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
2022-05-16 10:42:45	ga_ls8c_ard_3-2-1_104074_2022-05-16_final
2022-05-21 09:26:01	ga_ls8c_ard_3-2-1_091083_2022-05-20_final
2022-06-02 09:51:36	ga_ls8c_ard_3-2-1_095085_2022-06-02_final
2022-06-08 09:16:36	ga_ls8c_ard_3-2-1_089090_2022-06-07_final
2022-06-15 09:21:16	ga_ls8c_ard_3-2-1_090086_2022-06-14_final
2022-06-19 10:30:40	ga_ls8c_ard_3-2-1_102074_2022-06-19_final
2022-06-23 11:44:51	ga_ls8c_ard_3-2-1_114074_2022-06-23_final
2022-07-04 11:30:19	ga_ls8c_ard_3-2-1_111084_2022-07-04_final
2022-07-13 09:43:38	ga_ls8c_ard_3-2-1_094080_2022-07-13_final
2022-07-14 10:26:06	ga_ls8c_ard_3-2-1_101078_2022-07-14_final
2022-07-15 11:11:45	ga_ls8c_ard_3-2-1_108084_2022-07-15_final
2022-07-20 09:51:52	ga_ls8c_ard_3-2-1_095085_2022-07-20_final
2022-07-21 10:29:10	ga_ls8c_ard_3-2-1_102070_2022-07-21_final
2022-07-27 11:35:26	ga_ls8c_ard_3-2-1_112081_2022-07-27_final
2022-07-31 09:31:28	ga_ls8c_ard_3-2-1_092080_2022-07-31_final
2022-08-01 10:14:44	ga_ls8c_ard_3-2-1_099080_2022-08-01_final
2022-08-02 10:54:25	ga_ls8c_ard_3-2-1_106071_2022-08-02_final
2022-08-03 10:00:00	ga_ls8c_ard_3-2-1_097074_2022-08-03_final
2022-08-03 10:04:00	ga_ls8c_ard_3-2-1_097084_2022-08-03_final
2022-08-08 10:21:47	ga_ls8c_ard_3-2-1_100082_2022-08-08_final
2022-08-11 09:11:49	ga_ls8c_ard_3-2-1_089077_2022-08-10_final
2022-08-13 10:35:34	ga_ls8c_ard_3-2-1_103070_2022-08-13_final
2022-08-30 11:21:14	ga_ls8c_ard_3-2-1_110076_2022-08-30_final
2022-09-03 10:59:18	ga_ls8c_ard_3-2-1_106083_2022-09-03_final
2022-10-24 11:25:30	ga_ls8c_ard_3-2-1_111071_2022-10-24_final
2022-10-28 09:24:43	ga_ls8c_ard_3-2-1_091078_2022-10-27_final
2022-10-29 10:03:35	ga_ls8c_ard_3-2-1_098067_2022-10-29_final
2022-11-14 10:09:30	ga_ls8c_ard_3-2-1_098082_2022-11-14_final
2022-11-23 09:58:31	ga_ls8c_ard_3-2-1_097070_2022-11-23_final
2022-11-25 11:25:26	ga_ls8c_ard_3-2-1_111071_2022-11-25_final
2022-11-29 09:25:50	ga_ls8c_ard_3-2-1_091081_2022-11-28_final
2022-12-02 09:53:33	ga_ls8c_ard_3-2-1_096073_2022-12-02_final
2022-12-03 10:35:13	ga_ls8c_ard_3-2-1_103069_2022-12-03_final
2022-12-11 11:24:37	ga_ls8c_ard_3-2-1_111069_2022-12-11_final
2022-12-15 11:01:27	ga_ls8c_ard_3-2-1_107073_2022-12-15_final
2022-12-22 11:09:07	ga_ls8c_ard_3-2-1_108077_2022-12-22_final
2023-01-01 10:07:45	ga_ls8c_ard_3-2-1_098078_2023-01-01_final
2023-01-01 10:08:09	ga_ls8c_ard_3-2-1_098079_2023-01-01_final
2023-01-10 11:42:49	ga_ls8c_ard_3-2-1_113084_2023-01-10_final
2023-01-21 09:44:08	ga_ls8c_ard_3-2-1_094081_2023-01-21_final
2023-01-21 09:44:32	ga_ls8c_ard_3-2-1_094082_2023-01-21_final
2023-01-23 09:31:24	ga_ls8c_ard_3-2-1_092080_2023-01-23_final
2023-01-24 11:51:58	ga_ls8c_ard_3-2-1_115076_2023-01-24_final
2023-01-31 11:58:58	ga_ls8c_ard_3-2-1_116078_2023-01-31_final
2023-02-01 09:26:27	ga_ls8c_ard_3-2-1_091083_2023-01-31_final
2023-02-04 09:53:22	ga_ls8c_ard_3-2-1_096073_2023-02-04_final
2023-02-11 10:02:40	ga_ls8c_ard_3-2-1_097081_2023-02-11_final
2023-03-01 09:51:15	ga_ls8c_ard_3-2-1_095084_2023-03-01_final
2023-03-05 11:03:23	ga_ls8c_ard_3-2-1_107079_2023-03-05_final
2023-03-15 11:38:24	ga_ls8c_ard_3-2-1_113074_2023-03-15_final
