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
2022-04-12 10:58:12	ga_ls8c_ard_3-2-1_106082_2022-04-12_final
2022-04-13 11:38:17	ga_ls8c_ard_3-2-1_113074_2022-04-13_final
2022-04-21 09:12:44	ga_ls8c_ard_3-2-1_089081_2022-04-20_final
2022-04-24 11:18:54	ga_ls8c_ard_3-2-1_110072_2022-04-24_final
2022-05-05 09:26:42	ga_ls8c_ard_3-2-1_091085_2022-05-04_final
2022-05-10 09:45:42	ga_ls8c_ard_3-2-1_094086_2022-05-10_final
2022-05-10 09:46:06	ga_ls8c_ard_3-2-1_094087_2022-05-10_final
2022-05-19 09:39:34	ga_ls8c_ard_3-2-1_093086_2022-05-19_final
2022-05-22 10:08:05	ga_ls8c_ard_3-2-1_098080_2022-05-22_final
2022-05-28 09:28:59	ga_ls8c_ard_3-2-1_092075_2022-05-27_final
2022-05-30 10:56:20	ga_ls8c_ard_3-2-1_106077_2022-05-30_final
2022-06-05 10:22:09	ga_ls8c_ard_3-2-1_100084_2022-06-05_final
2022-06-13 09:34:48	ga_ls8c_ard_3-2-1_092089_2022-06-13_final
2022-06-13 11:07:18	ga_ls8c_ard_3-2-1_108073_2022-06-13_final
2022-06-22 11:01:35	ga_ls8c_ard_3-2-1_107074_2022-06-22_final
2022-07-13 11:18:56	ga_ls8c_ard_3-2-1_110071_2022-07-13_final
2022-07-16 10:15:44	ga_ls8c_ard_3-2-1_099083_2022-07-16_final
2022-07-20 09:46:17	ga_ls8c_ard_3-2-1_095071_2022-07-20_final
2022-07-20 11:26:22	ga_ls8c_ard_3-2-1_111074_2022-07-20_final
2022-08-09 11:04:39	ga_ls8c_ard_3-2-1_107081_2022-08-09_final
2022-08-10 10:04:15	ga_ls8c_ard_3-2-1_098069_2022-08-10_final
2022-08-10 10:08:14	ga_ls8c_ard_3-2-1_098079_2022-08-10_final
2022-08-13 10:38:21	ga_ls8c_ard_3-2-1_103077_2022-08-13_final
2022-08-21 11:26:37	ga_ls8c_ard_3-2-1_111074_2022-08-21_final
2022-08-27 09:12:39	ga_ls8c_ard_3-2-1_089079_2022-08-26_final
2022-08-30 09:45:09	ga_ls8c_ard_3-2-1_094083_2022-08-30_final
2022-09-12 09:13:55	ga_ls8c_ard_3-2-1_089082_2022-09-11_final
2022-09-15 11:20:56	ga_ls8c_ard_3-2-1_110075_2022-09-15_final
2022-09-16 10:23:43	ga_ls8c_ard_3-2-1_101071_2022-09-16_final
2022-10-10 11:12:41	ga_ls8c_ard_3-2-1_109070_2022-10-10_final
2022-10-17 09:46:21	ga_ls8c_ard_3-2-1_094086_2022-10-17_final
2022-10-30 10:47:39	ga_ls8c_ard_3-2-1_105069_2022-10-30_final
2022-11-02 11:19:45	ga_ls8c_ard_3-2-1_110072_2022-11-02_final
2022-11-09 09:51:01	ga_ls8c_ard_3-2-1_095082_2022-11-09_final
2022-11-13 11:02:20	ga_ls8c_ard_3-2-1_107075_2022-11-13_final
2022-11-13 11:02:44	ga_ls8c_ard_3-2-1_107076_2022-11-13_final
2022-11-18 09:45:31	ga_ls8c_ard_3-2-1_094084_2022-11-18_final
2022-11-19 10:28:00	ga_ls8c_ard_3-2-1_101082_2022-11-19_final
2022-11-20 09:31:35	ga_ls8c_ard_3-2-1_092080_2022-11-20_final
2022-11-25 11:27:02	ga_ls8c_ard_3-2-1_111075_2022-11-25_final
2022-11-29 11:02:19	ga_ls8c_ard_3-2-1_107075_2022-11-29_final
2022-12-02 11:32:26	ga_ls8c_ard_3-2-1_112073_2022-12-02_final
2022-12-04 11:19:16	ga_ls8c_ard_3-2-1_110071_2022-12-04_final
2022-12-06 11:06:30	ga_ls8c_ard_3-2-1_108070_2022-12-06_final
2022-12-09 10:04:30	ga_ls8c_ard_3-2-1_097085_2022-12-09_final
2022-12-10 10:42:57	ga_ls8c_ard_3-2-1_104073_2022-12-10_final
2022-12-15 09:26:34	ga_ls8c_ard_3-2-1_091083_2022-12-14_final
2022-12-17 10:47:52	ga_ls8c_ard_3-2-1_105070_2022-12-17_final
2023-01-18 09:13:35	ga_ls8c_ard_3-2-1_089082_2023-01-17_final
2023-01-21 11:19:02	ga_ls8c_ard_3-2-1_110071_2023-01-21_final
