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
2014-12-12 09:58:14	ga_ls8c_ard_3-0-0_096086_2014-12-12_final
2015-02-13 09:14:44	ga_ls8c_ard_3-0-0_089086_2015-02-12_final
2015-02-14 09:57:58	ga_ls8c_ard_3-0-0_096086_2015-02-14_final
2015-02-16 09:45:37	ga_ls8c_ard_3-0-0_094086_2015-02-16_final
2015-02-27 09:27:03	ga_ls8c_ard_3-0-0_091086_2015-02-26_final
2015-03-01 09:14:41	ga_ls8c_ard_3-0-0_089086_2015-02-28_final
2015-03-31 09:26:42	ga_ls8c_ard_3-0-0_091086_2015-03-30_final
2015-04-02 09:14:18	ga_ls8c_ard_3-0-0_089086_2015-04-01_final
2015-04-03 09:57:33	ga_ls8c_ard_3-0-0_096086_2015-04-03_final
2015-12-28 09:27:24	ga_ls8c_ard_3-0-0_091086_2015-12-27_final
2016-03-01 09:27:10	ga_ls8c_ard_3-0-0_091086_2016-02-29_final
2016-04-02 09:26:55	ga_ls8c_ard_3-0-0_091086_2016-04-01_final
2016-04-18 09:26:50	ga_ls8c_ard_3-0-0_091086_2016-04-17_final
2018-09-18 09:57:48	ga_ls8c_ard_3-0-0_096086_2018-09-18_final
2018-09-18 11:36:17	ga_ls8c_ard_3-0-0_112085_2018-09-18_final
2018-09-20 09:45:27	ga_ls8c_ard_3-0-0_094086_2018-09-20_final
2018-10-04 09:57:56	ga_ls8c_ard_3-0-0_096086_2018-10-04_final
2018-10-04 11:36:25	ga_ls8c_ard_3-0-0_112085_2018-10-04_final
2018-10-06 09:45:35	ga_ls8c_ard_3-0-0_094086_2018-10-06_final
2018-10-20 09:58:02	ga_ls8c_ard_3-0-0_096086_2018-10-20_final
2018-10-20 11:36:31	ga_ls8c_ard_3-0-0_112085_2018-10-20_final
2018-10-22 09:45:41	ga_ls8c_ard_3-0-0_094086_2018-10-22_final
2018-11-05 09:58:06	ga_ls8c_ard_3-0-0_096086_2018-11-05_final
2018-11-07 09:45:44	ga_ls8c_ard_3-0-0_094086_2018-11-07_final
2018-11-21 09:58:06	ga_ls8c_ard_3-0-0_096086_2018-11-21_final
2018-11-23 09:45:45	ga_ls8c_ard_3-0-0_094086_2018-11-23_final
2018-12-07 09:58:04	ga_ls8c_ard_3-0-0_096086_2018-12-07_final
2018-12-09 09:45:42	ga_ls8c_ard_3-0-0_094086_2018-12-09_final
2018-12-23 09:58:03	ga_ls8c_ard_3-0-0_096086_2018-12-23_final
2018-12-25 09:45:41	ga_ls8c_ard_3-0-0_094086_2018-12-25_final
2019-01-08 09:58:02	ga_ls8c_ard_3-0-0_096086_2019-01-08_final
2019-01-10 09:45:40	ga_ls8c_ard_3-0-0_094086_2019-01-10_final
2019-03-15 09:45:24	ga_ls8c_ard_3-1-0_094086_2019-03-15_final
2019-03-17 09:33:02	ga_ls8c_ard_3-1-0_092086_2019-03-17_final
2019-05-02 09:44:50	ga_ls8c_ard_3-0-0_094085_2019-05-02_final
2019-05-02 09:45:14	ga_ls8c_ard_3-0-0_094086_2019-05-02_final
2019-05-04 09:32:54	ga_ls8c_ard_3-0-0_092086_2019-05-04_final
2019-05-18 09:45:01	ga_ls8c_ard_3-0-0_094085_2019-05-18_final
2019-05-18 09:45:25	ga_ls8c_ard_3-0-0_094086_2019-05-18_final
2019-05-20 09:33:04	ga_ls8c_ard_3-0-0_092086_2019-05-20_final
2019-05-20 11:11:33	ga_ls8c_ard_3-0-0_108085_2019-05-20_final
2019-08-17 09:27:25	ga_ls8c_ard_3-1-0_091086_2019-08-16_final
2019-08-18 10:10:41	ga_ls8c_ard_3-1-0_098086_2019-08-18_final
2019-08-19 09:15:04	ga_ls8c_ard_3-1-0_089086_2019-08-18_final
2019-08-22 09:45:59	ga_ls8c_ard_3-1-0_094086_2019-08-22_final
2019-08-24 09:33:37	ga_ls8c_ard_3-1-0_092086_2019-08-24_final
2019-09-03 10:10:44	ga_ls8c_ard_3-1-0_098086_2019-09-03_final
2019-09-04 09:15:07	ga_ls8c_ard_3-1-0_089086_2019-09-03_final
