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
2014-12-06 10:30:13	ga_ls8c_ard_3-1-0_102073_2014-12-06_final
2015-06-30 09:06:07	ga_ls8c_ard_3-1-0_088081_2015-06-29_final
2016-04-13 09:06:20	ga_ls8c_ard_3-1-0_088081_2016-04-12_final
2016-11-02 10:23:50	ga_ls8c_ard_3-1-0_101072_2016-11-02_final
2017-07-05 09:06:31	ga_ls8c_ard_3-1-0_088081_2017-07-04_final
2018-01-15 10:28:07	ga_ls8c_ard_3-1-0_102068_2018-01-15_final
2018-07-24 09:05:57	ga_ls8c_ard_3-1-0_088081_2018-07-23_final
2019-03-12 10:46:37	ga_ls8c_ard_3-1-0_105069_2019-03-12_final
2019-03-28 10:52:09	ga_ls8c_ard_3-1-0_105083_2019-03-28_final
2019-04-06 09:06:15	ga_ls8c_ard_3-1-0_088081_2019-04-05_final
2019-04-13 10:45:41	ga_ls8c_ard_3-1-0_105067_2019-04-13_final
2019-04-17 10:25:20	ga_ls8c_ard_3-1-0_101078_2019-04-17_final
2019-06-14 09:26:41	ga_ls8c_ard_3-1-0_091085_2019-06-13_final
2019-06-15 10:02:46	ga_ls8c_ard_3-1-0_098067_2019-06-15_final
2019-06-17 09:57:12	ga_ls8c_ard_3-1-0_096084_2019-06-17_final
2019-06-26 11:23:10	ga_ls8c_ard_3-1-0_111067_2019-06-26_final
2019-07-01 10:06:50	ga_ls8c_ard_3-1-0_098077_2019-07-01_final
2019-07-07 11:11:04	ga_ls8c_ard_3-1-0_108083_2019-07-07_final
2019-07-29 10:32:53	ga_ls8c_ard_3-1-0_102080_2019-07-29_final
2019-08-12 09:06:51	ga_ls8c_ard_3-1-0_088081_2019-08-11_final
2019-08-13 11:25:25	ga_ls8c_ard_3-1-0_111072_2019-08-13_final
2019-08-14 10:28:36	ga_ls8c_ard_3-1-0_102069_2019-08-14_final
2019-08-14 10:30:35	ga_ls8c_ard_3-1-0_102074_2019-08-14_final
2019-08-23 10:22:51	ga_ls8c_ard_3-1-0_101070_2019-08-23_final
2019-09-02 09:28:16	ga_ls8c_ard_3-1-0_091088_2019-09-01_final
2019-09-08 10:23:19	ga_ls8c_ard_3-1-0_101071_2019-09-08_final
2019-09-15 10:28:21	ga_ls8c_ard_3-1-0_102068_2019-09-15_final
2019-09-19 10:09:38	ga_ls8c_ard_3-1-0_098083_2019-09-19_final
2019-09-21 11:36:10	ga_ls8c_ard_3-1-0_112083_2019-09-21_final
2019-09-24 10:26:12	ga_ls8c_ard_3-1-0_101078_2019-09-24_final
2019-10-10 10:27:51	ga_ls8c_ard_3-1-0_101082_2019-10-10_final
2019-10-17 10:28:28	ga_ls8c_ard_3-1-0_102068_2019-10-17_final
2019-10-17 10:28:52	ga_ls8c_ard_3-1-0_102069_2019-10-17_final
2019-10-26 10:23:53	ga_ls8c_ard_3-1-0_101072_2019-10-26_final
2019-10-27 11:07:32	ga_ls8c_ard_3-1-0_108073_2019-10-27_final
2019-11-01 09:52:23	ga_ls8c_ard_3-1-0_095086_2019-11-01_final
2019-11-05 09:24:03	ga_ls8c_ard_3-1-0_091077_2019-11-04_final
2019-11-05 09:28:03	ga_ls8c_ard_3-1-0_091087_2019-11-04_final
2019-11-07 10:48:11	ga_ls8c_ard_3-1-0_105071_2019-11-07_final
2019-11-08 11:36:38	ga_ls8c_ard_3-1-0_112084_2019-11-08_final
2019-11-12 11:07:06	ga_ls8c_ard_3-1-0_108072_2019-11-12_final
2019-11-23 10:47:20	ga_ls8c_ard_3-1-0_105069_2019-11-23_final
2019-11-23 10:48:07	ga_ls8c_ard_3-1-0_105071_2019-11-23_final
2019-11-24 09:52:30	ga_ls8c_ard_3-1-0_096071_2019-11-24_final
2019-11-27 10:23:24	ga_ls8c_ard_3-1-0_101071_2019-11-27_final
2019-11-27 10:23:48	ga_ls8c_ard_3-1-0_101072_2019-11-27_final
2019-11-28 11:07:28	ga_ls8c_ard_3-1-0_108073_2019-11-28_final
2019-12-09 10:46:31	ga_ls8c_ard_3-1-0_105067_2019-12-09_final
2019-12-09 10:47:43	ga_ls8c_ard_3-1-0_105070_2019-12-09_final
2019-12-25 10:47:16	ga_ls8c_ard_3-1-0_105069_2019-12-25_final
