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
2022-07-19 10:45:05	ga_ls8c_ard_3-2-1_104079_2022-07-19_final
2022-07-19 10:46:17	ga_ls8c_ard_3-2-1_104082_2022-07-19_final
2022-07-20 09:47:05	ga_ls8c_ard_3-2-1_095073_2022-07-20_final
2022-07-20 11:28:46	ga_ls8c_ard_3-2-1_111080_2022-07-20_final
2022-07-22 09:37:09	ga_ls8c_ard_3-2-1_093079_2022-07-22_final
2022-07-26 10:50:34	ga_ls8c_ard_3-2-1_105077_2022-07-26_final
2022-07-31 11:08:45	ga_ls8c_ard_3-2-1_108076_2022-07-31_final
2022-08-02 10:58:01	ga_ls8c_ard_3-2-1_106080_2022-08-02_final
2022-08-03 09:57:13	ga_ls8c_ard_3-2-1_097067_2022-08-03_final
2022-08-03 10:04:00	ga_ls8c_ard_3-2-1_097084_2022-08-03_final
2022-08-06 10:28:32	ga_ls8c_ard_3-2-1_102068_2022-08-06_final
2022-08-16 11:09:16	ga_ls8c_ard_3-2-1_108077_2022-08-16_final
2022-08-25 11:04:18	ga_ls8c_ard_3-2-1_107080_2022-08-25_final
2022-08-26 10:03:53	ga_ls8c_ard_3-2-1_098068_2022-08-26_final
2022-09-02 10:14:27	ga_ls8c_ard_3-2-1_099079_2022-09-02_final
2022-09-05 10:41:47	ga_ls8c_ard_3-2-1_104070_2022-09-05_final
2022-09-06 09:46:58	ga_ls8c_ard_3-2-1_095072_2022-09-06_final
2022-09-12 10:50:49	ga_ls8c_ard_3-2-1_105077_2022-09-12_final
2022-09-14 10:35:16	ga_ls8c_ard_3-2-1_103069_2022-09-14_final
2022-09-24 11:16:22	ga_ls8c_ard_3-2-1_109079_2022-09-24_final
2022-09-26 11:02:49	ga_ls8c_ard_3-2-1_107076_2022-09-26_final
2022-09-26 11:03:37	ga_ls8c_ard_3-2-1_107078_2022-09-26_final
2022-10-01 11:20:32	ga_ls8c_ard_3-2-1_110074_2022-10-01_final
2022-10-03 11:12:10	ga_ls8c_ard_3-2-1_108084_2022-10-03_final
2022-10-11 10:20:38	ga_ls8c_ard_3-2-1_100079_2022-10-11_final
2022-10-12 11:02:41	ga_ls8c_ard_3-2-1_107076_2022-10-12_final
2022-10-17 11:20:26	ga_ls8c_ard_3-2-1_110074_2022-10-17_final
2022-10-19 11:08:06	ga_ls8c_ard_3-2-1_108074_2022-10-19_final
2022-10-20 10:14:29	ga_ls8c_ard_3-2-1_099079_2022-10-20_final
2022-10-23 10:41:50	ga_ls8c_ard_3-2-1_104070_2022-10-23_final
2022-10-30 10:50:50	ga_ls8c_ard_3-2-1_105077_2022-10-30_final
2022-11-02 11:18:57	ga_ls8c_ard_3-2-1_110070_2022-11-02_final
2022-11-04 11:10:59	ga_ls8c_ard_3-2-1_108081_2022-11-04_final
2022-11-11 11:14:19	ga_ls8c_ard_3-2-1_109074_2022-11-11_final
2022-11-20 09:30:23	ga_ls8c_ard_3-2-1_092077_2022-11-20_final
2022-11-20 09:31:11	ga_ls8c_ard_3-2-1_092079_2022-11-20_final
2022-11-20 11:08:04	ga_ls8c_ard_3-2-1_108074_2022-11-20_final
2022-11-21 10:14:51	ga_ls8c_ard_3-2-1_099080_2022-11-21_final
2022-11-23 10:04:30	ga_ls8c_ard_3-2-1_097085_2022-11-23_final
2022-12-02 09:55:56	ga_ls8c_ard_3-2-1_096079_2022-12-02_final
2022-12-04 11:18:52	ga_ls8c_ard_3-2-1_110070_2022-12-04_final
2022-12-07 10:14:52	ga_ls8c_ard_3-2-1_099080_2022-12-07_final
2022-12-08 10:56:32	ga_ls8c_ard_3-2-1_106076_2022-12-08_final
2022-12-11 09:46:56	ga_ls8c_ard_3-2-1_095072_2022-12-11_final
2022-12-11 09:47:20	ga_ls8c_ard_3-2-1_095073_2022-12-11_final
2022-12-13 11:14:14	ga_ls8c_ard_3-2-1_109074_2022-12-13_final
2022-12-15 11:03:03	ga_ls8c_ard_3-2-1_107077_2022-12-15_final
2022-12-17 10:50:16	ga_ls8c_ard_3-2-1_105076_2022-12-17_final
2022-12-19 10:34:41	ga_ls8c_ard_3-2-1_103068_2022-12-19_final
2022-12-24 10:58:45	ga_ls8c_ard_3-2-1_106082_2022-12-24_final
