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
2017-05-12 09:44:24	ga_ls8c_ard_3-0-0_094084_2017-05-12_final
2017-05-12 09:44:48	ga_ls8c_ard_3-0-0_094085_2017-05-12_final
2017-05-12 11:23:17	ga_ls8c_ard_3-0-0_110084_2017-05-12_final
2017-05-12 11:23:41	ga_ls8c_ard_3-0-0_110085_2017-05-12_final
2017-05-13 10:27:41	ga_ls8c_ard_3-0-0_101084_2017-05-13_final
2017-05-14 09:32:28	ga_ls8c_ard_3-0-0_092085_2017-05-14_final
2017-05-14 11:10:57	ga_ls8c_ard_3-0-0_108084_2017-05-14_final
2017-05-14 11:11:21	ga_ls8c_ard_3-0-0_108085_2017-05-14_final
2017-05-15 10:15:44	ga_ls8c_ard_3-0-0_099085_2017-05-15_final
2017-05-16 09:19:44	ga_ls8c_ard_3-0-0_090084_2017-05-15_final
2017-05-16 09:20:08	ga_ls8c_ard_3-0-0_090085_2017-05-15_final
2017-05-16 10:58:37	ga_ls8c_ard_3-0-0_106084_2017-05-16_final
2017-07-02 10:15:42	ga_ls8c_ard_3-0-0_099084_2017-07-02_final
2017-07-02 10:16:06	ga_ls8c_ard_3-0-0_099085_2017-07-02_final
2017-07-03 09:20:28	ga_ls8c_ard_3-0-0_090085_2017-07-02_final
2017-07-03 10:58:57	ga_ls8c_ard_3-0-0_106084_2017-07-03_final
2022-01-23 10:04:08	ga_ls8c_ard_3-2-1_097085_2022-01-23_final
2022-01-25 09:51:21	ga_ls8c_ard_3-2-1_095084_2022-01-25_final
2022-01-25 09:51:45	ga_ls8c_ard_3-2-1_095085_2022-01-25_final
2022-04-21 09:13:56	ga_ls8c_ard_3-2-1_089084_2022-04-20_final
2022-04-21 09:14:20	ga_ls8c_ard_3-2-1_089085_2022-04-20_final
2022-04-22 09:57:11	ga_ls8c_ard_3-2-1_096084_2022-04-22_final
2022-04-22 09:57:35	ga_ls8c_ard_3-2-1_096085_2022-04-22_final
2022-04-22 11:36:04	ga_ls8c_ard_3-2-1_112084_2022-04-22_final
2022-04-24 09:44:49	ga_ls8c_ard_3-2-1_094084_2022-04-24_final
2022-04-24 09:45:12	ga_ls8c_ard_3-2-1_094085_2022-04-24_final
2022-04-24 11:23:42	ga_ls8c_ard_3-2-1_110084_2022-04-24_final
2022-04-24 11:24:05	ga_ls8c_ard_3-2-1_110085_2022-04-24_final
2022-04-26 09:32:50	ga_ls8c_ard_3-2-1_092085_2022-04-26_final
2022-04-26 11:11:19	ga_ls8c_ard_3-2-1_108084_2022-04-26_final
2022-04-27 10:15:41	ga_ls8c_ard_3-2-1_099084_2022-04-27_final
2022-04-27 10:16:05	ga_ls8c_ard_3-2-1_099085_2022-04-27_final
2022-04-28 09:20:03	ga_ls8c_ard_3-2-1_090084_2022-04-27_final
2022-04-28 09:20:27	ga_ls8c_ard_3-2-1_090085_2022-04-27_final
2022-04-29 10:03:18	ga_ls8c_ard_3-2-1_097084_2022-04-29_final
2022-04-29 10:03:42	ga_ls8c_ard_3-2-1_097085_2022-04-29_final
2022-04-29 11:42:11	ga_ls8c_ard_3-2-1_113084_2022-04-29_final
2022-05-01 09:50:59	ga_ls8c_ard_3-2-1_095084_2022-05-01_final
2022-05-01 09:51:23	ga_ls8c_ard_3-2-1_095085_2022-05-01_final
2022-05-01 11:29:52	ga_ls8c_ard_3-2-1_111084_2022-05-01_final
2022-05-03 09:39:03	ga_ls8c_ard_3-2-1_093085_2022-05-03_final
2022-05-04 10:21:55	ga_ls8c_ard_3-2-1_100084_2022-05-04_final
2022-05-05 09:26:19	ga_ls8c_ard_3-2-1_091084_2022-05-04_final
2022-05-05 09:26:42	ga_ls8c_ard_3-2-1_091085_2022-05-04_final
2022-05-06 10:09:35	ga_ls8c_ard_3-2-1_098084_2022-05-06_final
2022-05-06 10:09:59	ga_ls8c_ard_3-2-1_098085_2022-05-06_final
2022-05-07 09:13:58	ga_ls8c_ard_3-2-1_089084_2022-05-06_final
2022-05-07 09:14:22	ga_ls8c_ard_3-2-1_089085_2022-05-06_final
2022-11-02 09:46:03	ga_ls8c_ard_3-2-1_094085_2022-11-02_final
