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
2022-05-21 11:02:30	ga_ls8c_ard_3-2-1_107077_2022-05-21_final
2022-05-22 10:05:17	ga_ls8c_ard_3-2-1_098073_2022-05-22_final
2022-05-22 10:10:04	ga_ls8c_ard_3-2-1_098085_2022-05-22_final
2022-05-23 10:48:09	ga_ls8c_ard_3-2-1_105072_2022-05-23_final
2022-05-23 10:51:20	ga_ls8c_ard_3-2-1_105080_2022-05-23_final
2022-06-04 11:12:10	ga_ls8c_ard_3-2-1_109070_2022-06-04_final
2022-06-05 10:18:09	ga_ls8c_ard_3-2-1_100074_2022-06-05_final
2022-06-07 10:06:37	ga_ls8c_ard_3-2-1_098076_2022-06-07_final
2022-06-10 10:39:09	ga_ls8c_ard_3-2-1_103080_2022-06-10_final
2022-06-10 10:39:57	ga_ls8c_ard_3-2-1_103082_2022-06-10_final
2022-06-13 09:30:48	ga_ls8c_ard_3-2-1_092079_2022-06-13_final
2022-06-13 11:06:54	ga_ls8c_ard_3-2-1_108072_2022-06-13_final
2022-06-16 09:59:21	ga_ls8c_ard_3-2-1_097073_2022-06-16_final
2022-06-16 10:04:08	ga_ls8c_ard_3-2-1_097085_2022-06-16_final
2022-06-18 11:29:04	ga_ls8c_ard_3-2-1_111081_2022-06-18_final
2022-06-21 10:18:43	ga_ls8c_ard_3-2-1_100075_2022-06-21_final
2022-06-28 10:26:55	ga_ls8c_ard_3-2-1_101080_2022-06-28_final
2023-01-29 10:30:51	ga_ls8c_ard_3-2-1_102074_2023-01-29_final
2023-02-01 11:04:08	ga_ls8c_ard_3-2-1_107080_2023-02-01_final
2023-02-02 10:08:07	ga_ls8c_ard_3-2-1_098079_2023-02-02_final
2023-02-04 11:35:50	ga_ls8c_ard_3-2-1_112082_2023-02-04_final
2023-02-09 10:13:04	ga_ls8c_ard_3-2-1_099076_2023-02-09_final
2023-02-09 10:15:28	ga_ls8c_ard_3-2-1_099082_2023-02-09_final
2023-02-10 10:57:07	ga_ls8c_ard_3-2-1_106078_2023-02-10_final
2023-02-13 11:29:10	ga_ls8c_ard_3-2-1_111081_2023-02-13_final
2023-02-15 09:38:42	ga_ls8c_ard_3-2-1_093083_2023-02-15_final
2023-02-17 09:24:43	ga_ls8c_ard_3-2-1_091079_2023-02-16_final
2023-02-22 09:45:08	ga_ls8c_ard_3-2-1_094084_2023-02-22_final
2023-03-07 10:47:24	ga_ls8c_ard_3-2-1_105070_2023-03-07_final
2023-03-08 11:31:51	ga_ls8c_ard_3-2-1_112073_2023-03-08_final
2023-03-09 10:36:37	ga_ls8c_ard_3-2-1_103074_2023-03-09_final
2023-03-13 11:51:59	ga_ls8c_ard_3-2-1_115077_2023-03-13_final
2023-03-15 10:03:31	ga_ls8c_ard_3-2-1_097084_2023-03-15_final
2023-03-19 09:35:33	ga_ls8c_ard_3-2-1_093076_2023-03-19_final
2023-03-21 11:00:51	ga_ls8c_ard_3-2-1_107073_2023-03-21_final
2023-03-21 11:03:38	ga_ls8c_ard_3-2-1_107080_2023-03-21_final
2023-03-21 11:05:14	ga_ls8c_ard_3-2-1_107084_2023-03-21_final
2023-03-28 09:29:17	ga_ls8c_ard_3-2-1_092076_2023-03-27_final
2023-03-28 11:10:33	ga_ls8c_ard_3-2-1_108082_2023-03-28_final
2023-03-29 10:12:08	ga_ls8c_ard_3-2-1_099075_2023-03-29_final
2023-04-02 09:50:09	ga_ls8c_ard_3-2-1_095082_2023-04-02_final
2023-04-03 10:29:24	ga_ls8c_ard_3-2-1_102072_2023-04-03_final
2023-04-04 09:35:46	ga_ls8c_ard_3-2-1_093077_2023-04-04_final
2023-04-04 09:38:09	ga_ls8c_ard_3-2-1_093083_2023-04-04_final
2023-04-07 11:44:41	ga_ls8c_ard_3-2-1_114075_2023-04-07_final
2023-04-11 09:44:58	ga_ls8c_ard_3-2-1_094085_2023-04-11_final
2023-04-15 09:17:51	ga_ls8c_ard_3-2-1_090079_2023-04-14_final
2023-04-21 10:19:36	ga_ls8c_ard_3-2-1_100079_2023-04-21_final
2023-04-24 09:14:26	ga_ls8c_ard_3-2-1_089086_2023-04-23_final
2023-04-24 10:47:43	ga_ls8c_ard_3-2-1_105072_2023-04-24_final