2022-12-27 11:28:29	ga_ls8c_ard_3-2-1_111079_2022-12-27_final
2022-12-27 11:30:29	ga_ls8c_ard_3-2-1_111084_2022-12-27_final
2022-12-29 09:38:03	ga_ls8c_ard_3-2-1_093081_2022-12-29_final
2022-12-31 11:03:23	ga_ls8c_ard_3-2-1_107078_2022-12-31_final
2023-01-05 09:44:38	ga_ls8c_ard_3-2-1_094082_2023-01-05_final
2023-01-05 09:46:37	ga_ls8c_ard_3-2-1_094087_2023-01-05_final
2023-01-05 11:21:07	ga_ls8c_ard_3-2-1_110076_2023-01-05_final
2023-01-16 11:02:52	ga_ls8c_ard_3-2-1_107077_2023-01-16_final
2023-01-18 10:47:17	ga_ls8c_ard_3-2-1_105069_2023-01-18_final
2023-01-20 10:40:09	ga_ls8c_ard_3-2-1_103082_2023-01-20_final
2023-01-26 10:04:19	ga_ls8c_ard_3-2-1_097085_2023-01-26_final
2023-01-29 10:29:39	ga_ls8c_ard_3-2-1_102071_2023-01-29_final
2023-01-30 09:39:13	ga_ls8c_ard_3-2-1_093084_2023-01-30_final
2023-01-30 11:14:06	ga_ls8c_ard_3-2-1_109074_2023-01-30_final
2023-02-08 09:31:49	ga_ls8c_ard_3-2-1_092081_2023-02-08_final
2023-02-09 10:11:28	ga_ls8c_ard_3-2-1_099072_2023-02-09_final
2023-02-18 10:09:57	ga_ls8c_ard_3-2-1_098084_2023-02-18_final
2023-02-18 11:47:38	ga_ls8c_ard_3-2-1_114081_2023-02-18_final
2023-02-22 09:44:20	ga_ls8c_ard_3-2-1_094082_2023-02-22_final
2023-02-22 11:20:50	ga_ls8c_ard_3-2-1_110076_2023-02-22_final
2023-02-24 09:31:32	ga_ls8c_ard_3-2-1_092081_2023-02-24_final
2023-02-24 09:32:20	ga_ls8c_ard_3-2-1_092083_2023-02-24_final
2023-03-02 10:33:18	ga_ls8c_ard_3-2-1_102081_2023-03-02_final
2023-03-03 09:37:41	ga_ls8c_ard_3-2-1_093081_2023-03-03_final
2023-03-05 11:02:11	ga_ls8c_ard_3-2-1_107076_2023-03-05_final
2023-03-05 11:02:35	ga_ls8c_ard_3-2-1_107077_2023-03-05_final
2023-03-07 10:49:48	ga_ls8c_ard_3-2-1_105076_2023-03-07_final
2023-03-09 10:39:01	ga_ls8c_ard_3-2-1_103080_2023-03-09_final
2023-03-10 09:44:11	ga_ls8c_ard_3-2-1_094082_2023-03-10_final
2023-03-10 11:19:53	ga_ls8c_ard_3-2-1_110074_2023-03-10_final
2023-03-12 09:31:26	ga_ls8c_ard_3-2-1_092081_2023-03-12_final
2023-03-12 09:32:14	ga_ls8c_ard_3-2-1_092083_2023-03-12_final
2023-03-13 10:15:53	ga_ls8c_ard_3-2-1_099084_2023-03-13_final
2023-03-19 09:37:33	ga_ls8c_ard_3-2-1_093081_2023-03-19_final
2023-03-19 11:14:26	ga_ls8c_ard_3-2-1_109076_2023-03-19_final
2023-03-26 11:20:32	ga_ls8c_ard_3-2-1_110076_2023-03-26_final
2023-04-08 10:50:14	ga_ls8c_ard_3-2-1_105078_2023-04-08_final
2023-04-09 09:56:11	ga_ls8c_ard_3-2-1_096082_2023-04-09_final
2023-04-09 09:57:23	ga_ls8c_ard_3-2-1_096085_2023-04-09_final
2023-04-10 10:38:37	ga_ls8c_ard_3-2-1_103080_2023-04-10_final
2023-04-13 09:34:36	ga_ls8c_ard_3-2-1_092090_2023-04-13_final
2023-04-17 10:44:21	ga_ls8c_ard_3-2-1_104079_2023-04-17_final
2023-04-17 10:45:09	ga_ls8c_ard_3-2-1_104081_2023-04-17_final
2023-04-19 10:32:46	ga_ls8c_ard_3-2-1_102081_2023-04-19_final
2023-04-29 09:33:21	ga_ls8c_ard_3-2-1_092087_2023-04-29_final
2023-05-01 10:57:03	ga_ls8c_ard_3-2-1_106080_2023-05-01_final
2023-05-06 11:13:56	ga_ls8c_ard_3-2-1_109076_2023-05-06_final
2023-05-06 11:14:20	ga_ls8c_ard_3-2-1_109077_2023-05-06_final
2023-05-10 10:50:20	ga_ls8c_ard_3-2-1_105079_2023-05-10_final
2023-05-13 09:43:30	ga_ls8c_ard_3-2-1_094082_2023-05-13_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