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
2022-10-11 10:18:14	ga_ls8c_ard_3-2-1_100073_2022-10-11_final
2022-10-13 11:46:19	ga_ls8c_ard_3-2-1_114077_2022-10-13_final
2022-10-17 09:43:33	ga_ls8c_ard_3-2-1_094079_2022-10-17_final
2022-10-19 11:10:06	ga_ls8c_ard_3-2-1_108079_2022-10-19_final
2022-10-20 10:13:17	ga_ls8c_ard_3-2-1_099076_2022-10-20_final
2022-10-21 10:56:58	ga_ls8c_ard_3-2-1_106077_2022-10-21_final
2022-10-21 10:57:46	ga_ls8c_ard_3-2-1_106079_2022-10-21_final
2022-10-26 09:37:03	ga_ls8c_ard_3-2-1_093078_2022-10-26_final
2022-10-29 10:06:23	ga_ls8c_ard_3-2-1_098074_2022-10-29_final
2022-10-29 11:46:04	ga_ls8c_ard_3-2-1_114076_2022-10-29_final
2022-10-31 09:56:25	ga_ls8c_ard_3-2-1_096080_2022-10-31_final
2022-11-02 11:22:57	ga_ls8c_ard_3-2-1_110080_2022-11-02_final
2022-11-04 11:06:12	ga_ls8c_ard_3-2-1_108069_2022-11-04_final
2022-11-06 10:57:25	ga_ls8c_ard_3-2-1_106078_2022-11-06_final
2022-11-11 09:36:38	ga_ls8c_ard_3-2-1_093077_2022-11-11_final
2022-11-11 09:37:02	ga_ls8c_ard_3-2-1_093078_2022-11-11_final
2022-11-11 09:38:38	ga_ls8c_ard_3-2-1_093082_2022-11-11_final
2022-11-11 11:13:08	ga_ls8c_ard_3-2-1_109071_2022-11-11_final
2022-11-12 10:19:05	ga_ls8c_ard_3-2-1_100075_2022-11-12_final
2022-11-13 11:03:08	ga_ls8c_ard_3-2-1_107077_2022-11-13_final
2022-11-19 10:24:48	ga_ls8c_ard_3-2-1_101074_2022-11-19_final
2022-11-19 10:25:36	ga_ls8c_ard_3-2-1_101076_2022-11-19_final
2022-11-20 09:29:59	ga_ls8c_ard_3-2-1_092076_2022-11-19_final
2022-11-23 10:03:18	ga_ls8c_ard_3-2-1_097082_2022-11-23_final
2022-11-23 10:03:42	ga_ls8c_ard_3-2-1_097083_2022-11-23_final
2022-11-25 09:50:33	ga_ls8c_ard_3-2-1_095081_2022-11-25_final
2022-11-27 11:16:41	ga_ls8c_ard_3-2-1_109080_2022-11-27_final
2022-11-30 10:06:42	ga_ls8c_ard_3-2-1_098075_2022-11-30_final
2022-12-02 11:33:14	ga_ls8c_ard_3-2-1_112075_2022-12-02_final
2022-12-05 10:24:50	ga_ls8c_ard_3-2-1_101074_2022-12-05_final
2022-12-06 09:35:36	ga_ls8c_ard_3-2-1_092090_2022-12-06_final
2022-12-07 10:12:04	ga_ls8c_ard_3-2-1_099073_2022-12-07_final
2022-12-09 10:03:18	ga_ls8c_ard_3-2-1_097082_2022-12-09_final
2022-12-10 10:45:21	ga_ls8c_ard_3-2-1_104079_2022-12-10_final
2022-12-11 11:29:24	ga_ls8c_ard_3-2-1_111081_2022-12-11_final
2022-12-12 10:32:11	ga_ls8c_ard_3-2-1_102077_2022-12-12_final
2022-12-12 10:33:22	ga_ls8c_ard_3-2-1_102080_2022-12-12_final
2022-12-14 10:18:36	ga_ls8c_ard_3-2-1_100074_2022-12-14_final
2022-12-16 11:47:06	ga_ls8c_ard_3-2-1_114079_2022-12-16_final
2022-12-18 09:56:37	ga_ls8c_ard_3-2-1_096081_2022-12-18_final
2022-12-24 09:20:16	ga_ls8c_ard_3-2-1_090083_2022-12-23_final
2022-12-24 10:57:10	ga_ls8c_ard_3-2-1_106078_2022-12-24_final
2022-12-24 10:57:34	ga_ls8c_ard_3-2-1_106079_2022-12-24_final
2022-12-24 10:58:45	ga_ls8c_ard_3-2-1_106082_2022-12-24_final
2022-12-25 10:03:09	ga_ls8c_ard_3-2-1_097082_2022-12-25_final
2022-12-25 11:40:02	ga_ls8c_ard_3-2-1_113077_2022-12-25_final
2022-12-27 11:26:53	ga_ls8c_ard_3-2-1_111075_2022-12-27_final
2022-12-27 11:27:17	ga_ls8c_ard_3-2-1_111076_2022-12-27_final
2022-12-27 11:27:41	ga_ls8c_ard_3-2-1_111077_2022-12-27_final
2022-12-29 09:36:27	ga_ls8c_ard_3-2-1_093077_2022-12-29_final
