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
2018-09-16 10:10:09	ga_ls8c_ard_3-0-0_098086_2018-09-16_final
2018-09-17 09:14:32	ga_ls8c_ard_3-0-0_089086_2018-09-16_final
2018-09-17 09:14:56	ga_ls8c_ard_3-0-0_089087_2018-09-16_final
2018-11-19 10:10:28	ga_ls8c_ard_3-0-0_098086_2018-11-19_final
2018-11-20 09:14:51	ga_ls8c_ard_3-0-0_089086_2018-11-19_final
2018-11-20 09:15:15	ga_ls8c_ard_3-0-0_089087_2018-11-19_final
2019-01-06 10:10:24	ga_ls8c_ard_3-0-0_098086_2019-01-06_final
2019-01-07 09:14:46	ga_ls8c_ard_3-0-0_089086_2019-01-06_final
2019-01-07 09:15:10	ga_ls8c_ard_3-0-0_089087_2019-01-06_final
2020-06-25 09:20:49	ga_ls8c_ard_3-1-0_090086_2020-06-24_final
2020-06-25 09:21:13	ga_ls8c_ard_3-1-0_090087_2020-06-24_final
2020-07-11 09:20:56	ga_ls8c_ard_3-1-0_090086_2020-07-10_final
2020-07-11 09:21:20	ga_ls8c_ard_3-1-0_090087_2020-07-10_final
2020-07-12 10:04:12	ga_ls8c_ard_3-1-0_097086_2020-07-12_final
2020-07-16 09:39:30	ga_ls8c_ard_3-1-0_093086_2020-07-16_final
2020-07-16 09:39:54	ga_ls8c_ard_3-1-0_093087_2020-07-16_final
2020-07-19 10:10:25	ga_ls8c_ard_3-1-0_098086_2020-07-19_final
2020-07-20 09:14:48	ga_ls8c_ard_3-1-0_089086_2020-07-19_final
2020-07-20 09:15:12	ga_ls8c_ard_3-1-0_089087_2020-07-19_final
2020-07-21 09:58:04	ga_ls8c_ard_3-1-0_096086_2020-07-21_final
2020-07-21 09:58:28	ga_ls8c_ard_3-1-0_096087_2020-07-21_final
2020-08-03 09:27:13	ga_ls8c_ard_3-1-0_091086_2020-08-02_final
2020-08-03 09:27:37	ga_ls8c_ard_3-1-0_091087_2020-08-02_final
2020-08-15 09:52:00	ga_ls8c_ard_3-1-0_095086_2020-08-15_final
2020-08-15 09:52:24	ga_ls8c_ard_3-1-0_095087_2020-08-15_final
2020-08-17 09:39:39	ga_ls8c_ard_3-1-0_093086_2020-08-17_final
2020-08-17 09:40:03	ga_ls8c_ard_3-1-0_093087_2020-08-17_final
2020-08-19 09:27:19	ga_ls8c_ard_3-1-0_091086_2020-08-18_final
2020-08-19 09:27:43	ga_ls8c_ard_3-1-0_091087_2020-08-18_final
2020-08-22 09:58:15	ga_ls8c_ard_3-1-0_096086_2020-08-22_final
2020-08-22 09:58:39	ga_ls8c_ard_3-1-0_096087_2020-08-22_final
2020-08-24 09:45:54	ga_ls8c_ard_3-1-0_094086_2020-08-24_final
2020-08-24 09:46:18	ga_ls8c_ard_3-1-0_094087_2020-08-24_final
2020-08-26 09:33:33	ga_ls8c_ard_3-1-0_092086_2020-08-26_final
2020-08-26 09:33:57	ga_ls8c_ard_3-1-0_092087_2020-08-26_final
2020-08-31 09:52:08	ga_ls8c_ard_3-1-0_095086_2020-08-31_final
2020-08-31 09:52:32	ga_ls8c_ard_3-1-0_095087_2020-08-31_final
2020-09-05 10:10:43	ga_ls8c_ard_3-1-0_098086_2020-09-05_final
2020-09-06 09:15:06	ga_ls8c_ard_3-1-0_089086_2020-09-05_final
2020-09-06 09:15:30	ga_ls8c_ard_3-1-0_089087_2020-09-05_final
2020-09-11 09:33:40	ga_ls8c_ard_3-1-0_092086_2020-09-11_final
2020-09-11 09:34:04	ga_ls8c_ard_3-1-0_092087_2020-09-11_final
2020-09-16 09:52:14	ga_ls8c_ard_3-1-0_095086_2020-09-16_final
2020-09-16 09:52:38	ga_ls8c_ard_3-1-0_095087_2020-09-16_final
2022-02-26 09:52:01	ga_ls8c_ard_3-2-1_095086_2022-02-26_final