2022-02-21 09:33:29	ga_ls8c_ard_3-2-1_092086_2022-02-21_final
2022-02-23 09:21:07	ga_ls8c_ard_3-2-1_090086_2022-02-22_final
2022-02-26 09:52:01	ga_ls8c_ard_3-2-1_095086_2022-02-26_final
2022-02-28 09:39:39	ga_ls8c_ard_3-2-1_093086_2022-02-28_final
2022-03-02 09:27:17	ga_ls8c_ard_3-2-1_091086_2022-03-01_final
2022-03-14 09:51:56	ga_ls8c_ard_3-2-1_095086_2022-03-14_final
2022-03-25 09:33:16	ga_ls8c_ard_3-2-1_092086_2022-03-25_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
2022-04-01 09:39:22	ga_ls8c_ard_3-2-1_093086_2022-04-01_final
2022-04-08 09:45:36	ga_ls8c_ard_3-2-1_094086_2022-04-08_final
2022-04-10 09:33:16	ga_ls8c_ard_3-2-1_092086_2022-04-10_final
2022-04-12 09:20:55	ga_ls8c_ard_3-2-1_090086_2022-04-11_final
2022-04-15 09:51:50	ga_ls8c_ard_3-2-1_095086_2022-04-15_final
2022-04-17 09:39:28	ga_ls8c_ard_3-2-1_093086_2022-04-17_final
2022-04-19 09:27:06	ga_ls8c_ard_3-2-1_091086_2022-04-18_final
2022-04-21 09:14:44	ga_ls8c_ard_3-2-1_089086_2022-04-20_final
2022-04-22 09:57:59	ga_ls8c_ard_3-2-1_096086_2022-04-22_final
2022-04-24 09:45:36	ga_ls8c_ard_3-2-1_094086_2022-04-24_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 09:20:51	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
2022-05-12 09:33:21	ga_ls8c_ard_3-2-1_092086_2022-05-12_final
2022-05-14 09:21:01	ga_ls8c_ard_3-2-1_090086_2022-05-13_final
2022-07-22 09:39:56	ga_ls8c_ard_3-2-1_093086_2022-07-22_final
2022-07-27 09:58:33	ga_ls8c_ard_3-2-1_096086_2022-07-27_final
2022-07-29 09:46:12	ga_ls8c_ard_3-2-1_094086_2022-07-29_final
2022-07-29 11:24:41	ga_ls8c_ard_3-2-1_110085_2022-07-29_final
2022-07-31 09:33:52	ga_ls8c_ard_3-2-1_092086_2022-07-31_final
2022-08-01 10:16:44	ga_ls8c_ard_3-2-1_099085_2022-08-01_final
2022-08-02 09:21:31	ga_ls8c_ard_3-2-1_090086_2022-08-01_final
2022-08-03 10:04:24	ga_ls8c_ard_3-2-1_097085_2022-08-03_final
2022-08-05 09:52:27	ga_ls8c_ard_3-2-1_095086_2022-08-05_final
2022-08-07 09:40:06	ga_ls8c_ard_3-2-1_093086_2022-08-07_final
2022-08-09 09:27:46	ga_ls8c_ard_3-2-1_091086_2022-08-08_final
2022-08-11 09:15:25	ga_ls8c_ard_3-2-1_089086_2022-08-10_final
2022-08-12 09:58:41	ga_ls8c_ard_3-2-1_096086_2022-08-12_final
2022-08-14 09:46:20	ga_ls8c_ard_3-2-1_094086_2022-08-14_final
2022-08-14 11:24:49	ga_ls8c_ard_3-2-1_110085_2022-08-14_final
2022-08-16 09:33:59	ga_ls8c_ard_3-2-1_092086_2022-08-16_final
2022-08-18 09:21:13	ga_ls8c_ard_3-2-1_090085_2022-08-17_final
2022-08-18 09:21:37	ga_ls8c_ard_3-2-1_090086_2022-08-17_final
2022-08-28 09:58:42	ga_ls8c_ard_3-2-1_096086_2022-08-28_final
2022-08-30 09:46:21	ga_ls8c_ard_3-2-1_094086_2022-08-30_final
2022-10-24 09:52:36	ga_ls8c_ard_3-2-1_095086_2022-10-24_final
2022-10-26 09:40:15	ga_ls8c_ard_3-2-1_093086_2022-10-26_final
2022-10-28 09:27:54	ga_ls8c_ard_3-2-1_091086_2022-10-27_final
2022-10-30 09:15:33	ga_ls8c_ard_3-2-1_089086_2022-10-29_final
2022-11-27 09:40:11	ga_ls8c_ard_3-2-1_093086_2022-11-27_final
2022-12-11 09:52:31	ga_ls8c_ard_3-2-1_095086_2022-12-11_final
2022-12-22 09:33:50	ga_ls8c_ard_3-2-1_092086_2022-12-22_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