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
2018-12-16 08:10:35	ga_ls8c_ard_3-2-1_079080_2018-12-15_final
2020-06-12 08:10:20	ga_ls8c_ard_3-2-1_079080_2020-06-11_final
2021-01-06 08:10:58	ga_ls8c_ard_3-2-1_079080_2021-01-05_final
2023-01-24 10:09:05	ga_ls8c_ard_3-2-1_099066_2023-01-24_final
2023-03-04 11:57:25	ga_ls8c_ard_3-2-1_116075_2023-03-04_final
2023-07-26 10:21:04	ga_ls8c_ard_3-2-1_100082_2023-07-26_final
2023-07-29 10:51:37	ga_ls8c_ard_3-2-1_105081_2023-07-29_final
2023-08-03 09:29:19	ga_ls8c_ard_3-2-1_092076_2023-08-02_final
2023-08-04 10:11:23	ga_ls8c_ard_3-2-1_099073_2023-08-04_final
2023-08-04 10:12:35	ga_ls8c_ard_3-2-1_099076_2023-08-04_final
2023-08-05 09:19:21	ga_ls8c_ard_3-2-1_090082_2023-08-04_final
2023-08-06 09:59:25	ga_ls8c_ard_3-2-1_097074_2023-08-06_final
2023-08-11 10:17:57	ga_ls8c_ard_3-2-1_100074_2023-08-11_final
2023-08-11 10:21:09	ga_ls8c_ard_3-2-1_100082_2023-08-11_final
2023-08-20 11:51:58	ga_ls8c_ard_3-2-1_115077_2023-08-20_final
2023-08-21 10:57:09	ga_ls8c_ard_3-2-1_106079_2023-08-21_final
2023-08-22 10:01:32	ga_ls8c_ard_3-2-1_097079_2023-08-22_final
2023-08-25 10:33:39	ga_ls8c_ard_3-2-1_102082_2023-08-25_final
2023-08-28 11:01:22	ga_ls8c_ard_3-2-1_107074_2023-08-28_final
2023-08-30 09:12:55	ga_ls8c_ard_3-2-1_089081_2023-08-29_final
2023-09-08 10:41:12	ga_ls8c_ard_3-2-1_104070_2023-09-08_final
2023-09-12 10:18:56	ga_ls8c_ard_3-2-1_100076_2023-09-12_final
2023-09-13 09:26:07	ga_ls8c_ard_3-2-1_091083_2023-09-12_final
2023-09-18 09:45:05	ga_ls8c_ard_3-2-1_094084_2023-09-18_final
2023-09-24 10:44:30	ga_ls8c_ard_3-2-1_104078_2023-09-24_final
2023-09-29 09:27:00	ga_ls8c_ard_3-2-1_091085_2023-09-28_final
2023-09-29 09:28:11	ga_ls8c_ard_3-2-1_091088_2023-09-28_final
2023-10-06 11:11:39	ga_ls8c_ard_3-2-1_108084_2023-10-06_final
2023-10-09 11:41:23	ga_ls8c_ard_3-2-1_113081_2023-10-09_final
2023-10-09 11:41:47	ga_ls8c_ard_3-2-1_113082_2023-10-09_final
2023-10-10 10:40:59	ga_ls8c_ard_3-2-1_104069_2023-10-10_final
2023-10-13 11:15:05	ga_ls8c_ard_3-2-1_109077_2023-10-13_final
2023-10-13 11:17:05	ga_ls8c_ard_3-2-1_109082_2023-10-13_final
2023-10-16 11:44:47	ga_ls8c_ard_3-2-1_114074_2023-10-16_final
2023-10-22 11:10:06	ga_ls8c_ard_3-2-1_108080_2023-10-22_final
2023-10-25 09:59:21	ga_ls8c_ard_3-2-1_097073_2023-10-25_final
2023-10-25 09:59:45	ga_ls8c_ard_3-2-1_097074_2023-10-25_final
2023-10-29 09:39:03	ga_ls8c_ard_3-2-1_093084_2023-10-29_final
2023-10-29 09:39:27	ga_ls8c_ard_3-2-1_093085_2023-10-29_final
2023-10-29 11:12:45	ga_ls8c_ard_3-2-1_109071_2023-10-29_final
2023-10-30 10:17:55	ga_ls8c_ard_3-2-1_100073_2023-10-30_final
2023-11-01 11:47:14	ga_ls8c_ard_3-2-1_114080_2023-11-01_final
2023-11-02 09:14:19	ga_ls8c_ard_3-2-1_089084_2023-11-01_final
2023-11-03 09:52:48	ga_ls8c_ard_3-2-1_096072_2023-11-03_final
2023-11-05 09:45:36	ga_ls8c_ard_3-2-1_094085_2023-11-05_final
2023-11-06 10:24:52	ga_ls8c_ard_3-2-1_101075_2023-11-06_final
2023-11-07 11:10:54	ga_ls8c_ard_3-2-1_108082_2023-11-07_final
2023-11-10 09:58:53	ga_ls8c_ard_3-2-1_097072_2023-11-10_final
2023-11-10 11:41:46	ga_ls8c_ard_3-2-1_113082_2023-11-10_final
2023-11-12 09:51:45	ga_ls8c_ard_3-2-1_095085_2023-11-12_final
