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
2022-08-21 09:47:20	ga_ls8c_ard_3-2-1_095073_2022-08-21_final
2022-08-21 11:26:37	ga_ls8c_ard_3-2-1_111074_2022-08-21_final
2022-09-04 11:38:11	ga_ls8c_ard_3-2-1_113072_2022-09-04_final
2022-09-10 09:23:29	ga_ls8c_ard_3-2-1_091075_2022-09-09_final
2022-09-12 10:52:25	ga_ls8c_ard_3-2-1_105081_2022-09-12_final
2022-09-13 11:36:29	ga_ls8c_ard_3-2-1_112083_2022-09-13_final
2022-09-15 09:41:15	ga_ls8c_ard_3-2-1_094073_2022-09-15_final
2022-09-17 09:31:42	ga_ls8c_ard_3-2-1_092080_2022-09-17_final
2022-09-17 11:06:35	ga_ls8c_ard_3-2-1_108070_2022-09-17_final
2022-09-24 09:39:29	ga_ls8c_ard_3-2-1_093084_2022-09-24_final
2022-09-26 09:23:32	ga_ls8c_ard_3-2-1_091075_2022-09-25_final
2022-09-28 09:14:45	ga_ls8c_ard_3-2-1_089084_2022-09-27_final
2022-09-28 10:52:27	ga_ls8c_ard_3-2-1_105081_2022-09-28_final
2022-10-03 09:34:28	ga_ls8c_ard_3-2-1_092087_2022-10-03_final
2022-10-03 11:07:46	ga_ls8c_ard_3-2-1_108073_2022-10-03_final
2022-10-04 10:15:20	ga_ls8c_ard_3-2-1_099081_2022-10-04_final
2022-10-07 10:41:01	ga_ls8c_ard_3-2-1_104068_2022-10-07_final
2022-10-08 09:46:35	ga_ls8c_ard_3-2-1_095071_2022-10-08_final
2022-10-08 09:47:23	ga_ls8c_ard_3-2-1_095073_2022-10-08_final
2022-10-08 09:52:34	ga_ls8c_ard_3-2-1_095086_2022-10-08_final
2022-10-08 11:25:28	ga_ls8c_ard_3-2-1_111071_2022-10-08_final
2022-10-10 11:15:04	ga_ls8c_ard_3-2-1_109076_2022-10-10_final
2022-10-12 11:05:52	ga_ls8c_ard_3-2-1_107084_2022-10-12_final
2022-10-13 10:07:50	ga_ls8c_ard_3-2-1_098078_2022-10-13_final
2022-10-14 09:12:12	ga_ls8c_ard_3-2-1_089078_2022-10-13_final
2022-10-14 10:48:18	ga_ls8c_ard_3-2-1_105071_2022-10-14_final
2022-10-14 10:52:17	ga_ls8c_ard_3-2-1_105081_2022-10-14_final
2022-10-16 10:35:10	ga_ls8c_ard_3-2-1_103069_2022-10-16_final
2022-10-19 09:34:48	ga_ls8c_ard_3-2-1_092088_2022-10-19_final
2022-10-22 09:58:57	ga_ls8c_ard_3-2-1_097071_2022-10-22_final
2022-10-24 09:47:01	ga_ls8c_ard_3-2-1_095072_2022-10-24_final
2022-10-25 10:30:41	ga_ls8c_ard_3-2-1_102073_2022-10-25_final
2022-10-30 09:15:09	ga_ls8c_ard_3-2-1_089085_2022-10-29_final
2022-10-30 09:15:33	ga_ls8c_ard_3-2-1_089086_2022-10-29_final
2022-11-02 09:41:16	ga_ls8c_ard_3-2-1_094073_2022-11-02_final
2022-11-02 09:44:28	ga_ls8c_ard_3-2-1_094081_2022-11-02_final
2022-11-05 10:11:46	ga_ls8c_ard_3-2-1_099072_2022-11-05_final
2022-11-06 09:23:19	ga_ls8c_ard_3-2-1_090090_2022-11-05_final
2022-11-06 10:54:13	ga_ls8c_ard_3-2-1_106070_2022-11-06_final
2022-11-08 10:45:03	ga_ls8c_ard_3-2-1_104078_2022-11-08_final
2022-11-09 09:52:36	ga_ls8c_ard_3-2-1_095086_2022-11-09_final
2022-11-13 11:00:45	ga_ls8c_ard_3-2-1_107071_2022-11-13_final
2022-11-14 10:03:55	ga_ls8c_ard_3-2-1_098068_2022-11-14_final
2022-11-15 09:12:16	ga_ls8c_ard_3-2-1_089078_2022-11-14_final
2022-11-15 09:13:52	ga_ls8c_ard_3-2-1_089082_2022-11-14_final
2022-11-15 10:47:57	ga_ls8c_ard_3-2-1_105070_2022-11-15_final
2022-11-22 10:58:07	ga_ls8c_ard_3-2-1_106080_2022-11-22_final
2022-11-23 10:01:42	ga_ls8c_ard_3-2-1_097078_2022-11-23_final
2022-11-23 10:04:30	ga_ls8c_ard_3-2-1_097085_2022-11-23_final
2022-11-27 09:37:48	ga_ls8c_ard_3-2-1_093080_2022-11-27_final
