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
2023-02-03 09:12:54	ga_ls8c_ard_3-2-1_089080_2023-02-02_final
2023-03-13 11:51:35	ga_ls8c_ard_3-2-1_115076_2023-03-13_final
2023-03-19 11:13:14	ga_ls8c_ard_3-2-1_109073_2023-03-19_final
2023-03-22 11:46:05	ga_ls8c_ard_3-2-1_114078_2023-03-22_final
2023-03-23 10:46:51	ga_ls8c_ard_3-2-1_105069_2023-03-23_final
2023-05-02 11:41:06	ga_ls8c_ard_3-2-1_113082_2023-05-02_final
2023-05-03 09:06:59	ga_ls8c_ard_3-2-1_088083_2023-05-02_final
2023-05-08 11:00:44	ga_ls8c_ard_3-2-1_107074_2023-05-08_final
2023-05-15 11:10:25	ga_ls8c_ard_3-2-1_108083_2023-05-15_final
2023-05-20 09:49:40	ga_ls8c_ard_3-2-1_095082_2023-05-20_final
2023-05-22 11:12:37	ga_ls8c_ard_3-2-1_109073_2023-05-22_final
2023-05-25 11:46:20	ga_ls8c_ard_3-2-1_114080_2023-05-25_final
2023-05-26 09:11:01	ga_ls8c_ard_3-2-1_089078_2023-05-25_final
2023-05-29 11:18:01	ga_ls8c_ard_3-2-1_110071_2023-05-29_final
2023-06-01 10:12:02	ga_ls8c_ard_3-2-1_099076_2023-06-01_final
2023-06-05 09:51:45	ga_ls8c_ard_3-2-1_095087_2023-06-05_final
2023-06-08 10:17:54	ga_ls8c_ard_3-2-1_100075_2023-06-08_final
2023-06-09 09:23:05	ga_ls8c_ard_3-2-1_091077_2023-06-08_final
2023-06-11 09:11:09	ga_ls8c_ard_3-2-1_089078_2023-06-10_final
2023-06-12 11:35:18	ga_ls8c_ard_3-2-1_112083_2023-06-12_final
2023-06-15 10:22:33	ga_ls8c_ard_3-2-1_101071_2023-06-15_final
2023-06-15 10:25:20	ga_ls8c_ard_3-2-1_101078_2023-06-15_final
2023-07-11 11:04:39	ga_ls8c_ard_3-2-1_107083_2023-07-11_final
2023-07-12 11:44:20	ga_ls8c_ard_3-2-1_114074_2023-07-12_final
2023-07-12 11:47:07	ga_ls8c_ard_3-2-1_114081_2023-07-12_final
2023-07-20 10:54:53	ga_ls8c_ard_3-2-1_106074_2023-07-20_final
2023-07-23 09:50:56	ga_ls8c_ard_3-2-1_095084_2023-07-23_final
2023-07-27 10:59:58	ga_ls8c_ard_3-2-1_107071_2023-07-27_final
2023-07-27 11:01:57	ga_ls8c_ard_3-2-1_107076_2023-07-27_final
2023-07-28 10:06:21	ga_ls8c_ard_3-2-1_098076_2023-07-28_final
2023-07-29 09:11:08	ga_ls8c_ard_3-2-1_089077_2023-07-28_final
2023-07-29 10:46:49	ga_ls8c_ard_3-2-1_105069_2023-07-29_final
2023-08-05 10:54:39	ga_ls8c_ard_3-2-1_106073_2023-08-05_final
2023-08-10 11:13:11	ga_ls8c_ard_3-2-1_109073_2023-08-10_final
2023-08-17 09:45:45	ga_ls8c_ard_3-2-1_094086_2023-08-17_final
2023-08-18 10:25:26	ga_ls8c_ard_3-2-1_101077_2023-08-18_final
2023-08-19 11:05:55	ga_ls8c_ard_3-2-1_108070_2023-08-19_final
2023-08-20 10:15:29	ga_ls8c_ard_3-2-1_099083_2023-08-20_final
2023-08-21 10:53:58	ga_ls8c_ard_3-2-1_106071_2023-08-21_final
2023-08-24 09:46:48	ga_ls8c_ard_3-2-1_095073_2023-08-24_final
2023-08-24 11:29:40	ga_ls8c_ard_3-2-1_111083_2023-08-24_final
2023-08-26 09:39:14	ga_ls8c_ard_3-2-1_093085_2023-08-26_final
2023-08-27 10:18:54	ga_ls8c_ard_3-2-1_100076_2023-08-27_final
2023-08-29 11:47:25	ga_ls8c_ard_3-2-1_114081_2023-08-29_final
2023-08-30 09:14:31	ga_ls8c_ard_3-2-1_089085_2023-08-29_final
2023-08-31 11:36:15	ga_ls8c_ard_3-2-1_112084_2023-08-31_final
2023-09-10 10:28:52	ga_ls8c_ard_3-2-1_102070_2023-09-10_final
2023-09-11 09:35:15	ga_ls8c_ard_3-2-1_093075_2023-09-11_final
2023-09-13 11:01:24	ga_ls8c_ard_3-2-1_107074_2023-09-13_final
2023-09-14 10:09:23	ga_ls8c_ard_3-2-1_098083_2023-09-14_final
