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 09:57:23	ga_ls8c_ard_3-1-0_096085_2019-03-13_final
2019-03-22 09:47:11	ga_ls8c_ard_3-1-0_095075_2019-03-22_final
2019-03-26 09:24:50	ga_ls8c_ard_3-1-0_091081_2019-03-25_final
2019-03-26 09:27:14	ga_ls8c_ard_3-1-0_091087_2019-03-25_final
2019-03-28 10:47:46	ga_ls8c_ard_3-1-0_105072_2019-03-28_final
2019-04-02 11:08:41	ga_ls8c_ard_3-1-0_108078_2019-04-02_final
2019-04-07 09:49:06	ga_ls8c_ard_3-1-0_095080_2019-04-07_final
2019-04-11 09:25:10	ga_ls8c_ard_3-1-0_091082_2019-04-10_final
2019-04-13 10:48:05	ga_ls8c_ard_3-1-0_105073_2019-04-13_final
2019-04-13 10:49:41	ga_ls8c_ard_3-1-0_105077_2019-04-13_final
2019-04-18 11:05:23	ga_ls8c_ard_3-1-0_108070_2019-04-18_final
2019-07-07 11:09:04	ga_ls8c_ard_3-1-0_108078_2019-07-07_final
2019-07-18 10:48:33	ga_ls8c_ard_3-1-0_105073_2019-07-18_final
2019-07-19 09:56:32	ga_ls8c_ard_3-1-0_096082_2019-07-19_final
2019-07-28 09:47:37	ga_ls8c_ard_3-1-0_095075_2019-07-28_final
2019-08-01 09:23:44	ga_ls8c_ard_3-1-0_091077_2019-07-31_final
2019-08-08 11:09:14	ga_ls8c_ard_3-1-0_108078_2019-08-08_final
2019-08-17 09:25:01	ga_ls8c_ard_3-1-0_091080_2019-08-16_final
2019-08-19 10:50:45	ga_ls8c_ard_3-1-0_105078_2019-08-19_final
2019-08-24 11:09:19	ga_ls8c_ard_3-1-0_108078_2019-08-24_final
2019-09-02 09:23:29	ga_ls8c_ard_3-1-0_091076_2019-09-01_final
2019-09-02 09:25:52	ga_ls8c_ard_3-1-0_091082_2019-09-01_final
2019-09-02 09:28:40	ga_ls8c_ard_3-1-0_091089_2019-09-01_final
2019-09-04 10:48:49	ga_ls8c_ard_3-1-0_105073_2019-09-04_final
2019-09-09 11:09:22	ga_ls8c_ard_3-1-0_108078_2019-09-09_final
2019-09-25 11:09:28	ga_ls8c_ard_3-1-0_108078_2019-09-25_final
2019-09-30 09:51:56	ga_ls8c_ard_3-1-0_095085_2019-09-30_final
2019-10-11 11:09:31	ga_ls8c_ard_3-1-0_108078_2019-10-11_final
2019-10-11 11:10:43	ga_ls8c_ard_3-1-0_108081_2019-10-11_final
2019-10-22 10:51:48	ga_ls8c_ard_3-1-0_105080_2019-10-22_final
2019-11-05 09:23:40	ga_ls8c_ard_3-1-0_091076_2019-11-04_final
2019-11-12 11:09:30	ga_ls8c_ard_3-1-0_108078_2019-11-12_final
2019-11-23 10:47:20	ga_ls8c_ard_3-1-0_105069_2019-11-23_final
2019-11-28 11:09:28	ga_ls8c_ard_3-1-0_108078_2019-11-28_final
2019-12-03 09:46:43	ga_ls8c_ard_3-1-0_095072_2019-12-03_final
2019-12-07 09:25:59	ga_ls8c_ard_3-1-0_091082_2019-12-06_final
2019-12-07 09:28:23	ga_ls8c_ard_3-1-0_091088_2019-12-06_final
2019-12-09 10:50:31	ga_ls8c_ard_3-1-0_105077_2019-12-09_final
2020-01-11 09:53:34	ga_ls8c_ard_3-1-0_096074_2020-01-11_final
2020-01-11 09:53:58	ga_ls8c_ard_3-1-0_096075_2020-01-11_final
2020-01-24 09:27:48	ga_ls8c_ard_3-1-0_091087_2020-01-23_final
2020-01-31 11:09:14	ga_ls8c_ard_3-1-0_108078_2020-01-31_final
2020-02-11 10:48:15	ga_ls8c_ard_3-1-0_105072_2020-02-11_final
2020-02-12 09:56:37	ga_ls8c_ard_3-1-0_096082_2020-02-12_final
2020-02-16 11:10:22	ga_ls8c_ard_3-1-0_108081_2020-02-16_final
2020-02-25 09:28:51	ga_ls8c_ard_3-1-0_091090_2020-02-24_final
2020-03-14 10:48:28	ga_ls8c_ard_3-1-0_105073_2020-03-14_final
2020-03-14 10:50:04	ga_ls8c_ard_3-1-0_105077_2020-03-14_final
2020-03-14 10:51:16	ga_ls8c_ard_3-1-0_105080_2020-03-14_final
