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:

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First 100 results (query limit)

Time (local)	Label
2022-01-26 10:33:00	ga_ls8c_ard_3-2-1_102080_2022-01-26_final
2022-02-01 11:33:36	ga_ls8c_ard_3-2-1_112077_2022-02-01_final
2022-02-08 11:40:34	ga_ls8c_ard_3-2-1_113079_2022-02-08_final
2022-02-12 09:38:32	ga_ls8c_ard_3-2-1_093083_2022-02-12_final
2022-02-17 11:34:19	ga_ls8c_ard_3-2-1_112079_2022-02-17_final
2022-02-19 09:43:27	ga_ls8c_ard_3-2-1_094080_2022-02-19_final
2022-02-24 10:03:11	ga_ls8c_ard_3-2-1_097083_2022-02-24_final
2022-02-25 10:43:39	ga_ls8c_ard_3-2-1_104076_2022-02-25_final
2022-02-28 11:15:44	ga_ls8c_ard_3-2-1_109079_2022-02-28_final
2022-03-02 11:02:59	ga_ls8c_ard_3-2-1_107078_2022-03-02_final
2022-03-04 10:47:49	ga_ls8c_ard_3-2-1_105071_2022-03-04_final
2022-03-08 10:24:16	ga_ls8c_ard_3-2-1_101074_2022-03-08_final
2022-03-10 10:14:42	ga_ls8c_ard_3-2-1_099081_2022-03-10_final
2022-03-12 10:03:07	ga_ls8c_ard_3-2-1_097083_2022-03-12_final
2022-03-12 11:40:24	ga_ls8c_ard_3-2-1_113079_2022-03-12_final
2022-03-13 10:43:58	ga_ls8c_ard_3-2-1_104077_2022-03-13_final
2022-03-14 09:49:32	ga_ls8c_ard_3-2-1_095080_2022-03-14_final
2022-03-20 10:47:41	ga_ls8c_ard_3-2-1_105071_2022-03-20_final
2022-03-22 10:37:18	ga_ls8c_ard_3-2-1_103076_2022-03-22_final
2022-03-23 11:22:08	ga_ls8c_ard_3-2-1_110080_2022-03-23_final
2022-03-25 11:09:45	ga_ls8c_ard_3-2-1_108080_2022-03-25_final
2022-03-29 10:40:58	ga_ls8c_ard_3-2-1_104070_2022-03-29_final
2022-04-05 10:47:34	ga_ls8c_ard_3-2-1_105071_2022-04-05_final
2022-04-13 10:02:59	ga_ls8c_ard_3-2-1_097083_2022-04-13_final
2022-04-13 11:39:05	ga_ls8c_ard_3-2-1_113076_2022-04-13_final
2022-04-15 11:27:07	ga_ls8c_ard_3-2-1_111077_2022-04-15_final
2022-04-15 11:28:19	ga_ls8c_ard_3-2-1_111080_2022-04-15_final
2022-04-17 09:38:40	ga_ls8c_ard_3-2-1_093084_2022-04-17_final
2022-04-20 11:46:03	ga_ls8c_ard_3-2-1_114078_2022-04-20_final
2022-04-26 11:08:31	ga_ls8c_ard_3-2-1_108077_2022-04-26_final
2022-05-03 09:37:51	ga_ls8c_ard_3-2-1_093082_2022-05-03_final
2022-05-03 11:15:56	ga_ls8c_ard_3-2-1_109080_2022-05-03_final
2022-05-05 11:04:00	ga_ls8c_ard_3-2-1_107081_2022-05-05_final
2022-05-09 10:35:20	ga_ls8c_ard_3-2-1_103071_2022-05-09_final
2022-05-09 10:36:31	ga_ls8c_ard_3-2-1_103074_2022-05-09_final
2022-05-09 10:36:55	ga_ls8c_ard_3-2-1_103075_2022-05-09_final
2022-05-19 11:12:04	ga_ls8c_ard_3-2-1_109070_2022-05-19_final
2022-05-22 11:45:46	ga_ls8c_ard_3-2-1_114077_2022-05-22_final
2022-05-25 10:36:59	ga_ls8c_ard_3-2-1_103075_2022-05-25_final
2022-05-28 11:06:40	ga_ls8c_ard_3-2-1_108072_2022-05-28_final
2022-06-02 09:49:12	ga_ls8c_ard_3-2-1_095079_2022-06-02_final
2022-06-11 09:41:57	ga_ls8c_ard_3-2-1_094076_2022-06-11_final
2022-06-16 10:02:56	ga_ls8c_ard_3-2-1_097082_2022-06-16_final
2022-06-22 11:03:35	ga_ls8c_ard_3-2-1_107079_2022-06-22_final
2022-06-23 10:05:34	ga_ls8c_ard_3-2-1_098073_2022-06-23_final
2022-06-23 11:45:39	ga_ls8c_ard_3-2-1_114076_2022-06-23_final
2022-06-25 09:56:48	ga_ls8c_ard_3-2-1_096082_2022-06-25_final
2022-06-25 11:32:54	ga_ls8c_ard_3-2-1_112075_2022-06-25_final
2022-06-26 10:37:41	ga_ls8c_ard_3-2-1_103076_2022-06-26_final
