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
2021-12-30 10:51:39	ga_ls8c_ard_3-2-1_105080_2021-12-30_final
2022-01-02 11:23:45	ga_ls8c_ard_3-2-1_110083_2022-01-02_final
2022-01-06 09:20:08	ga_ls8c_ard_3-2-1_090083_2022-01-05_final
2022-01-06 10:57:49	ga_ls8c_ard_3-2-1_106080_2022-01-06_final
2022-01-07 11:40:17	ga_ls8c_ard_3-2-1_113078_2022-01-07_final
2022-01-13 09:25:54	ga_ls8c_ard_3-2-1_091082_2022-01-12_final
2022-01-16 11:34:53	ga_ls8c_ard_3-2-1_112080_2022-01-16_final
2022-01-20 09:32:03	ga_ls8c_ard_3-2-1_092082_2022-01-20_final
2022-01-23 10:01:44	ga_ls8c_ard_3-2-1_097079_2022-01-23_final
2022-01-24 10:42:11	ga_ls8c_ard_3-2-1_104072_2022-01-24_final
2022-01-29 09:25:49	ga_ls8c_ard_3-2-1_091082_2022-01-28_final
2022-02-01 11:35:12	ga_ls8c_ard_3-2-1_112081_2022-02-01_final
2022-02-03 11:22:26	ga_ls8c_ard_3-2-1_110080_2022-02-03_final
2022-02-05 09:29:35	ga_ls8c_ard_3-2-1_092076_2022-02-04_final
2022-02-08 11:40:10	ga_ls8c_ard_3-2-1_113078_2022-02-08_final
2022-02-09 10:45:20	ga_ls8c_ard_3-2-1_104080_2022-02-09_final
2022-02-11 10:31:22	ga_ls8c_ard_3-2-1_102076_2022-02-11_final
2022-02-12 11:16:37	ga_ls8c_ard_3-2-1_109081_2022-02-12_final
2022-02-20 10:26:18	ga_ls8c_ard_3-2-1_101079_2022-02-20_final
2022-02-21 09:30:41	ga_ls8c_ard_3-2-1_092079_2022-02-21_final
2022-02-21 09:33:29	ga_ls8c_ard_3-2-1_092086_2022-02-21_final
2022-02-24 11:40:04	ga_ls8c_ard_3-2-1_113078_2022-02-24_final
2022-03-02 11:03:23	ga_ls8c_ard_3-2-1_107079_2022-03-02_final
2022-03-04 10:50:13	ga_ls8c_ard_3-2-1_105077_2022-03-04_final
2022-03-07 09:43:49	ga_ls8c_ard_3-2-1_094081_2022-03-07_final
2022-03-07 09:45:01	ga_ls8c_ard_3-2-1_094084_2022-03-07_final
2022-03-13 10:41:35	ga_ls8c_ard_3-2-1_104071_2022-03-13_final
2022-03-13 10:41:59	ga_ls8c_ard_3-2-1_104072_2022-03-13_final
2022-03-17 10:18:25	ga_ls8c_ard_3-2-1_100075_2022-03-17_final
2022-03-25 11:08:09	ga_ls8c_ard_3-2-1_108076_2022-03-25_final
2022-03-28 11:39:48	ga_ls8c_ard_3-2-1_113078_2022-03-28_final
2022-03-30 11:27:01	ga_ls8c_ard_3-2-1_111077_2022-03-30_final
2022-04-01 09:37:22	ga_ls8c_ard_3-2-1_093081_2022-04-01_final
2022-04-05 10:49:58	ga_ls8c_ard_3-2-1_105077_2022-04-05_final
2022-04-07 10:39:37	ga_ls8c_ard_3-2-1_103082_2022-04-07_final
2022-04-09 10:24:29	ga_ls8c_ard_3-2-1_101075_2022-04-09_final
2022-04-10 11:11:21	ga_ls8c_ard_3-2-1_108084_2022-04-10_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
2022-04-17 09:35:28	ga_ls8c_ard_3-2-1_093076_2022-04-17_final
2022-04-20 11:46:27	ga_ls8c_ard_3-2-1_114079_2022-04-20_final
2022-04-23 10:35:15	ga_ls8c_ard_3-2-1_103071_2022-04-23_final
2022-04-26 09:34:50	ga_ls8c_ard_3-2-1_092090_2022-04-26_final
2022-04-26 11:05:20	ga_ls8c_ard_3-2-1_108069_2022-04-26_final
2022-05-03 09:39:03	ga_ls8c_ard_3-2-1_093085_2022-05-03_final
2022-05-06 11:46:28	ga_ls8c_ard_3-2-1_114079_2022-05-06_final
2022-05-09 10:36:07	ga_ls8c_ard_3-2-1_103073_2022-05-09_final
2022-05-12 11:05:27	ga_ls8c_ard_3-2-1_108069_2022-05-12_final
2022-05-20 10:17:39	ga_ls8c_ard_3-2-1_100073_2022-05-20_final
2022-05-26 11:22:38	ga_ls8c_ard_3-2-1_110081_2022-05-26_final
2022-05-31 11:40:01	ga_ls8c_ard_3-2-1_113078_2022-05-31_final
