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
2014-10-22 09:27:54	ga_ls8c_ard_3-1-0_091087_2014-10-21_final
2019-03-17 11:07:56	ga_ls8c_ard_3-1-0_108076_2019-03-17_final
2019-04-11 09:23:10	ga_ls8c_ard_3-1-0_091077_2019-04-10_final
2019-04-14 09:52:27	ga_ls8c_ard_3-1-0_096073_2019-04-14_final
2019-06-14 09:24:18	ga_ls8c_ard_3-1-0_091079_2019-06-13_final
2019-06-26 09:47:05	ga_ls8c_ard_3-1-0_095074_2019-06-26_final
2019-06-26 09:51:04	ga_ls8c_ard_3-1-0_095084_2019-06-26_final
2019-06-30 09:24:46	ga_ls8c_ard_3-1-0_091080_2019-06-29_final
2019-07-28 09:50:25	ga_ls8c_ard_3-1-0_095082_2019-07-28_final
2019-07-28 11:28:54	ga_ls8c_ard_3-1-0_111081_2019-07-28_final
2019-08-29 09:51:47	ga_ls8c_ard_3-1-0_095085_2019-08-29_final
2019-09-05 09:57:35	ga_ls8c_ard_3-1-0_096084_2019-09-05_final
2019-09-05 09:57:59	ga_ls8c_ard_3-1-0_096085_2019-09-05_final
2019-09-14 09:51:52	ga_ls8c_ard_3-1-0_095085_2019-09-14_final
2019-10-06 10:52:58	ga_ls8c_ard_3-1-0_105083_2019-10-06_final
2019-10-20 09:26:28	ga_ls8c_ard_3-1-0_091083_2019-10-19_final
2019-10-27 11:10:44	ga_ls8c_ard_3-1-0_108081_2019-10-27_final
2019-11-01 09:51:59	ga_ls8c_ard_3-1-0_095085_2019-11-01_final
2019-11-07 10:47:47	ga_ls8c_ard_3-1-0_105070_2019-11-07_final
2019-11-17 09:50:20	ga_ls8c_ard_3-1-0_095081_2019-11-17_final
2019-11-17 11:29:13	ga_ls8c_ard_3-1-0_111081_2019-11-17_final
2019-11-23 10:52:31	ga_ls8c_ard_3-1-0_105082_2019-11-23_final
2019-11-23 10:52:55	ga_ls8c_ard_3-1-0_105083_2019-11-23_final
2019-11-28 11:10:39	ga_ls8c_ard_3-1-0_108081_2019-11-28_final
2019-12-07 09:25:35	ga_ls8c_ard_3-1-0_091081_2019-12-06_final
2019-12-30 11:09:46	ga_ls8c_ard_3-1-0_108079_2019-12-30_final
2020-01-11 09:56:22	ga_ls8c_ard_3-1-0_096081_2020-01-11_final
2020-01-20 11:29:02	ga_ls8c_ard_3-1-0_111081_2020-01-20_final
2020-01-24 09:26:12	ga_ls8c_ard_3-1-0_091083_2020-01-23_final
2020-01-31 11:07:14	ga_ls8c_ard_3-1-0_108073_2020-01-31_final
2020-01-31 11:10:26	ga_ls8c_ard_3-1-0_108081_2020-01-31_final
2020-02-05 09:50:51	ga_ls8c_ard_3-1-0_095083_2020-02-05_final
2020-02-25 09:25:40	ga_ls8c_ard_3-1-0_091082_2020-02-24_final
2020-02-27 10:50:11	ga_ls8c_ard_3-1-0_105077_2020-02-27_final
2020-03-03 11:09:29	ga_ls8c_ard_3-1-0_108079_2020-03-03_final
2020-03-08 09:50:42	ga_ls8c_ard_3-1-0_095083_2020-03-08_final
2020-03-08 11:26:24	ga_ls8c_ard_3-1-0_111075_2020-03-08_final
2020-03-12 09:25:09	ga_ls8c_ard_3-1-0_091081_2020-03-11_final
2020-03-19 11:09:22	ga_ls8c_ard_3-1-0_108079_2020-03-19_final
2020-03-28 09:25:25	ga_ls8c_ard_3-1-0_091082_2020-03-27_final
2020-03-30 10:47:07	ga_ls8c_ard_3-1-0_105070_2020-03-30_final
2020-03-31 09:52:41	ga_ls8c_ard_3-1-0_096073_2020-03-31_final
2020-04-09 09:47:38	ga_ls8c_ard_3-1-0_095076_2020-04-09_final
2020-04-09 09:50:02	ga_ls8c_ard_3-1-0_095082_2020-04-09_final
2020-04-09 09:52:02	ga_ls8c_ard_3-1-0_095087_2020-04-09_final
2020-05-06 11:05:46	ga_ls8c_ard_3-1-0_108071_2020-05-06_final
2022-03-30 09:51:20	ga_ls8c_ard_3-2-1_095085_2022-03-30_final
2022-04-01 11:17:03	ga_ls8c_ard_3-2-1_109083_2022-04-01_final
2022-04-03 09:25:00	ga_ls8c_ard_3-2-1_091081_2022-04-02_final
2022-04-03 11:05:05	ga_ls8c_ard_3-2-1_107084_2022-04-03_final
