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
2022-06-15 09:18:28	ga_ls8c_ard_3-2-1_090079_2022-06-14_final
2022-06-28 10:23:43	ga_ls8c_ard_3-2-1_101072_2022-06-28_final
2022-06-30 11:53:03	ga_ls8c_ard_3-2-1_115079_2022-06-30_final
2022-07-02 10:01:24	ga_ls8c_ard_3-2-1_097078_2022-07-02_final
2022-07-06 11:12:46	ga_ls8c_ard_3-2-1_109071_2022-07-06_final
2022-07-09 10:05:11	ga_ls8c_ard_3-2-1_098072_2022-07-09_final
2022-07-13 09:41:15	ga_ls8c_ard_3-2-1_094074_2022-07-13_final
2022-07-16 10:12:56	ga_ls8c_ard_3-2-1_099076_2022-07-16_final
2022-07-17 09:20:56	ga_ls8c_ard_3-2-1_090085_2022-07-16_final
2022-07-19 10:40:42	ga_ls8c_ard_3-2-1_104068_2022-07-19_final
2022-07-21 10:33:57	ga_ls8c_ard_3-2-1_102082_2022-07-21_final
2022-07-25 11:46:58	ga_ls8c_ard_3-2-1_114079_2022-07-25_final
2022-07-26 10:47:22	ga_ls8c_ard_3-2-1_105069_2022-07-26_final
2022-08-02 09:20:43	ga_ls8c_ard_3-2-1_090084_2022-08-01_final
2022-08-05 11:25:45	ga_ls8c_ard_3-2-1_111072_2022-08-05_final
2022-08-10 11:45:07	ga_ls8c_ard_3-2-1_114074_2022-08-10_final
2022-08-14 09:41:32	ga_ls8c_ard_3-2-1_094074_2022-08-14_final
2022-08-16 11:08:28	ga_ls8c_ard_3-2-1_108075_2022-08-16_final
2022-08-22 10:29:24	ga_ls8c_ard_3-2-1_102070_2022-08-22_final
2022-08-23 11:12:16	ga_ls8c_ard_3-2-1_109069_2022-08-23_final
2022-08-25 11:00:18	ga_ls8c_ard_3-2-1_107070_2022-08-25_final
2022-08-26 11:46:22	ga_ls8c_ard_3-2-1_114077_2022-08-26_final
2022-08-27 10:48:45	ga_ls8c_ard_3-2-1_105072_2022-08-27_final
2022-09-05 10:42:58	ga_ls8c_ard_3-2-1_104073_2022-09-05_final
2022-09-06 09:51:45	ga_ls8c_ard_3-2-1_095084_2022-09-06_final
2022-09-08 11:15:06	ga_ls8c_ard_3-2-1_109076_2022-09-08_final
2022-09-10 09:25:04	ga_ls8c_ard_3-2-1_091079_2022-09-09_final
2022-09-10 09:25:28	ga_ls8c_ard_3-2-1_091080_2022-09-09_final
2022-09-12 10:53:12	ga_ls8c_ard_3-2-1_105083_2022-09-12_final
2022-09-15 11:19:20	ga_ls8c_ard_3-2-1_110071_2022-09-15_final
2022-09-17 11:12:10	ga_ls8c_ard_3-2-1_108084_2022-09-17_final
2022-09-24 11:13:59	ga_ls8c_ard_3-2-1_109073_2022-09-24_final
2022-10-03 11:06:58	ga_ls8c_ard_3-2-1_108071_2022-10-03_final
2022-10-04 11:51:25	ga_ls8c_ard_3-2-1_115074_2022-10-04_final
2022-10-05 10:55:00	ga_ls8c_ard_3-2-1_106072_2022-10-05_final
2022-10-06 09:58:58	ga_ls8c_ard_3-2-1_097071_2022-10-06_final
2022-10-12 09:24:12	ga_ls8c_ard_3-2-1_091077_2022-10-11_final
2022-10-15 11:32:23	ga_ls8c_ard_3-2-1_112073_2022-10-15_final
2022-10-17 09:44:45	ga_ls8c_ard_3-2-1_094082_2022-10-17_final
2022-10-21 10:55:46	ga_ls8c_ard_3-2-1_106074_2022-10-21_final
2022-10-22 09:59:21	ga_ls8c_ard_3-2-1_097072_2022-10-22_final
2022-10-25 10:30:17	ga_ls8c_ard_3-2-1_102072_2022-10-25_final
2022-10-29 11:46:04	ga_ls8c_ard_3-2-1_114076_2022-10-29_final
2022-10-30 09:13:09	ga_ls8c_ard_3-2-1_089080_2022-10-29_final
2022-11-02 09:44:28	ga_ls8c_ard_3-2-1_094081_2022-11-02_final
2022-11-03 10:26:31	ga_ls8c_ard_3-2-1_101078_2022-11-03_final
2022-11-04 11:06:59	ga_ls8c_ard_3-2-1_108071_2022-11-04_final
2022-11-06 10:58:13	ga_ls8c_ard_3-2-1_106080_2022-11-06_final
2022-11-08 10:43:03	ga_ls8c_ard_3-2-1_104073_2022-11-08_final
2022-11-09 11:27:06	ga_ls8c_ard_3-2-1_111075_2022-11-09_final
