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
2016-01-09 09:51:39	ga_ls8c_ard_3-0-0_095085_2016-01-09_final
2016-01-09 09:52:03	ga_ls8c_ard_3-0-0_095086_2016-01-09_final
2016-01-09 11:30:32	ga_ls8c_ard_3-0-0_111085_2016-01-09_final
2016-03-09 10:16:11	ga_ls8c_ard_3-0-0_099085_2016-03-09_final
2016-03-10 09:20:33	ga_ls8c_ard_3-0-0_090085_2016-03-09_final
2016-03-10 09:20:57	ga_ls8c_ard_3-0-0_090086_2016-03-09_final
2016-03-11 10:03:49	ga_ls8c_ard_3-0-0_097085_2016-03-11_final
2016-03-11 10:04:13	ga_ls8c_ard_3-0-0_097086_2016-03-11_final
2016-03-13 09:51:26	ga_ls8c_ard_3-0-0_095085_2016-03-13_final
2016-03-13 09:51:50	ga_ls8c_ard_3-0-0_095086_2016-03-13_final
2017-03-28 10:15:55	ga_ls8c_ard_3-0-0_099085_2017-03-28_final
2017-03-29 09:20:17	ga_ls8c_ard_3-0-0_090085_2017-03-28_final
2017-03-29 09:20:41	ga_ls8c_ard_3-0-0_090086_2017-03-28_final
2017-04-30 09:19:59	ga_ls8c_ard_3-0-0_090085_2017-04-29_final
2017-04-30 09:20:23	ga_ls8c_ard_3-0-0_090086_2017-04-29_final
2017-05-01 10:03:14	ga_ls8c_ard_3-0-0_097085_2017-05-01_final
2017-05-03 09:50:52	ga_ls8c_ard_3-0-0_095085_2017-05-03_final
2017-05-03 09:51:16	ga_ls8c_ard_3-0-0_095086_2017-05-03_final
2017-05-03 11:29:45	ga_ls8c_ard_3-0-0_111085_2017-05-03_final
2017-06-02 10:03:34	ga_ls8c_ard_3-0-0_097085_2017-06-02_final
2017-06-02 10:03:58	ga_ls8c_ard_3-0-0_097086_2017-06-02_final
2017-06-04 09:51:13	ga_ls8c_ard_3-0-0_095085_2017-06-04_final
2017-06-04 09:51:37	ga_ls8c_ard_3-0-0_095086_2017-06-04_final
2017-06-04 11:30:06	ga_ls8c_ard_3-0-0_111085_2017-06-04_final
2017-07-20 10:03:49	ga_ls8c_ard_3-0-0_097085_2017-07-20_final
2017-07-20 10:04:13	ga_ls8c_ard_3-0-0_097086_2017-07-20_final
2017-07-22 09:51:29	ga_ls8c_ard_3-0-0_095085_2017-07-22_final
2017-07-22 09:51:53	ga_ls8c_ard_3-0-0_095086_2017-07-22_final
2017-07-22 11:30:22	ga_ls8c_ard_3-0-0_111085_2017-07-22_final
2018-03-10 09:57:47	ga_ls8c_ard_3-0-0_096086_2018-03-10_final
2018-03-10 11:36:16	ga_ls8c_ard_3-0-0_112085_2018-03-10_final
2018-04-13 09:44:45	ga_ls8c_ard_3-0-0_094085_2018-04-13_final
2018-04-13 09:45:09	ga_ls8c_ard_3-0-0_094086_2018-04-13_final
2018-04-15 09:32:46	ga_ls8c_ard_3-0-0_092086_2018-04-15_final
2018-04-25 10:09:45	ga_ls8c_ard_3-0-0_098086_2018-04-25_final
2018-04-26 09:14:07	ga_ls8c_ard_3-0-0_089086_2018-04-25_final
2018-04-27 09:57:22	ga_ls8c_ard_3-0-0_096086_2018-04-27_final
2018-04-29 09:45:00	ga_ls8c_ard_3-0-0_094086_2018-04-29_final
2018-05-01 09:32:37	ga_ls8c_ard_3-0-0_092086_2018-05-01_final
2022-01-25 09:52:09	ga_ls8c_ard_3-2-1_095086_2022-01-25_final
2022-02-17 09:58:14	ga_ls8c_ard_3-2-1_096086_2022-02-17_final
2022-02-19 09:45:27	ga_ls8c_ard_3-2-1_094085_2022-02-19_final
2022-02-19 09:45:51	ga_ls8c_ard_3-2-1_094086_2022-02-19_final
2022-02-19 11:24:20	ga_ls8c_ard_3-2-1_110085_2022-02-19_final
2022-02-24 10:03:59	ga_ls8c_ard_3-2-1_097085_2022-02-24_final
2022-02-26 09:52:01	ga_ls8c_ard_3-2-1_095086_2022-02-26_final
2022-03-05 09:58:11	ga_ls8c_ard_3-2-1_096086_2022-03-05_final
2022-03-07 09:45:24	ga_ls8c_ard_3-2-1_094085_2022-03-07_final
2022-03-07 09:45:48	ga_ls8c_ard_3-2-1_094086_2022-03-07_final
