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
2022-01-14 10:05:34	ga_ls8c_ard_3-2-1_098073_2022-01-14_final
2022-01-14 10:05:58	ga_ls8c_ard_3-2-1_098074_2022-01-14_final
2022-01-14 10:09:10	ga_ls8c_ard_3-2-1_098082_2022-01-14_final
2023-02-02 10:06:07	ga_ls8c_ard_3-2-1_098074_2023-02-02_final
2023-02-02 10:08:55	ga_ls8c_ard_3-2-1_098081_2023-02-02_final
2023-02-04 09:56:09	ga_ls8c_ard_3-2-1_096080_2023-02-04_final
2023-02-04 09:56:57	ga_ls8c_ard_3-2-1_096082_2023-02-04_final
2023-03-15 09:59:55	ga_ls8c_ard_3-2-1_097075_2023-03-15_final
2023-03-16 10:40:47	ga_ls8c_ard_3-2-1_104069_2023-03-16_final
2023-03-21 11:02:50	ga_ls8c_ard_3-2-1_107078_2023-03-21_final
2023-03-24 09:56:00	ga_ls8c_ard_3-2-1_096081_2023-03-24_final
2023-03-24 09:56:24	ga_ls8c_ard_3-2-1_096082_2023-03-24_final
2023-04-03 10:30:12	ga_ls8c_ard_3-2-1_102074_2023-04-03_final
2023-04-03 10:31:00	ga_ls8c_ard_3-2-1_102076_2023-04-03_final
2023-04-12 10:26:14	ga_ls8c_ard_3-2-1_101080_2023-04-12_final
2023-04-14 10:11:29	ga_ls8c_ard_3-2-1_099074_2023-04-14_final
2023-04-17 10:40:46	ga_ls8c_ard_3-2-1_104070_2023-04-17_final
2023-04-18 09:49:07	ga_ls8c_ard_3-2-1_095080_2023-04-18_final
2023-04-18 11:28:00	ga_ls8c_ard_3-2-1_111080_2023-04-18_final
2023-05-03 10:44:40	ga_ls8c_ard_3-2-1_104080_2023-05-03_final
2023-05-03 10:45:04	ga_ls8c_ard_3-2-1_104081_2023-05-03_final
2023-05-06 09:35:51	ga_ls8c_ard_3-2-1_093078_2023-05-06_final
2023-05-11 09:55:53	ga_ls8c_ard_3-2-1_096082_2023-05-11_final
2023-05-14 10:26:22	ga_ls8c_ard_3-2-1_101081_2023-05-14_final
2023-05-19 10:43:17	ga_ls8c_ard_3-2-1_104077_2023-05-19_final
2023-05-22 09:37:19	ga_ls8c_ard_3-2-1_093082_2023-05-22_final
2023-05-24 11:02:40	ga_ls8c_ard_3-2-1_107079_2023-05-24_final
2023-05-31 11:08:03	ga_ls8c_ard_3-2-1_108077_2023-05-31_final
2023-06-01 10:10:50	ga_ls8c_ard_3-2-1_099073_2023-06-01_final
2023-06-04 10:43:46	ga_ls8c_ard_3-2-1_104078_2023-06-04_final
2023-06-07 09:37:25	ga_ls8c_ard_3-2-1_093082_2023-06-07_final
2023-06-14 09:41:16	ga_ls8c_ard_3-2-1_094076_2023-06-14_final
2023-06-16 09:31:43	ga_ls8c_ard_3-2-1_092083_2023-06-16_final
2023-06-17 10:10:59	ga_ls8c_ard_3-2-1_099073_2023-06-17_final
2023-06-20 10:41:30	ga_ls8c_ard_3-2-1_104072_2023-06-20_final
2023-06-22 10:31:55	ga_ls8c_ard_3-2-1_102079_2023-06-22_final
2023-06-23 09:36:18	ga_ls8c_ard_3-2-1_093079_2023-06-23_final
2023-06-25 09:23:35	ga_ls8c_ard_3-2-1_091078_2023-06-24_final
2023-06-25 09:23:59	ga_ls8c_ard_3-2-1_091079_2023-06-24_final
2023-07-02 11:08:22	ga_ls8c_ard_3-2-1_108077_2023-07-02_final
2023-07-04 10:56:01	ga_ls8c_ard_3-2-1_106077_2023-07-04_final
2023-07-05 10:02:24	ga_ls8c_ard_3-2-1_097082_2023-07-05_final
2023-07-11 09:23:46	ga_ls8c_ard_3-2-1_091078_2023-07-10_final
2023-07-12 10:05:03	ga_ls8c_ard_3-2-1_098073_2023-07-12_final
2023-07-13 10:52:18	ga_ls8c_ard_3-2-1_105083_2023-07-13_final
2023-07-14 09:56:17	ga_ls8c_ard_3-2-1_096082_2023-07-14_final
2023-07-15 10:37:57	ga_ls8c_ard_3-2-1_103078_2023-07-15_final
2023-07-18 09:31:57	ga_ls8c_ard_3-2-1_092083_2023-07-18_final
2023-07-19 10:11:37	ga_ls8c_ard_3-2-1_099074_2023-07-19_final
2023-07-20 09:18:23	ga_ls8c_ard_3-2-1_090080_2023-07-19_final
