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
2019-03-13 09:52:59	ga_ls8c_ard_3-1-0_096074_2019-03-13_final
2019-03-17 11:05:56	ga_ls8c_ard_3-1-0_108071_2019-03-17_final
2019-04-14 09:52:03	ga_ls8c_ard_3-1-0_096072_2019-04-14_final
2019-06-30 09:21:35	ga_ls8c_ard_3-1-0_091072_2019-06-29_final
2019-06-30 09:24:46	ga_ls8c_ard_3-1-0_091080_2019-06-29_final
2019-06-30 09:26:46	ga_ls8c_ard_3-1-0_091085_2019-06-29_final
2019-07-16 09:26:01	ga_ls8c_ard_3-1-0_091083_2019-07-15_final
2019-08-01 09:24:56	ga_ls8c_ard_3-1-0_091080_2019-07-31_final
2019-08-01 09:27:19	ga_ls8c_ard_3-1-0_091086_2019-07-31_final
2019-08-04 09:52:15	ga_ls8c_ard_3-1-0_096071_2019-08-04_final
2019-09-02 09:25:05	ga_ls8c_ard_3-1-0_091080_2019-09-01_final
2019-10-04 09:25:14	ga_ls8c_ard_3-1-0_091080_2019-10-03_final
2019-11-05 09:28:51	ga_ls8c_ard_3-1-0_091089_2019-11-04_final
2019-11-21 09:27:35	ga_ls8c_ard_3-1-0_091086_2019-11-20_final
2019-11-28 11:08:40	ga_ls8c_ard_3-1-0_108076_2019-11-28_final
2019-12-25 10:51:15	ga_ls8c_ard_3-1-0_105079_2019-12-25_final
2020-01-31 11:08:26	ga_ls8c_ard_3-1-0_108076_2020-01-31_final
2020-02-05 09:46:04	ga_ls8c_ard_3-1-0_095071_2020-02-05_final
2020-02-05 09:46:52	ga_ls8c_ard_3-1-0_095073_2020-02-05_final
2020-02-12 09:53:02	ga_ls8c_ard_3-1-0_096073_2020-02-12_final
2020-03-24 09:45:47	ga_ls8c_ard_3-1-0_095071_2020-03-24_final
2020-03-24 09:48:11	ga_ls8c_ard_3-1-0_095077_2020-03-24_final
2020-03-28 09:27:00	ga_ls8c_ard_3-1-0_091086_2020-03-27_final
2020-04-13 09:27:41	ga_ls8c_ard_3-1-0_091088_2020-04-12_final
2020-04-16 09:52:58	ga_ls8c_ard_3-1-0_096074_2020-04-16_final
2022-03-31 10:31:24	ga_ls8c_ard_3-2-1_102077_2022-03-31_final
2022-03-31 10:31:48	ga_ls8c_ard_3-2-1_102078_2022-03-31_final
2022-04-01 09:34:11	ga_ls8c_ard_3-2-1_093073_2022-04-01_final
2022-04-01 09:35:46	ga_ls8c_ard_3-2-1_093077_2022-04-01_final
2022-04-04 10:03:06	ga_ls8c_ard_3-2-1_098068_2022-04-04_final
2022-04-04 10:05:29	ga_ls8c_ard_3-2-1_098074_2022-04-04_final
2022-04-05 10:46:46	ga_ls8c_ard_3-2-1_105069_2022-04-05_final
2022-04-05 10:47:34	ga_ls8c_ard_3-2-1_105071_2022-04-05_final
2022-04-12 10:53:25	ga_ls8c_ard_3-2-1_106070_2022-04-12_final
2022-04-13 11:39:52	ga_ls8c_ard_3-2-1_113078_2022-04-13_final
2022-04-15 11:28:43	ga_ls8c_ard_3-2-1_111081_2022-04-15_final
2022-04-16 10:31:30	ga_ls8c_ard_3-2-1_102077_2022-04-16_final
2022-04-17 09:35:52	ga_ls8c_ard_3-2-1_093077_2022-04-17_final
2022-04-17 11:11:34	ga_ls8c_ard_3-2-1_109069_2022-04-17_final
2022-04-20 10:05:10	ga_ls8c_ard_3-2-1_098073_2022-04-20_final
2022-04-20 10:06:22	ga_ls8c_ard_3-2-1_098076_2022-04-20_final
2022-04-20 10:07:58	ga_ls8c_ard_3-2-1_098080_2022-04-20_final
2022-04-21 10:47:13	ga_ls8c_ard_3-2-1_105070_2022-04-21_final
2022-04-23 10:39:38	ga_ls8c_ard_3-2-1_103082_2022-04-23_final
2022-04-25 10:26:04	ga_ls8c_ard_3-2-1_101079_2022-04-25_final
2022-04-27 10:14:29	ga_ls8c_ard_3-2-1_099081_2022-04-27_final
2022-04-29 09:59:19	ga_ls8c_ard_3-2-1_097074_2022-04-29_final
2022-04-29 10:01:19	ga_ls8c_ard_3-2-1_097079_2022-04-29_final
2022-04-29 10:03:42	ga_ls8c_ard_3-2-1_097085_2022-04-29_final
2022-04-30 10:45:47	ga_ls8c_ard_3-2-1_104082_2022-04-30_final
