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
2022-02-02 10:36:23	ga_ls8c_ard_3-2-1_103073_2022-02-02_final
2022-02-03 09:44:45	ga_ls8c_ard_3-2-1_094083_2022-02-03_final
2022-02-17 11:33:07	ga_ls8c_ard_3-2-1_112076_2022-02-17_final
2022-02-20 10:26:18	ga_ls8c_ard_3-2-1_101079_2022-02-20_final
2022-02-28 11:16:08	ga_ls8c_ard_3-2-1_109080_2022-02-28_final
2022-03-05 11:34:16	ga_ls8c_ard_3-2-1_112079_2022-03-05_final
2022-03-07 09:43:01	ga_ls8c_ard_3-2-1_094079_2022-03-07_final
2022-03-09 09:35:02	ga_ls8c_ard_3-2-1_092090_2022-03-09_final
2022-03-13 10:43:35	ga_ls8c_ard_3-2-1_104076_2022-03-13_final
2022-03-14 11:27:14	ga_ls8c_ard_3-2-1_111077_2022-03-14_final
2022-03-16 11:15:39	ga_ls8c_ard_3-2-1_109079_2022-03-16_final
2022-03-22 10:36:30	ga_ls8c_ard_3-2-1_103074_2022-03-22_final
2022-03-23 09:44:27	ga_ls8c_ard_3-2-1_094083_2022-03-23_final
2022-03-28 10:02:55	ga_ls8c_ard_3-2-1_097083_2022-03-28_final
2022-04-03 11:02:42	ga_ls8c_ard_3-2-1_107078_2022-04-03_final
2022-04-04 10:05:29	ga_ls8c_ard_3-2-1_098074_2022-04-04_final
2022-04-07 10:35:14	ga_ls8c_ard_3-2-1_103071_2022-04-07_final
2022-04-08 11:22:06	ga_ls8c_ard_3-2-1_110080_2022-04-08_final
2022-04-13 11:38:41	ga_ls8c_ard_3-2-1_113075_2022-04-13_final
2022-04-14 10:43:51	ga_ls8c_ard_3-2-1_104077_2022-04-14_final
2022-04-20 11:45:15	ga_ls8c_ard_3-2-1_114076_2022-04-20_final
2022-04-24 11:22:06	ga_ls8c_ard_3-2-1_110080_2022-04-24_final
2022-05-01 11:28:16	ga_ls8c_ard_3-2-1_111080_2022-05-01_final
2022-05-03 09:36:39	ga_ls8c_ard_3-2-1_093079_2022-05-03_final
2022-05-10 11:22:11	ga_ls8c_ard_3-2-1_110080_2022-05-10_final
2022-05-23 10:47:45	ga_ls8c_ard_3-2-1_105071_2022-05-23_final
2022-05-24 09:52:07	ga_ls8c_ard_3-2-1_096071_2022-05-24_final
2022-05-24 11:33:00	ga_ls8c_ard_3-2-1_112076_2022-05-24_final
2022-05-27 10:26:36	ga_ls8c_ard_3-2-1_101080_2022-05-27_final
2022-05-29 10:12:40	ga_ls8c_ard_3-2-1_099076_2022-05-29_final
2022-06-04 09:36:04	ga_ls8c_ard_3-2-1_093077_2022-06-04_final
2022-06-06 11:03:02	ga_ls8c_ard_3-2-1_107078_2022-06-06_final
2022-06-10 10:36:46	ga_ls8c_ard_3-2-1_103074_2022-06-10_final
2022-06-16 11:39:25	ga_ls8c_ard_3-2-1_113076_2022-06-16_final
2022-06-17 10:42:13	ga_ls8c_ard_3-2-1_104072_2022-06-17_final
2022-06-20 11:15:56	ga_ls8c_ard_3-2-1_109079_2022-06-20_final
2022-06-27 09:42:03	ga_ls8c_ard_3-2-1_094076_2022-06-27_final
2022-06-27 11:18:33	ga_ls8c_ard_3-2-1_110070_2022-06-27_final
2022-07-02 10:00:36	ga_ls8c_ard_3-2-1_097076_2022-07-02_final
2022-07-03 10:43:52	ga_ls8c_ard_3-2-1_104076_2022-07-03_final
2022-07-04 09:48:15	ga_ls8c_ard_3-2-1_095076_2022-07-04_final
2022-07-06 11:16:22	ga_ls8c_ard_3-2-1_109080_2022-07-06_final
2022-07-08 09:24:19	ga_ls8c_ard_3-2-1_091078_2022-07-07_final
2022-07-11 11:32:54	ga_ls8c_ard_3-2-1_112075_2022-07-11_final
2022-07-16 10:12:32	ga_ls8c_ard_3-2-1_099075_2022-07-16_final
2022-07-19 10:43:05	ga_ls8c_ard_3-2-1_104074_2022-07-19_final
2022-07-19 10:44:17	ga_ls8c_ard_3-2-1_104077_2022-07-19_final
2022-07-25 10:05:41	ga_ls8c_ard_3-2-1_098073_2022-07-25_final
2022-07-26 10:50:58	ga_ls8c_ard_3-2-1_105078_2022-07-26_final
2022-07-28 10:37:02	ga_ls8c_ard_3-2-1_103074_2022-07-28_final
