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
2019-04-07 09:47:31	ga_ls8c_ard_3-1-0_095076_2019-04-07_final
2019-04-07 09:48:19	ga_ls8c_ard_3-1-0_095078_2019-04-07_final
2019-07-12 09:48:20	ga_ls8c_ard_3-1-0_095077_2019-07-12_final
2019-07-12 09:48:44	ga_ls8c_ard_3-1-0_095078_2019-07-12_final
2019-08-01 09:27:43	ga_ls8c_ard_3-1-0_091087_2019-07-31_final
2019-08-13 09:48:31	ga_ls8c_ard_3-1-0_095077_2019-08-13_final
2019-08-29 09:48:35	ga_ls8c_ard_3-1-0_095077_2019-08-29_final
2019-08-29 09:48:59	ga_ls8c_ard_3-1-0_095078_2019-08-29_final
2019-09-30 09:49:33	ga_ls8c_ard_3-1-0_095079_2019-09-30_final
2019-11-17 09:48:44	ga_ls8c_ard_3-1-0_095077_2019-11-17_final
2019-12-03 09:48:43	ga_ls8c_ard_3-1-0_095077_2019-12-03_final
2020-01-04 09:51:24	ga_ls8c_ard_3-1-0_095084_2020-01-04_final
2020-01-20 09:49:45	ga_ls8c_ard_3-1-0_095080_2020-01-20_final
2020-02-05 09:47:16	ga_ls8c_ard_3-1-0_095074_2020-02-05_final
2020-02-21 09:48:24	ga_ls8c_ard_3-1-0_095077_2020-02-21_final
2020-03-08 09:48:19	ga_ls8c_ard_3-1-0_095077_2020-03-08_final
2020-04-09 09:48:50	ga_ls8c_ard_3-1-0_095079_2020-04-09_final
2020-04-25 09:48:19	ga_ls8c_ard_3-1-0_095078_2020-04-25_final
2022-04-02 10:17:02	ga_ls8c_ard_3-2-1_100072_2022-04-02_final
2022-04-02 10:19:50	ga_ls8c_ard_3-2-1_100079_2022-04-02_final
2022-04-02 10:20:14	ga_ls8c_ard_3-2-1_100080_2022-04-02_final
2022-04-02 10:20:38	ga_ls8c_ard_3-2-1_100081_2022-04-02_final
2022-04-04 10:07:29	ga_ls8c_ard_3-2-1_098079_2022-04-04_final
2022-04-04 10:08:41	ga_ls8c_ard_3-2-1_098082_2022-04-04_final
2022-04-05 10:50:46	ga_ls8c_ard_3-2-1_105079_2022-04-05_final
2022-04-06 09:54:21	ga_ls8c_ard_3-2-1_096077_2022-04-06_final
2022-04-06 11:34:02	ga_ls8c_ard_3-2-1_112079_2022-04-06_final
2022-04-07 10:34:50	ga_ls8c_ard_3-2-1_103070_2022-04-07_final
2022-04-07 10:36:02	ga_ls8c_ard_3-2-1_103073_2022-04-07_final
2022-04-08 09:43:12	ga_ls8c_ard_3-2-1_094080_2022-04-08_final
2022-04-09 10:23:41	ga_ls8c_ard_3-2-1_101073_2022-04-09_final
2022-04-09 10:25:41	ga_ls8c_ard_3-2-1_101078_2022-04-09_final
2022-04-09 10:26:53	ga_ls8c_ard_3-2-1_101081_2022-04-09_final
2022-04-11 11:51:25	ga_ls8c_ard_3-2-1_115076_2022-04-11_final
2022-04-12 09:19:19	ga_ls8c_ard_3-2-1_090082_2022-04-11_final
2022-04-12 10:53:49	ga_ls8c_ard_3-2-1_106071_2022-04-12_final
2022-04-14 10:41:28	ga_ls8c_ard_3-2-1_104071_2022-04-14_final
2022-04-14 10:43:04	ga_ls8c_ard_3-2-1_104075_2022-04-14_final
2022-04-15 09:49:26	ga_ls8c_ard_3-2-1_095080_2022-04-15_final
2022-04-16 10:29:30	ga_ls8c_ard_3-2-1_102072_2022-04-16_final
2022-04-20 10:07:34	ga_ls8c_ard_3-2-1_098079_2022-04-20_final
2022-04-20 10:07:58	ga_ls8c_ard_3-2-1_098080_2022-04-20_final
2022-04-20 10:08:45	ga_ls8c_ard_3-2-1_098082_2022-04-20_final
2022-04-21 10:47:13	ga_ls8c_ard_3-2-1_105070_2022-04-21_final
2022-04-21 10:50:01	ga_ls8c_ard_3-2-1_105077_2022-04-21_final
2022-04-21 10:50:25	ga_ls8c_ard_3-2-1_105078_2022-04-21_final
2022-04-23 10:36:03	ga_ls8c_ard_3-2-1_103073_2022-04-23_final
2022-04-24 09:42:01	ga_ls8c_ard_3-2-1_094077_2022-04-24_final
2022-04-24 09:45:36	ga_ls8c_ard_3-2-1_094086_2022-04-24_final
2022-04-24 11:22:06	ga_ls8c_ard_3-2-1_110080_2022-04-24_final