2022-04-06 11:35:38	ga_ls8c_ard_3-2-1_112083_2022-04-06_final
2022-04-10 11:06:09	ga_ls8c_ard_3-2-1_108071_2022-04-10_final
2022-04-12 10:55:01	ga_ls8c_ard_3-2-1_106074_2022-04-12_final
2022-04-13 10:00:11	ga_ls8c_ard_3-2-1_097076_2022-04-13_final
2022-04-13 10:00:59	ga_ls8c_ard_3-2-1_097078_2022-04-13_final
2022-04-13 10:01:23	ga_ls8c_ard_3-2-1_097079_2022-04-13_final
2022-04-13 10:03:47	ga_ls8c_ard_3-2-1_097085_2022-04-13_final
2022-04-16 10:32:42	ga_ls8c_ard_3-2-1_102080_2022-04-16_final
2022-04-17 11:12:46	ga_ls8c_ard_3-2-1_109072_2022-04-17_final
2022-04-18 10:20:20	ga_ls8c_ard_3-2-1_100080_2022-04-18_final
2022-04-22 11:35:40	ga_ls8c_ard_3-2-1_112083_2022-04-22_final
2022-04-24 11:22:54	ga_ls8c_ard_3-2-1_110082_2022-04-24_final
2022-04-26 11:05:20	ga_ls8c_ard_3-2-1_108069_2022-04-26_final
2022-04-28 10:54:33	ga_ls8c_ard_3-2-1_106073_2022-04-28_final
2022-04-28 10:54:56	ga_ls8c_ard_3-2-1_106074_2022-04-28_final
2022-04-30 10:45:23	ga_ls8c_ard_3-2-1_104081_2022-04-30_final
2022-05-01 09:46:59	ga_ls8c_ard_3-2-1_095074_2022-05-01_final
2022-05-01 09:51:23	ga_ls8c_ard_3-2-1_095085_2022-05-01_final
2022-05-01 11:29:28	ga_ls8c_ard_3-2-1_111083_2022-05-01_final
2022-05-03 11:11:33	ga_ls8c_ard_3-2-1_109069_2022-05-03_final
2022-05-04 10:18:20	ga_ls8c_ard_3-2-1_100075_2022-05-04_final
2022-05-07 09:12:46	ga_ls8c_ard_3-2-1_089081_2022-05-06_final
2022-05-07 10:46:52	ga_ls8c_ard_3-2-1_105069_2022-05-07_final
2022-05-10 09:45:18	ga_ls8c_ard_3-2-1_094085_2022-05-10_final
2022-05-13 10:15:26	ga_ls8c_ard_3-2-1_099083_2022-05-13_final
2022-05-14 10:53:54	ga_ls8c_ard_3-2-1_106071_2022-05-14_final
2022-05-18 10:29:12	ga_ls8c_ard_3-2-1_102071_2022-05-18_final
2022-05-19 09:38:23	ga_ls8c_ard_3-2-1_093083_2022-05-19_final
2022-05-19 11:12:28	ga_ls8c_ard_3-2-1_109071_2022-05-19_final
2022-05-20 10:20:26	ga_ls8c_ard_3-2-1_100080_2022-05-20_final
2022-05-24 09:56:55	ga_ls8c_ard_3-2-1_096083_2022-05-24_final
2022-05-26 09:41:45	ga_ls8c_ard_3-2-1_094076_2022-05-26_final
2022-05-26 09:43:21	ga_ls8c_ard_3-2-1_094080_2022-05-26_final
2022-05-26 11:22:38	ga_ls8c_ard_3-2-1_110081_2022-05-26_final
2022-05-30 10:54:45	ga_ls8c_ard_3-2-1_106073_2022-05-30_final
2022-05-31 11:40:01	ga_ls8c_ard_3-2-1_113078_2022-05-31_final
2022-06-01 10:41:13	ga_ls8c_ard_3-2-1_104070_2022-06-01_final
2022-06-04 09:36:04	ga_ls8c_ard_3-2-1_093077_2022-06-04_final
2022-06-04 11:14:58	ga_ls8c_ard_3-2-1_109077_2022-06-04_final
2022-06-05 11:58:38	ga_ls8c_ard_3-2-1_116078_2022-06-05_final
2022-06-07 11:45:06	ga_ls8c_ard_3-2-1_114075_2022-06-07_final
2022-06-07 11:46:18	ga_ls8c_ard_3-2-1_114078_2022-06-07_final
2022-06-07 11:46:42	ga_ls8c_ard_3-2-1_114079_2022-06-07_final
2022-06-07 11:47:06	ga_ls8c_ard_3-2-1_114080_2022-06-07_final
2022-06-15 10:55:21	ga_ls8c_ard_3-2-1_106074_2022-06-15_final
2022-06-16 09:58:57	ga_ls8c_ard_3-2-1_097072_2022-06-16_final
2022-06-16 09:59:44	ga_ls8c_ard_3-2-1_097074_2022-06-16_final
2022-06-20 09:36:15	ga_ls8c_ard_3-2-1_093077_2022-06-20_final
2022-06-20 09:36:39	ga_ls8c_ard_3-2-1_093078_2022-06-20_final
2022-06-22 09:23:54	ga_ls8c_ard_3-2-1_091077_2022-06-21_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years