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
2013-11-30 11:40:28	ga_ls8c_ard_3-0-0_113075_2013-11-30_final
2018-03-17 11:38:24	ga_ls8c_ard_3-0-0_113075_2018-03-17_final
2018-03-17 11:38:48	ga_ls8c_ard_3-0-0_113076_2018-03-17_final
2018-03-17 11:39:12	ga_ls8c_ard_3-0-0_113077_2018-03-17_final
2018-03-17 11:39:36	ga_ls8c_ard_3-0-0_113078_2018-03-17_final
2018-03-17 11:40:00	ga_ls8c_ard_3-0-0_113079_2018-03-17_final
2018-03-17 11:40:23	ga_ls8c_ard_3-0-0_113080_2018-03-17_final
2018-03-17 11:40:47	ga_ls8c_ard_3-0-0_113081_2018-03-17_final
2018-03-19 11:29:13	ga_ls8c_ard_3-0-0_111083_2018-03-19_final
2018-03-19 11:29:37	ga_ls8c_ard_3-0-0_111084_2018-03-19_final
2018-03-19 11:30:01	ga_ls8c_ard_3-0-0_111085_2018-03-19_final
2018-06-05 11:37:37	ga_ls8c_ard_3-0-0_113075_2018-06-05_final
2018-06-05 11:38:01	ga_ls8c_ard_3-0-0_113076_2018-06-05_final
2018-06-05 11:38:25	ga_ls8c_ard_3-0-0_113077_2018-06-05_final
2018-06-05 11:38:49	ga_ls8c_ard_3-0-0_113078_2018-06-05_final
2018-06-05 11:39:13	ga_ls8c_ard_3-0-0_113079_2018-06-05_final
2018-06-05 11:39:37	ga_ls8c_ard_3-0-0_113080_2018-06-05_final
2018-06-05 11:40:01	ga_ls8c_ard_3-0-0_113081_2018-06-05_final
2018-06-07 11:28:28	ga_ls8c_ard_3-0-0_111083_2018-06-07_final
2018-06-07 11:28:52	ga_ls8c_ard_3-0-0_111084_2018-06-07_final
2018-06-07 11:29:16	ga_ls8c_ard_3-0-0_111085_2018-06-07_final
2018-07-30 11:43:54	ga_ls8c_ard_3-0-0_114074_2018-07-30_final
2018-07-30 11:44:18	ga_ls8c_ard_3-0-0_114075_2018-07-30_final
2018-07-30 11:44:42	ga_ls8c_ard_3-0-0_114076_2018-07-30_final
2018-08-15 11:44:03	ga_ls8c_ard_3-0-0_114074_2018-08-15_final
2018-08-15 11:44:27	ga_ls8c_ard_3-0-0_114075_2018-08-15_final
2018-08-15 11:44:51	ga_ls8c_ard_3-0-0_114076_2018-08-15_final
2018-08-17 11:33:42	ga_ls8c_ard_3-0-0_112079_2018-08-17_final
2018-08-17 11:34:06	ga_ls8c_ard_3-0-0_112080_2018-08-17_final
2018-08-17 11:34:30	ga_ls8c_ard_3-0-0_112081_2018-08-17_final
2018-08-17 11:34:54	ga_ls8c_ard_3-0-0_112082_2018-08-17_final
2018-08-17 11:35:18	ga_ls8c_ard_3-0-0_112083_2018-08-17_final
2018-08-17 11:35:42	ga_ls8c_ard_3-0-0_112084_2018-08-17_final
2018-08-17 11:36:06	ga_ls8c_ard_3-0-0_112085_2018-08-17_final
2018-09-18 11:34:18	ga_ls8c_ard_3-0-0_112080_2018-09-18_final
2018-09-18 11:34:41	ga_ls8c_ard_3-0-0_112081_2018-09-18_final
2018-09-18 11:35:05	ga_ls8c_ard_3-0-0_112082_2018-09-18_final
2018-09-18 11:35:29	ga_ls8c_ard_3-0-0_112083_2018-09-18_final
2018-09-18 11:35:53	ga_ls8c_ard_3-0-0_112084_2018-09-18_final
2018-09-18 11:36:17	ga_ls8c_ard_3-0-0_112085_2018-09-18_final
2018-09-25 11:38:32	ga_ls8c_ard_3-0-0_113075_2018-09-25_final
2018-09-25 11:38:56	ga_ls8c_ard_3-0-0_113076_2018-09-25_final
2018-09-25 11:39:20	ga_ls8c_ard_3-0-0_113077_2018-09-25_final
2018-09-25 11:39:44	ga_ls8c_ard_3-0-0_113078_2018-09-25_final
2018-09-25 11:40:07	ga_ls8c_ard_3-0-0_113079_2018-09-25_final
2018-09-25 11:40:31	ga_ls8c_ard_3-0-0_113080_2018-09-25_final
2018-09-25 11:40:55	ga_ls8c_ard_3-0-0_113081_2018-09-25_final
2018-10-04 11:34:01	ga_ls8c_ard_3-0-0_112079_2018-10-04_final
2018-10-04 11:34:25	ga_ls8c_ard_3-0-0_112080_2018-10-04_final
2018-10-04 11:34:49	ga_ls8c_ard_3-0-0_112081_2018-10-04_final
