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
2023-07-30 09:51:37	ga_ls8c_ard_3-2-1_096070_2023-07-30_final
2023-07-30 11:35:41	ga_ls8c_ard_3-2-1_112083_2023-07-30_final
2023-08-03 11:06:12	ga_ls8c_ard_3-2-1_108071_2023-08-03_final
2023-08-05 10:54:39	ga_ls8c_ard_3-2-1_106073_2023-08-05_final
2023-08-06 09:58:13	ga_ls8c_ard_3-2-1_097071_2023-08-06_final
2023-08-09 10:28:43	ga_ls8c_ard_3-2-1_102070_2023-08-09_final
2023-08-11 10:21:33	ga_ls8c_ard_3-2-1_100083_2023-08-11_final
2023-08-12 09:24:45	ga_ls8c_ard_3-2-1_091080_2023-08-11_final
2023-08-12 11:03:38	ga_ls8c_ard_3-2-1_107080_2023-08-12_final
2023-08-13 10:03:38	ga_ls8c_ard_3-2-1_098069_2023-08-13_final
2023-08-13 11:46:54	ga_ls8c_ard_3-2-1_114080_2023-08-13_final
2023-08-14 09:12:01	ga_ls8c_ard_3-2-1_089079_2023-08-13_final
2023-08-18 10:24:14	ga_ls8c_ard_3-2-1_101074_2023-08-18_final
2023-08-19 11:11:30	ga_ls8c_ard_3-2-1_108084_2023-08-19_final
2023-08-21 09:20:16	ga_ls8c_ard_3-2-1_090084_2023-08-20_final
2023-08-21 09:20:40	ga_ls8c_ard_3-2-1_090085_2023-08-20_final
2023-08-21 10:53:34	ga_ls8c_ard_3-2-1_106070_2023-08-21_final
2023-08-21 10:57:09	ga_ls8c_ard_3-2-1_106079_2023-08-21_final
2023-08-23 10:41:13	ga_ls8c_ard_3-2-1_104070_2023-08-23_final
2023-08-24 09:51:11	ga_ls8c_ard_3-2-1_095084_2023-08-24_final
2023-08-24 09:51:35	ga_ls8c_ard_3-2-1_095085_2023-08-24_final
2023-08-25 10:28:52	ga_ls8c_ard_3-2-1_102070_2023-08-25_final
2023-08-27 10:18:06	ga_ls8c_ard_3-2-1_100074_2023-08-27_final
2023-08-30 09:14:31	ga_ls8c_ard_3-2-1_089085_2023-08-29_final
2023-08-30 10:48:12	ga_ls8c_ard_3-2-1_105072_2023-08-30_final
2023-08-31 11:36:15	ga_ls8c_ard_3-2-1_112084_2023-08-31_final
2023-09-03 10:23:52	ga_ls8c_ard_3-2-1_101073_2023-09-03_final
2023-09-05 10:16:17	ga_ls8c_ard_3-2-1_099085_2023-09-05_final
2023-09-06 09:22:39	ga_ls8c_ard_3-2-1_090090_2023-09-05_final
2023-09-09 09:46:48	ga_ls8c_ard_3-2-1_095073_2023-09-09_final
2023-09-12 10:18:08	ga_ls8c_ard_3-2-1_100074_2023-09-12_final
2023-09-13 09:28:30	ga_ls8c_ard_3-2-1_091089_2023-09-12_final
2023-09-13 11:01:24	ga_ls8c_ard_3-2-1_107074_2023-09-13_final
2023-09-14 10:05:00	ga_ls8c_ard_3-2-1_098072_2023-09-14_final
2023-09-16 09:52:39	ga_ls8c_ard_3-2-1_096072_2023-09-16_final
2023-09-18 09:45:05	ga_ls8c_ard_3-2-1_094084_2023-09-18_final
2023-09-18 11:23:34	ga_ls8c_ard_3-2-1_110083_2023-09-18_final
2023-09-19 10:24:21	ga_ls8c_ard_3-2-1_101074_2023-09-19_final
2023-09-20 11:06:01	ga_ls8c_ard_3-2-1_108070_2023-09-20_final
2023-09-21 11:50:53	ga_ls8c_ard_3-2-1_115074_2023-09-21_final
2023-09-21 11:51:40	ga_ls8c_ard_3-2-1_115076_2023-09-21_final
2023-09-23 09:59:38	ga_ls8c_ard_3-2-1_097074_2023-09-23_final
2023-09-23 11:42:06	ga_ls8c_ard_3-2-1_113083_2023-09-23_final
2023-09-27 11:17:50	ga_ls8c_ard_3-2-1_109084_2023-09-27_final
2023-09-28 10:19:01	ga_ls8c_ard_3-2-1_100076_2023-09-28_final
2023-09-28 10:19:49	ga_ls8c_ard_3-2-1_100078_2023-09-28_final
2023-09-29 11:00:17	ga_ls8c_ard_3-2-1_107071_2023-09-29_final
2023-09-29 11:04:41	ga_ls8c_ard_3-2-1_107082_2023-09-29_final
2023-09-29 11:05:05	ga_ls8c_ard_3-2-1_107083_2023-09-29_final
2023-09-30 10:05:04	ga_ls8c_ard_3-2-1_098072_2023-09-30_final
