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
2022-09-30 10:39:17	ga_ls8c_ard_3-2-1_103079_2022-09-30_final
2022-10-01 09:43:15	ga_ls8c_ard_3-2-1_094078_2022-10-01_final
2022-10-01 09:45:15	ga_ls8c_ard_3-2-1_094083_2022-10-01_final
2022-10-02 10:26:30	ga_ls8c_ard_3-2-1_101078_2022-10-02_final
2022-10-05 10:56:59	ga_ls8c_ard_3-2-1_106077_2022-10-05_final
2022-10-07 10:45:24	ga_ls8c_ard_3-2-1_104079_2022-10-07_final
2022-10-09 10:33:01	ga_ls8c_ard_3-2-1_102079_2022-10-09_final
2022-10-17 09:42:21	ga_ls8c_ard_3-2-1_094076_2022-10-17_final
2022-10-19 11:08:54	ga_ls8c_ard_3-2-1_108076_2022-10-19_final
2022-10-19 11:10:06	ga_ls8c_ard_3-2-1_108079_2022-10-19_final
2022-10-24 09:49:00	ga_ls8c_ard_3-2-1_095077_2022-10-24_final
2022-10-25 10:31:53	ga_ls8c_ard_3-2-1_102076_2022-10-25_final
2022-10-26 11:16:20	ga_ls8c_ard_3-2-1_109079_2022-10-26_final
2022-10-28 11:04:23	ga_ls8c_ard_3-2-1_107080_2022-10-28_final
2022-11-01 10:37:17	ga_ls8c_ard_3-2-1_103074_2022-11-01_final
2022-11-04 11:10:11	ga_ls8c_ard_3-2-1_108079_2022-11-04_final
2022-11-05 11:51:27	ga_ls8c_ard_3-2-1_115074_2022-11-05_final
2022-11-07 10:00:35	ga_ls8c_ard_3-2-1_097075_2022-11-07_final
2022-11-08 10:45:27	ga_ls8c_ard_3-2-1_104079_2022-11-08_final
2022-11-09 11:28:42	ga_ls8c_ard_3-2-1_111079_2022-11-09_final
2022-11-10 10:33:04	ga_ls8c_ard_3-2-1_102079_2022-11-10_final
2022-11-10 10:33:28	ga_ls8c_ard_3-2-1_102080_2022-11-10_final
2022-11-11 11:15:55	ga_ls8c_ard_3-2-1_109078_2022-11-11_final
2022-11-12 10:18:41	ga_ls8c_ard_3-2-1_100074_2022-11-12_final
2022-11-13 11:05:56	ga_ls8c_ard_3-2-1_107084_2022-11-13_final
2022-11-15 10:51:33	ga_ls8c_ard_3-2-1_105079_2022-11-15_final
2022-11-16 09:55:07	ga_ls8c_ard_3-2-1_096077_2022-11-16_final
2022-11-16 09:55:31	ga_ls8c_ard_3-2-1_096078_2022-11-16_final
2022-11-16 11:33:36	ga_ls8c_ard_3-2-1_112076_2022-11-16_final
2022-11-16 11:34:48	ga_ls8c_ard_3-2-1_112079_2022-11-16_final
2022-11-17 10:38:46	ga_ls8c_ard_3-2-1_103078_2022-11-17_final
2022-11-17 10:39:10	ga_ls8c_ard_3-2-1_103079_2022-11-17_final
2022-11-18 09:42:20	ga_ls8c_ard_3-2-1_094076_2022-11-18_final
2022-11-19 10:27:36	ga_ls8c_ard_3-2-1_101081_2022-11-19_final
2022-11-21 10:12:27	ga_ls8c_ard_3-2-1_099074_2022-11-21_final
2022-11-24 10:45:22	ga_ls8c_ard_3-2-1_104079_2022-11-24_final
2022-11-25 11:28:14	ga_ls8c_ard_3-2-1_111078_2022-11-25_final
2022-11-25 11:29:02	ga_ls8c_ard_3-2-1_111080_2022-11-25_final
2022-11-27 11:15:53	ga_ls8c_ard_3-2-1_109078_2022-11-27_final
2022-11-27 11:16:17	ga_ls8c_ard_3-2-1_109079_2022-11-27_final
2022-11-27 11:16:41	ga_ls8c_ard_3-2-1_109080_2022-11-27_final
2022-11-28 10:21:27	ga_ls8c_ard_3-2-1_100081_2022-11-28_final
2022-11-28 11:58:45	ga_ls8c_ard_3-2-1_116077_2022-11-28_final
2022-11-29 11:04:19	ga_ls8c_ard_3-2-1_107080_2022-11-29_final
2022-12-02 11:34:02	ga_ls8c_ard_3-2-1_112077_2022-12-02_final
2022-12-09 10:00:30	ga_ls8c_ard_3-2-1_097075_2022-12-09_final
2022-12-11 09:50:31	ga_ls8c_ard_3-2-1_095081_2022-12-11_final
2022-12-13 09:37:21	ga_ls8c_ard_3-2-1_093079_2022-12-13_final
2022-12-16 10:09:25	ga_ls8c_ard_3-2-1_098082_2022-12-16_final
2022-12-17 09:14:10	ga_ls8c_ard_3-2-1_089083_2022-12-16_final
