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
2018-02-10 09:32:29	ga_ls8c_ard_3-0-0_092084_2018-02-10_final
2018-02-10 11:10:58	ga_ls8c_ard_3-0-0_108083_2018-02-10_final
2018-02-10 11:11:22	ga_ls8c_ard_3-0-0_108084_2018-02-10_final
2018-02-11 10:15:21	ga_ls8c_ard_3-0-0_099083_2018-02-11_final
2018-02-11 10:15:45	ga_ls8c_ard_3-0-0_099084_2018-02-11_final
2018-02-12 09:20:07	ga_ls8c_ard_3-0-0_090084_2018-02-11_final
2018-02-12 10:59:00	ga_ls8c_ard_3-0-0_106084_2018-02-12_final
2018-02-13 10:03:22	ga_ls8c_ard_3-0-0_097084_2018-02-13_final
2018-02-13 11:42:15	ga_ls8c_ard_3-0-0_113084_2018-02-13_final
2018-02-14 09:07:21	ga_ls8c_ard_3-0-0_088083_2018-02-13_final
2018-02-14 09:07:45	ga_ls8c_ard_3-0-0_088084_2018-02-13_final
2018-06-14 09:55:51	ga_ls8c_ard_3-0-0_096083_2018-06-14_final
2018-06-14 09:56:15	ga_ls8c_ard_3-0-0_096084_2018-06-14_final
2018-06-14 11:34:44	ga_ls8c_ard_3-0-0_112083_2018-06-14_final
2018-06-14 11:35:08	ga_ls8c_ard_3-0-0_112084_2018-06-14_final
2018-06-15 10:39:07	ga_ls8c_ard_3-0-0_103083_2018-06-15_final
2018-06-16 09:43:31	ga_ls8c_ard_3-0-0_094083_2018-06-16_final
2018-06-16 09:43:55	ga_ls8c_ard_3-0-0_094084_2018-06-16_final
2018-06-16 11:22:24	ga_ls8c_ard_3-0-0_110083_2018-06-16_final
2018-06-16 11:22:48	ga_ls8c_ard_3-0-0_110084_2018-06-16_final
2018-06-17 10:26:47	ga_ls8c_ard_3-0-0_101083_2018-06-17_final
2018-06-17 10:27:11	ga_ls8c_ard_3-0-0_101084_2018-06-17_final
2018-07-16 09:56:09	ga_ls8c_ard_3-0-0_096083_2018-07-16_final
2018-07-16 09:56:33	ga_ls8c_ard_3-0-0_096084_2018-07-16_final
2018-07-16 11:35:02	ga_ls8c_ard_3-0-0_112083_2018-07-16_final
2018-07-16 11:35:26	ga_ls8c_ard_3-0-0_112084_2018-07-16_final
2018-07-17 10:39:25	ga_ls8c_ard_3-0-0_103083_2018-07-17_final
2018-07-18 09:43:48	ga_ls8c_ard_3-0-0_094083_2018-07-18_final
2018-07-18 09:44:12	ga_ls8c_ard_3-0-0_094084_2018-07-18_final
2018-07-18 11:22:41	ga_ls8c_ard_3-0-0_110083_2018-07-18_final
2018-07-18 11:23:05	ga_ls8c_ard_3-0-0_110084_2018-07-18_final
2018-07-19 10:27:28	ga_ls8c_ard_3-0-0_101084_2018-07-19_final
2018-09-02 09:56:32	ga_ls8c_ard_3-0-0_096083_2018-09-02_final
2018-09-02 09:56:56	ga_ls8c_ard_3-0-0_096084_2018-09-02_final
2018-09-02 11:35:49	ga_ls8c_ard_3-0-0_112084_2018-09-02_final
2018-09-03 10:39:48	ga_ls8c_ard_3-0-0_103083_2018-09-03_final
2018-09-04 09:44:11	ga_ls8c_ard_3-0-0_094083_2018-09-04_final
2018-09-04 09:44:35	ga_ls8c_ard_3-0-0_094084_2018-09-04_final
2018-09-04 11:23:04	ga_ls8c_ard_3-0-0_110083_2018-09-04_final
2018-09-04 11:23:28	ga_ls8c_ard_3-0-0_110084_2018-09-04_final
2018-09-05 10:27:27	ga_ls8c_ard_3-0-0_101083_2018-09-05_final
2018-09-05 10:27:51	ga_ls8c_ard_3-0-0_101084_2018-09-05_final
2018-09-16 10:08:58	ga_ls8c_ard_3-0-0_098083_2018-09-16_final
2018-09-16 10:09:21	ga_ls8c_ard_3-0-0_098084_2018-09-16_final
2018-09-17 09:13:20	ga_ls8c_ard_3-0-0_089083_2018-09-16_final
2018-09-17 09:13:44	ga_ls8c_ard_3-0-0_089084_2018-09-16_final
2018-09-17 10:52:13	ga_ls8c_ard_3-0-0_105083_2018-09-17_final
2019-01-06 10:09:36	ga_ls8c_ard_3-0-0_098084_2019-01-06_final
2019-01-07 09:13:58	ga_ls8c_ard_3-0-0_089084_2019-01-06_final
2022-06-15 09:20:04	ga_ls8c_ard_3-2-1_090083_2022-06-14_final