2023-07-22 10:43:20	ga_ls8c_ard_3-2-1_104076_2023-07-22_final
2023-07-23 09:49:20	ga_ls8c_ard_3-2-1_095080_2023-07-23_final
2023-07-28 10:05:33	ga_ls8c_ard_3-2-1_098074_2023-07-28_final
2023-07-29 10:52:25	ga_ls8c_ard_3-2-1_105083_2023-07-29_final
2023-07-30 09:56:24	ga_ls8c_ard_3-2-1_096082_2023-07-30_final
2023-07-30 11:34:29	ga_ls8c_ard_3-2-1_112080_2023-07-30_final
2023-08-01 09:43:15	ga_ls8c_ard_3-2-1_094080_2023-08-01_final
2023-08-03 09:32:06	ga_ls8c_ard_3-2-1_092083_2023-08-03_final
2023-08-05 10:56:14	ga_ls8c_ard_3-2-1_106077_2023-08-05_final
2023-08-07 10:45:29	ga_ls8c_ard_3-2-1_104081_2023-08-07_final
2023-08-12 09:25:32	ga_ls8c_ard_3-2-1_091082_2023-08-11_final
2023-08-13 10:05:14	ga_ls8c_ard_3-2-1_098073_2023-08-13_final
2023-08-15 09:52:54	ga_ls8c_ard_3-2-1_096073_2023-08-15_final
2023-08-15 09:53:18	ga_ls8c_ard_3-2-1_096074_2023-08-15_final
2023-08-17 11:22:14	ga_ls8c_ard_3-2-1_110080_2023-08-17_final
2023-08-20 10:12:17	ga_ls8c_ard_3-2-1_099075_2023-08-20_final
2023-08-24 11:27:17	ga_ls8c_ard_3-2-1_111077_2023-08-24_final
2023-08-26 09:38:02	ga_ls8c_ard_3-2-1_093082_2023-08-26_final
2023-08-26 11:12:32	ga_ls8c_ard_3-2-1_109071_2023-08-26_final
2023-08-29 10:05:21	ga_ls8c_ard_3-2-1_098073_2023-08-29_final
2023-08-30 10:51:00	ga_ls8c_ard_3-2-1_105079_2023-08-30_final
2023-08-31 09:56:34	ga_ls8c_ard_3-2-1_096082_2023-08-31_final
2023-09-02 09:44:36	ga_ls8c_ard_3-2-1_094083_2023-09-02_final
2023-09-02 11:22:17	ga_ls8c_ard_3-2-1_110080_2023-09-02_final
2023-09-05 10:11:54	ga_ls8c_ard_3-2-1_099074_2023-09-05_final
2023-09-08 10:44:00	ga_ls8c_ard_3-2-1_104077_2023-09-08_final
2023-09-08 10:45:36	ga_ls8c_ard_3-2-1_104081_2023-09-08_final
2023-09-15 10:52:39	ga_ls8c_ard_3-2-1_105083_2023-09-15_final
2023-09-16 09:52:39	ga_ls8c_ard_3-2-1_096072_2023-09-16_final
2023-09-16 09:56:38	ga_ls8c_ard_3-2-1_096082_2023-09-16_final
2023-09-18 09:43:29	ga_ls8c_ard_3-2-1_094080_2023-09-18_final
2023-09-20 09:30:20	ga_ls8c_ard_3-2-1_092078_2023-09-20_final
2023-09-27 09:35:45	ga_ls8c_ard_3-2-1_093076_2023-09-27_final
2023-09-29 09:25:48	ga_ls8c_ard_3-2-1_091082_2023-09-28_final
2023-10-01 10:51:07	ga_ls8c_ard_3-2-1_105079_2023-10-01_final
2023-10-01 10:52:43	ga_ls8c_ard_3-2-1_105083_2023-10-01_final
2023-10-02 09:56:42	ga_ls8c_ard_3-2-1_096082_2023-10-02_final
2023-10-09 10:03:18	ga_ls8c_ard_3-2-1_097083_2023-10-09_final
2023-10-12 10:29:50	ga_ls8c_ard_3-2-1_102072_2023-10-12_final
2023-10-16 10:05:54	ga_ls8c_ard_3-2-1_098074_2023-10-16_final
2023-10-17 10:51:09	ga_ls8c_ard_3-2-1_105079_2023-10-17_final
2023-10-17 10:52:45	ga_ls8c_ard_3-2-1_105083_2023-10-17_final
2023-10-23 10:12:06	ga_ls8c_ard_3-2-1_099074_2023-10-23_final
2023-10-26 10:44:13	ga_ls8c_ard_3-2-1_104077_2023-10-26_final
2023-10-29 09:36:15	ga_ls8c_ard_3-2-1_093077_2023-10-29_final
2023-10-31 11:04:46	ga_ls8c_ard_3-2-1_107082_2023-10-31_final
2023-11-03 09:56:47	ga_ls8c_ard_3-2-1_096082_2023-11-03_final
2023-11-12 11:26:38	ga_ls8c_ard_3-2-1_111075_2023-11-12_final
2023-11-19 11:35:17	ga_ls8c_ard_3-2-1_112081_2023-11-19_final
2023-11-20 10:37:17	ga_ls8c_ard_3-2-1_103075_2023-11-20_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