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
2022-10-17 09:42:45	ga_ls8c_ard_3-2-1_094077_2022-10-17_final
2022-10-17 11:20:02	ga_ls8c_ard_3-2-1_110073_2022-10-17_final
2022-10-19 11:07:42	ga_ls8c_ard_3-2-1_108073_2022-10-19_final
2022-10-19 11:08:30	ga_ls8c_ard_3-2-1_108075_2022-10-19_final
2022-10-19 11:09:18	ga_ls8c_ard_3-2-1_108077_2022-10-19_final
2022-10-19 11:10:06	ga_ls8c_ard_3-2-1_108079_2022-10-19_final
2022-10-20 10:15:41	ga_ls8c_ard_3-2-1_099082_2022-10-20_final
2022-10-20 11:52:58	ga_ls8c_ard_3-2-1_115078_2022-10-20_final
2022-10-30 10:51:38	ga_ls8c_ard_3-2-1_105079_2022-10-30_final
2022-11-01 10:38:53	ga_ls8c_ard_3-2-1_103078_2022-11-01_final
2022-11-02 09:42:28	ga_ls8c_ard_3-2-1_094076_2022-11-02_final
2022-11-02 09:43:16	ga_ls8c_ard_3-2-1_094078_2022-11-02_final
2022-11-03 10:24:56	ga_ls8c_ard_3-2-1_101074_2022-11-03_final
2022-11-04 09:30:30	ga_ls8c_ard_3-2-1_092077_2022-11-04_final
2022-11-04 09:33:18	ga_ls8c_ard_3-2-1_092084_2022-11-04_final
2022-11-04 11:10:35	ga_ls8c_ard_3-2-1_108080_2022-11-04_final
2022-11-04 11:11:23	ga_ls8c_ard_3-2-1_108082_2022-11-04_final
2022-11-05 10:15:21	ga_ls8c_ard_3-2-1_099081_2022-11-05_final
2022-11-05 10:15:45	ga_ls8c_ard_3-2-1_099082_2022-11-05_final
2022-11-07 11:39:29	ga_ls8c_ard_3-2-1_113075_2022-11-07_final
2022-11-13 11:02:44	ga_ls8c_ard_3-2-1_107076_2022-11-13_final
2022-11-14 10:08:18	ga_ls8c_ard_3-2-1_098079_2022-11-14_final
2022-11-16 09:55:07	ga_ls8c_ard_3-2-1_096077_2022-11-16_final
2022-11-16 11:33:36	ga_ls8c_ard_3-2-1_112076_2022-11-16_final
2022-11-16 11:34:00	ga_ls8c_ard_3-2-1_112077_2022-11-16_final
2022-11-16 11:34:48	ga_ls8c_ard_3-2-1_112079_2022-11-16_final
2022-11-17 10:38:46	ga_ls8c_ard_3-2-1_103078_2022-11-17_final
2022-11-18 11:20:01	ga_ls8c_ard_3-2-1_110073_2022-11-18_final
2022-11-24 10:41:47	ga_ls8c_ard_3-2-1_104070_2022-11-24_final
2022-11-28 10:20:39	ga_ls8c_ard_3-2-1_100079_2022-11-28_final
2022-11-30 10:09:30	ga_ls8c_ard_3-2-1_098082_2022-11-30_final
2022-12-02 11:36:01	ga_ls8c_ard_3-2-1_112082_2022-12-02_final
2022-12-04 09:42:47	ga_ls8c_ard_3-2-1_094077_2022-12-04_final
2022-12-04 09:43:11	ga_ls8c_ard_3-2-1_094078_2022-12-04_final
2022-12-04 09:43:35	ga_ls8c_ard_3-2-1_094079_2022-12-04_final
2022-12-09 11:42:35	ga_ls8c_ard_3-2-1_113083_2022-12-09_final
2022-12-11 11:28:36	ga_ls8c_ard_3-2-1_111079_2022-12-11_final
2022-12-14 10:19:24	ga_ls8c_ard_3-2-1_100076_2022-12-14_final
2022-12-18 09:58:37	ga_ls8c_ard_3-2-1_096086_2022-12-18_final
2022-12-18 11:36:18	ga_ls8c_ard_3-2-1_112083_2022-12-18_final
2022-12-20 09:42:38	ga_ls8c_ard_3-2-1_094077_2022-12-20_final
2022-12-20 11:20:43	ga_ls8c_ard_3-2-1_110075_2022-12-20_final
2022-12-27 09:51:12	ga_ls8c_ard_3-2-1_095083_2022-12-27_final
2022-12-27 11:26:29	ga_ls8c_ard_3-2-1_111074_2022-12-27_final
2022-12-29 11:16:08	ga_ls8c_ard_3-2-1_109079_2022-12-29_final
2022-12-30 10:20:55	ga_ls8c_ard_3-2-1_100080_2022-12-30_final
2023-01-01 10:09:45	ga_ls8c_ard_3-2-1_098083_2023-01-01_final
2023-01-02 09:13:44	ga_ls8c_ard_3-2-1_089082_2023-01-01_final
2023-01-03 11:36:16	ga_ls8c_ard_3-2-1_112083_2023-01-03_final
2023-01-05 09:44:14	ga_ls8c_ard_3-2-1_094081_2023-01-05_final