2022-05-01 09:46:59	ga_ls8c_ard_3-2-1_095074_2022-05-01_final
2022-05-01 11:25:52	ga_ls8c_ard_3-2-1_111074_2022-05-01_final
2022-05-01 11:29:52	ga_ls8c_ard_3-2-1_111084_2022-05-01_final
2022-05-02 10:31:28	ga_ls8c_ard_3-2-1_102077_2022-05-02_final
2022-05-03 09:34:39	ga_ls8c_ard_3-2-1_093074_2022-05-03_final
2022-05-03 09:35:51	ga_ls8c_ard_3-2-1_093077_2022-05-03_final
2022-05-04 10:17:32	ga_ls8c_ard_3-2-1_100073_2022-05-04_final
2022-05-04 10:18:44	ga_ls8c_ard_3-2-1_100076_2022-05-04_final
2022-05-06 10:05:35	ga_ls8c_ard_3-2-1_098074_2022-05-06_final
2022-05-06 10:06:23	ga_ls8c_ard_3-2-1_098076_2022-05-06_final
2022-05-06 10:08:23	ga_ls8c_ard_3-2-1_098081_2022-05-06_final
2022-05-06 11:46:28	ga_ls8c_ard_3-2-1_114079_2022-05-06_final
2022-05-07 09:14:46	ga_ls8c_ard_3-2-1_089086_2022-05-06_final
2022-05-09 10:39:43	ga_ls8c_ard_3-2-1_103082_2022-05-09_final
2022-05-11 10:25:47	ga_ls8c_ard_3-2-1_101078_2022-05-11_final
2022-05-13 10:13:50	ga_ls8c_ard_3-2-1_099079_2022-05-13_final
2022-05-14 09:16:37	ga_ls8c_ard_3-2-1_090075_2022-05-13_final
2022-05-14 09:20:13	ga_ls8c_ard_3-2-1_090084_2022-05-13_final
2022-05-14 10:53:31	ga_ls8c_ard_3-2-1_106070_2022-05-14_final
2022-05-14 10:58:18	ga_ls8c_ard_3-2-1_106082_2022-05-14_final
2022-05-15 10:03:29	ga_ls8c_ard_3-2-1_097084_2022-05-15_final
2022-05-15 11:38:22	ga_ls8c_ard_3-2-1_113074_2022-05-15_final
2022-05-17 09:46:44	ga_ls8c_ard_3-2-1_095073_2022-05-17_final
2022-05-18 10:33:12	ga_ls8c_ard_3-2-1_102081_2022-05-18_final
2022-05-19 11:11:40	ga_ls8c_ard_3-2-1_109069_2022-05-19_final
2022-05-20 10:21:14	ga_ls8c_ard_3-2-1_100082_2022-05-20_final
2022-05-24 09:56:07	ga_ls8c_ard_3-2-1_096081_2022-05-24_final
2022-05-26 09:40:09	ga_ls8c_ard_3-2-1_094072_2022-05-26_final
2022-05-26 11:23:49	ga_ls8c_ard_3-2-1_110084_2022-05-26_final
2022-05-30 10:53:09	ga_ls8c_ard_3-2-1_106069_2022-05-30_final
2022-05-31 09:58:44	ga_ls8c_ard_3-2-1_097072_2022-05-31_final
2022-05-31 09:59:08	ga_ls8c_ard_3-2-1_097073_2022-05-31_final
2022-06-02 11:29:41	ga_ls8c_ard_3-2-1_111083_2022-06-02_final
2022-06-02 11:30:05	ga_ls8c_ard_3-2-1_111084_2022-06-02_final
2022-06-03 10:32:53	ga_ls8c_ard_3-2-1_102080_2022-06-03_final
2022-06-05 10:21:21	ga_ls8c_ard_3-2-1_100082_2022-06-05_final
2022-06-07 10:05:01	ga_ls8c_ard_3-2-1_098072_2022-06-07_final
2022-06-07 10:08:13	ga_ls8c_ard_3-2-1_098080_2022-06-07_final
2022-06-08 09:14:12	ga_ls8c_ard_3-2-1_089084_2022-06-07_final
2022-06-08 10:46:42	ga_ls8c_ard_3-2-1_105068_2022-06-08_final
2022-06-08 10:47:54	ga_ls8c_ard_3-2-1_105071_2022-06-08_final
2022-06-15 10:53:22	ga_ls8c_ard_3-2-1_106069_2022-06-15_final
2022-06-15 10:53:46	ga_ls8c_ard_3-2-1_106070_2022-06-15_final
2022-06-15 10:58:33	ga_ls8c_ard_3-2-1_106082_2022-06-15_final
2022-06-16 09:58:57	ga_ls8c_ard_3-2-1_097072_2022-06-16_final
2022-06-16 10:03:20	ga_ls8c_ard_3-2-1_097083_2022-06-16_final
2022-06-16 11:38:38	ga_ls8c_ard_3-2-1_113074_2022-06-16_final
2022-06-16 11:40:37	ga_ls8c_ard_3-2-1_113079_2022-06-16_final
2022-06-17 10:46:12	ga_ls8c_ard_3-2-1_104082_2022-06-17_final
2022-06-22 09:24:42	ga_ls8c_ard_3-2-1_091079_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