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
2018-01-30 09:51:30	ga_ls8c_ard_3-0-0_095085_2018-01-30_final
2018-01-30 11:30:23	ga_ls8c_ard_3-0-0_111085_2018-01-30_final
2018-02-01 09:39:07	ga_ls8c_ard_3-0-0_093085_2018-02-01_final
2018-02-01 11:18:00	ga_ls8c_ard_3-0-0_109085_2018-02-01_final
2018-02-02 10:22:22	ga_ls8c_ard_3-0-0_100085_2018-02-02_final
2018-02-06 09:57:38	ga_ls8c_ard_3-0-0_096085_2018-02-06_final
2018-02-06 11:36:31	ga_ls8c_ard_3-0-0_112085_2018-02-06_final
2018-02-08 09:45:15	ga_ls8c_ard_3-0-0_094085_2018-02-08_final
2018-02-08 11:24:08	ga_ls8c_ard_3-0-0_110085_2018-02-08_final
2018-02-22 09:57:32	ga_ls8c_ard_3-0-0_096085_2018-02-22_final
2018-02-22 11:36:25	ga_ls8c_ard_3-0-0_112085_2018-02-22_final
2018-02-24 09:45:09	ga_ls8c_ard_3-0-0_094085_2018-02-24_final
2018-02-24 11:24:02	ga_ls8c_ard_3-0-0_110085_2018-02-24_final
2018-03-10 09:57:23	ga_ls8c_ard_3-0-0_096085_2018-03-10_final
2018-03-10 11:36:16	ga_ls8c_ard_3-0-0_112085_2018-03-10_final
2018-03-12 09:45:01	ga_ls8c_ard_3-0-0_094085_2018-03-12_final
2018-03-12 11:23:54	ga_ls8c_ard_3-0-0_110085_2018-03-12_final
2018-03-19 09:51:08	ga_ls8c_ard_3-0-0_095085_2018-03-19_final
2018-03-19 11:30:01	ga_ls8c_ard_3-0-0_111085_2018-03-19_final
2018-03-21 09:38:46	ga_ls8c_ard_3-0-0_093085_2018-03-21_final
2018-03-21 11:17:39	ga_ls8c_ard_3-0-0_109085_2018-03-21_final
2018-03-22 10:22:01	ga_ls8c_ard_3-0-0_100085_2018-03-22_final
2018-03-26 09:57:16	ga_ls8c_ard_3-0-0_096085_2018-03-26_final
2018-03-26 11:36:09	ga_ls8c_ard_3-0-0_112085_2018-03-26_final
2018-03-28 09:44:53	ga_ls8c_ard_3-0-0_094085_2018-03-28_final
2018-03-28 11:23:46	ga_ls8c_ard_3-0-0_110085_2018-03-28_final
2018-04-04 09:51:01	ga_ls8c_ard_3-0-0_095085_2018-04-04_final
2018-04-04 11:29:54	ga_ls8c_ard_3-0-0_111085_2018-04-04_final
2018-04-06 09:38:38	ga_ls8c_ard_3-0-0_093085_2018-04-06_final
2018-04-06 11:17:31	ga_ls8c_ard_3-0-0_109085_2018-04-06_final
2018-04-07 10:21:53	ga_ls8c_ard_3-0-0_100085_2018-04-07_final
2018-04-11 09:57:08	ga_ls8c_ard_3-0-0_096085_2018-04-11_final
2018-04-11 11:36:01	ga_ls8c_ard_3-0-0_112085_2018-04-11_final
2018-04-13 09:44:45	ga_ls8c_ard_3-0-0_094085_2018-04-13_final
2018-04-13 11:23:38	ga_ls8c_ard_3-0-0_110085_2018-04-13_final
2018-09-16 10:09:45	ga_ls8c_ard_3-0-0_098085_2018-09-16_final
2018-09-17 09:13:44	ga_ls8c_ard_3-0-0_089084_2018-09-16_final
2018-09-17 09:14:08	ga_ls8c_ard_3-0-0_089085_2018-09-16_final
2019-01-06 10:10:00	ga_ls8c_ard_3-0-0_098085_2019-01-06_final
2019-01-07 09:14:22	ga_ls8c_ard_3-0-0_089085_2019-01-06_final
2023-01-05 09:45:49	ga_ls8c_ard_3-2-1_094085_2023-01-05_final
2023-01-05 11:24:42	ga_ls8c_ard_3-2-1_110085_2023-01-05_final
2023-01-08 10:16:43	ga_ls8c_ard_3-2-1_099085_2023-01-08_final
2023-01-09 09:21:05	ga_ls8c_ard_3-2-1_090085_2023-01-08_final
2023-01-10 10:04:20	ga_ls8c_ard_3-2-1_097085_2023-01-10_final
2023-01-12 09:51:57	ga_ls8c_ard_3-2-1_095085_2023-01-12_final
2023-01-14 09:39:34	ga_ls8c_ard_3-2-1_093085_2023-01-14_final
2023-01-18 09:14:47	ga_ls8c_ard_3-2-1_089085_2023-01-17_final
2023-01-19 09:58:04	ga_ls8c_ard_3-2-1_096085_2023-01-19_final
2023-01-21 09:45:44	ga_ls8c_ard_3-2-1_094085_2023-01-21_final