2023-01-05 09:46:13	ga_ls8c_ard_3-2-1_094086_2023-01-05_final
2023-01-05 09:46:37	ga_ls8c_ard_3-2-1_094087_2023-01-05_final
2023-01-05 11:24:18	ga_ls8c_ard_3-2-1_110084_2023-01-05_final
2023-01-07 09:33:51	ga_ls8c_ard_3-2-1_092086_2023-01-07_final
2023-01-07 11:06:21	ga_ls8c_ard_3-2-1_108070_2023-01-07_final
2023-01-07 11:09:57	ga_ls8c_ard_3-2-1_108079_2023-01-07_final
2023-01-08 10:11:07	ga_ls8c_ard_3-2-1_099071_2023-01-08_final
2023-01-08 10:15:31	ga_ls8c_ard_3-2-1_099082_2023-01-08_final
2023-01-09 10:58:22	ga_ls8c_ard_3-2-1_106081_2023-01-09_final
2023-01-11 10:42:00	ga_ls8c_ard_3-2-1_104071_2023-01-11_final
2023-01-11 10:44:47	ga_ls8c_ard_3-2-1_104078_2023-01-11_final
2023-01-12 11:27:39	ga_ls8c_ard_3-2-1_111077_2023-01-12_final
2023-01-13 10:30:01	ga_ls8c_ard_3-2-1_102072_2023-01-13_final
2023-01-13 10:31:13	ga_ls8c_ard_3-2-1_102075_2023-01-13_final
2023-01-14 09:36:46	ga_ls8c_ard_3-2-1_093078_2023-01-14_final
2023-01-14 09:38:22	ga_ls8c_ard_3-2-1_093082_2023-01-14_final
2023-01-14 11:15:15	ga_ls8c_ard_3-2-1_109077_2023-01-14_final
2023-01-19 09:54:52	ga_ls8c_ard_3-2-1_096077_2023-01-19_final
2023-01-19 09:57:40	ga_ls8c_ard_3-2-1_096084_2023-01-19_final
2023-01-19 11:36:09	ga_ls8c_ard_3-2-1_112083_2023-01-19_final
2023-01-19 11:36:33	ga_ls8c_ard_3-2-1_112084_2023-01-19_final
2023-01-21 09:44:08	ga_ls8c_ard_3-2-1_094081_2023-01-21_final
2023-01-21 09:46:08	ga_ls8c_ard_3-2-1_094086_2023-01-21_final
2023-01-22 10:23:49	ga_ls8c_ard_3-2-1_101072_2023-01-22_final
2023-01-23 09:29:24	ga_ls8c_ard_3-2-1_092075_2023-01-22_final
2023-01-23 11:09:05	ga_ls8c_ard_3-2-1_108077_2023-01-23_final
2023-01-24 11:51:10	ga_ls8c_ard_3-2-1_115074_2023-01-24_final
2023-01-30 11:16:06	ga_ls8c_ard_3-2-1_109079_2023-01-30_final
2023-01-30 11:17:42	ga_ls8c_ard_3-2-1_109083_2023-01-30_final
2023-02-06 11:20:40	ga_ls8c_ard_3-2-1_110075_2023-02-06_final
2023-02-08 11:09:06	ga_ls8c_ard_3-2-1_108077_2023-02-08_final
2023-02-08 11:11:05	ga_ls8c_ard_3-2-1_108082_2023-02-08_final
2023-02-13 09:49:05	ga_ls8c_ard_3-2-1_095078_2023-02-13_final
2023-02-16 10:20:45	ga_ls8c_ard_3-2-1_100080_2023-02-16_final
2023-02-17 09:26:18	ga_ls8c_ard_3-2-1_091083_2023-02-16_final
2023-02-22 09:45:32	ga_ls8c_ard_3-2-1_094085_2023-02-22_final
2023-02-24 09:30:44	ga_ls8c_ard_3-2-1_092079_2023-02-24_final
2023-03-01 11:27:20	ga_ls8c_ard_3-2-1_111077_2023-03-01_final
2023-03-01 11:30:08	ga_ls8c_ard_3-2-1_111084_2023-03-01_final
2023-03-03 09:38:53	ga_ls8c_ard_3-2-1_093084_2023-03-03_final
2023-03-03 11:14:58	ga_ls8c_ard_3-2-1_109077_2023-03-03_final
2023-03-04 10:20:08	ga_ls8c_ard_3-2-1_100079_2023-03-04_final
2023-03-04 11:57:49	ga_ls8c_ard_3-2-1_116076_2023-03-04_final
2023-03-05 11:02:11	ga_ls8c_ard_3-2-1_107076_2023-03-05_final
2023-03-08 09:55:22	ga_ls8c_ard_3-2-1_096079_2023-03-08_final
2023-03-08 11:34:15	ga_ls8c_ard_3-2-1_112079_2023-03-08_final
2023-03-08 11:34:38	ga_ls8c_ard_3-2-1_112080_2023-03-08_final
2023-03-09 10:36:13	ga_ls8c_ard_3-2-1_103073_2023-03-09_final
2023-03-10 11:21:05	ga_ls8c_ard_3-2-1_110077_2023-03-10_final
2023-03-12 09:32:38	ga_ls8c_ard_3-2-1_092084_2023-03-12_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