2022-11-02 11:24:56	ga_ls8c_ard_3-2-1_110085_2022-11-02_final
2022-11-04 09:33:18	ga_ls8c_ard_3-2-1_092084_2022-11-04_final
2022-11-04 09:33:42	ga_ls8c_ard_3-2-1_092085_2022-11-04_final
2022-11-05 10:16:33	ga_ls8c_ard_3-2-1_099084_2022-11-05_final
2022-11-05 10:16:57	ga_ls8c_ard_3-2-1_099085_2022-11-05_final
2022-11-06 09:21:20	ga_ls8c_ard_3-2-1_090085_2022-11-05_final
2022-11-07 10:04:35	ga_ls8c_ard_3-2-1_097085_2022-11-07_final
2022-11-07 11:43:04	ga_ls8c_ard_3-2-1_113084_2022-11-07_final
2022-11-09 09:52:12	ga_ls8c_ard_3-2-1_095085_2022-11-09_final
2022-11-11 09:39:50	ga_ls8c_ard_3-2-1_093085_2022-11-11_final
2022-11-11 11:18:19	ga_ls8c_ard_3-2-1_109084_2022-11-11_final
2022-11-13 09:27:03	ga_ls8c_ard_3-2-1_091084_2022-11-12_final
2022-11-13 09:27:27	ga_ls8c_ard_3-2-1_091085_2022-11-12_final
2022-11-14 10:10:18	ga_ls8c_ard_3-2-1_098084_2022-11-14_final
2022-11-14 10:10:42	ga_ls8c_ard_3-2-1_098085_2022-11-14_final
2022-11-15 09:15:04	ga_ls8c_ard_3-2-1_089085_2022-11-14_final
2022-11-16 09:57:54	ga_ls8c_ard_3-2-1_096084_2022-11-16_final
2022-11-16 09:58:18	ga_ls8c_ard_3-2-1_096085_2022-11-16_final
2022-11-18 09:45:55	ga_ls8c_ard_3-2-1_094085_2022-11-18_final
2022-11-18 11:24:48	ga_ls8c_ard_3-2-1_110085_2022-11-18_final
2022-11-20 09:33:35	ga_ls8c_ard_3-2-1_092085_2022-11-20_final
2022-11-21 10:16:27	ga_ls8c_ard_3-2-1_099084_2022-11-21_final
2022-11-21 10:16:51	ga_ls8c_ard_3-2-1_099085_2022-11-21_final
2022-11-22 09:21:14	ga_ls8c_ard_3-2-1_090085_2022-11-21_final
2022-11-23 10:04:06	ga_ls8c_ard_3-2-1_097084_2022-11-23_final
2022-11-23 10:04:30	ga_ls8c_ard_3-2-1_097085_2022-11-23_final
2022-11-25 09:51:45	ga_ls8c_ard_3-2-1_095084_2022-11-25_final
2022-11-25 09:52:09	ga_ls8c_ard_3-2-1_095085_2022-11-25_final
2022-12-04 09:45:34	ga_ls8c_ard_3-2-1_094084_2022-12-04_final
2022-12-04 09:45:58	ga_ls8c_ard_3-2-1_094085_2022-12-04_final
2023-02-11 10:04:16	ga_ls8c_ard_3-2-1_097085_2023-02-11_final
2023-02-11 11:42:45	ga_ls8c_ard_3-2-1_113084_2023-02-11_final
2023-02-13 09:51:29	ga_ls8c_ard_3-2-1_095084_2023-02-13_final
2023-02-13 09:51:53	ga_ls8c_ard_3-2-1_095085_2023-02-13_final
2023-02-18 10:10:21	ga_ls8c_ard_3-2-1_098085_2023-02-18_final
2023-02-19 09:14:42	ga_ls8c_ard_3-2-1_089085_2023-02-18_final
2023-02-22 11:24:25	ga_ls8c_ard_3-2-1_110085_2023-02-22_final
2023-02-24 09:33:08	ga_ls8c_ard_3-2-1_092085_2023-02-24_final
2023-02-25 10:16:22	ga_ls8c_ard_3-2-1_099085_2023-02-25_final
2023-02-26 09:20:45	ga_ls8c_ard_3-2-1_090085_2023-02-25_final
2023-02-27 10:04:01	ga_ls8c_ard_3-2-1_097085_2023-02-27_final
2023-03-01 09:51:39	ga_ls8c_ard_3-2-1_095085_2023-03-01_final
2023-03-03 09:39:17	ga_ls8c_ard_3-2-1_093085_2023-03-03_final
2023-03-05 09:26:54	ga_ls8c_ard_3-2-1_091085_2023-03-04_final
2023-03-06 10:10:09	ga_ls8c_ard_3-2-1_098085_2023-03-06_final
2023-03-07 09:14:31	ga_ls8c_ard_3-2-1_089085_2023-03-06_final
2023-03-08 09:57:45	ga_ls8c_ard_3-2-1_096085_2023-03-08_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
2023-03-12 09:33:02	ga_ls8c_ard_3-2-1_092085_2023-03-12_final
2023-03-13 10:16:17	ga_ls8c_ard_3-2-1_099085_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years