2023-04-26 10:38:33	ga_ls8c_ard_3-2-1_103080_2023-04-26_final
2023-04-28 10:22:59	ga_ls8c_ard_3-2-1_101072_2023-04-28_final
2023-05-01 09:20:34	ga_ls8c_ard_3-2-1_090086_2023-04-30_final
2023-05-05 10:28:42	ga_ls8c_ard_3-2-1_102071_2023-05-05_final
2023-05-09 11:45:35	ga_ls8c_ard_3-2-1_114078_2023-05-09_final
2023-05-10 09:12:15	ga_ls8c_ard_3-2-1_089081_2023-05-09_final
2023-05-13 11:18:00	ga_ls8c_ard_3-2-1_110071_2023-05-13_final
2023-05-17 10:53:15	ga_ls8c_ard_3-2-1_106071_2023-05-17_final
2023-05-17 10:54:02	ga_ls8c_ard_3-2-1_106073_2023-05-17_final
2023-05-18 11:40:06	ga_ls8c_ard_3-2-1_113080_2023-05-18_final
2023-05-20 11:24:10	ga_ls8c_ard_3-2-1_111071_2023-05-20_final
2023-05-22 11:11:49	ga_ls8c_ard_3-2-1_109071_2023-05-22_final
2023-05-30 10:22:24	ga_ls8c_ard_3-2-1_101071_2023-05-30_final
2023-06-03 09:58:29	ga_ls8c_ard_3-2-1_097073_2023-06-03_final
2023-06-03 10:00:29	ga_ls8c_ard_3-2-1_097078_2023-06-03_final
2023-06-03 10:02:29	ga_ls8c_ard_3-2-1_097083_2023-06-03_final
2023-06-08 10:19:30	ga_ls8c_ard_3-2-1_100079_2023-06-08_final
2023-06-12 09:52:01	ga_ls8c_ard_3-2-1_096072_2023-06-12_final
2023-06-12 09:52:25	ga_ls8c_ard_3-2-1_096073_2023-06-12_final
2023-06-13 10:34:30	ga_ls8c_ard_3-2-1_103070_2023-06-13_final
2023-07-01 10:25:53	ga_ls8c_ard_3-2-1_101079_2023-07-01_final
2023-07-02 11:10:21	ga_ls8c_ard_3-2-1_108082_2023-07-02_final
2023-07-06 10:40:53	ga_ls8c_ard_3-2-1_104070_2023-07-06_final
2023-07-09 09:34:55	ga_ls8c_ard_3-2-1_093075_2023-07-09_final
2023-07-10 10:17:24	ga_ls8c_ard_3-2-1_100073_2023-07-10_final
2023-07-11 09:25:46	ga_ls8c_ard_3-2-1_091083_2023-07-10_final
2023-07-18 09:29:58	ga_ls8c_ard_3-2-1_092078_2023-07-17_final
2023-07-20 09:19:35	ga_ls8c_ard_3-2-1_090083_2023-07-19_final
2023-07-20 10:53:41	ga_ls8c_ard_3-2-1_106071_2023-07-20_final
2023-07-24 10:30:13	ga_ls8c_ard_3-2-1_102074_2023-07-24_final
2023-07-25 09:35:24	ga_ls8c_ard_3-2-1_093076_2023-07-25_final
2023-07-25 09:38:36	ga_ls8c_ard_3-2-1_093084_2023-07-25_final
2023-07-26 10:17:53	ga_ls8c_ard_3-2-1_100074_2023-07-26_final
2023-07-27 09:24:16	ga_ls8c_ard_3-2-1_091079_2023-07-26_final
2023-08-02 10:22:56	ga_ls8c_ard_3-2-1_101071_2023-08-02_final
2023-08-08 09:47:04	ga_ls8c_ard_3-2-1_095074_2023-08-08_final
2023-08-08 09:47:28	ga_ls8c_ard_3-2-1_095075_2023-08-08_final
2023-08-08 09:51:03	ga_ls8c_ard_3-2-1_095084_2023-08-08_final
2023-08-08 11:28:20	ga_ls8c_ard_3-2-1_111080_2023-08-08_final
2023-08-14 10:46:07	ga_ls8c_ard_3-2-1_105067_2023-08-14_final
2023-08-16 10:34:58	ga_ls8c_ard_3-2-1_103070_2023-08-16_final
2023-08-22 09:58:45	ga_ls8c_ard_3-2-1_097072_2023-08-22_final
2023-08-25 10:29:16	ga_ls8c_ard_3-2-1_102071_2023-08-25_final
2023-08-26 09:34:50	ga_ls8c_ard_3-2-1_093074_2023-08-26_final
2023-08-26 11:16:31	ga_ls8c_ard_3-2-1_109081_2023-08-26_final
2023-08-28 09:26:04	ga_ls8c_ard_3-2-1_091083_2023-08-27_final
2023-09-06 09:20:15	ga_ls8c_ard_3-2-1_090084_2023-09-05_final
2023-09-11 11:16:56	ga_ls8c_ard_3-2-1_109082_2023-09-11_final
2023-09-13 11:03:48	ga_ls8c_ard_3-2-1_107080_2023-09-13_final
2023-09-16 11:35:07	ga_ls8c_ard_3-2-1_112081_2023-09-16_nrt

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