2022-04-27 10:11:18	ga_ls8c_ard_3-2-1_099073_2022-04-27_final
2022-04-28 09:20:51	ga_ls8c_ard_3-2-1_090086_2022-04-27_final
2022-04-28 10:53:21	ga_ls8c_ard_3-2-1_106070_2022-04-28_final
2022-04-30 10:42:59	ga_ls8c_ard_3-2-1_104075_2022-04-30_final
2022-05-01 11:28:40	ga_ls8c_ard_3-2-1_111081_2022-05-01_final
2022-05-01 11:29:04	ga_ls8c_ard_3-2-1_111082_2022-05-01_final
2022-05-03 11:15:56	ga_ls8c_ard_3-2-1_109080_2022-05-03_final
2022-05-04 10:17:32	ga_ls8c_ard_3-2-1_100073_2022-05-04_final
2022-05-05 11:00:24	ga_ls8c_ard_3-2-1_107072_2022-05-05_final
2022-05-05 11:05:12	ga_ls8c_ard_3-2-1_107084_2022-05-05_final
2022-05-06 11:46:52	ga_ls8c_ard_3-2-1_114080_2022-05-06_final
2022-05-07 10:47:40	ga_ls8c_ard_3-2-1_105071_2022-05-07_final
2022-05-07 10:48:28	ga_ls8c_ard_3-2-1_105073_2022-05-07_final
2022-05-07 10:50:04	ga_ls8c_ard_3-2-1_105077_2022-05-07_final
2022-05-07 10:50:28	ga_ls8c_ard_3-2-1_105078_2022-05-07_final
2022-05-08 09:54:51	ga_ls8c_ard_3-2-1_096078_2022-05-08_final
2022-05-08 09:55:15	ga_ls8c_ard_3-2-1_096079_2022-05-08_final
2022-05-11 10:26:58	ga_ls8c_ard_3-2-1_101081_2022-05-11_final
2022-05-12 11:08:15	ga_ls8c_ard_3-2-1_108076_2022-05-12_final
2022-05-12 11:09:03	ga_ls8c_ard_3-2-1_108078_2022-05-12_final
2022-05-13 10:11:50	ga_ls8c_ard_3-2-1_099074_2022-05-13_final
2022-05-13 10:12:14	ga_ls8c_ard_3-2-1_099075_2022-05-13_final
2022-05-13 10:14:38	ga_ls8c_ard_3-2-1_099081_2022-05-13_final
2022-05-13 10:15:02	ga_ls8c_ard_3-2-1_099082_2022-05-13_final
2022-05-15 10:00:41	ga_ls8c_ard_3-2-1_097077_2022-05-15_final
2022-05-16 10:41:34	ga_ls8c_ard_3-2-1_104071_2022-05-16_final
2022-05-16 10:44:21	ga_ls8c_ard_3-2-1_104078_2022-05-16_final
2022-05-17 09:46:20	ga_ls8c_ard_3-2-1_095072_2022-05-17_final
2022-05-17 09:48:20	ga_ls8c_ard_3-2-1_095077_2022-05-17_final
2022-05-18 10:28:01	ga_ls8c_ard_3-2-1_102068_2022-05-18_final
2022-05-19 11:12:52	ga_ls8c_ard_3-2-1_109072_2022-05-19_final
2022-05-19 11:16:28	ga_ls8c_ard_3-2-1_109081_2022-05-19_final
2022-05-20 10:18:51	ga_ls8c_ard_3-2-1_100076_2022-05-20_final
2022-05-24 09:52:07	ga_ls8c_ard_3-2-1_096071_2022-05-24_final
2022-05-24 09:55:19	ga_ls8c_ard_3-2-1_096079_2022-05-24_final
2022-05-30 10:53:57	ga_ls8c_ard_3-2-1_106071_2022-05-30_final
2022-05-31 10:00:44	ga_ls8c_ard_3-2-1_097077_2022-05-31_final
2022-06-03 10:29:41	ga_ls8c_ard_3-2-1_102072_2022-06-03_final
2022-06-04 11:16:33	ga_ls8c_ard_3-2-1_109081_2022-06-04_final
2022-06-05 10:20:33	ga_ls8c_ard_3-2-1_100080_2022-06-05_final
2022-06-08 10:50:18	ga_ls8c_ard_3-2-1_105077_2022-06-08_final
2022-06-08 10:50:41	ga_ls8c_ard_3-2-1_105078_2022-06-08_final
2022-06-08 10:51:05	ga_ls8c_ard_3-2-1_105079_2022-06-08_final
2022-06-15 10:57:21	ga_ls8c_ard_3-2-1_106079_2022-06-15_final
2022-06-17 10:41:49	ga_ls8c_ard_3-2-1_104071_2022-06-17_final
2022-06-17 10:43:49	ga_ls8c_ard_3-2-1_104076_2022-06-17_final
2022-06-17 10:44:12	ga_ls8c_ard_3-2-1_104077_2022-06-17_final
2022-06-19 10:29:52	ga_ls8c_ard_3-2-1_102072_2022-06-19_final
2022-06-19 10:33:04	ga_ls8c_ard_3-2-1_102080_2022-06-19_final
2022-06-20 09:37:27	ga_ls8c_ard_3-2-1_093080_2022-06-20_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