2023-03-27 10:23:19	ga_ls8c_ard_3-2-1_101072_2023-03-27_final
2023-04-02 11:24:39	ga_ls8c_ard_3-2-1_111071_2023-04-02_final
2023-04-16 09:58:42	ga_ls8c_ard_3-2-1_097073_2023-04-16_final
2023-04-18 11:26:25	ga_ls8c_ard_3-2-1_111076_2023-04-18_final
2023-04-25 09:51:42	ga_ls8c_ard_3-2-1_096071_2023-04-25_final
2023-05-10 09:12:39	ga_ls8c_ard_3-2-1_089082_2023-05-09_final
2023-05-15 09:27:08	ga_ls8c_ard_3-2-1_092072_2023-05-14_final
2023-05-23 11:57:53	ga_ls8c_ard_3-2-1_116078_2023-05-23_final
2023-06-13 10:37:17	ga_ls8c_ard_3-2-1_103077_2023-06-13_final
2023-06-26 10:04:04	ga_ls8c_ard_3-2-1_098071_2023-06-26_final
2023-07-11 10:59:52	ga_ls8c_ard_3-2-1_107071_2023-07-11_final
2023-07-14 11:35:58	ga_ls8c_ard_3-2-1_112084_2023-07-14_final
2023-07-21 10:03:39	ga_ls8c_ard_3-2-1_097085_2023-07-21_final
2023-07-22 10:42:32	ga_ls8c_ard_3-2-1_104074_2023-07-22_final
2023-07-28 10:07:32	ga_ls8c_ard_3-2-1_098079_2023-07-28_final
2023-08-02 10:24:08	ga_ls8c_ard_3-2-1_101074_2023-08-02_final
2023-08-19 09:31:49	ga_ls8c_ard_3-2-1_092082_2023-08-19_final
2023-08-22 10:00:21	ga_ls8c_ard_3-2-1_097076_2023-08-22_final
2023-09-02 11:18:42	ga_ls8c_ard_3-2-1_110071_2023-09-02_final
2023-09-04 09:33:26	ga_ls8c_ard_3-2-1_092086_2023-09-04_final
2023-09-14 10:06:59	ga_ls8c_ard_3-2-1_098077_2023-09-14_final
2023-09-14 11:45:52	ga_ls8c_ard_3-2-1_114077_2023-09-14_final
2023-09-15 09:14:10	ga_ls8c_ard_3-2-1_089084_2023-09-14_final
2023-09-25 09:46:54	ga_ls8c_ard_3-2-1_095073_2023-09-25_final
2023-09-27 11:15:02	ga_ls8c_ard_3-2-1_109077_2023-09-27_final
2023-10-06 11:10:03	ga_ls8c_ard_3-2-1_108080_2023-10-06_final
2023-10-07 10:12:51	ga_ls8c_ard_3-2-1_099076_2023-10-07_final
2023-10-07 11:50:56	ga_ls8c_ard_3-2-1_115074_2023-10-07_final
2023-10-11 11:25:27	ga_ls8c_ard_3-2-1_111072_2023-10-11_final
2023-10-14 11:58:45	ga_ls8c_ard_3-2-1_116078_2023-10-14_final
2023-11-01 10:08:21	ga_ls8c_ard_3-2-1_098080_2023-11-01_final
2023-11-01 11:44:51	ga_ls8c_ard_3-2-1_114074_2023-11-01_final
2023-11-03 09:57:59	ga_ls8c_ard_3-2-1_096085_2023-11-03_final
2023-11-05 09:44:01	ga_ls8c_ard_3-2-1_094081_2023-11-05_final
2023-11-07 09:31:13	ga_ls8c_ard_3-2-1_092080_2023-11-07_final
2023-11-07 11:10:54	ga_ls8c_ard_3-2-1_108082_2023-11-07_final
2023-11-14 09:37:25	ga_ls8c_ard_3-2-1_093080_2023-11-14_final
2023-12-06 10:36:21	ga_ls8c_ard_3-2-1_103073_2023-12-06_final
2023-12-25 11:06:09	ga_ls8c_ard_3-2-1_108070_2023-12-25_final
2024-01-04 11:45:54	ga_ls8c_ard_3-2-1_114077_2024-01-04_final
2024-01-13 11:41:22	ga_ls8c_ard_3-2-1_113081_2024-01-13_final
2024-01-18 11:58:42	ga_ls8c_ard_3-2-1_116078_2024-01-18_final
2024-01-21 09:12:36	ga_ls8c_ard_3-2-1_089080_2024-01-20_final
2024-01-22 11:34:20	ga_ls8c_ard_3-2-1_112079_2024-01-22_final
2024-02-04 11:00:15	ga_ls8c_ard_3-2-1_107071_2024-02-04_final
2024-02-14 10:01:38	ga_ls8c_ard_3-2-1_097079_2024-02-14_final
2024-02-19 10:20:10	ga_ls8c_ard_3-2-1_100079_2024-02-19_final
2024-02-25 09:42:15	ga_ls8c_ard_3-2-1_094077_2024-02-25_final
2024-02-25 11:21:08	ga_ls8c_ard_3-2-1_110077_2024-02-25_final
2024-03-07 09:23:32	ga_ls8c_ard_3-2-1_091077_2024-03-06_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years