2019-12-29 10:23:43	ga_ls8c_ard_3-1-0_101072_2019-12-29_final
2019-12-29 10:26:07	ga_ls8c_ard_3-1-0_101078_2019-12-29_final
2020-01-04 09:47:24	ga_ls8c_ard_3-1-0_095074_2020-01-04_final
2020-01-05 10:29:04	ga_ls8c_ard_3-1-0_102070_2020-01-05_final
2020-01-14 10:23:40	ga_ls8c_ard_3-1-0_101072_2020-01-14_final
2020-01-14 10:27:39	ga_ls8c_ard_3-1-0_101082_2020-01-14_final
2020-01-26 10:52:43	ga_ls8c_ard_3-1-0_105083_2020-01-26_final
2020-01-30 10:23:11	ga_ls8c_ard_3-1-0_101071_2020-01-30_final
2020-01-30 10:25:35	ga_ls8c_ard_3-1-0_101077_2020-01-30_final
2020-01-30 10:27:34	ga_ls8c_ard_3-1-0_101082_2020-01-30_final
2020-02-10 10:03:48	ga_ls8c_ard_3-1-0_098069_2020-02-10_final
2020-02-12 11:35:54	ga_ls8c_ard_3-1-0_112083_2020-02-12_final
2020-02-27 10:52:10	ga_ls8c_ard_3-1-0_105082_2020-02-27_final
2020-03-09 10:33:34	ga_ls8c_ard_3-1-0_102082_2020-03-09_final
2020-03-19 11:11:22	ga_ls8c_ard_3-1-0_108084_2020-03-19_final
2020-03-24 11:25:04	ga_ls8c_ard_3-1-0_111072_2020-03-24_final
2020-03-24 11:25:52	ga_ls8c_ard_3-1-0_111074_2020-03-24_final
2020-03-31 11:31:58	ga_ls8c_ard_3-1-0_112074_2020-03-31_final
2020-03-31 11:35:34	ga_ls8c_ard_3-1-0_112083_2020-03-31_final
2020-04-09 09:46:50	ga_ls8c_ard_3-1-0_095074_2020-04-09_final
2020-04-30 10:03:13	ga_ls8c_ard_3-1-0_098069_2020-04-30_final
2022-04-03 09:25:24	ga_ls8c_ard_3-2-1_091082_2022-04-02_final
2022-04-03 11:01:54	ga_ls8c_ard_3-2-1_107076_2022-04-03_final
2022-04-03 11:04:41	ga_ls8c_ard_3-2-1_107083_2022-04-03_final
2022-04-04 10:09:05	ga_ls8c_ard_3-2-1_098083_2022-04-04_final
2022-04-05 09:12:16	ga_ls8c_ard_3-2-1_089080_2022-04-04_final
2022-04-05 10:46:46	ga_ls8c_ard_3-2-1_105069_2022-04-05_final
2022-04-06 09:51:33	ga_ls8c_ard_3-2-1_096070_2022-04-06_final
2022-04-13 11:38:17	ga_ls8c_ard_3-2-1_113074_2022-04-13_final
2022-04-14 10:40:16	ga_ls8c_ard_3-2-1_104068_2022-04-14_final
2022-04-19 09:24:42	ga_ls8c_ard_3-2-1_091080_2022-04-18_final
2022-04-20 10:09:57	ga_ls8c_ard_3-2-1_098085_2022-04-20_final
2022-04-27 10:12:29	ga_ls8c_ard_3-2-1_099076_2022-04-27_final
2022-04-28 10:52:57	ga_ls8c_ard_3-2-1_106069_2022-04-28_final
2022-04-30 09:06:06	ga_ls8c_ard_3-2-1_088080_2022-04-29_final
2022-05-01 11:25:04	ga_ls8c_ard_3-2-1_111072_2022-05-01_final
2022-05-05 09:26:19	ga_ls8c_ard_3-2-1_091084_2022-05-04_final
2022-05-07 09:13:34	ga_ls8c_ard_3-2-1_089083_2022-05-06_final
2022-05-07 10:46:28	ga_ls8c_ard_3-2-1_105068_2022-05-07_final
2022-05-08 09:51:39	ga_ls8c_ard_3-2-1_096070_2022-05-08_final
2022-05-12 11:05:51	ga_ls8c_ard_3-2-1_108070_2022-05-12_final
2022-05-18 10:28:25	ga_ls8c_ard_3-2-1_102069_2022-05-18_final
2022-05-26 09:46:08	ga_ls8c_ard_3-2-1_094087_2022-05-26_final
2022-05-31 10:03:56	ga_ls8c_ard_3-2-1_097085_2022-05-31_final
2022-05-31 11:41:37	ga_ls8c_ard_3-2-1_113082_2022-05-31_final
2022-06-03 10:28:53	ga_ls8c_ard_3-2-1_102070_2022-06-03_final
2022-06-13 09:34:48	ga_ls8c_ard_3-2-1_092089_2022-06-13_final
2022-06-13 11:07:18	ga_ls8c_ard_3-2-1_108073_2022-06-13_final
2022-06-16 09:57:21	ga_ls8c_ard_3-2-1_097068_2022-06-16_final
2022-06-22 09:25:30	ga_ls8c_ard_3-2-1_091081_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