2022-06-02 11:28:53	ga_ls8c_ard_3-2-1_111081_2022-06-02_final
2022-06-07 11:46:42	ga_ls8c_ard_3-2-1_114079_2022-06-07_final
2022-06-10 10:38:21	ga_ls8c_ard_3-2-1_103078_2022-06-10_final
2022-06-12 10:25:13	ga_ls8c_ard_3-2-1_101076_2022-06-12_final
2022-06-12 10:27:13	ga_ls8c_ard_3-2-1_101081_2022-06-12_final
2022-06-18 09:50:35	ga_ls8c_ard_3-2-1_095082_2022-06-18_final
2022-06-20 11:13:08	ga_ls8c_ard_3-2-1_109072_2022-06-20_final
2022-06-29 11:10:59	ga_ls8c_ard_3-2-1_108082_2022-06-29_final
2022-07-05 10:33:54	ga_ls8c_ard_3-2-1_102082_2022-07-05_final
2022-07-09 10:06:23	ga_ls8c_ard_3-2-1_098075_2022-07-09_final
2022-07-10 10:47:39	ga_ls8c_ard_3-2-1_105070_2022-07-10_final
2022-07-11 09:53:13	ga_ls8c_ard_3-2-1_096073_2022-07-11_final
2022-07-12 10:38:04	ga_ls8c_ard_3-2-1_103077_2022-07-12_final
2022-07-14 10:27:18	ga_ls8c_ard_3-2-1_101081_2022-07-14_final
2022-07-20 11:27:10	ga_ls8c_ard_3-2-1_111076_2022-07-20_final
2022-08-03 10:03:36	ga_ls8c_ard_3-2-1_097083_2022-08-03_final
2022-08-12 09:53:53	ga_ls8c_ard_3-2-1_096074_2022-08-12_final
2022-08-13 10:35:34	ga_ls8c_ard_3-2-1_103070_2022-08-13_final
2022-08-13 10:37:09	ga_ls8c_ard_3-2-1_103074_2022-08-13_final
2022-08-16 09:32:47	ga_ls8c_ard_3-2-1_092083_2022-08-16_final
2022-08-18 09:18:50	ga_ls8c_ard_3-2-1_090079_2022-08-17_final
2022-08-18 09:20:01	ga_ls8c_ard_3-2-1_090082_2022-08-17_final
2022-08-19 10:03:41	ga_ls8c_ard_3-2-1_097083_2022-08-19_final
2022-11-24 10:44:58	ga_ls8c_ard_3-2-1_104078_2022-11-24_final
2022-12-05 10:26:50	ga_ls8c_ard_3-2-1_101079_2022-12-05_final
2022-12-07 10:12:52	ga_ls8c_ard_3-2-1_099075_2022-12-07_final
2022-12-08 09:19:14	ga_ls8c_ard_3-2-1_090080_2022-12-07_final
2022-12-11 11:30:12	ga_ls8c_ard_3-2-1_111083_2022-12-11_final
2023-01-19 09:55:16	ga_ls8c_ard_3-2-1_096078_2023-01-19_final
2023-01-19 09:56:28	ga_ls8c_ard_3-2-1_096081_2023-01-19_final
2023-01-20 10:36:57	ga_ls8c_ard_3-2-1_103074_2023-01-20_final
2023-01-22 10:27:25	ga_ls8c_ard_3-2-1_101081_2023-01-22_final
2023-01-23 11:09:53	ga_ls8c_ard_3-2-1_108079_2023-01-23_final
2023-01-29 10:31:15	ga_ls8c_ard_3-2-1_102075_2023-01-29_final
2023-02-06 11:22:40	ga_ls8c_ard_3-2-1_110080_2023-02-06_final
2023-02-08 11:11:29	ga_ls8c_ard_3-2-1_108083_2023-02-08_final
2023-02-10 10:57:31	ga_ls8c_ard_3-2-1_106079_2023-02-10_final
2023-02-11 11:39:58	ga_ls8c_ard_3-2-1_113077_2023-02-11_final
2023-02-14 10:31:32	ga_ls8c_ard_3-2-1_102076_2023-02-14_final
2023-02-15 11:15:35	ga_ls8c_ard_3-2-1_109078_2023-02-15_final
2023-02-26 09:19:57	ga_ls8c_ard_3-2-1_090083_2023-02-25_final
2023-02-26 10:57:14	ga_ls8c_ard_3-2-1_106079_2023-02-26_final
2023-02-27 11:38:54	ga_ls8c_ard_3-2-1_113075_2023-02-27_final
2023-02-28 10:41:17	ga_ls8c_ard_3-2-1_104070_2023-02-28_final
2023-02-28 10:43:41	ga_ls8c_ard_3-2-1_104076_2023-02-28_final
2023-03-01 11:26:32	ga_ls8c_ard_3-2-1_111075_2023-03-01_final
2023-03-01 11:29:44	ga_ls8c_ard_3-2-1_111083_2023-03-01_final
2023-03-03 09:38:05	ga_ls8c_ard_3-2-1_093082_2023-03-03_final
2023-03-06 10:06:09	ga_ls8c_ard_3-2-1_098075_2023-03-06_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