2023-02-05 10:35:25	ga_ls8c_ard_3-2-1_103070_2023-02-05_final
2023-02-08 09:29:25	ga_ls8c_ard_3-2-1_092075_2023-02-07_final
2023-02-08 09:33:24	ga_ls8c_ard_3-2-1_092085_2023-02-08_final
2023-02-09 11:51:57	ga_ls8c_ard_3-2-1_115076_2023-02-09_final
2023-02-10 10:55:07	ga_ls8c_ard_3-2-1_106073_2023-02-10_final
2023-02-12 09:07:50	ga_ls8c_ard_3-2-1_088083_2023-02-11_final
2023-02-17 09:23:31	ga_ls8c_ard_3-2-1_091076_2023-02-16_final
2023-02-19 10:51:59	ga_ls8c_ard_3-2-1_105081_2023-02-19_final
2023-03-03 09:40:28	ga_ls8c_ard_3-2-1_093088_2023-03-03_final
2023-03-05 09:28:54	ga_ls8c_ard_3-2-1_091090_2023-03-04_final
2023-03-11 10:23:52	ga_ls8c_ard_3-2-1_101073_2023-03-11_final
2023-03-13 11:53:10	ga_ls8c_ard_3-2-1_115080_2023-03-13_final
2023-03-15 11:42:00	ga_ls8c_ard_3-2-1_113083_2023-03-15_final
2023-03-22 10:07:36	ga_ls8c_ard_3-2-1_098079_2023-03-22_final
2023-03-30 10:53:47	ga_ls8c_ard_3-2-1_106071_2023-03-30_final
2023-04-15 09:17:03	ga_ls8c_ard_3-2-1_090077_2023-04-14_final
2023-04-19 10:27:35	ga_ls8c_ard_3-2-1_102068_2023-04-19_final
2023-04-24 09:12:50	ga_ls8c_ard_3-2-1_089082_2023-04-23_final
2023-04-25 09:57:41	ga_ls8c_ard_3-2-1_096086_2023-04-25_final
2023-04-27 11:20:13	ga_ls8c_ard_3-2-1_110076_2023-04-27_final
2023-04-28 10:24:35	ga_ls8c_ard_3-2-1_101076_2023-04-28_final
2023-04-29 11:05:03	ga_ls8c_ard_3-2-1_108069_2023-04-29_final
2023-05-06 11:17:08	ga_ls8c_ard_3-2-1_109084_2023-05-06_final
2023-06-02 09:19:36	ga_ls8c_ard_3-2-1_090084_2023-06-01_final
2023-06-12 09:51:13	ga_ls8c_ard_3-2-1_096070_2023-06-12_final
2023-06-23 11:16:47	ga_ls8c_ard_3-2-1_109083_2023-06-23_final
2023-06-27 10:46:09	ga_ls8c_ard_3-2-1_105068_2023-06-27_final
2023-07-03 11:51:14	ga_ls8c_ard_3-2-1_115076_2023-07-03_final
2023-07-04 10:54:50	ga_ls8c_ard_3-2-1_106074_2023-07-04_final
2023-07-16 09:40:20	ga_ls8c_ard_3-2-1_094073_2023-07-16_final
2023-07-17 10:22:47	ga_ls8c_ard_3-2-1_101071_2023-07-17_final
2023-08-13 10:07:37	ga_ls8c_ard_3-2-1_098079_2023-08-13_final
2023-08-22 09:57:57	ga_ls8c_ard_3-2-1_097070_2023-08-22_final
2023-08-28 11:01:22	ga_ls8c_ard_3-2-1_107074_2023-08-28_final
2023-08-30 10:46:37	ga_ls8c_ard_3-2-1_105068_2023-08-30_final
2023-09-02 11:22:41	ga_ls8c_ard_3-2-1_110081_2023-09-02_final
2023-09-05 10:11:30	ga_ls8c_ard_3-2-1_099073_2023-09-05_final
2023-09-14 10:03:24	ga_ls8c_ard_3-2-1_098068_2023-09-14_final
2023-09-20 11:11:36	ga_ls8c_ard_3-2-1_108084_2023-09-20_final
2023-09-25 09:49:41	ga_ls8c_ard_3-2-1_095080_2023-09-25_final
2023-09-26 10:28:10	ga_ls8c_ard_3-2-1_102068_2023-09-26_final
2023-10-03 10:38:22	ga_ls8c_ard_3-2-1_103078_2023-10-03_final
2023-10-08 09:22:25	ga_ls8c_ard_3-2-1_090089_2023-10-07_final
2023-10-09 09:58:31	ga_ls8c_ard_3-2-1_097071_2023-10-09_final
2023-10-23 10:09:42	ga_ls8c_ard_3-2-1_099068_2023-10-23_final
2023-10-24 10:58:58	ga_ls8c_ard_3-2-1_106083_2023-10-24_final
2023-10-29 11:13:33	ga_ls8c_ard_3-2-1_109073_2023-10-29_final
2023-11-01 10:05:10	ga_ls8c_ard_3-2-1_098072_2023-11-01_final
2023-11-02 09:16:43	ga_ls8c_ard_3-2-1_089090_2023-11-01_final
2023-11-07 09:32:01	ga_ls8c_ard_3-2-1_092082_2023-11-07_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