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
2022-06-12 10:28:01	ga_ls8c_ard_3-2-1_101083_2022-06-12_final
2022-06-18 09:52:35	ga_ls8c_ard_3-2-1_095087_2022-06-18_final
2022-06-22 10:59:59	ga_ls8c_ard_3-2-1_107070_2022-06-22_final
2022-06-23 10:04:22	ga_ls8c_ard_3-2-1_098070_2022-06-23_final
2022-06-24 10:46:26	ga_ls8c_ard_3-2-1_105067_2022-06-24_final
2022-06-29 11:07:23	ga_ls8c_ard_3-2-1_108073_2022-06-29_final
2022-07-04 11:29:55	ga_ls8c_ard_3-2-1_111083_2022-07-04_final
2022-07-21 10:30:22	ga_ls8c_ard_3-2-1_102073_2022-07-21_final
2022-08-02 09:18:20	ga_ls8c_ard_3-2-1_090078_2022-08-01_final
2022-08-03 11:38:53	ga_ls8c_ard_3-2-1_113074_2022-08-03_final
2022-08-10 10:03:51	ga_ls8c_ard_3-2-1_098068_2022-08-10_final
2022-08-10 10:04:39	ga_ls8c_ard_3-2-1_098070_2022-08-10_final
2022-08-11 10:53:06	ga_ls8c_ard_3-2-1_105083_2022-08-11_final
2022-08-12 09:55:53	ga_ls8c_ard_3-2-1_096079_2022-08-12_final
2022-08-25 09:25:25	ga_ls8c_ard_3-2-1_091080_2022-08-24_final
2022-08-25 11:02:18	ga_ls8c_ard_3-2-1_107075_2022-08-25_final
2022-08-26 10:04:41	ga_ls8c_ard_3-2-1_098070_2022-08-26_final
2022-08-29 10:35:11	ga_ls8c_ard_3-2-1_103069_2022-08-29_final
2022-09-03 10:54:07	ga_ls8c_ard_3-2-1_106070_2022-09-03_final
2022-09-11 10:10:44	ga_ls8c_ard_3-2-1_098085_2022-09-11_final
2022-09-21 10:41:29	ga_ls8c_ard_3-2-1_104069_2022-09-21_final
2022-09-27 10:05:36	ga_ls8c_ard_3-2-1_098072_2022-09-27_final
2022-10-03 11:06:34	ga_ls8c_ard_3-2-1_108070_2022-10-03_final
2022-10-04 11:51:49	ga_ls8c_ard_3-2-1_115075_2022-10-04_final
2022-10-04 11:53:25	ga_ls8c_ard_3-2-1_115079_2022-10-04_final
2022-10-04 11:53:49	ga_ls8c_ard_3-2-1_115080_2022-10-04_final
2022-10-29 11:46:52	ga_ls8c_ard_3-2-1_114078_2022-10-29_final
2022-11-04 11:11:47	ga_ls8c_ard_3-2-1_108083_2022-11-04_final
2022-11-06 10:55:01	ga_ls8c_ard_3-2-1_106072_2022-11-06_final
2022-11-06 10:55:25	ga_ls8c_ard_3-2-1_106073_2022-11-06_final
2022-11-06 10:55:49	ga_ls8c_ard_3-2-1_106074_2022-11-06_final
2022-11-20 09:29:35	ga_ls8c_ard_3-2-1_092075_2022-11-19_final
2022-11-25 11:25:26	ga_ls8c_ard_3-2-1_111071_2022-11-25_final
2022-11-27 11:13:05	ga_ls8c_ard_3-2-1_109071_2022-11-27_final
2022-12-25 09:59:33	ga_ls8c_ard_3-2-1_097073_2022-12-25_final
2022-12-26 10:42:25	ga_ls8c_ard_3-2-1_104072_2022-12-26_final
2022-12-26 10:42:49	ga_ls8c_ard_3-2-1_104073_2022-12-26_final
2022-12-27 09:52:24	ga_ls8c_ard_3-2-1_095086_2022-12-27_final
2022-12-29 11:18:08	ga_ls8c_ard_3-2-1_109084_2022-12-29_final
2023-01-11 10:42:48	ga_ls8c_ard_3-2-1_104073_2023-01-11_final
2023-01-16 11:02:28	ga_ls8c_ard_3-2-1_107076_2023-01-16_final
2023-01-21 09:45:44	ga_ls8c_ard_3-2-1_094085_2023-01-21_final
2023-01-31 10:18:53	ga_ls8c_ard_3-2-1_100075_2023-01-31_final
2023-01-31 10:22:05	ga_ls8c_ard_3-2-1_100083_2023-01-31_final
2023-02-01 11:02:33	ga_ls8c_ard_3-2-1_107076_2023-02-01_final
2023-02-09 10:15:52	ga_ls8c_ard_3-2-1_099083_2023-02-09_final
2023-02-19 09:16:42	ga_ls8c_ard_3-2-1_089090_2023-02-18_final
2023-03-05 11:01:23	ga_ls8c_ard_3-2-1_107074_2023-03-05_final
2023-03-08 09:53:22	ga_ls8c_ard_3-2-1_096074_2023-03-08_final
2023-03-11 10:25:28	ga_ls8c_ard_3-2-1_101077_2023-03-11_final
