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
2022-02-22 10:12:45	ga_ls8c_ard_3-2-1_099076_2022-02-22_final
2022-02-22 11:52:50	ga_ls8c_ard_3-2-1_115079_2022-02-22_final
2022-02-26 09:49:37	ga_ls8c_ard_3-2-1_095080_2022-02-26_final
2022-03-07 09:43:49	ga_ls8c_ard_3-2-1_094081_2022-03-07_final
2022-03-18 09:23:59	ga_ls8c_ard_3-2-1_091078_2022-03-17_final
2022-03-19 10:10:01	ga_ls8c_ard_3-2-1_098085_2022-03-19_final
2022-03-25 11:05:22	ga_ls8c_ard_3-2-1_108069_2022-03-25_final
2022-03-28 09:58:32	ga_ls8c_ard_3-2-1_097072_2022-03-28_final
2022-03-31 10:31:24	ga_ls8c_ard_3-2-1_102077_2022-03-31_final
2022-04-12 09:19:19	ga_ls8c_ard_3-2-1_090082_2022-04-11_final
2022-04-13 11:41:28	ga_ls8c_ard_3-2-1_113082_2022-04-13_final
2022-04-22 11:32:52	ga_ls8c_ard_3-2-1_112076_2022-04-22_final
2022-04-23 10:34:51	ga_ls8c_ard_3-2-1_103070_2022-04-23_final
2022-04-24 11:23:18	ga_ls8c_ard_3-2-1_110083_2022-04-24_final
2022-04-26 11:06:08	ga_ls8c_ard_3-2-1_108071_2022-04-26_final
2022-04-29 11:41:00	ga_ls8c_ard_3-2-1_113081_2022-04-29_final
2022-05-04 10:18:44	ga_ls8c_ard_3-2-1_100076_2022-05-04_final
2022-05-07 09:14:22	ga_ls8c_ard_3-2-1_089085_2022-05-06_final
2022-05-10 11:23:23	ga_ls8c_ard_3-2-1_110083_2022-05-10_final
2022-05-15 10:00:17	ga_ls8c_ard_3-2-1_097076_2022-05-15_final
2022-05-16 10:41:34	ga_ls8c_ard_3-2-1_104071_2022-05-16_final
2022-05-19 11:12:52	ga_ls8c_ard_3-2-1_109072_2022-05-19_final
2022-05-29 11:53:09	ga_ls8c_ard_3-2-1_115080_2022-05-29_final
2022-06-02 11:29:17	ga_ls8c_ard_3-2-1_111082_2022-06-02_final
2022-06-04 11:12:10	ga_ls8c_ard_3-2-1_109070_2022-06-04_final
2022-06-06 11:01:02	ga_ls8c_ard_3-2-1_107073_2022-06-06_final
2022-06-15 09:18:52	ga_ls8c_ard_3-2-1_090080_2022-06-14_final
2022-06-17 10:41:49	ga_ls8c_ard_3-2-1_104071_2022-06-17_final
2022-06-18 11:27:29	ga_ls8c_ard_3-2-1_111077_2022-06-18_final
2022-06-25 09:52:49	ga_ls8c_ard_3-2-1_096072_2022-06-25_final
2022-06-25 11:36:05	ga_ls8c_ard_3-2-1_112083_2022-06-25_final
2022-06-29 09:32:30	ga_ls8c_ard_3-2-1_092083_2022-06-29_final
2022-07-06 11:12:22	ga_ls8c_ard_3-2-1_109070_2022-07-06_final
2022-07-06 11:15:34	ga_ls8c_ard_3-2-1_109078_2022-07-06_final
2022-07-08 11:01:12	ga_ls8c_ard_3-2-1_107073_2022-07-08_final
2022-07-09 10:07:59	ga_ls8c_ard_3-2-1_098079_2022-07-09_final
2022-07-11 09:53:13	ga_ls8c_ard_3-2-1_096073_2022-07-11_final
2022-07-12 10:36:52	ga_ls8c_ard_3-2-1_103074_2022-07-12_final
2022-07-15 09:32:28	ga_ls8c_ard_3-2-1_092083_2022-07-15_final
2022-07-15 11:06:34	ga_ls8c_ard_3-2-1_108071_2022-07-15_final
2022-07-18 11:41:30	ga_ls8c_ard_3-2-1_113081_2022-07-18_final
2022-07-19 10:41:54	ga_ls8c_ard_3-2-1_104071_2022-07-19_final
2022-07-19 10:45:53	ga_ls8c_ard_3-2-1_104081_2022-07-19_final
2022-07-20 11:26:46	ga_ls8c_ard_3-2-1_111075_2022-07-20_final
2022-07-27 09:53:45	ga_ls8c_ard_3-2-1_096074_2022-07-27_final
2022-07-29 09:44:36	ga_ls8c_ard_3-2-1_094082_2022-07-29_final
2022-08-06 10:32:08	ga_ls8c_ard_3-2-1_102077_2022-08-06_final
2022-08-08 10:18:11	ga_ls8c_ard_3-2-1_100073_2022-08-08_final
2022-08-21 09:47:44	ga_ls8c_ard_3-2-1_095074_2022-08-21_final
2022-08-21 11:29:25	ga_ls8c_ard_3-2-1_111081_2022-08-21_final
