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
2016-01-18 09:45:54	ga_ls8c_ard_3-0-0_094086_2016-01-18_final
2016-01-18 09:46:18	ga_ls8c_ard_3-0-0_094087_2016-01-18_final
2016-01-20 09:33:32	ga_ls8c_ard_3-0-0_092086_2016-01-20_final
2016-01-20 09:33:56	ga_ls8c_ard_3-0-0_092087_2016-01-20_final
2016-03-06 09:45:42	ga_ls8c_ard_3-0-0_094086_2016-03-06_final
2016-03-06 09:46:06	ga_ls8c_ard_3-0-0_094087_2016-03-06_final
2016-03-08 09:33:43	ga_ls8c_ard_3-0-0_092087_2016-03-08_final
2016-03-17 09:27:05	ga_ls8c_ard_3-0-0_091086_2016-03-16_final
2016-03-17 09:27:29	ga_ls8c_ard_3-0-0_091087_2016-03-16_final
2016-03-18 10:10:20	ga_ls8c_ard_3-0-0_098086_2016-03-18_final
2016-03-19 09:14:42	ga_ls8c_ard_3-0-0_089086_2016-03-18_final
2016-03-19 09:15:06	ga_ls8c_ard_3-0-0_089087_2016-03-18_final
2016-03-22 09:45:35	ga_ls8c_ard_3-0-0_094086_2016-03-22_final
2016-03-22 09:45:59	ga_ls8c_ard_3-0-0_094087_2016-03-22_final
2016-03-24 09:33:12	ga_ls8c_ard_3-0-0_092086_2016-03-24_final
2016-03-24 09:33:36	ga_ls8c_ard_3-0-0_092087_2016-03-24_final
2016-04-19 10:10:05	ga_ls8c_ard_3-0-0_098086_2016-04-19_final
2016-04-20 09:14:27	ga_ls8c_ard_3-0-0_089086_2016-04-19_final
2016-04-20 09:14:51	ga_ls8c_ard_3-0-0_089087_2016-04-19_final
2019-04-14 09:57:38	ga_ls8c_ard_3-1-0_096086_2019-04-14_final
2019-04-14 09:58:02	ga_ls8c_ard_3-1-0_096087_2019-04-14_final
2019-04-16 09:45:16	ga_ls8c_ard_3-1-0_094086_2019-04-16_final
2019-04-16 09:45:40	ga_ls8c_ard_3-1-0_094087_2019-04-16_final
2019-06-17 09:58:00	ga_ls8c_ard_3-1-0_096086_2019-06-17_final
2019-06-17 09:58:24	ga_ls8c_ard_3-1-0_096087_2019-06-17_final
2019-07-09 09:21:01	ga_ls8c_ard_3-1-0_090086_2019-07-08_final
2019-07-09 09:21:25	ga_ls8c_ard_3-1-0_090087_2019-07-08_final
2019-07-10 10:04:17	ga_ls8c_ard_3-1-0_097086_2019-07-10_final
2019-08-10 09:21:12	ga_ls8c_ard_3-1-0_090086_2019-08-09_final
2019-08-10 09:21:36	ga_ls8c_ard_3-1-0_090087_2019-08-09_final
2019-08-26 09:21:16	ga_ls8c_ard_3-1-0_090086_2019-08-25_final
2019-08-26 09:21:40	ga_ls8c_ard_3-1-0_090087_2019-08-25_final
2019-09-27 09:21:26	ga_ls8c_ard_3-1-0_090086_2019-09-26_final
2019-09-27 09:21:50	ga_ls8c_ard_3-1-0_090087_2019-09-26_final
2019-10-13 09:21:29	ga_ls8c_ard_3-1-0_090086_2019-10-12_final
2019-10-14 10:04:44	ga_ls8c_ard_3-1-0_097086_2019-10-14_final
2021-11-24 09:39:59	ga_ls8c_ard_3-2-0_093086_2021-11-24_final
2021-11-24 09:40:23	ga_ls8c_ard_3-2-0_093087_2021-11-24_final
2021-11-26 09:27:37	ga_ls8c_ard_3-2-0_091086_2021-11-25_final
2021-11-26 09:28:01	ga_ls8c_ard_3-2-0_091087_2021-11-25_final
2021-11-27 10:10:53	ga_ls8c_ard_3-2-0_098086_2021-11-27_final
2021-11-28 09:15:16	ga_ls8c_ard_3-2-0_089086_2021-11-27_final
2021-11-29 09:58:32	ga_ls8c_ard_3-2-0_096086_2021-11-29_final
2021-12-03 09:33:49	ga_ls8c_ard_3-2-0_092086_2021-12-03_final
2021-12-03 09:34:13	ga_ls8c_ard_3-2-0_092087_2021-12-03_final
2021-12-05 09:21:27	ga_ls8c_ard_3-2-0_090086_2021-12-04_final
2021-12-05 09:21:51	ga_ls8c_ard_3-2-0_090087_2021-12-04_final
2021-12-08 09:52:21	ga_ls8c_ard_3-2-1_095086_2021-12-08_final
2021-12-08 09:52:45	ga_ls8c_ard_3-2-1_095087_2021-12-08_final