2018-10-04 11:35:13	ga_ls8c_ard_3-0-0_112082_2018-10-04_final
2018-10-04 11:35:37	ga_ls8c_ard_3-0-0_112083_2018-10-04_final
2018-10-04 11:36:01	ga_ls8c_ard_3-0-0_112084_2018-10-04_final
2018-10-04 11:36:25	ga_ls8c_ard_3-0-0_112085_2018-10-04_final
2018-10-13 11:29:30	ga_ls8c_ard_3-0-0_111083_2018-10-13_final
2018-10-13 11:29:54	ga_ls8c_ard_3-0-0_111084_2018-10-13_final
2018-10-13 11:30:18	ga_ls8c_ard_3-0-0_111085_2018-10-13_final
2018-10-27 11:38:45	ga_ls8c_ard_3-0-0_113075_2018-10-27_final
2018-10-27 11:39:08	ga_ls8c_ard_3-0-0_113076_2018-10-27_final
2018-10-27 11:39:32	ga_ls8c_ard_3-0-0_113077_2018-10-27_final
2018-10-27 11:39:56	ga_ls8c_ard_3-0-0_113078_2018-10-27_final
2018-10-27 11:40:20	ga_ls8c_ard_3-0-0_113079_2018-10-27_final
2018-10-27 11:40:44	ga_ls8c_ard_3-0-0_113080_2018-10-27_final
2018-10-27 11:41:08	ga_ls8c_ard_3-0-0_113081_2018-10-27_final
2019-01-15 11:38:41	ga_ls8c_ard_3-0-0_113075_2019-01-15_final
2019-01-15 11:39:05	ga_ls8c_ard_3-0-0_113076_2019-01-15_final
2019-01-15 11:39:29	ga_ls8c_ard_3-0-0_113077_2019-01-15_final
2019-01-15 11:39:53	ga_ls8c_ard_3-0-0_113078_2019-01-15_final
2019-01-15 11:40:17	ga_ls8c_ard_3-0-0_113079_2019-01-15_final
2019-01-15 11:40:41	ga_ls8c_ard_3-0-0_113080_2019-01-15_final
2019-01-15 11:41:05	ga_ls8c_ard_3-0-0_113081_2019-01-15_final
2022-11-09 11:30:18	ga_ls8c_ard_3-2-1_111083_2022-11-09_final
2022-11-09 11:30:42	ga_ls8c_ard_3-2-1_111084_2022-11-09_final
2022-11-14 11:45:11	ga_ls8c_ard_3-2-1_114074_2022-11-14_final
2022-11-14 11:45:35	ga_ls8c_ard_3-2-1_114075_2022-11-14_final
2022-11-14 11:45:59	ga_ls8c_ard_3-2-1_114076_2022-11-14_final
2022-11-16 11:34:48	ga_ls8c_ard_3-2-1_112079_2022-11-16_final
2022-11-16 11:35:12	ga_ls8c_ard_3-2-1_112080_2022-11-16_final
2022-11-16 11:35:36	ga_ls8c_ard_3-2-1_112081_2022-11-16_final
2022-11-16 11:36:00	ga_ls8c_ard_3-2-1_112082_2022-11-16_final
2022-11-16 11:36:24	ga_ls8c_ard_3-2-1_112083_2022-11-16_final
2022-11-16 11:36:47	ga_ls8c_ard_3-2-1_112084_2022-11-16_final
2023-11-12 11:29:50	ga_ls8c_ard_3-2-1_111083_2023-11-12_final
2023-11-12 11:30:14	ga_ls8c_ard_3-2-1_111084_2023-11-12_final
2023-11-17 11:44:50	ga_ls8c_ard_3-2-1_114074_2023-11-17_final
2023-11-17 11:45:14	ga_ls8c_ard_3-2-1_114075_2023-11-17_final
2023-11-17 11:45:38	ga_ls8c_ard_3-2-1_114076_2023-11-17_final
2023-11-19 11:34:29	ga_ls8c_ard_3-2-1_112079_2023-11-19_final
2023-11-19 11:34:53	ga_ls8c_ard_3-2-1_112080_2023-11-19_final
2023-11-19 11:35:17	ga_ls8c_ard_3-2-1_112081_2023-11-19_final
2023-11-19 11:35:41	ga_ls8c_ard_3-2-1_112082_2023-11-19_final
2023-11-19 11:36:05	ga_ls8c_ard_3-2-1_112083_2023-11-19_final
2023-11-19 11:36:29	ga_ls8c_ard_3-2-1_112084_2023-11-19_final
2023-12-03 11:44:47	ga_ls8c_ard_3-2-1_114074_2023-12-03_final
2023-12-03 11:45:11	ga_ls8c_ard_3-2-1_114075_2023-12-03_final
2023-12-03 11:45:35	ga_ls8c_ard_3-2-1_114076_2023-12-03_final
2023-12-05 11:34:47	ga_ls8c_ard_3-2-1_112080_2023-12-05_final
2023-12-05 11:35:11	ga_ls8c_ard_3-2-1_112081_2023-12-05_final
2023-12-05 11:35:35	ga_ls8c_ard_3-2-1_112082_2023-12-05_final
2023-12-05 11:35:59	ga_ls8c_ard_3-2-1_112083_2023-12-05_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