2023-03-16 10:40:23	ga_ls8c_ard_3-2-1_104068_2023-03-16_final
2023-03-28 11:09:21	ga_ls8c_ard_3-2-1_108079_2023-03-28_final
2023-04-04 11:11:27	ga_ls8c_ard_3-2-1_109069_2023-04-04_final
2023-04-06 09:28:33	ga_ls8c_ard_3-2-1_091090_2023-04-05_final
2023-04-08 09:16:08	ga_ls8c_ard_3-2-1_089090_2023-04-07_final
2023-04-09 11:34:40	ga_ls8c_ard_3-2-1_112081_2023-04-09_final
2023-04-16 10:03:30	ga_ls8c_ard_3-2-1_097085_2023-04-16_final
2023-04-29 11:10:38	ga_ls8c_ard_3-2-1_108083_2023-04-29_final
2023-05-02 09:57:26	ga_ls8c_ard_3-2-1_097070_2023-05-02_final
2023-05-07 10:16:42	ga_ls8c_ard_3-2-1_100072_2023-05-07_final
2023-05-10 10:45:33	ga_ls8c_ard_3-2-1_105067_2023-05-10_final
2023-05-13 09:39:55	ga_ls8c_ard_3-2-1_094073_2023-05-13_final
2023-05-23 11:57:05	ga_ls8c_ard_3-2-1_116076_2023-05-23_final
2023-05-29 11:18:49	ga_ls8c_ard_3-2-1_110073_2023-05-29_final
2023-06-03 11:40:10	ga_ls8c_ard_3-2-1_113080_2023-06-03_final
2023-06-07 11:16:42	ga_ls8c_ard_3-2-1_109083_2023-06-07_final
2023-06-09 09:24:17	ga_ls8c_ard_3-2-1_091080_2023-06-08_final
2023-06-10 10:03:34	ga_ls8c_ard_3-2-1_098070_2023-06-10_final
2023-06-25 09:26:23	ga_ls8c_ard_3-2-1_091085_2023-06-24_final
2023-06-26 11:46:33	ga_ls8c_ard_3-2-1_114080_2023-06-26_final
2023-07-09 11:11:49	ga_ls8c_ard_3-2-1_109070_2023-07-09_final
2023-07-18 11:10:50	ga_ls8c_ard_3-2-1_108083_2023-07-18_final
2023-07-18 11:11:14	ga_ls8c_ard_3-2-1_108084_2023-07-18_final
2023-07-19 10:14:01	ga_ls8c_ard_3-2-1_099080_2023-07-19_final
2023-08-06 10:03:25	ga_ls8c_ard_3-2-1_097084_2023-08-06_final
2023-08-12 11:01:38	ga_ls8c_ard_3-2-1_107075_2023-08-12_final
2023-08-17 09:40:34	ga_ls8c_ard_3-2-1_094073_2023-08-17_final
2023-08-30 09:13:19	ga_ls8c_ard_3-2-1_089082_2023-08-29_final
2023-09-09 09:51:35	ga_ls8c_ard_3-2-1_095085_2023-09-09_final
2023-09-22 09:20:45	ga_ls8c_ard_3-2-1_090085_2023-09-21_final
2023-09-24 10:44:30	ga_ls8c_ard_3-2-1_104078_2023-09-24_final
2023-09-28 10:21:49	ga_ls8c_ard_3-2-1_100083_2023-09-28_final
2023-09-30 10:04:16	ga_ls8c_ard_3-2-1_098070_2023-09-30_final
2023-09-30 10:07:28	ga_ls8c_ard_3-2-1_098078_2023-09-30_final
2023-09-30 11:47:09	ga_ls8c_ard_3-2-1_114080_2023-09-30_final
2023-10-13 11:13:30	ga_ls8c_ard_3-2-1_109073_2023-10-13_final
2023-10-15 11:00:20	ga_ls8c_ard_3-2-1_107071_2023-10-15_final
2023-10-16 10:04:18	ga_ls8c_ard_3-2-1_098070_2023-10-16_final
2023-10-16 10:05:06	ga_ls8c_ard_3-2-1_098072_2023-10-16_final
2023-10-21 10:25:38	ga_ls8c_ard_3-2-1_101077_2023-10-21_final
2023-10-22 11:06:31	ga_ls8c_ard_3-2-1_108071_2023-10-22_final
2023-10-31 11:00:47	ga_ls8c_ard_3-2-1_107072_2023-10-31_final
2023-11-03 11:36:28	ga_ls8c_ard_3-2-1_112084_2023-11-03_final
2023-11-05 11:19:42	ga_ls8c_ard_3-2-1_110073_2023-11-05_final
2023-11-10 10:03:40	ga_ls8c_ard_3-2-1_097084_2023-11-10_final
2023-11-11 09:07:40	ga_ls8c_ard_3-2-1_088083_2023-11-10_final
2023-11-13 10:29:02	ga_ls8c_ard_3-2-1_102070_2023-11-13_final
2023-11-14 11:11:55	ga_ls8c_ard_3-2-1_109069_2023-11-14_final
2023-11-17 11:46:02	ga_ls8c_ard_3-2-1_114077_2023-11-17_final
2023-11-26 10:01:24	ga_ls8c_ard_3-2-1_097078_2023-11-26_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