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
2022-09-30 10:39:41	ga_ls8c_ard_3-2-1_103080_2022-09-30_final
2022-10-10 11:15:04	ga_ls8c_ard_3-2-1_109076_2022-10-10_final
2022-10-17 09:45:33	ga_ls8c_ard_3-2-1_094084_2022-10-17_final
2022-10-19 09:34:24	ga_ls8c_ard_3-2-1_092087_2022-10-19_final
2022-10-20 10:16:29	ga_ls8c_ard_3-2-1_099084_2022-10-20_final
2022-10-24 09:50:12	ga_ls8c_ard_3-2-1_095080_2022-10-24_final
2022-11-02 09:41:16	ga_ls8c_ard_3-2-1_094073_2022-11-02_final
2022-11-07 11:41:28	ga_ls8c_ard_3-2-1_113080_2022-11-07_final
2022-11-13 11:03:08	ga_ls8c_ard_3-2-1_107077_2022-11-13_final
2022-11-13 11:03:32	ga_ls8c_ard_3-2-1_107078_2022-11-13_final
2022-11-18 09:41:32	ga_ls8c_ard_3-2-1_094074_2022-11-18_final
2022-11-18 11:20:25	ga_ls8c_ard_3-2-1_110074_2022-11-18_final
2022-11-18 11:20:49	ga_ls8c_ard_3-2-1_110075_2022-11-18_final
2022-11-20 11:09:16	ga_ls8c_ard_3-2-1_108077_2022-11-20_final
2022-11-20 11:10:52	ga_ls8c_ard_3-2-1_108081_2022-11-20_final
2022-11-21 10:10:51	ga_ls8c_ard_3-2-1_099070_2022-11-21_final
2022-11-23 11:38:59	ga_ls8c_ard_3-2-1_113074_2022-11-23_final
2022-11-24 10:46:10	ga_ls8c_ard_3-2-1_104081_2022-11-24_final
2022-11-29 11:03:31	ga_ls8c_ard_3-2-1_107078_2022-11-29_final
2022-12-01 10:50:46	ga_ls8c_ard_3-2-1_105077_2022-12-01_final
2022-12-03 10:40:24	ga_ls8c_ard_3-2-1_103082_2022-12-03_final
2022-12-04 11:21:16	ga_ls8c_ard_3-2-1_110076_2022-12-04_final
2022-12-06 09:35:36	ga_ls8c_ard_3-2-1_092090_2022-12-06_final
2022-12-10 10:46:09	ga_ls8c_ard_3-2-1_104081_2022-12-10_final
2022-12-13 11:14:14	ga_ls8c_ard_3-2-1_109074_2022-12-13_final
2022-12-15 09:27:21	ga_ls8c_ard_3-2-1_091085_2022-12-14_final
2022-12-15 11:03:27	ga_ls8c_ard_3-2-1_107078_2022-12-15_final
2022-12-17 10:51:04	ga_ls8c_ard_3-2-1_105078_2022-12-17_final
2022-12-24 10:56:22	ga_ls8c_ard_3-2-1_106076_2022-12-24_final
2023-01-02 10:51:49	ga_ls8c_ard_3-2-1_105080_2023-01-02_final
2023-01-07 09:32:39	ga_ls8c_ard_3-2-1_092083_2023-01-07_final
2023-01-12 11:30:26	ga_ls8c_ard_3-2-1_111084_2023-01-12_final
2023-01-13 10:33:12	ga_ls8c_ard_3-2-1_102080_2023-01-13_final
2023-01-15 10:22:25	ga_ls8c_ard_3-2-1_100084_2023-01-15_final
2023-01-17 10:03:38	ga_ls8c_ard_3-2-1_098068_2023-01-17_final
2023-02-01 11:03:21	ga_ls8c_ard_3-2-1_107078_2023-02-01_final
2023-02-03 10:50:11	ga_ls8c_ard_3-2-1_105076_2023-02-03_final
2023-02-03 10:51:47	ga_ls8c_ard_3-2-1_105080_2023-02-03_final
2023-02-04 11:35:50	ga_ls8c_ard_3-2-1_112082_2023-02-04_final
2023-02-08 09:31:49	ga_ls8c_ard_3-2-1_092081_2023-02-08_final
2023-02-10 10:59:06	ga_ls8c_ard_3-2-1_106083_2023-02-10_final
2023-02-16 10:22:21	ga_ls8c_ard_3-2-1_100084_2023-02-16_final
2023-02-17 11:05:35	ga_ls8c_ard_3-2-1_107084_2023-02-17_final
2023-02-18 11:46:02	ga_ls8c_ard_3-2-1_114077_2023-02-18_final
2023-02-21 10:39:11	ga_ls8c_ard_3-2-1_103080_2023-02-21_final
2023-02-22 11:20:50	ga_ls8c_ard_3-2-1_110076_2023-02-22_final
2023-03-02 10:28:31	ga_ls8c_ard_3-2-1_102069_2023-03-02_final
2023-03-02 10:29:19	ga_ls8c_ard_3-2-1_102071_2023-03-02_final
2023-03-04 10:22:08	ga_ls8c_ard_3-2-1_100084_2023-03-04_final
2023-03-05 09:26:06	ga_ls8c_ard_3-2-1_091083_2023-03-04_final