2023-09-30 10:10:15	ga_ls8c_ard_3-2-1_098085_2023-09-30_final
2023-09-30 11:47:09	ga_ls8c_ard_3-2-1_114080_2023-09-30_final
2023-10-02 09:52:43	ga_ls8c_ard_3-2-1_096072_2023-10-02_final
2023-10-04 11:20:49	ga_ls8c_ard_3-2-1_110076_2023-10-04_final
2023-10-05 10:23:12	ga_ls8c_ard_3-2-1_101071_2023-10-05_final
2023-10-05 10:24:00	ga_ls8c_ard_3-2-1_101073_2023-10-05_final
2023-10-06 11:11:39	ga_ls8c_ard_3-2-1_108084_2023-10-06_final
2023-10-07 10:09:39	ga_ls8c_ard_3-2-1_099068_2023-10-07_final
2023-10-07 10:10:51	ga_ls8c_ard_3-2-1_099071_2023-10-07_final
2023-10-08 09:20:26	ga_ls8c_ard_3-2-1_090084_2023-10-07_final
2023-10-08 10:53:44	ga_ls8c_ard_3-2-1_106070_2023-10-08_final
2023-10-08 10:54:55	ga_ls8c_ard_3-2-1_106073_2023-10-08_final
2023-10-10 10:42:59	ga_ls8c_ard_3-2-1_104074_2023-10-10_final
2023-10-13 09:35:24	ga_ls8c_ard_3-2-1_093075_2023-10-13_final
2023-10-13 11:13:30	ga_ls8c_ard_3-2-1_109073_2023-10-13_final
2023-10-13 11:17:53	ga_ls8c_ard_3-2-1_109084_2023-10-13_final
2023-10-14 11:58:45	ga_ls8c_ard_3-2-1_116078_2023-10-14_final
2023-10-15 11:00:20	ga_ls8c_ard_3-2-1_107071_2023-10-15_final
2023-10-15 11:04:19	ga_ls8c_ard_3-2-1_107081_2023-10-15_final
2023-10-16 10:05:06	ga_ls8c_ard_3-2-1_098072_2023-10-16_final
2023-10-19 10:34:47	ga_ls8c_ard_3-2-1_103069_2023-10-19_final
2023-10-20 11:21:14	ga_ls8c_ard_3-2-1_110077_2023-10-20_final
2023-10-20 11:24:02	ga_ls8c_ard_3-2-1_110084_2023-10-20_final
2023-10-21 10:22:50	ga_ls8c_ard_3-2-1_101070_2023-10-21_final
2023-10-22 09:29:37	ga_ls8c_ard_3-2-1_092076_2023-10-21_final
2023-10-23 10:15:41	ga_ls8c_ard_3-2-1_099083_2023-10-23_final
2023-10-24 10:55:22	ga_ls8c_ard_3-2-1_106074_2023-10-24_final
2023-10-25 09:58:33	ga_ls8c_ard_3-2-1_097071_2023-10-25_final
2023-10-25 11:41:26	ga_ls8c_ard_3-2-1_113081_2023-10-25_final
2023-10-28 10:29:05	ga_ls8c_ard_3-2-1_102070_2023-10-28_final
2023-10-31 11:01:35	ga_ls8c_ard_3-2-1_107074_2023-10-31_final
2023-10-31 11:04:46	ga_ls8c_ard_3-2-1_107082_2023-10-31_final
2023-11-01 10:05:57	ga_ls8c_ard_3-2-1_098074_2023-11-01_final
2023-11-02 09:11:32	ga_ls8c_ard_3-2-1_089077_2023-11-01_final
2023-11-02 09:14:19	ga_ls8c_ard_3-2-1_089084_2023-11-01_final
2023-11-04 10:36:27	ga_ls8c_ard_3-2-1_103073_2023-11-04_final
2023-11-05 09:44:01	ga_ls8c_ard_3-2-1_094081_2023-11-05_final
2023-11-05 09:46:00	ga_ls8c_ard_3-2-1_094086_2023-11-05_final
2023-11-05 11:21:18	ga_ls8c_ard_3-2-1_110077_2023-11-05_final
2023-11-08 10:16:28	ga_ls8c_ard_3-2-1_099085_2023-11-08_final
2023-11-09 09:18:02	ga_ls8c_ard_3-2-1_090078_2023-11-08_final
2023-11-09 09:19:38	ga_ls8c_ard_3-2-1_090082_2023-11-08_final
2023-11-09 10:55:19	ga_ls8c_ard_3-2-1_106074_2023-11-09_final
2023-11-10 09:58:29	ga_ls8c_ard_3-2-1_097071_2023-11-10_final
2023-11-10 10:04:04	ga_ls8c_ard_3-2-1_097085_2023-11-10_final
2023-11-12 11:29:26	ga_ls8c_ard_3-2-1_111082_2023-11-12_final
2023-11-14 11:13:30	ga_ls8c_ard_3-2-1_109073_2023-11-14_final
2023-11-14 11:17:06	ga_ls8c_ard_3-2-1_109082_2023-11-14_final
2023-11-15 11:58:23	ga_ls8c_ard_3-2-1_116077_2023-11-15_final
2023-11-15 11:58:46	ga_ls8c_ard_3-2-1_116078_2023-11-15_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