2022-08-01 10:11:57	ga_ls8c_ard_3-2-1_099073_2022-08-01_final
2022-08-07 11:15:48	ga_ls8c_ard_3-2-1_109078_2022-08-07_final
2022-08-09 09:24:34	ga_ls8c_ard_3-2-1_091078_2022-08-08_final
2022-08-10 10:05:50	ga_ls8c_ard_3-2-1_098073_2022-08-10_final
2022-08-10 11:45:55	ga_ls8c_ard_3-2-1_114076_2022-08-10_final
2022-08-12 09:56:41	ga_ls8c_ard_3-2-1_096081_2022-08-12_final
2022-08-16 11:09:16	ga_ls8c_ard_3-2-1_108077_2022-08-16_final
2022-08-16 11:10:52	ga_ls8c_ard_3-2-1_108081_2022-08-16_final
2022-08-21 09:50:08	ga_ls8c_ard_3-2-1_095080_2022-08-21_final
2022-08-25 11:03:30	ga_ls8c_ard_3-2-1_107078_2022-08-25_final
2022-08-27 10:51:32	ga_ls8c_ard_3-2-1_105079_2022-08-27_final
2022-08-28 09:56:19	ga_ls8c_ard_3-2-1_096080_2022-08-28_final
2022-08-31 10:23:13	ga_ls8c_ard_3-2-1_101070_2022-08-31_final
2022-09-01 11:09:16	ga_ls8c_ard_3-2-1_108077_2022-09-01_final
2022-09-04 10:03:41	ga_ls8c_ard_3-2-1_097083_2022-09-04_final
2022-09-05 10:42:34	ga_ls8c_ard_3-2-1_104072_2022-09-05_final
2022-09-11 10:09:08	ga_ls8c_ard_3-2-1_098081_2022-09-11_final
2022-09-21 10:42:40	ga_ls8c_ard_3-2-1_104072_2022-09-21_final
2022-09-21 10:46:16	ga_ls8c_ard_3-2-1_104081_2022-09-21_final
2022-10-07 10:45:00	ga_ls8c_ard_3-2-1_104078_2022-10-07_final
2022-10-14 10:51:29	ga_ls8c_ard_3-2-1_105079_2022-10-14_final
2022-10-15 11:33:34	ga_ls8c_ard_3-2-1_112076_2022-10-15_final
2022-10-17 11:22:02	ga_ls8c_ard_3-2-1_110078_2022-10-17_final
2022-10-31 11:33:42	ga_ls8c_ard_3-2-1_112076_2022-10-31_final
2022-11-03 10:27:19	ga_ls8c_ard_3-2-1_101080_2022-11-03_final
2022-11-07 10:03:23	ga_ls8c_ard_3-2-1_097082_2022-11-07_final
2022-11-15 10:51:33	ga_ls8c_ard_3-2-1_105079_2022-11-15_final
2022-11-23 11:40:11	ga_ls8c_ard_3-2-1_113077_2022-11-23_final
2022-11-24 10:46:10	ga_ls8c_ard_3-2-1_104081_2022-11-24_final
2022-11-30 10:09:06	ga_ls8c_ard_3-2-1_098081_2022-11-30_final
2022-12-02 11:35:13	ga_ls8c_ard_3-2-1_112080_2022-12-02_final
2022-12-05 10:23:15	ga_ls8c_ard_3-2-1_101070_2022-12-05_final
2022-12-11 09:50:07	ga_ls8c_ard_3-2-1_095080_2022-12-11_final
2022-12-12 10:33:22	ga_ls8c_ard_3-2-1_102080_2022-12-12_final
2022-12-26 10:46:01	ga_ls8c_ard_3-2-1_104081_2022-12-26_final
2022-12-29 09:38:27	ga_ls8c_ard_3-2-1_093082_2022-12-29_final
2023-01-09 10:58:46	ga_ls8c_ard_3-2-1_106082_2023-01-09_final
2023-01-10 11:40:25	ga_ls8c_ard_3-2-1_113078_2023-01-10_final
2023-01-19 09:54:04	ga_ls8c_ard_3-2-1_096075_2023-01-19_final
2023-01-21 09:42:56	ga_ls8c_ard_3-2-1_094078_2023-01-21_final
2023-01-30 09:37:13	ga_ls8c_ard_3-2-1_093079_2023-01-30_final
2023-02-06 09:44:59	ga_ls8c_ard_3-2-1_094083_2023-02-06_final
2023-02-06 11:22:16	ga_ls8c_ard_3-2-1_110079_2023-02-06_final
2023-02-11 10:03:28	ga_ls8c_ard_3-2-1_097083_2023-02-11_final
2023-02-13 11:28:46	ga_ls8c_ard_3-2-1_111080_2023-02-13_final
2023-02-23 10:26:23	ga_ls8c_ard_3-2-1_101079_2023-02-23_final
2023-02-27 10:03:13	ga_ls8c_ard_3-2-1_097083_2023-02-27_final
2023-02-28 10:44:29	ga_ls8c_ard_3-2-1_104078_2023-02-28_final
2023-03-02 10:32:31	ga_ls8c_ard_3-2-1_102079_2023-03-02_final
2023-03-08 09:56:09	ga_ls8c_ard_3-2-1_096081_2023-03-08_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