2023-09-16 09:52:15	ga_ls8c_ard_3-2-1_096071_2023-09-16_final
2023-09-17 10:34:43	ga_ls8c_ard_3-2-1_103069_2023-09-17_final
2023-09-18 09:44:17	ga_ls8c_ard_3-2-1_094082_2023-09-18_final
2023-09-19 10:25:09	ga_ls8c_ard_3-2-1_101076_2023-09-19_final
2023-09-21 10:14:23	ga_ls8c_ard_3-2-1_099080_2023-09-21_final
2023-09-22 10:54:03	ga_ls8c_ard_3-2-1_106071_2023-09-22_final
2023-09-29 09:26:12	ga_ls8c_ard_3-2-1_091083_2023-09-28_final
2023-09-30 11:47:09	ga_ls8c_ard_3-2-1_114080_2023-09-30_final
2023-10-05 10:24:00	ga_ls8c_ard_3-2-1_101073_2023-10-05_final
2023-10-05 10:24:48	ga_ls8c_ard_3-2-1_101075_2023-10-05_final
2023-10-14 10:21:52	ga_ls8c_ard_3-2-1_100083_2023-10-14_final
2023-10-15 11:00:44	ga_ls8c_ard_3-2-1_107072_2023-10-15_final
2023-10-16 10:07:54	ga_ls8c_ard_3-2-1_098079_2023-10-16_final
2023-10-26 10:40:38	ga_ls8c_ard_3-2-1_104068_2023-10-26_final
2023-10-26 10:41:02	ga_ls8c_ard_3-2-1_104069_2023-10-26_final
2023-10-29 11:17:08	ga_ls8c_ard_3-2-1_109082_2023-10-29_final
2023-11-14 11:12:18	ga_ls8c_ard_3-2-1_109070_2023-11-14_final
2023-11-14 11:17:06	ga_ls8c_ard_3-2-1_109082_2023-11-14_final
2023-12-03 10:07:54	ga_ls8c_ard_3-2-1_098079_2023-12-03_final
2023-12-06 10:37:56	ga_ls8c_ard_3-2-1_103077_2023-12-06_final
2023-12-07 09:44:18	ga_ls8c_ard_3-2-1_094082_2023-12-07_final
2023-12-13 10:43:47	ga_ls8c_ard_3-2-1_104076_2023-12-13_final
2023-12-18 09:25:05	ga_ls8c_ard_3-2-1_091080_2023-12-17_final
2023-12-18 11:05:34	ga_ls8c_ard_3-2-1_107084_2023-12-18_final
2023-12-19 11:45:14	ga_ls8c_ard_3-2-1_114075_2023-12-19_final
2023-12-20 10:52:25	ga_ls8c_ard_3-2-1_105082_2023-12-20_final
2023-12-26 10:12:55	ga_ls8c_ard_3-2-1_099076_2023-12-26_final
2024-01-03 09:24:58	ga_ls8c_ard_3-2-1_091080_2024-01-02_final
2024-01-08 11:24:00	ga_ls8c_ard_3-2-1_110084_2024-01-08_final
2024-01-12 09:22:49	ga_ls8c_ard_3-2-1_090090_2024-01-11_final
2024-01-13 10:01:17	ga_ls8c_ard_3-2-1_097078_2024-01-13_final
2024-01-18 11:58:42	ga_ls8c_ard_3-2-1_116078_2024-01-18_final
2024-02-18 09:35:42	ga_ls8c_ard_3-2-1_093076_2024-02-18_final
2024-02-20 11:01:26	ga_ls8c_ard_3-2-1_107074_2024-02-20_final
2024-02-21 11:46:17	ga_ls8c_ard_3-2-1_114078_2024-02-21_final
2024-02-22 09:14:58	ga_ls8c_ard_3-2-1_089086_2024-02-21_final
2024-02-23 11:32:43	ga_ls8c_ard_3-2-1_112075_2024-02-23_final
2024-03-01 09:58:20	ga_ls8c_ard_3-2-1_097071_2024-03-01_final
2024-03-01 11:40:49	ga_ls8c_ard_3-2-1_113080_2024-03-01_final
2024-03-05 11:16:49	ga_ls8c_ard_3-2-1_109082_2024-03-05_final
2024-03-06 10:18:23	ga_ls8c_ard_3-2-1_100075_2024-03-06_final
2024-03-08 11:44:29	ga_ls8c_ard_3-2-1_114074_2024-03-08_final
2024-03-11 10:37:18	ga_ls8c_ard_3-2-1_103076_2024-03-11_final
2024-03-12 09:41:16	ga_ls8c_ard_3-2-1_094075_2024-03-12_nrt
2024-03-14 11:06:35	ga_ls8c_ard_3-2-1_108072_2024-03-14_nrt
2024-03-21 09:36:35	ga_ls8c_ard_3-2-1_093079_2024-03-21_nrt
2024-03-22 10:21:26	ga_ls8c_ard_3-2-1_100083_2024-03-22_nrt
2024-03-23 09:28:11	ga_ls8c_ard_3-2-1_091089_2024-03-22_nrt
2024-03-30 11:05:33	ga_ls8c_ard_3-2-1_108070_2024-03-30_nrt
2024-04-05 10:33:16	ga_ls8c_ard_3-2-1_102082_2024-04-05_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