46:20	ga_ls8c_ard_3-2-1_094086_2022-08-14_final
2022-09-04 09:57:18	ga_ls8c_ard_3-2-1_097067_2022-09-04_final
2022-09-22 09:46:39	ga_ls8c_ard_3-2-1_095071_2022-09-22_final
2022-09-26 09:29:31	ga_ls8c_ard_3-2-1_091090_2022-09-25_final
2022-10-05 10:56:11	ga_ls8c_ard_3-2-1_106075_2022-10-05_final
2022-10-31 11:32:07	ga_ls8c_ard_3-2-1_112072_2022-10-31_final
2022-11-13 09:22:39	ga_ls8c_ard_3-2-1_091073_2022-11-12_final
2023-06-05 11:23:27	ga_ls8c_ard_3-2-1_111069_2023-06-05_final
2023-06-25 09:28:23	ga_ls8c_ard_3-2-1_091090_2023-06-24_final
2023-07-02 09:27:29	ga_ls8c_ard_3-2-1_092072_2023-07-01_final
2023-09-02 09:40:13	ga_ls8c_ard_3-2-1_094072_2023-09-02_final
2023-09-07 09:56:44	ga_ls8c_ard_3-2-1_097067_2023-09-07_final
2023-09-08 10:42:24	ga_ls8c_ard_3-2-1_104073_2023-09-08_final
2023-09-15 10:49:27	ga_ls8c_ard_3-2-1_105075_2023-09-15_final
2023-10-02 11:31:59	ga_ls8c_ard_3-2-1_112073_2023-10-02_final
2023-10-11 09:46:10	ga_ls8c_ard_3-2-1_095071_2023-10-11_final
2023-10-13 09:40:12	ga_ls8c_ard_3-2-1_093087_2023-10-13_final
2023-10-16 10:09:30	ga_ls8c_ard_3-2-1_098083_2023-10-16_final
2023-10-17 10:49:33	ga_ls8c_ard_3-2-1_105075_2023-10-17_final
2023-11-02 10:52:01	ga_ls8c_ard_3-2-1_105081_2023-11-02_final
2023-11-05 11:24:29	ga_ls8c_ard_3-2-1_110085_2023-11-05_final
2023-11-26 10:04:12	ga_ls8c_ard_3-2-1_097085_2023-11-26_final
2024-01-01 09:34:34	ga_ls8c_ard_3-2-1_093073_2024-01-01_final
2024-02-09 11:24:24	ga_ls8c_ard_3-2-1_110085_2024-02-09_final
2024-02-13 09:17:59	ga_ls8c_ard_3-2-1_090078_2024-02-12_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