2020-03-15 09:52:03	ga_ls8c_ard_3-1-0_096071_2020-03-15_final
2020-03-15 09:53:14	ga_ls8c_ard_3-1-0_096074_2020-03-15_final
2020-03-19 11:08:58	ga_ls8c_ard_3-1-0_108078_2020-03-19_final
2020-04-04 11:08:48	ga_ls8c_ard_3-1-0_108078_2020-04-04_final
2020-04-25 09:51:07	ga_ls8c_ard_3-1-0_095085_2020-04-25_final
2020-04-29 09:26:45	ga_ls8c_ard_3-1-0_091086_2020-04-28_final
2020-05-02 09:52:02	ga_ls8c_ard_3-1-0_096072_2020-05-02_final
2020-05-06 11:08:33	ga_ls8c_ard_3-1-0_108078_2020-05-06_final
2022-04-01 09:37:22	ga_ls8c_ard_3-2-1_093081_2022-04-01_final
2022-04-03 10:59:30	ga_ls8c_ard_3-2-1_107070_2022-04-03_final
2022-04-04 10:05:53	ga_ls8c_ard_3-2-1_098075_2022-04-04_final
2022-04-05 10:49:58	ga_ls8c_ard_3-2-1_105077_2022-04-05_final
2022-04-11 10:15:20	ga_ls8c_ard_3-2-1_099083_2022-04-11_final
2022-04-14 10:41:52	ga_ls8c_ard_3-2-1_104072_2022-04-14_final
2022-04-15 09:47:26	ga_ls8c_ard_3-2-1_095075_2022-04-15_final
2022-04-18 10:17:08	ga_ls8c_ard_3-2-1_100072_2022-04-18_final
2022-04-20 10:05:10	ga_ls8c_ard_3-2-1_098073_2022-04-20_final
2022-04-20 10:05:58	ga_ls8c_ard_3-2-1_098075_2022-04-20_final
2022-04-24 11:23:18	ga_ls8c_ard_3-2-1_110083_2022-04-24_final
2022-04-27 10:15:41	ga_ls8c_ard_3-2-1_099084_2022-04-27_final
2022-04-29 11:38:36	ga_ls8c_ard_3-2-1_113075_2022-04-29_final
2022-05-05 11:04:24	ga_ls8c_ard_3-2-1_107082_2022-05-05_final
2022-05-06 10:05:12	ga_ls8c_ard_3-2-1_098073_2022-05-06_final
2022-05-06 10:05:35	ga_ls8c_ard_3-2-1_098074_2022-05-06_final
2022-05-07 09:14:22	ga_ls8c_ard_3-2-1_089085_2022-05-06_final
2022-05-07 09:14:46	ga_ls8c_ard_3-2-1_089086_2022-05-06_final
2022-05-08 09:56:27	ga_ls8c_ard_3-2-1_096082_2022-05-08_final
2022-05-08 11:34:56	ga_ls8c_ard_3-2-1_112081_2022-05-08_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 10:55:06	ga_ls8c_ard_3-2-1_106074_2022-05-14_final
2022-05-16 10:41:57	ga_ls8c_ard_3-2-1_104072_2022-05-16_final
2022-05-20 11:57:44	ga_ls8c_ard_3-2-1_116076_2022-05-20_final
2022-05-25 10:34:35	ga_ls8c_ard_3-2-1_103069_2022-05-25_final
2022-05-25 10:37:46	ga_ls8c_ard_3-2-1_103077_2022-05-25_final
2022-05-26 11:20:14	ga_ls8c_ard_3-2-1_110075_2022-05-26_final
2022-05-26 11:23:25	ga_ls8c_ard_3-2-1_110083_2022-05-26_final
2022-05-30 10:56:44	ga_ls8c_ard_3-2-1_106078_2022-05-30_final
2022-06-01 10:42:01	ga_ls8c_ard_3-2-1_104072_2022-06-01_final
2022-06-04 11:13:22	ga_ls8c_ard_3-2-1_109073_2022-06-04_final
2022-06-05 10:18:09	ga_ls8c_ard_3-2-1_100074_2022-06-05_final
2022-06-07 10:05:49	ga_ls8c_ard_3-2-1_098074_2022-06-07_final
2022-06-08 10:52:41	ga_ls8c_ard_3-2-1_105083_2022-06-08_final
2022-06-13 09:34:24	ga_ls8c_ard_3-2-1_092088_2022-06-13_final
2022-06-15 10:56:33	ga_ls8c_ard_3-2-1_106077_2022-06-15_final
2022-06-16 09:58:57	ga_ls8c_ard_3-2-1_097072_2022-06-16_final
2022-06-17 10:40:37	ga_ls8c_ard_3-2-1_104068_2022-06-17_final
2022-06-19 10:30:40	ga_ls8c_ard_3-2-1_102074_2022-06-19_final
2022-06-20 11:17:32	ga_ls8c_ard_3-2-1_109083_2022-06-20_final
2022-06-21 10:19:07	ga_ls8c_ard_3-2-1_100076_2022-06-21_final
2022-06-22 09:25:54	ga_ls8c_ard_3-2-1_091082_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