2023-11-14 09:37:49	ga_ls8c_ard_3-2-1_093081_2023-11-14_final
2023-11-17 10:05:57	ga_ls8c_ard_3-2-1_098074_2023-11-17_final
2023-11-21 09:45:39	ga_ls8c_ard_3-2-1_094085_2023-11-21_final
2023-11-21 11:18:57	ga_ls8c_ard_3-2-1_110071_2023-11-21_final
2023-11-25 10:58:38	ga_ls8c_ard_3-2-1_106082_2023-11-25_final
2023-11-28 09:47:50	ga_ls8c_ard_3-2-1_095075_2023-11-28_final
2023-11-29 10:29:06	ga_ls8c_ard_3-2-1_102070_2023-11-29_final
2023-12-03 10:08:18	ga_ls8c_ard_3-2-1_098080_2023-12-03_final
2023-12-04 10:47:57	ga_ls8c_ard_3-2-1_105071_2023-12-04_final
2023-12-06 10:35:33	ga_ls8c_ard_3-2-1_103071_2023-12-06_final
2023-12-06 10:39:08	ga_ls8c_ard_3-2-1_103080_2023-12-06_final
2023-12-12 10:01:43	ga_ls8c_ard_3-2-1_097079_2023-12-12_final
2023-12-12 10:03:18	ga_ls8c_ard_3-2-1_097083_2023-12-12_final
2023-12-12 11:39:00	ga_ls8c_ard_3-2-1_113075_2023-12-12_final
2023-12-13 10:41:24	ga_ls8c_ard_3-2-1_104070_2023-12-13_final
2023-12-16 11:16:43	ga_ls8c_ard_3-2-1_109081_2023-12-16_final
2023-12-19 10:05:57	ga_ls8c_ard_3-2-1_098074_2023-12-19_final
2023-12-23 11:22:55	ga_ls8c_ard_3-2-1_110081_2023-12-23_final
2024-01-07 10:36:44	ga_ls8c_ard_3-2-1_103074_2024-01-07_final
2024-01-07 10:37:56	ga_ls8c_ard_3-2-1_103077_2024-01-07_final
2024-01-08 11:23:12	ga_ls8c_ard_3-2-1_110082_2024-01-08_final
2024-01-10 11:06:28	ga_ls8c_ard_3-2-1_108071_2024-01-10_final
2024-01-11 10:16:26	ga_ls8c_ard_3-2-1_099085_2024-01-11_final
2024-01-13 11:37:47	ga_ls8c_ard_3-2-1_113072_2024-01-13_final
2024-01-24 11:23:08	ga_ls8c_ard_3-2-1_110082_2024-01-24_final
2024-01-24 11:23:56	ga_ls8c_ard_3-2-1_110084_2024-01-24_final
2024-01-25 10:24:18	ga_ls8c_ard_3-2-1_101074_2024-01-25_final
2024-01-27 10:15:07	ga_ls8c_ard_3-2-1_099082_2024-01-27_final
2024-01-29 11:40:52	ga_ls8c_ard_3-2-1_113080_2024-01-29_final
2024-02-02 09:34:55	ga_ls8c_ard_3-2-1_093074_2024-02-02_final
2024-02-05 11:45:07	ga_ls8c_ard_3-2-1_114075_2024-02-05_final
2024-02-06 10:52:42	ga_ls8c_ard_3-2-1_105083_2024-02-06_final
2024-02-27 11:06:46	ga_ls8c_ard_3-2-1_108072_2024-02-27_final
2024-02-29 10:57:34	ga_ls8c_ard_3-2-1_106080_2024-02-29_final
2024-03-01 10:03:31	ga_ls8c_ard_3-2-1_097084_2024-03-01_final
2024-03-03 09:50:20	ga_ls8c_ard_3-2-1_095082_2024-03-03_final
2024-03-03 11:28:49	ga_ls8c_ard_3-2-1_111081_2024-03-03_final
2024-03-03 11:29:13	ga_ls8c_ard_3-2-1_111082_2024-03-03_final
2024-03-08 10:06:00	ga_ls8c_ard_3-2-1_098075_2024-03-08_final
2024-03-15 10:16:08	ga_ls8c_ard_3-2-1_099085_2024-03-15_nrt
2024-03-19 09:51:22	ga_ls8c_ard_3-2-1_095085_2024-03-19_nrt
2024-03-24 11:45:55	ga_ls8c_ard_3-2-1_114078_2024-03-24_nrt
2024-03-28 11:23:53	ga_ls8c_ard_3-2-1_110085_2024-03-28_nrt
2024-04-01 09:18:18	ga_ls8c_ard_3-2-1_090080_2024-03-31_nrt
2024-04-01 10:55:35	ga_ls8c_ard_3-2-1_106076_2024-04-01_nrt
2024-04-03 10:41:14	ga_ls8c_ard_3-2-1_104071_2024-04-03_final
2024-04-04 11:29:41	ga_ls8c_ard_3-2-1_111084_2024-04-04_final
2024-04-08 09:24:52	ga_ls8c_ard_3-2-1_091081_2024-04-07_nrt
2024-04-09 11:45:01	ga_ls8c_ard_3-2-1_114076_2024-04-09_nrt
2024-04-15 09:32:35	ga_ls8c_ard_3-2-1_092085_2024-04-15_nrt

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