2022-08-25 09:27:01	ga_ls8c_ard_3-2-1_091084_2022-08-24_final
2022-08-31 10:26:25	ga_ls8c_ard_3-2-1_101078_2022-08-31_final
2022-09-01 09:31:35	ga_ls8c_ard_3-2-1_092080_2022-09-01_final
2022-09-01 09:32:47	ga_ls8c_ard_3-2-1_092083_2022-09-01_final
2022-09-04 10:03:17	ga_ls8c_ard_3-2-1_097082_2022-09-04_final
2022-09-08 11:16:18	ga_ls8c_ard_3-2-1_109079_2022-09-08_final
2022-09-09 10:22:41	ga_ls8c_ard_3-2-1_100084_2022-09-09_final
2022-09-12 09:15:31	ga_ls8c_ard_3-2-1_089086_2022-09-11_final
2022-09-19 09:18:09	ga_ls8c_ard_3-2-1_090077_2022-09-18_final
2022-09-27 11:47:40	ga_ls8c_ard_3-2-1_114080_2022-09-27_final
2022-09-29 09:54:01	ga_ls8c_ard_3-2-1_096074_2022-09-29_final
2022-10-07 10:42:13	ga_ls8c_ard_3-2-1_104071_2022-10-07_final
2022-10-12 09:24:36	ga_ls8c_ard_3-2-1_091078_2022-10-11_final
2022-10-15 09:55:29	ga_ls8c_ard_3-2-1_096078_2022-10-15_final
2022-10-18 10:26:26	ga_ls8c_ard_3-2-1_101078_2022-10-18_final
2022-10-27 11:58:25	ga_ls8c_ard_3-2-1_116076_2022-10-27_final
2022-11-04 11:06:12	ga_ls8c_ard_3-2-1_108069_2022-11-04_final
2022-11-11 11:15:31	ga_ls8c_ard_3-2-1_109077_2022-11-11_final
2022-11-27 11:15:53	ga_ls8c_ard_3-2-1_109078_2022-11-27_final
2022-11-30 10:07:30	ga_ls8c_ard_3-2-1_098077_2022-11-30_final
2022-12-03 10:37:36	ga_ls8c_ard_3-2-1_103075_2022-12-03_final
2022-12-03 10:38:24	ga_ls8c_ard_3-2-1_103077_2022-12-03_final
2022-12-06 11:06:54	ga_ls8c_ard_3-2-1_108071_2022-12-06_final
2022-12-11 11:30:12	ga_ls8c_ard_3-2-1_111083_2022-12-11_final
2022-12-15 11:03:51	ga_ls8c_ard_3-2-1_107079_2022-12-15_final
2022-12-16 11:47:30	ga_ls8c_ard_3-2-1_114080_2022-12-16_final
2022-12-25 09:58:21	ga_ls8c_ard_3-2-1_097070_2022-12-25_final
2023-01-16 11:02:52	ga_ls8c_ard_3-2-1_107077_2023-01-16_final
2023-01-24 10:15:04	ga_ls8c_ard_3-2-1_099081_2023-01-24_final
2023-01-25 09:21:51	ga_ls8c_ard_3-2-1_090087_2023-01-24_final
2023-01-26 10:01:32	ga_ls8c_ard_3-2-1_097078_2023-01-26_final
2023-01-26 11:40:01	ga_ls8c_ard_3-2-1_113077_2023-01-26_final
2023-02-05 10:37:49	ga_ls8c_ard_3-2-1_103076_2023-02-05_final
2023-02-06 09:46:11	ga_ls8c_ard_3-2-1_094086_2023-02-06_final
2023-03-08 09:55:22	ga_ls8c_ard_3-2-1_096079_2023-03-08_final
2023-03-08 11:35:26	ga_ls8c_ard_3-2-1_112082_2023-03-08_final
2023-03-10 09:43:48	ga_ls8c_ard_3-2-1_094081_2023-03-10_final
2023-03-11 10:23:28	ga_ls8c_ard_3-2-1_101072_2023-03-11_final
2023-03-13 11:51:59	ga_ls8c_ard_3-2-1_115077_2023-03-13_final
2023-03-26 11:21:20	ga_ls8c_ard_3-2-1_110078_2023-03-26_final
2023-03-27 10:24:54	ga_ls8c_ard_3-2-1_101076_2023-03-27_final
2023-04-07 10:05:48	ga_ls8c_ard_3-2-1_098075_2023-04-07_final
2023-04-13 11:09:30	ga_ls8c_ard_3-2-1_108080_2023-04-13_final
2023-04-25 09:52:54	ga_ls8c_ard_3-2-1_096074_2023-04-25_final
2023-04-26 10:36:57	ga_ls8c_ard_3-2-1_103076_2023-04-26_final
2023-05-08 09:23:03	ga_ls8c_ard_3-2-1_091077_2023-05-07_final
2023-05-11 09:55:29	ga_ls8c_ard_3-2-1_096081_2023-05-11_final
2023-05-13 09:44:42	ga_ls8c_ard_3-2-1_094085_2023-05-13_final
2023-05-23 10:20:12	ga_ls8c_ard_3-2-1_100081_2023-05-23_final
2023-05-23 11:57:05	ga_ls8c_ard_3-2-1_116076_2023-05-23_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