2021-12-10 09:39:59	ga_ls8c_ard_3-2-1_093086_2021-12-10_final
2021-12-10 09:40:23	ga_ls8c_ard_3-2-1_093087_2021-12-10_final
2021-12-12 09:27:37	ga_ls8c_ard_3-2-1_091086_2021-12-11_final
2021-12-12 09:28:01	ga_ls8c_ard_3-2-1_091087_2021-12-11_final
2021-12-21 09:21:25	ga_ls8c_ard_3-2-1_090086_2021-12-20_final
2021-12-21 09:21:49	ga_ls8c_ard_3-2-1_090087_2021-12-20_final
2021-12-24 09:52:18	ga_ls8c_ard_3-2-1_095086_2021-12-24_final
2021-12-24 09:52:41	ga_ls8c_ard_3-2-1_095087_2021-12-24_final
2021-12-26 09:39:55	ga_ls8c_ard_3-2-1_093086_2021-12-26_final
2021-12-26 09:40:19	ga_ls8c_ard_3-2-1_093087_2021-12-26_final
2021-12-28 09:27:32	ga_ls8c_ard_3-2-1_091086_2021-12-27_final
2021-12-28 09:27:56	ga_ls8c_ard_3-2-1_091087_2021-12-27_final
2022-01-02 09:46:03	ga_ls8c_ard_3-2-1_094086_2022-01-02_final
2022-01-02 09:46:27	ga_ls8c_ard_3-2-1_094087_2022-01-02_final
2022-01-04 09:33:42	ga_ls8c_ard_3-2-1_092086_2022-01-04_final
2022-01-04 09:34:06	ga_ls8c_ard_3-2-1_092087_2022-01-04_final
2022-01-09 09:52:14	ga_ls8c_ard_3-2-1_095086_2022-01-09_final
2022-01-09 09:52:38	ga_ls8c_ard_3-2-1_095087_2022-01-09_final
2022-01-11 09:39:52	ga_ls8c_ard_3-2-1_093086_2022-01-11_final
2022-01-11 09:40:16	ga_ls8c_ard_3-2-1_093087_2022-01-11_final
2022-02-01 09:58:18	ga_ls8c_ard_3-2-1_096086_2022-02-01_final
2022-02-03 09:45:57	ga_ls8c_ard_3-2-1_094086_2022-02-03_final
2022-02-03 09:46:21	ga_ls8c_ard_3-2-1_094087_2022-02-03_final
2022-02-05 09:33:35	ga_ls8c_ard_3-2-1_092086_2022-02-05_final
2022-02-05 09:33:59	ga_ls8c_ard_3-2-1_092087_2022-02-05_final
2022-04-03 09:27:00	ga_ls8c_ard_3-2-1_091086_2022-04-02_final
2022-04-03 09:27:24	ga_ls8c_ard_3-2-1_091087_2022-04-02_final
2022-04-08 09:46:00	ga_ls8c_ard_3-2-1_094087_2022-04-08_final
2022-04-10 09:33:16	ga_ls8c_ard_3-2-1_092086_2022-04-10_final
2022-04-10 09:33:40	ga_ls8c_ard_3-2-1_092087_2022-04-10_final
2022-04-12 09:21:19	ga_ls8c_ard_3-2-1_090087_2022-04-11_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
2022-04-24 09:46:00	ga_ls8c_ard_3-2-1_094087_2022-04-24_final
2022-04-26 09:33:14	ga_ls8c_ard_3-2-1_092086_2022-04-26_final
2022-04-26 09:33:38	ga_ls8c_ard_3-2-1_092087_2022-04-26_final
2022-04-28 09:20:51	ga_ls8c_ard_3-2-1_090086_2022-04-27_final
2022-04-28 09:21:15	ga_ls8c_ard_3-2-1_090087_2022-04-27_final
2022-05-17 09:51:56	ga_ls8c_ard_3-2-1_095086_2022-05-17_final
2022-05-17 09:52:20	ga_ls8c_ard_3-2-1_095087_2022-05-17_final
2022-05-19 09:39:34	ga_ls8c_ard_3-2-1_093086_2022-05-19_final
2022-05-19 09:39:58	ga_ls8c_ard_3-2-1_093087_2022-05-19_final
2022-05-23 09:14:51	ga_ls8c_ard_3-2-1_089086_2022-05-22_final
2022-05-24 09:58:06	ga_ls8c_ard_3-2-1_096086_2022-05-24_final
2022-09-19 09:21:44	ga_ls8c_ard_3-2-1_090086_2022-09-18_final
2022-09-19 09:22:08	ga_ls8c_ard_3-2-1_090087_2022-09-18_final
2022-09-22 09:52:38	ga_ls8c_ard_3-2-1_095086_2022-09-22_final
2022-09-22 09:53:02	ga_ls8c_ard_3-2-1_095087_2022-09-22_final
2022-09-24 09:40:17	ga_ls8c_ard_3-2-1_093086_2022-09-24_final
2022-09-24 09:40:41	ga_ls8c_ard_3-2-1_093087_2022-09-24_final
2022-09-26 09:27:55	ga_ls8c_ard_3-2-1_091086_2022-09-25_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