2022-06-29 11:08:59	ga_ls8c_ard_3-2-1_108077_2022-06-29_final
2022-07-03 10:42:16	ga_ls8c_ard_3-2-1_104072_2022-07-03_final
2022-07-03 10:44:16	ga_ls8c_ard_3-2-1_104077_2022-07-03_final
2022-07-09 10:05:59	ga_ls8c_ard_3-2-1_098074_2022-07-09_final
2022-07-09 10:06:47	ga_ls8c_ard_3-2-1_098076_2022-07-09_final
2022-07-18 11:39:06	ga_ls8c_ard_3-2-1_113075_2022-07-18_final
2022-07-19 10:42:18	ga_ls8c_ard_3-2-1_104072_2022-07-19_final
2022-07-19 10:45:05	ga_ls8c_ard_3-2-1_104079_2022-07-19_final
2022-07-20 09:49:53	ga_ls8c_ard_3-2-1_095080_2022-07-20_final
2022-07-25 10:09:17	ga_ls8c_ard_3-2-1_098082_2022-07-25_final
2022-07-27 09:56:33	ga_ls8c_ard_3-2-1_096081_2022-07-27_final
2022-07-28 10:37:49	ga_ls8c_ard_3-2-1_103076_2022-07-28_final
2022-07-29 11:22:18	ga_ls8c_ard_3-2-1_110079_2022-07-29_final
2022-08-03 11:39:17	ga_ls8c_ard_3-2-1_113075_2022-08-03_final
2022-08-07 09:36:31	ga_ls8c_ard_3-2-1_093077_2022-08-07_final
2022-08-12 11:33:10	ga_ls8c_ard_3-2-1_112075_2022-08-12_final
2022-08-13 10:39:09	ga_ls8c_ard_3-2-1_103079_2022-08-13_final
2022-08-16 11:10:28	ga_ls8c_ard_3-2-1_108080_2022-08-16_final
2022-08-28 09:57:07	ga_ls8c_ard_3-2-1_096082_2022-08-28_final
2022-09-05 10:46:10	ga_ls8c_ard_3-2-1_104081_2022-09-05_final
2022-09-11 10:05:57	ga_ls8c_ard_3-2-1_098073_2022-09-11_final
2022-09-13 09:57:12	ga_ls8c_ard_3-2-1_096082_2022-09-13_final
2022-09-18 10:12:10	ga_ls8c_ard_3-2-1_099073_2022-09-18_final
2022-09-24 11:12:23	ga_ls8c_ard_3-2-1_109069_2022-09-24_final
2022-10-05 10:56:59	ga_ls8c_ard_3-2-1_106077_2022-10-05_final
2022-10-07 10:42:37	ga_ls8c_ard_3-2-1_104072_2022-10-07_final
2022-10-07 10:45:24	ga_ls8c_ard_3-2-1_104079_2022-10-07_final
2022-10-14 09:13:48	ga_ls8c_ard_3-2-1_089082_2022-10-13_final
2022-10-23 10:42:37	ga_ls8c_ard_3-2-1_104072_2022-10-23_final
2022-10-31 11:35:18	ga_ls8c_ard_3-2-1_112080_2022-10-31_final
2022-11-08 10:42:39	ga_ls8c_ard_3-2-1_104072_2022-11-08_final
2022-11-08 10:46:14	ga_ls8c_ard_3-2-1_104081_2022-11-08_final
2022-11-10 10:32:40	ga_ls8c_ard_3-2-1_102078_2022-11-10_final
2022-11-13 11:03:32	ga_ls8c_ard_3-2-1_107078_2022-11-13_final
2022-11-18 09:41:56	ga_ls8c_ard_3-2-1_094075_2022-11-18_final
2022-11-19 10:26:48	ga_ls8c_ard_3-2-1_101079_2022-11-19_final
2022-12-02 11:34:02	ga_ls8c_ard_3-2-1_112077_2022-12-02_final
2022-12-03 10:40:24	ga_ls8c_ard_3-2-1_103082_2022-12-03_final
2022-12-10 10:42:34	ga_ls8c_ard_3-2-1_104072_2022-12-10_final
2022-12-16 10:09:01	ga_ls8c_ard_3-2-1_098081_2022-12-16_final
2022-12-18 11:34:42	ga_ls8c_ard_3-2-1_112079_2022-12-18_final
2022-12-19 10:37:04	ga_ls8c_ard_3-2-1_103074_2022-12-19_final
2022-12-31 09:24:53	ga_ls8c_ard_3-2-1_091079_2022-12-30_final
2023-01-03 09:56:12	ga_ls8c_ard_3-2-1_096080_2023-01-03_final
2023-01-03 09:56:59	ga_ls8c_ard_3-2-1_096082_2023-01-03_final
2023-01-05 11:23:55	ga_ls8c_ard_3-2-1_110083_2023-01-05_final
2023-01-11 10:45:59	ga_ls8c_ard_3-2-1_104081_2023-01-11_final
2023-01-20 10:38:33	ga_ls8c_ard_3-2-1_103078_2023-01-20_final
2023-01-26 10:03:31	ga_ls8c_ard_3-2-1_097083_2023-01-26_final
2023-02-06 09:42:59	ga_ls8c_ard_3-2-1_094078_2023-02-06_final
2023-02-20 09:53:57	ga_ls8c_ard_3-2-1_096075_2023-02-20_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