2023-03-06 10:05:22	ga_ls8c_ard_3-2-1_098073_2023-03-06_final
2023-03-11 10:22:40	ga_ls8c_ard_3-2-1_101070_2023-03-11_final
2023-03-12 11:07:07	ga_ls8c_ard_3-2-1_108073_2023-03-12_final
2023-03-13 10:10:18	ga_ls8c_ard_3-2-1_099070_2023-03-13_final
2023-03-16 10:45:34	ga_ls8c_ard_3-2-1_104081_2023-03-16_final
2023-03-17 09:50:20	ga_ls8c_ard_3-2-1_095082_2023-03-17_final
2023-03-19 09:37:33	ga_ls8c_ard_3-2-1_093081_2023-03-19_final
2023-03-19 11:13:38	ga_ls8c_ard_3-2-1_109074_2023-03-19_final
2023-03-23 10:46:03	ga_ls8c_ard_3-2-1_105067_2023-03-23_final
2023-03-23 10:47:15	ga_ls8c_ard_3-2-1_105070_2023-03-23_final
2023-03-27 10:24:06	ga_ls8c_ard_3-2-1_101074_2023-03-27_final
2023-03-31 10:01:45	ga_ls8c_ard_3-2-1_097080_2023-03-31_final
2023-04-02 09:51:45	ga_ls8c_ard_3-2-1_095086_2023-04-02_final
2023-04-04 11:15:03	ga_ls8c_ard_3-2-1_109078_2023-04-04_final
2023-04-06 11:02:38	ga_ls8c_ard_3-2-1_107078_2023-04-06_final
2023-04-06 11:05:02	ga_ls8c_ard_3-2-1_107084_2023-04-06_final
2023-04-08 10:49:50	ga_ls8c_ard_3-2-1_105077_2023-04-08_final
2023-04-19 10:27:35	ga_ls8c_ard_3-2-1_102068_2023-04-19_final
2023-04-19 10:27:59	ga_ls8c_ard_3-2-1_102069_2023-04-19_final
2023-04-19 10:33:10	ga_ls8c_ard_3-2-1_102082_2023-04-19_final
2023-04-21 11:57:18	ga_ls8c_ard_3-2-1_116076_2023-04-21_final
2023-04-24 10:50:55	ga_ls8c_ard_3-2-1_105080_2023-04-24_final
2023-04-27 09:43:43	ga_ls8c_ard_3-2-1_094082_2023-04-27_final
2023-05-01 09:20:34	ga_ls8c_ard_3-2-1_090086_2023-04-30_final
2023-05-04 11:29:07	ga_ls8c_ard_3-2-1_111083_2023-05-04_final
2023-05-06 09:39:26	ga_ls8c_ard_3-2-1_093087_2023-05-06_final
2023-05-11 11:35:34	ga_ls8c_ard_3-2-1_112084_2023-05-11_final
2023-05-25 10:04:15	ga_ls8c_ard_3-2-1_098072_2023-05-25_final
2023-06-04 10:44:57	ga_ls8c_ard_3-2-1_104081_2023-06-04_final
2023-06-05 09:48:57	ga_ls8c_ard_3-2-1_095080_2023-06-05_final
2023-06-05 11:25:27	ga_ls8c_ard_3-2-1_111074_2023-06-05_final
2023-06-07 09:37:01	ga_ls8c_ard_3-2-1_093081_2023-06-07_final
2023-06-09 09:23:05	ga_ls8c_ard_3-2-1_091077_2023-06-08_final
2023-06-14 11:23:21	ga_ls8c_ard_3-2-1_110084_2023-06-14_final
2023-06-20 10:40:42	ga_ls8c_ard_3-2-1_104070_2023-06-20_final
2023-06-21 09:45:28	ga_ls8c_ard_3-2-1_095071_2023-06-21_final
2023-06-21 11:25:33	ga_ls8c_ard_3-2-1_111074_2023-06-21_final
2023-07-02 11:07:58	ga_ls8c_ard_3-2-1_108076_2023-07-02_final
2023-07-09 09:36:07	ga_ls8c_ard_3-2-1_093078_2023-07-09_final
2023-07-16 09:40:20	ga_ls8c_ard_3-2-1_094073_2023-07-16_final
2023-07-17 10:22:47	ga_ls8c_ard_3-2-1_101071_2023-07-17_final
2023-07-23 09:49:20	ga_ls8c_ard_3-2-1_095080_2023-07-23_final
2023-07-25 09:38:36	ga_ls8c_ard_3-2-1_093084_2023-07-25_final
2023-08-07 10:41:05	ga_ls8c_ard_3-2-1_104070_2023-08-07_final
2023-08-07 10:44:41	ga_ls8c_ard_3-2-1_104079_2023-08-07_final
2023-08-09 10:27:56	ga_ls8c_ard_3-2-1_102068_2023-08-09_final
2023-08-10 09:38:41	ga_ls8c_ard_3-2-1_093084_2023-08-10_final
2023-08-24 09:52:23	ga_ls8c_ard_3-2-1_095087_2023-08-24_final
2023-09-04 11:05:56	ga_ls8c_ard_3-2-1_108070_2023-09-04_final
2023-09-09 11:24:53	ga_ls8c_ard_3-2-1_111071_2023-09-09_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