2022-06-15 09:20:28	ga_ls8c_ard_3-2-1_090084_2022-06-14_final
2022-06-15 10:58:57	ga_ls8c_ard_3-2-1_106083_2022-06-15_final
2022-06-16 10:03:20	ga_ls8c_ard_3-2-1_097083_2022-06-16_final
2022-06-16 10:03:44	ga_ls8c_ard_3-2-1_097084_2022-06-16_final
2022-07-13 11:23:43	ga_ls8c_ard_3-2-1_110083_2022-07-13_final
2022-07-13 11:24:07	ga_ls8c_ard_3-2-1_110084_2022-07-13_final
2022-07-15 09:32:28	ga_ls8c_ard_3-2-1_092083_2022-07-15_final
2022-07-15 09:32:52	ga_ls8c_ard_3-2-1_092084_2022-07-15_final
2022-07-15 11:11:45	ga_ls8c_ard_3-2-1_108084_2022-07-15_final
2022-07-16 10:16:08	ga_ls8c_ard_3-2-1_099084_2022-07-16_final
2022-07-26 10:52:57	ga_ls8c_ard_3-2-1_105083_2022-07-26_final
2022-07-27 09:57:21	ga_ls8c_ard_3-2-1_096083_2022-07-27_final
2022-07-27 09:57:45	ga_ls8c_ard_3-2-1_096084_2022-07-27_final
2022-07-27 11:36:14	ga_ls8c_ard_3-2-1_112083_2022-07-27_final
2022-07-27 11:36:38	ga_ls8c_ard_3-2-1_112084_2022-07-27_final
2022-07-31 11:11:33	ga_ls8c_ard_3-2-1_108083_2022-07-31_final
2022-07-31 11:11:57	ga_ls8c_ard_3-2-1_108084_2022-07-31_final
2022-08-01 10:15:56	ga_ls8c_ard_3-2-1_099083_2022-08-01_final
2022-08-01 10:16:20	ga_ls8c_ard_3-2-1_099084_2022-08-01_final
2022-08-02 09:20:19	ga_ls8c_ard_3-2-1_090083_2022-08-01_final
2022-08-02 09:20:43	ga_ls8c_ard_3-2-1_090084_2022-08-01_final
2022-08-03 10:04:00	ga_ls8c_ard_3-2-1_097084_2022-08-03_final
2022-08-03 11:42:29	ga_ls8c_ard_3-2-1_113083_2022-08-03_final
2022-08-03 11:42:53	ga_ls8c_ard_3-2-1_113084_2022-08-03_final
2022-08-04 09:07:59	ga_ls8c_ard_3-2-1_088083_2022-08-03_final
2022-08-05 09:51:15	ga_ls8c_ard_3-2-1_095083_2022-08-05_final
2022-08-05 09:51:39	ga_ls8c_ard_3-2-1_095084_2022-08-05_final
2022-08-25 09:27:01	ga_ls8c_ard_3-2-1_091084_2022-08-24_final
2022-08-25 11:05:30	ga_ls8c_ard_3-2-1_107083_2022-08-25_final
2022-08-25 11:05:54	ga_ls8c_ard_3-2-1_107084_2022-08-25_final
2022-08-26 10:09:52	ga_ls8c_ard_3-2-1_098083_2022-08-26_final
2022-08-26 10:10:16	ga_ls8c_ard_3-2-1_098084_2022-08-26_final
2022-08-27 09:14:39	ga_ls8c_ard_3-2-1_089084_2022-08-26_final
2022-09-03 09:20:25	ga_ls8c_ard_3-2-1_090083_2022-09-02_final
2022-09-03 09:20:49	ga_ls8c_ard_3-2-1_090084_2022-09-02_final
2022-09-04 10:03:41	ga_ls8c_ard_3-2-1_097083_2022-09-04_final
2022-09-04 10:04:05	ga_ls8c_ard_3-2-1_097084_2022-09-04_final
2022-09-04 11:42:35	ga_ls8c_ard_3-2-1_113083_2022-09-04_final
2022-09-04 11:42:58	ga_ls8c_ard_3-2-1_113084_2022-09-04_final
2022-09-05 09:08:05	ga_ls8c_ard_3-2-1_088083_2022-09-04_final
2022-09-06 09:51:21	ga_ls8c_ard_3-2-1_095083_2022-09-06_final
2022-09-06 09:51:45	ga_ls8c_ard_3-2-1_095084_2022-09-06_final
2022-09-06 11:30:38	ga_ls8c_ard_3-2-1_111084_2022-09-06_final
2022-09-08 09:39:01	ga_ls8c_ard_3-2-1_093083_2022-09-08_final
2022-09-08 09:39:25	ga_ls8c_ard_3-2-1_093084_2022-09-08_final
2022-09-08 11:18:18	ga_ls8c_ard_3-2-1_109084_2022-09-08_final
2022-09-09 10:22:41	ga_ls8c_ard_3-2-1_100084_2022-09-09_final
2022-09-10 09:27:04	ga_ls8c_ard_3-2-1_091084_2022-09-09_final
2022-09-10 11:05:57	ga_ls8c_ard_3-2-1_107084_2022-09-10_final
2022-09-11 10:10:20	ga_ls8c_ard_3-2-1_098084_2022-09-11_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