2022-11-27 09:38:12	ga_ls8c_ard_3-2-1_093081_2022-11-27_final
2022-11-27 11:15:05	ga_ls8c_ard_3-2-1_109076_2022-11-27_final
2022-11-30 10:07:54	ga_ls8c_ard_3-2-1_098078_2022-11-30_final
2022-12-01 09:14:40	ga_ls8c_ard_3-2-1_089084_2022-11-30_final
2022-12-01 10:52:22	ga_ls8c_ard_3-2-1_105081_2022-12-01_final
2022-12-02 11:32:50	ga_ls8c_ard_3-2-1_112074_2022-12-02_final
2022-12-06 11:12:05	ga_ls8c_ard_3-2-1_108084_2022-12-06_final
2022-12-07 10:10:53	ga_ls8c_ard_3-2-1_099070_2022-12-07_final
2022-12-10 10:42:57	ga_ls8c_ard_3-2-1_104073_2022-12-10_final
2022-12-12 10:28:59	ga_ls8c_ard_3-2-1_102069_2022-12-12_final
2022-12-14 10:17:48	ga_ls8c_ard_3-2-1_100072_2022-12-14_final
2022-12-15 11:00:39	ga_ls8c_ard_3-2-1_107071_2022-12-15_final
2022-12-18 09:57:49	ga_ls8c_ard_3-2-1_096084_2022-12-18_final
2022-12-20 11:21:31	ga_ls8c_ard_3-2-1_110077_2022-12-20_final
2022-12-20 11:24:19	ga_ls8c_ard_3-2-1_110084_2022-12-20_final
2022-12-23 10:14:41	ga_ls8c_ard_3-2-1_099080_2022-12-23_final
2022-12-31 09:27:17	ga_ls8c_ard_3-2-1_091085_2022-12-30_final
2023-01-02 09:14:56	ga_ls8c_ard_3-2-1_089085_2023-01-01_final
2023-01-02 10:47:26	ga_ls8c_ard_3-2-1_105069_2023-01-02_final
2023-01-04 10:35:52	ga_ls8c_ard_3-2-1_103071_2023-01-04_final
2023-01-08 10:13:31	ga_ls8c_ard_3-2-1_099077_2023-01-08_final
2023-01-09 09:19:53	ga_ls8c_ard_3-2-1_090082_2023-01-08_final
2023-01-10 10:04:20	ga_ls8c_ard_3-2-1_097085_2023-01-10_final
2023-01-10 11:42:25	ga_ls8c_ard_3-2-1_113083_2023-01-10_final
2023-01-11 10:43:36	ga_ls8c_ard_3-2-1_104075_2023-01-11_final
2023-01-12 11:26:27	ga_ls8c_ard_3-2-1_111074_2023-01-12_final
2023-01-12 11:30:26	ga_ls8c_ard_3-2-1_111084_2023-01-12_final
2023-01-16 11:01:40	ga_ls8c_ard_3-2-1_107074_2023-01-16_final
2023-01-18 09:12:23	ga_ls8c_ard_3-2-1_089079_2023-01-17_final
2023-01-18 09:13:11	ga_ls8c_ard_3-2-1_089081_2023-01-17_final
2023-01-18 10:49:17	ga_ls8c_ard_3-2-1_105074_2023-01-18_final
2023-01-18 10:50:04	ga_ls8c_ard_3-2-1_105076_2023-01-18_final
2023-01-21 09:46:32	ga_ls8c_ard_3-2-1_094087_2023-01-21_final
2023-01-23 11:07:29	ga_ls8c_ard_3-2-1_108073_2023-01-23_final
2023-01-24 10:13:52	ga_ls8c_ard_3-2-1_099078_2023-01-24_final
2023-01-24 11:51:34	ga_ls8c_ard_3-2-1_115075_2023-01-24_final
2023-01-25 10:55:33	ga_ls8c_ard_3-2-1_106074_2023-01-25_final
2023-01-25 10:56:45	ga_ls8c_ard_3-2-1_106077_2023-01-25_final
2023-02-06 11:20:40	ga_ls8c_ard_3-2-1_110075_2023-02-06_final
2023-02-12 09:07:26	ga_ls8c_ard_3-2-1_088082_2023-02-11_final
2023-02-12 10:45:31	ga_ls8c_ard_3-2-1_104080_2023-02-12_final
2023-02-16 10:22:21	ga_ls8c_ard_3-2-1_100084_2023-02-16_final
2023-02-24 11:11:13	ga_ls8c_ard_3-2-1_108083_2023-02-24_final
2023-02-25 11:52:27	ga_ls8c_ard_3-2-1_115078_2023-02-25_final
2023-02-26 10:55:14	ga_ls8c_ard_3-2-1_106074_2023-02-26_final
2023-02-27 10:03:37	ga_ls8c_ard_3-2-1_097084_2023-02-27_final
2023-02-27 11:42:06	ga_ls8c_ard_3-2-1_113083_2023-02-27_final
2023-03-05 09:28:06	ga_ls8c_ard_3-2-1_091088_2023-03-04_final
2023-03-06 10:05:45	ga_ls8c_ard_3-2-1_098074_2023-03-06_final
2023-03-08 09:52:34	ga_ls8c_ard_3-2-1_096072_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