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
2022-11-05 10:16:33	ga_ls8c_ard_3-2-1_099084_2022-11-05_final
2022-11-06 10:59:01	ga_ls8c_ard_3-2-1_106082_2022-11-06_final
2022-11-16 09:54:19	ga_ls8c_ard_3-2-1_096075_2022-11-16_final
2022-11-16 09:55:07	ga_ls8c_ard_3-2-1_096077_2022-11-16_final
2022-11-17 10:38:46	ga_ls8c_ard_3-2-1_103078_2022-11-17_final
2022-11-18 09:42:44	ga_ls8c_ard_3-2-1_094077_2022-11-18_final
2022-11-18 09:43:32	ga_ls8c_ard_3-2-1_094079_2022-11-18_final
2022-11-18 11:22:01	ga_ls8c_ard_3-2-1_110078_2022-11-18_final
2022-11-22 09:22:26	ga_ls8c_ard_3-2-1_090088_2022-11-21_final
2022-11-23 10:01:42	ga_ls8c_ard_3-2-1_097078_2022-11-23_final
2022-11-23 10:02:30	ga_ls8c_ard_3-2-1_097080_2022-11-23_final
2022-11-25 09:51:45	ga_ls8c_ard_3-2-1_095084_2022-11-25_final
2022-11-25 09:52:09	ga_ls8c_ard_3-2-1_095085_2022-11-25_final
2022-11-26 10:30:13	ga_ls8c_ard_3-2-1_102072_2022-11-26_final
2022-11-27 11:14:41	ga_ls8c_ard_3-2-1_109075_2022-11-27_final
2022-12-02 11:33:38	ga_ls8c_ard_3-2-1_112076_2022-12-02_final
2022-12-06 11:08:54	ga_ls8c_ard_3-2-1_108076_2022-12-06_final
2022-12-06 11:09:42	ga_ls8c_ard_3-2-1_108078_2022-12-06_final
2022-12-07 10:15:16	ga_ls8c_ard_3-2-1_099081_2022-12-07_final
2022-12-08 09:20:02	ga_ls8c_ard_3-2-1_090082_2022-12-07_final
2022-12-13 09:38:09	ga_ls8c_ard_3-2-1_093081_2022-12-13_final
2022-12-13 11:15:02	ga_ls8c_ard_3-2-1_109076_2022-12-13_final
2022-12-13 11:15:50	ga_ls8c_ard_3-2-1_109078_2022-12-13_final
2022-12-14 10:18:12	ga_ls8c_ard_3-2-1_100073_2022-12-14_final
2022-12-16 10:09:25	ga_ls8c_ard_3-2-1_098082_2022-12-16_final
2022-12-18 11:33:31	ga_ls8c_ard_3-2-1_112076_2022-12-18_final
2022-12-18 11:35:06	ga_ls8c_ard_3-2-1_112080_2022-12-18_final
2022-12-19 10:38:40	ga_ls8c_ard_3-2-1_103078_2022-12-19_final
2022-12-20 09:43:02	ga_ls8c_ard_3-2-1_094078_2022-12-20_final
2022-12-22 09:30:38	ga_ls8c_ard_3-2-1_092078_2022-12-22_final
2022-12-22 11:09:31	ga_ls8c_ard_3-2-1_108078_2022-12-22_final
2022-12-23 11:51:11	ga_ls8c_ard_3-2-1_115074_2022-12-23_final
2022-12-25 11:38:50	ga_ls8c_ard_3-2-1_113074_2022-12-25_final
2022-12-27 09:49:12	ga_ls8c_ard_3-2-1_095078_2022-12-27_final
2022-12-27 09:50:24	ga_ls8c_ard_3-2-1_095081_2022-12-27_final
2022-12-27 09:51:36	ga_ls8c_ard_3-2-1_095084_2022-12-27_final
2022-12-27 09:52:00	ga_ls8c_ard_3-2-1_095085_2022-12-27_final
2022-12-28 10:33:40	ga_ls8c_ard_3-2-1_102081_2022-12-28_final
2022-12-29 09:38:03	ga_ls8c_ard_3-2-1_093081_2022-12-29_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
2022-12-31 11:02:35	ga_ls8c_ard_3-2-1_107076_2022-12-31_final
2023-01-01 10:09:21	ga_ls8c_ard_3-2-1_098082_2023-01-01_final
2023-01-03 09:55:00	ga_ls8c_ard_3-2-1_096077_2023-01-03_final
2023-01-03 09:56:12	ga_ls8c_ard_3-2-1_096080_2023-01-03_final
2023-01-05 11:21:55	ga_ls8c_ard_3-2-1_110078_2023-01-05_final
2023-01-06 10:23:30	ga_ls8c_ard_3-2-1_101071_2023-01-06_final
2023-01-07 11:06:45	ga_ls8c_ard_3-2-1_108071_2023-01-07_final
2023-01-07 11:09:33	ga_ls8c_ard_3-2-1_108078_2023-01-07_final
2023-01-07 11:10:44	ga_ls8c_ard_3-2-1_108081_2023-01-07_final