2022-03-09 09:33:26	ga_ls8c_ard_3-2-1_092086_2022-03-09_final
2022-03-16 09:39:09	ga_ls8c_ard_3-2-1_093085_2022-03-16_final
2022-03-16 09:39:33	ga_ls8c_ard_3-2-1_093086_2022-03-16_final
2022-03-18 09:27:10	ga_ls8c_ard_3-2-1_091086_2022-03-17_final
2022-03-19 10:10:01	ga_ls8c_ard_3-2-1_098085_2022-03-19_final
2022-03-20 09:14:47	ga_ls8c_ard_3-2-1_089086_2022-03-19_final
2022-03-21 09:57:38	ga_ls8c_ard_3-2-1_096085_2022-03-21_final
2022-03-21 09:58:02	ga_ls8c_ard_3-2-1_096086_2022-03-21_final
2022-03-23 09:45:15	ga_ls8c_ard_3-2-1_094085_2022-03-23_final
2022-03-23 09:45:39	ga_ls8c_ard_3-2-1_094086_2022-03-23_final
2022-03-25 09:33:16	ga_ls8c_ard_3-2-1_092086_2022-03-25_final
2022-03-27 09:20:28	ga_ls8c_ard_3-2-1_090085_2022-03-26_final
2022-03-27 09:20:52	ga_ls8c_ard_3-2-1_090086_2022-03-26_final
2022-03-30 09:51:44	ga_ls8c_ard_3-2-1_095086_2022-03-30_final
2022-04-03 09:27:00	ga_ls8c_ard_3-2-1_091086_2022-04-02_final
2022-04-24 09:45:12	ga_ls8c_ard_3-2-1_094085_2022-04-24_final
2022-04-24 09:45:36	ga_ls8c_ard_3-2-1_094086_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 09:33:14	ga_ls8c_ard_3-2-1_092086_2022-04-26_final
2022-04-27 10:16:05	ga_ls8c_ard_3-2-1_099085_2022-04-27_final
2022-04-28 09:20:27	ga_ls8c_ard_3-2-1_090085_2022-04-27_final
2022-04-28 09:20:51	ga_ls8c_ard_3-2-1_090086_2022-04-27_final
2022-04-29 10:03:42	ga_ls8c_ard_3-2-1_097085_2022-04-29_final
2022-05-01 09:51:23	ga_ls8c_ard_3-2-1_095085_2022-05-01_final
2022-05-01 09:51:46	ga_ls8c_ard_3-2-1_095086_2022-05-01_final
2022-05-03 09:39:03	ga_ls8c_ard_3-2-1_093085_2022-05-03_final
2022-05-03 09:39:27	ga_ls8c_ard_3-2-1_093086_2022-05-03_final
2022-05-05 09:26:42	ga_ls8c_ard_3-2-1_091085_2022-05-04_final
2022-05-05 09:27:06	ga_ls8c_ard_3-2-1_091086_2022-05-04_final
2022-05-06 10:09:59	ga_ls8c_ard_3-2-1_098085_2022-05-06_final
2022-05-07 09:14:22	ga_ls8c_ard_3-2-1_089085_2022-05-06_final
2022-05-07 09:14:46	ga_ls8c_ard_3-2-1_089086_2022-05-06_final
2022-05-19 09:39:10	ga_ls8c_ard_3-2-1_093085_2022-05-19_final
2022-05-19 09:39:34	ga_ls8c_ard_3-2-1_093086_2022-05-19_final
2022-05-21 09:26:49	ga_ls8c_ard_3-2-1_091085_2022-05-20_final
2022-05-21 09:27:13	ga_ls8c_ard_3-2-1_091086_2022-05-20_final
2022-05-22 10:10:04	ga_ls8c_ard_3-2-1_098085_2022-05-22_final
2022-05-23 09:14:27	ga_ls8c_ard_3-2-1_089085_2022-05-22_final
2022-05-23 09:14:51	ga_ls8c_ard_3-2-1_089086_2022-05-22_final
2022-05-24 09:57:43	ga_ls8c_ard_3-2-1_096085_2022-05-24_final
2022-05-24 09:58:06	ga_ls8c_ard_3-2-1_096086_2022-05-24_final
2022-05-26 09:45:20	ga_ls8c_ard_3-2-1_094085_2022-05-26_final
2022-05-26 09:45:44	ga_ls8c_ard_3-2-1_094086_2022-05-26_final
2022-05-26 11:24:13	ga_ls8c_ard_3-2-1_110085_2022-05-26_final
2022-05-28 09:33:22	ga_ls8c_ard_3-2-1_092086_2022-05-28_final
2022-05-29 10:16:15	ga_ls8c_ard_3-2-1_099085_2022-05-29_final
2022-05-30 09:20:39	ga_ls8c_ard_3-2-1_090085_2022-05-29_final
2022-05-30 09:21:03	ga_ls8c_ard_3-2-1_090086_2022-05-29_final
2022-05-31 10:03:56	ga_ls8c_ard_3-2-1_097085_2022-05-31_final
2022-06-02 09:51:36	ga_ls8c_ard_3-2-1_095085_2022-06-02_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