2022-02-26 09:52:25	ga_ls8c_ard_3-2-1_095087_2022-02-26_final
2022-02-28 09:39:39	ga_ls8c_ard_3-2-1_093086_2022-02-28_final
2022-02-28 09:40:03	ga_ls8c_ard_3-2-1_093087_2022-02-28_final
2022-03-02 09:27:17	ga_ls8c_ard_3-2-1_091086_2022-03-01_final
2022-03-02 09:27:41	ga_ls8c_ard_3-2-1_091087_2022-03-01_final
2022-03-14 09:52:20	ga_ls8c_ard_3-2-1_095087_2022-03-14_final
2022-04-15 09:51:50	ga_ls8c_ard_3-2-1_095086_2022-04-15_final
2022-04-15 09:52:14	ga_ls8c_ard_3-2-1_095087_2022-04-15_final
2022-04-17 09:39:28	ga_ls8c_ard_3-2-1_093086_2022-04-17_final
2022-04-17 09:39:52	ga_ls8c_ard_3-2-1_093087_2022-04-17_final
2022-04-19 09:27:06	ga_ls8c_ard_3-2-1_091086_2022-04-18_final
2022-04-19 09:27:30	ga_ls8c_ard_3-2-1_091087_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
2022-04-24 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
2022-05-01 09:51:46	ga_ls8c_ard_3-2-1_095086_2022-05-01_final
2022-05-01 09:52:10	ga_ls8c_ard_3-2-1_095087_2022-05-01_final
2022-05-03 09:39:27	ga_ls8c_ard_3-2-1_093086_2022-05-03_final
2022-05-03 09:39:51	ga_ls8c_ard_3-2-1_093087_2022-05-03_final
2022-05-05 09:27:06	ga_ls8c_ard_3-2-1_091086_2022-05-04_final
2022-05-05 09:27:30	ga_ls8c_ard_3-2-1_091087_2022-05-04_final
2022-05-07 09:14:46	ga_ls8c_ard_3-2-1_089086_2022-05-06_final
2022-05-08 09:58:02	ga_ls8c_ard_3-2-1_096086_2022-05-08_final
2022-05-10 09:45:42	ga_ls8c_ard_3-2-1_094086_2022-05-10_final
2022-05-10 09:46:06	ga_ls8c_ard_3-2-1_094087_2022-05-10_final
2022-05-12 09:33:21	ga_ls8c_ard_3-2-1_092086_2022-05-12_final
2022-05-12 09:33:45	ga_ls8c_ard_3-2-1_092087_2022-05-12_final
2022-05-14 09:21:01	ga_ls8c_ard_3-2-1_090086_2022-05-13_final
2022-05-14 09:21:25	ga_ls8c_ard_3-2-1_090087_2022-05-13_final
2022-07-27 09:58:33	ga_ls8c_ard_3-2-1_096086_2022-07-27_final
2022-07-31 09:33:52	ga_ls8c_ard_3-2-1_092086_2022-07-31_final
2022-07-31 09:34:16	ga_ls8c_ard_3-2-1_092087_2022-07-31_final
2022-08-07 09:40:06	ga_ls8c_ard_3-2-1_093086_2022-08-07_final
2022-08-07 09:40:30	ga_ls8c_ard_3-2-1_093087_2022-08-07_final
2022-08-09 09:27:46	ga_ls8c_ard_3-2-1_091086_2022-08-08_final
2022-08-09 09:28:10	ga_ls8c_ard_3-2-1_091087_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 09:46:44	ga_ls8c_ard_3-2-1_094087_2022-08-14_final
2022-08-16 09:33:59	ga_ls8c_ard_3-2-1_092086_2022-08-16_final
2022-08-16 09:34:22	ga_ls8c_ard_3-2-1_092087_2022-08-16_final
2022-08-18 09:21:37	ga_ls8c_ard_3-2-1_090086_2022-08-17_final
2022-08-18 09:22:01	ga_ls8c_ard_3-2-1_090087_2022-08-17_final
2022-08-28 09:58:42	ga_ls8c_ard_3-2-1_096086_2022-08-28_final
2022-11-09 09:52:36	ga_ls8c_ard_3-2-1_095086_2022-11-09_final
2022-11-09 09:53:00	ga_ls8c_ard_3-2-1_095087_2022-11-09_final
2022-11-13 09:27:51	ga_ls8c_ard_3-2-1_091086_2022-11-12_final
2022-11-13 09:28:15	ga_ls8c_ard_3-2-1_091087_2022-11-12_final
2022-11-18 09:46:19	ga_ls8c_ard_3-2-1_094086_2022-11-18_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