2023-01-13 10:30:01	ga_ls8c_ard_3-2-1_102072_2023-01-13_final
2023-01-14 09:39:10	ga_ls8c_ard_3-2-1_093084_2023-01-14_final
2023-01-14 11:14:03	ga_ls8c_ard_3-2-1_109074_2023-01-14_final
2023-01-14 11:14:51	ga_ls8c_ard_3-2-1_109076_2023-01-14_final
2023-01-14 11:15:39	ga_ls8c_ard_3-2-1_109078_2023-01-14_final
2023-01-15 10:22:01	ga_ls8c_ard_3-2-1_100083_2023-01-15_final
2023-01-17 10:03:38	ga_ls8c_ard_3-2-1_098068_2023-01-17_final
2023-01-17 10:09:13	ga_ls8c_ard_3-2-1_098082_2023-01-17_final
2023-01-17 11:47:18	ga_ls8c_ard_3-2-1_114080_2023-01-17_final
2023-01-19 11:34:33	ga_ls8c_ard_3-2-1_112079_2023-01-19_final
2023-01-21 09:42:08	ga_ls8c_ard_3-2-1_094076_2023-01-21_final
2023-01-21 09:42:32	ga_ls8c_ard_3-2-1_094077_2023-01-21_final
2023-01-21 11:21:49	ga_ls8c_ard_3-2-1_110078_2023-01-21_final
2023-01-23 11:09:29	ga_ls8c_ard_3-2-1_108078_2023-01-23_final
2023-01-23 11:10:17	ga_ls8c_ard_3-2-1_108080_2023-01-23_final
2023-01-24 10:14:16	ga_ls8c_ard_3-2-1_099079_2023-01-24_final
2023-01-26 10:01:32	ga_ls8c_ard_3-2-1_097078_2023-01-26_final
2023-01-29 10:30:51	ga_ls8c_ard_3-2-1_102074_2023-01-29_final
2023-01-30 09:36:01	ga_ls8c_ard_3-2-1_093076_2023-01-30_final
2023-01-30 09:37:13	ga_ls8c_ard_3-2-1_093079_2023-01-30_final
2023-02-06 09:43:23	ga_ls8c_ard_3-2-1_094079_2023-02-06_final
2023-02-06 09:44:11	ga_ls8c_ard_3-2-1_094081_2023-02-06_final
2023-02-06 11:21:52	ga_ls8c_ard_3-2-1_110078_2023-02-06_final
2023-02-08 11:09:30	ga_ls8c_ard_3-2-1_108078_2023-02-08_final
2023-02-08 11:10:18	ga_ls8c_ard_3-2-1_108080_2023-02-08_final
2023-02-13 09:49:53	ga_ls8c_ard_3-2-1_095080_2023-02-13_final
2023-02-13 09:50:17	ga_ls8c_ard_3-2-1_095081_2023-02-13_final
2023-02-14 10:31:08	ga_ls8c_ard_3-2-1_102075_2023-02-14_final
2023-02-15 09:37:30	ga_ls8c_ard_3-2-1_093080_2023-02-15_final
2023-02-15 09:37:54	ga_ls8c_ard_3-2-1_093081_2023-02-15_final
2023-02-15 09:39:06	ga_ls8c_ard_3-2-1_093084_2023-02-15_final
2023-02-15 11:15:59	ga_ls8c_ard_3-2-1_109079_2023-02-15_final
2023-02-16 10:20:21	ga_ls8c_ard_3-2-1_100079_2023-02-16_final
2023-02-16 10:20:45	ga_ls8c_ard_3-2-1_100080_2023-02-16_final
2023-02-20 09:51:58	ga_ls8c_ard_3-2-1_096070_2023-02-20_final
2023-02-20 09:55:57	ga_ls8c_ard_3-2-1_096080_2023-02-20_final
2023-02-20 11:32:50	ga_ls8c_ard_3-2-1_112075_2023-02-20_final
2023-02-20 11:33:14	ga_ls8c_ard_3-2-1_112076_2023-02-20_final
2023-02-20 11:34:26	ga_ls8c_ard_3-2-1_112079_2023-02-20_final
2023-02-21 10:36:48	ga_ls8c_ard_3-2-1_103074_2023-02-21_final
2023-02-22 09:42:21	ga_ls8c_ard_3-2-1_094077_2023-02-22_final
2023-03-01 09:50:27	ga_ls8c_ard_3-2-1_095082_2023-03-01_final
2023-03-01 11:27:20	ga_ls8c_ard_3-2-1_111077_2023-03-01_final
2023-03-03 11:15:22	ga_ls8c_ard_3-2-1_109078_2023-03-03_final
2023-03-03 11:15:46	ga_ls8c_ard_3-2-1_109079_2023-03-03_final
2023-03-03 11:17:22	ga_ls8c_ard_3-2-1_109083_2023-03-03_final
2023-03-05 09:24:06	ga_ls8c_ard_3-2-1_091078_2023-03-04_final
2023-03-08 09:54:58	ga_ls8c_ard_3-2-1_096078_2023-03-08_final
2023-03-08 09:55:45	ga_ls8c_ard_3-2-1_096080_2023-03-08_final
2023-03-08 11:33:03	ga_ls8c_ard_3-2-1_112076_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