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

57 results

Time (local)	Label
2013-10-04 10:04:50	ga_ls8c_ard_3-0-0_098067_2013-10-04_final
2014-02-25 10:04:52	ga_ls8c_ard_3-0-0_098070_2014-02-25_final
2014-06-08 10:08:48	ga_ls8c_ard_3-0-0_099067_2014-06-08_final
2014-06-21 11:23:37	ga_ls8c_ard_3-0-0_110084_2014-06-21_final
2014-07-05 11:29:41	ga_ls8c_ard_3-0-0_112068_2014-07-05_final
2014-08-27 10:13:12	ga_ls8c_ard_3-0-0_099077_2014-08-27_final
2014-08-31 11:28:58	ga_ls8c_ard_3-0-0_111081_2014-08-31_final
2015-01-29 11:31:25	ga_ls8c_ard_3-0-0_112072_2015-01-29_final
2015-05-30 09:49:29	ga_ls8c_ard_3-0-0_095082_2015-05-30_final
2015-07-21 09:28:27	ga_ls8c_ard_3-0-0_091090_2015-07-20_final
2015-11-15 09:40:20	ga_ls8c_ard_3-0-0_094072_2015-11-15_final
2015-12-21 09:17:14	ga_ls8c_ard_3-0-0_090076_2015-12-20_final
2016-05-12 10:15:03	ga_ls8c_ard_3-0-0_099083_2016-05-12_final
2016-06-07 09:09:48	ga_ls8c_ard_3-0-0_089074_2016-06-06_final
2016-11-08 09:47:08	ga_ls8c_ard_3-0-0_095073_2016-11-08_final
2016-11-20 10:09:04	ga_ls8c_ard_3-2-1_099066_2016-11-20_final
2016-12-26 09:52:14	ga_ls8c_ard_3-0-0_095086_2016-12-26_final
2017-02-07 09:34:14	ga_ls8c_ard_3-0-0_092088_2017-02-07_final
2017-02-11 09:07:29	ga_ls8c_ard_3-0-0_088083_2017-02-10_final
2017-02-22 10:27:47	ga_ls8c_ard_3-0-0_101083_2017-02-22_final
2017-02-25 09:16:59	ga_ls8c_ard_3-0-0_090076_2017-02-24_final
2017-03-03 10:16:45	ga_ls8c_ard_3-0-0_100071_2017-03-03_final
2017-03-11 11:07:43	ga_ls8c_ard_3-0-0_108075_2017-03-11_final
2017-04-13 10:15:23	ga_ls8c_ard_3-0-0_099084_2017-04-13_final
2017-05-02 09:06:00	ga_ls8c_ard_3-1-0_088081_2017-05-01_final
2017-06-15 09:28:22	ga_ls8c_ard_3-0-0_092074_2017-06-14_final
2017-09-10 09:32:10	ga_ls8c_ard_3-0-0_093067_2017-09-10_final
2017-09-20 10:13:40	ga_ls8c_ard_3-0-0_099078_2017-09-20_final
2017-11-19 10:40:04	ga_ls8c_ard_3-0-0_103082_2017-11-19_final
2017-12-01 09:27:01	ga_ls8c_ard_3-0-0_091085_2017-11-30_final
2017-12-31 09:37:00	ga_ls8c_ard_3-0-0_093079_2017-12-31_final
2018-08-05 09:28:00	ga_ls8c_ard_3-0-0_092074_2018-08-04_final
2019-03-08 11:16:33	ga_ls8c_ard_3-1-0_109082_2019-03-08_final
2019-03-13 11:31:04	ga_ls8c_ard_3-1-0_112072_2019-03-13_final
2019-10-07 11:30:15	ga_ls8c_ard_3-1-0_112068_2019-10-07_final
2019-10-16 09:46:24	ga_ls8c_ard_3-1-0_095071_2019-10-16_final
2019-10-22 10:50:12	ga_ls8c_ard_3-1-0_105076_2019-10-22_final
2019-11-02 10:33:39	ga_ls8c_ard_3-1-0_102081_2019-11-02_final
2020-01-20 09:46:10	ga_ls8c_ard_3-1-0_095071_2020-01-20_final
2020-02-10 11:45:28	ga_ls8c_ard_3-1-0_114076_2020-02-10_final
2020-05-22 09:33:17	ga_ls8c_ard_3-1-0_092087_2020-05-22_final
2020-12-04 09:07:53	ga_ls8c_ard_3-1-0_088083_2020-12-03_final
2021-10-11 10:49:25	ga_ls8c_ard_3-2-0_105074_2021-10-11_final
2021-12-20 10:09:03	ga_ls8c_ard_3-2-1_099066_2021-12-20_final
2022-01-05 10:08:59	ga_ls8c_ard_3-2-1_099066_2022-01-05_final
2022-01-16 11:36:04	ga_ls8c_ard_3-2-1_112083_2022-01-16_final
2022-01-20 09:33:39	ga_ls8c_ard_3-2-1_092086_2022-01-20_final
2022-02-07 09:23:13	ga_ls8c_ard_3-2-1_090091_2022-02-06_final
2022-05-14 10:55:30	ga_ls8c_ard_3-2-1_106075_2022-05-14_final
2022-05-15 09:56:42	ga_ls8c_ard_3-2-1_097067_2022-05-15_final
2022-06-08 10:49:06	ga_ls8c_ard_3-2-1_105074_2022-06-08_final
2022-06-24 10:49:14	ga_ls8c_ard_3-2-1_105074_2022-06-24_final
2022-10-12 09:26:59	ga_ls8c_ard_3-2-1_091084_2022-10-11_final
2022-10-26 09:34:16	ga_ls8c_ard_3-2-1_093071_2022-10-26_final
2022-11-10 10:29:28	ga_ls8c_ard_3-2-1_102070_2022-11-10_final
2023-09-06 10:55:09	ga_ls8c_ard_3-2-1_106074_2023-09-06_final
2023-10-13 09:34:13	ga_ls8c_ard_3-2-1_093072_2023-10-13_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