2023-01-30 09:39:37	ga_ls8c_ard_3-2-1_093085_2023-01-30_final
2023-03-10 09:45:23	ga_ls8c_ard_3-2-1_094085_2023-03-10_final
2023-03-10 11:24:16	ga_ls8c_ard_3-2-1_110085_2023-03-10_final
2023-03-13 10:16:17	ga_ls8c_ard_3-2-1_099085_2023-03-13_final
2023-03-19 09:39:09	ga_ls8c_ard_3-2-1_093085_2023-03-19_final
2023-03-21 09:26:45	ga_ls8c_ard_3-2-1_091085_2023-03-20_final
2023-03-22 10:10:00	ga_ls8c_ard_3-2-1_098085_2023-03-22_final
2023-03-23 09:14:21	ga_ls8c_ard_3-2-1_089085_2023-03-22_final
2023-03-24 09:57:36	ga_ls8c_ard_3-2-1_096085_2023-03-24_final
2023-03-26 09:45:14	ga_ls8c_ard_3-2-1_094085_2023-03-26_final
2023-03-26 11:24:07	ga_ls8c_ard_3-2-1_110085_2023-03-26_final
2023-03-28 09:32:52	ga_ls8c_ard_3-2-1_092085_2023-03-28_final
2023-03-29 10:16:07	ga_ls8c_ard_3-2-1_099085_2023-03-29_final
2023-03-30 09:20:29	ga_ls8c_ard_3-2-1_090085_2023-03-29_final
2023-03-31 10:03:44	ga_ls8c_ard_3-2-1_097085_2023-03-31_final
2023-04-02 09:51:21	ga_ls8c_ard_3-2-1_095085_2023-04-02_final
2023-04-04 09:38:57	ga_ls8c_ard_3-2-1_093085_2023-04-04_final
2023-04-06 09:26:33	ga_ls8c_ard_3-2-1_091085_2023-04-05_final
2023-04-07 10:09:47	ga_ls8c_ard_3-2-1_098085_2023-04-07_final
2023-04-08 09:14:09	ga_ls8c_ard_3-2-1_089085_2023-04-07_final
2023-04-09 09:57:23	ga_ls8c_ard_3-2-1_096085_2023-04-09_final
2023-04-11 09:44:58	ga_ls8c_ard_3-2-1_094085_2023-04-11_final
2023-04-11 11:23:51	ga_ls8c_ard_3-2-1_110085_2023-04-11_final
2023-04-13 09:32:37	ga_ls8c_ard_3-2-1_092085_2023-04-13_final
2023-04-14 10:15:52	ga_ls8c_ard_3-2-1_099085_2023-04-14_final
2023-04-15 09:20:14	ga_ls8c_ard_3-2-1_090085_2023-04-14_final
2023-04-18 09:51:07	ga_ls8c_ard_3-2-1_095085_2023-04-18_final
2023-04-24 09:14:02	ga_ls8c_ard_3-2-1_089085_2023-04-23_final
2023-05-17 09:19:57	ga_ls8c_ard_3-2-1_090085_2023-05-16_final
2023-05-18 10:02:48	ga_ls8c_ard_3-2-1_097084_2023-05-18_final
2023-05-18 10:03:12	ga_ls8c_ard_3-2-1_097085_2023-05-18_final
2023-05-18 11:41:42	ga_ls8c_ard_3-2-1_113084_2023-05-18_final
2023-05-20 09:50:28	ga_ls8c_ard_3-2-1_095084_2023-05-20_final
2023-05-20 09:50:52	ga_ls8c_ard_3-2-1_095085_2023-05-20_final
2023-05-20 11:29:21	ga_ls8c_ard_3-2-1_111084_2023-05-20_final
2023-05-22 09:38:31	ga_ls8c_ard_3-2-1_093085_2023-05-22_final
2023-05-23 10:21:23	ga_ls8c_ard_3-2-1_100084_2023-05-23_final
2023-05-24 09:26:10	ga_ls8c_ard_3-2-1_091085_2023-05-23_final
2023-05-24 11:04:39	ga_ls8c_ard_3-2-1_107084_2023-05-24_final
2023-05-26 09:13:25	ga_ls8c_ard_3-2-1_089084_2023-05-25_final
2023-05-26 09:13:49	ga_ls8c_ard_3-2-1_089085_2023-05-25_final
2023-05-27 09:57:05	ga_ls8c_ard_3-2-1_096085_2023-05-27_final
2023-05-29 09:44:19	ga_ls8c_ard_3-2-1_094084_2023-05-29_final
2023-05-29 09:44:43	ga_ls8c_ard_3-2-1_094085_2023-05-29_final
2023-05-29 11:23:12	ga_ls8c_ard_3-2-1_110084_2023-05-29_final
2023-05-29 11:23:36	ga_ls8c_ard_3-2-1_110085_2023-05-29_final
2023-05-31 09:32:22	ga_ls8c_ard_3-2-1_092085_2023-05-31_final
2023-05-31 11:10:51	ga_ls8c_ard_3-2-1_108084_2023-05-31_final
2023-06-01 10:15:37	ga_ls8c_ard_3-2-1_099085_2023-06-01_final
2023-06-02 09:20:00	ga_ls8c_ard_3-2-1_090085_2023-06-01_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