2022-12-29 09:36:51	ga_ls8c_ard_3-2-1_093078_2022-12-29_final
2022-12-29 09:37:39	ga_ls8c_ard_3-2-1_093080_2022-12-29_final
2023-01-01 11:47:02	ga_ls8c_ard_3-2-1_114079_2023-01-01_final
2023-01-05 09:43:50	ga_ls8c_ard_3-2-1_094080_2023-01-05_final
2023-01-05 11:23:07	ga_ls8c_ard_3-2-1_110081_2023-01-05_final
2023-01-06 10:26:41	ga_ls8c_ard_3-2-1_101079_2023-01-06_final
2023-01-07 11:11:08	ga_ls8c_ard_3-2-1_108082_2023-01-07_final
2023-01-09 10:57:34	ga_ls8c_ard_3-2-1_106079_2023-01-09_final
2023-01-13 10:32:00	ga_ls8c_ard_3-2-1_102077_2023-01-13_final
2023-01-13 10:33:12	ga_ls8c_ard_3-2-1_102080_2023-01-13_final
2023-01-13 10:34:00	ga_ls8c_ard_3-2-1_102082_2023-01-13_final
2023-01-17 10:08:01	ga_ls8c_ard_3-2-1_098079_2023-01-17_final
2023-01-17 11:46:54	ga_ls8c_ard_3-2-1_114079_2023-01-17_final
2023-01-19 09:54:04	ga_ls8c_ard_3-2-1_096075_2023-01-19_final
2023-01-19 09:55:16	ga_ls8c_ard_3-2-1_096078_2023-01-19_final
2023-01-21 11:23:01	ga_ls8c_ard_3-2-1_110081_2023-01-21_final
2023-01-22 10:25:25	ga_ls8c_ard_3-2-1_101076_2023-01-22_final
2023-01-23 09:30:12	ga_ls8c_ard_3-2-1_092077_2023-01-23_final
2023-01-25 10:57:32	ga_ls8c_ard_3-2-1_106079_2023-01-25_final
2023-01-26 09:59:32	ga_ls8c_ard_3-2-1_097073_2023-01-26_final
2023-01-26 10:00:44	ga_ls8c_ard_3-2-1_097076_2023-01-26_final
2023-01-30 09:36:25	ga_ls8c_ard_3-2-1_093077_2023-01-30_final
2023-02-05 10:37:49	ga_ls8c_ard_3-2-1_103076_2023-02-05_final
2023-02-08 09:31:25	ga_ls8c_ard_3-2-1_092080_2023-02-08_final
2023-02-10 09:20:14	ga_ls8c_ard_3-2-1_090083_2023-02-09_final
2023-02-10 10:56:43	ga_ls8c_ard_3-2-1_106077_2023-02-10_final
2023-02-11 10:02:40	ga_ls8c_ard_3-2-1_097081_2023-02-11_final
2023-02-12 10:44:19	ga_ls8c_ard_3-2-1_104077_2023-02-12_final
2023-02-14 10:33:08	ga_ls8c_ard_3-2-1_102080_2023-02-14_final
2023-02-15 09:37:06	ga_ls8c_ard_3-2-1_093079_2023-02-15_final
2023-02-15 09:37:54	ga_ls8c_ard_3-2-1_093081_2023-02-15_final
2023-02-15 11:15:35	ga_ls8c_ard_3-2-1_109078_2023-02-15_final
2023-02-17 09:24:43	ga_ls8c_ard_3-2-1_091079_2023-02-16_final
2023-02-20 11:34:50	ga_ls8c_ard_3-2-1_112080_2023-02-20_final
2023-02-22 09:43:57	ga_ls8c_ard_3-2-1_094081_2023-02-22_final
2023-02-22 09:45:56	ga_ls8c_ard_3-2-1_094086_2023-02-22_final
2023-02-24 09:32:44	ga_ls8c_ard_3-2-1_092084_2023-02-24_final
2023-02-25 10:11:58	ga_ls8c_ard_3-2-1_099074_2023-02-25_final
2023-02-25 10:12:22	ga_ls8c_ard_3-2-1_099075_2023-02-25_final
2023-02-26 10:57:14	ga_ls8c_ard_3-2-1_106079_2023-02-26_final
2023-03-01 11:26:32	ga_ls8c_ard_3-2-1_111075_2023-03-01_final
2023-03-04 10:21:20	ga_ls8c_ard_3-2-1_100082_2023-03-04_final
2023-03-05 11:03:47	ga_ls8c_ard_3-2-1_107080_2023-03-05_final
2023-03-06 10:06:09	ga_ls8c_ard_3-2-1_098075_2023-03-06_final
2023-03-07 10:51:00	ga_ls8c_ard_3-2-1_105079_2023-03-07_final
2023-03-08 09:55:22	ga_ls8c_ard_3-2-1_096079_2023-03-08_final
2023-03-08 11:34:38	ga_ls8c_ard_3-2-1_112080_2023-03-08_final
2023-03-10 11:18:41	ga_ls8c_ard_3-2-1_110071_2023-03-10_final
2023-03-12 11:08:19	ga_ls8c_ard_3-2-1_108076_2023-03-12_final
2023-03-13 10:11:54	ga_ls8c_ard_3-2-1_099074_2023-03-13_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