2022-12-18 09:55:02	ga_ls8c_ard_3-2-1_096077_2022-12-18_final
2022-12-18 11:35:06	ga_ls8c_ard_3-2-1_112080_2022-12-18_final
2022-12-22 09:31:02	ga_ls8c_ard_3-2-1_092079_2022-12-22_final
2022-12-22 11:10:19	ga_ls8c_ard_3-2-1_108080_2022-12-22_final
2022-12-23 11:51:11	ga_ls8c_ard_3-2-1_115074_2022-12-23_final
2022-12-27 09:48:24	ga_ls8c_ard_3-2-1_095076_2022-12-27_final
2022-12-27 09:50:24	ga_ls8c_ard_3-2-1_095081_2022-12-27_final
2022-12-27 11:28:05	ga_ls8c_ard_3-2-1_111078_2022-12-27_final
2022-12-28 10:31:16	ga_ls8c_ard_3-2-1_102075_2022-12-28_final
2022-12-28 10:33:40	ga_ls8c_ard_3-2-1_102081_2022-12-28_final
2022-12-29 09:37:39	ga_ls8c_ard_3-2-1_093080_2022-12-29_final
2022-12-30 10:20:55	ga_ls8c_ard_3-2-1_100080_2022-12-30_final
2022-12-30 10:21:19	ga_ls8c_ard_3-2-1_100081_2022-12-30_final
2022-12-31 09:24:30	ga_ls8c_ard_3-2-1_091078_2022-12-30_final
2022-12-31 11:03:23	ga_ls8c_ard_3-2-1_107078_2022-12-31_final
2023-01-03 09:55:48	ga_ls8c_ard_3-2-1_096079_2023-01-03_final
2023-01-03 11:33:53	ga_ls8c_ard_3-2-1_112077_2023-01-03_final
2023-01-06 10:27:29	ga_ls8c_ard_3-2-1_101081_2023-01-06_final
2023-01-09 10:58:46	ga_ls8c_ard_3-2-1_106082_2023-01-09_final
2023-01-12 09:47:58	ga_ls8c_ard_3-2-1_095075_2023-01-12_final
2023-01-12 11:28:50	ga_ls8c_ard_3-2-1_111080_2023-01-12_final
2023-01-19 09:54:52	ga_ls8c_ard_3-2-1_096077_2023-01-19_final
2023-01-19 09:55:40	ga_ls8c_ard_3-2-1_096079_2023-01-19_final
2023-01-30 11:16:06	ga_ls8c_ard_3-2-1_109079_2023-01-30_final
2023-02-01 09:24:28	ga_ls8c_ard_3-2-1_091078_2023-01-31_final
2023-02-06 09:43:23	ga_ls8c_ard_3-2-1_094079_2023-02-06_final
2023-02-06 09:43:47	ga_ls8c_ard_3-2-1_094080_2023-02-06_final
2023-02-08 09:31:25	ga_ls8c_ard_3-2-1_092080_2023-02-08_final
2023-02-10 10:58:43	ga_ls8c_ard_3-2-1_106082_2023-02-10_final
2023-02-14 10:33:08	ga_ls8c_ard_3-2-1_102080_2023-02-14_final
2023-02-15 09:37:30	ga_ls8c_ard_3-2-1_093080_2023-02-15_final
2023-02-15 11:15:59	ga_ls8c_ard_3-2-1_109079_2023-02-15_final
2023-02-17 09:24:19	ga_ls8c_ard_3-2-1_091078_2023-02-16_final
2023-02-17 11:04:00	ga_ls8c_ard_3-2-1_107080_2023-02-17_final
2023-02-22 09:45:56	ga_ls8c_ard_3-2-1_094086_2023-02-22_final
2023-02-24 09:29:56	ga_ls8c_ard_3-2-1_092077_2023-02-23_final
2023-02-26 10:56:26	ga_ls8c_ard_3-2-1_106077_2023-02-26_final
2023-02-28 10:44:29	ga_ls8c_ard_3-2-1_104078_2023-02-28_final
2023-03-01 09:50:03	ga_ls8c_ard_3-2-1_095081_2023-03-01_final
2023-03-01 11:27:44	ga_ls8c_ard_3-2-1_111078_2023-03-01_final
2023-03-02 10:32:54	ga_ls8c_ard_3-2-1_102080_2023-03-02_final
2023-03-04 10:20:32	ga_ls8c_ard_3-2-1_100080_2023-03-04_final
2023-03-05 11:03:47	ga_ls8c_ard_3-2-1_107080_2023-03-05_final
2023-03-08 09:56:09	ga_ls8c_ard_3-2-1_096081_2023-03-08_final
2023-03-09 10:37:01	ga_ls8c_ard_3-2-1_103075_2023-03-09_final
2023-03-09 10:37:25	ga_ls8c_ard_3-2-1_103076_2023-03-09_final
2023-03-09 10:38:37	ga_ls8c_ard_3-2-1_103079_2023-03-09_final
2023-03-10 09:43:24	ga_ls8c_ard_3-2-1_094080_2023-03-10_final
2023-03-12 11:08:19	ga_ls8c_ard_3-2-1_108076_2023-03-12_final
2023-03-15 10:02:43	ga_ls8c_ard_3-2-1_097082_2023-03-15_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