2022-11-09 11:29:30	ga_ls8c_ard_3-2-1_111081_2022-11-09_final
2022-11-14 11:46:47	ga_ls8c_ard_3-2-1_114078_2022-11-14_final
2022-11-15 09:13:04	ga_ls8c_ard_3-2-1_089080_2022-11-14_final
2022-11-16 09:53:07	ga_ls8c_ard_3-2-1_096072_2022-11-16_final
2022-11-16 09:53:55	ga_ls8c_ard_3-2-1_096074_2022-11-16_final
2022-11-20 09:32:23	ga_ls8c_ard_3-2-1_092082_2022-11-20_final
2022-11-23 09:59:42	ga_ls8c_ard_3-2-1_097073_2022-11-23_final
2022-11-27 09:38:12	ga_ls8c_ard_3-2-1_093081_2022-11-27_final
2022-11-27 09:38:59	ga_ls8c_ard_3-2-1_093083_2022-11-27_final
2022-11-29 09:25:02	ga_ls8c_ard_3-2-1_091079_2022-11-28_final
2022-11-30 11:45:35	ga_ls8c_ard_3-2-1_114075_2022-11-30_final
2022-12-02 09:52:21	ga_ls8c_ard_3-2-1_096070_2022-12-02_final
2022-12-03 10:34:49	ga_ls8c_ard_3-2-1_103068_2022-12-03_final
2022-12-08 09:19:38	ga_ls8c_ard_3-2-1_090081_2022-12-07_final
2022-12-10 10:44:33	ga_ls8c_ard_3-2-1_104077_2022-12-10_final
2022-12-10 10:44:57	ga_ls8c_ard_3-2-1_104078_2022-12-10_final
2022-12-12 10:30:11	ga_ls8c_ard_3-2-1_102072_2022-12-12_final
2022-12-13 09:40:32	ga_ls8c_ard_3-2-1_093087_2022-12-13_final
2022-12-14 11:58:41	ga_ls8c_ard_3-2-1_116077_2022-12-14_final
2022-12-16 11:45:30	ga_ls8c_ard_3-2-1_114075_2022-12-16_final
2022-12-17 09:12:59	ga_ls8c_ard_3-2-1_089080_2022-12-16_final
2022-12-18 11:36:18	ga_ls8c_ard_3-2-1_112083_2022-12-18_final
2022-12-24 10:57:34	ga_ls8c_ard_3-2-1_106079_2022-12-24_final
2022-12-25 10:03:57	ga_ls8c_ard_3-2-1_097084_2022-12-25_final
2022-12-27 09:52:24	ga_ls8c_ard_3-2-1_095086_2022-12-27_final
2022-12-31 11:02:35	ga_ls8c_ard_3-2-1_107076_2022-12-31_final
2022-12-31 11:05:46	ga_ls8c_ard_3-2-1_107084_2022-12-31_final
2023-01-10 11:39:14	ga_ls8c_ard_3-2-1_113075_2023-01-10_final
2023-01-11 10:42:48	ga_ls8c_ard_3-2-1_104073_2023-01-11_final
2023-01-11 10:45:11	ga_ls8c_ard_3-2-1_104079_2023-01-11_final
2023-01-12 11:30:26	ga_ls8c_ard_3-2-1_111084_2023-01-12_final
2023-01-16 11:04:27	ga_ls8c_ard_3-2-1_107081_2023-01-16_final
2023-01-17 11:46:30	ga_ls8c_ard_3-2-1_114078_2023-01-17_final
2023-01-19 09:53:40	ga_ls8c_ard_3-2-1_096074_2023-01-19_final
2023-01-20 10:40:09	ga_ls8c_ard_3-2-1_103082_2023-01-20_final
2023-01-21 11:21:02	ga_ls8c_ard_3-2-1_110076_2023-01-21_final
2023-01-25 09:20:39	ga_ls8c_ard_3-2-1_090084_2023-01-24_final
2023-01-26 10:01:56	ga_ls8c_ard_3-2-1_097079_2023-01-26_final
2023-02-08 09:29:25	ga_ls8c_ard_3-2-1_092075_2023-02-07_final
2023-02-09 10:15:52	ga_ls8c_ard_3-2-1_099083_2023-02-09_final
2023-02-10 09:20:37	ga_ls8c_ard_3-2-1_090084_2023-02-09_final
2023-02-13 09:47:29	ga_ls8c_ard_3-2-1_095074_2023-02-13_final
2023-02-15 09:35:54	ga_ls8c_ard_3-2-1_093076_2023-02-15_final
2023-02-17 11:02:24	ga_ls8c_ard_3-2-1_107076_2023-02-17_final
2023-02-18 11:45:38	ga_ls8c_ard_3-2-1_114076_2023-02-18_final
2023-02-27 10:01:13	ga_ls8c_ard_3-2-1_097078_2023-02-27_final
2023-03-01 09:50:27	ga_ls8c_ard_3-2-1_095082_2023-03-01_final
2023-03-03 11:14:34	ga_ls8c_ard_3-2-1_109076_2023-03-03_final
2023-03-05 11:00:12	ga_ls8c_ard_3-2-1_107071_2023-03-05_final
2023-03-06 11:46:14	ga_ls8c_ard_3-2-1_114078_2023-03-06_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