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
2018-06-19 11:49:21	ga_ls8c_ard_3-0-0_115073_2018-06-19_final
2018-07-05 11:49:30	ga_ls8c_ard_3-0-0_115073_2018-07-05_final
2018-07-07 11:38:45	ga_ls8c_ard_3-0-0_113077_2018-07-07_final
2018-07-07 11:39:09	ga_ls8c_ard_3-0-0_113078_2018-07-07_final
2018-07-07 11:39:33	ga_ls8c_ard_3-0-0_113079_2018-07-07_final
2018-07-07 11:39:57	ga_ls8c_ard_3-0-0_113080_2018-07-07_final
2018-07-07 11:40:21	ga_ls8c_ard_3-0-0_113081_2018-07-07_final
2018-07-07 11:40:45	ga_ls8c_ard_3-0-0_113082_2018-07-07_final
2018-07-23 11:38:52	ga_ls8c_ard_3-0-0_113077_2018-07-23_final
2018-07-23 11:39:16	ga_ls8c_ard_3-0-0_113078_2018-07-23_final
2018-07-23 11:39:40	ga_ls8c_ard_3-0-0_113079_2018-07-23_final
2018-07-23 11:40:04	ga_ls8c_ard_3-0-0_113080_2018-07-23_final
2018-07-23 11:40:27	ga_ls8c_ard_3-0-0_113081_2018-07-23_final
2018-07-23 11:40:51	ga_ls8c_ard_3-0-0_113082_2018-07-23_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
2018-08-06 11:49:45	ga_ls8c_ard_3-0-0_115073_2018-08-06_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
2018-09-25 11:41:19	ga_ls8c_ard_3-0-0_113082_2018-09-25_final
2018-09-27 11:29:47	ga_ls8c_ard_3-0-0_111084_2018-09-27_final
2018-09-27 11:30:11	ga_ls8c_ard_3-0-0_111085_2018-09-27_final
2018-10-25 11:50:18	ga_ls8c_ard_3-0-0_115073_2018-10-25_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
2018-10-27 11:41:32	ga_ls8c_ard_3-0-0_113082_2018-10-27_final
2018-10-29 11:29:59	ga_ls8c_ard_3-0-0_111084_2018-10-29_final
2018-10-29 11:30:23	ga_ls8c_ard_3-0-0_111085_2018-10-29_final
2019-01-01 11:29:57	ga_ls8c_ard_3-0-0_111084_2019-01-01_final
2019-01-01 11:30:21	ga_ls8c_ard_3-0-0_111085_2019-01-01_final
2019-01-17 11:30:18	ga_ls8c_ard_3-0-0_111085_2019-01-17_final
2019-06-22 11:50:16	ga_ls8c_ard_3-1-0_115073_2019-06-22_final
2019-07-17 11:44:11	ga_ls8c_ard_3-1-0_114073_2019-07-17_final
2019-07-17 11:44:34	ga_ls8c_ard_3-1-0_114074_2019-07-17_final
2019-07-17 11:44:58	ga_ls8c_ard_3-1-0_114075_2019-07-17_final
2019-07-17 11:45:22	ga_ls8c_ard_3-1-0_114076_2019-07-17_final
2019-07-17 11:45:46	ga_ls8c_ard_3-1-0_114077_2019-07-17_final
2019-07-17 11:46:10	ga_ls8c_ard_3-1-0_114078_2019-07-17_final
2019-07-24 11:50:24	ga_ls8c_ard_3-1-0_115073_2019-07-24_final
2019-08-09 11:50:31	ga_ls8c_ard_3-1-0_115073_2019-08-09_final
2019-08-11 11:39:45	ga_ls8c_ard_3-1-0_113077_2019-08-11_final
2019-08-11 11:40:09	ga_ls8c_ard_3-1-0_113078_2019-08-11_final
2019-08-11 11:40:33	ga_ls8c_ard_3-1-0_113079_2019-08-11_final
2019-08-11 11:40:57	ga_ls8c_ard_3-1-0_113080_2019-08-11_final
2019-08-11 11:41:21	ga_ls8c_ard_3-1-0_113081_2019-08-11_final
2019-08-11 11:41:45	ga_ls8c_ard_3-1-0_113082_2019-08-11_final
2020-03-13 11:44:30	ga_ls8c_ard_3-1-0_114074_2020-03-13_final
2020-03-13 11:44:54	ga_ls8c_ard_3-1-0_114075_2020-03-13_final
2020-03-13 11:45:18	ga_ls8c_ard_3-1-0_114076_2020-03-13_final
2020-03-13 11:45:42	ga_ls8c_ard_3-1-0_114077_2020-03-13_final
2020-03-13 11:46:06	ga_ls8c_ard_3-1-0_114078_2020-03-13_final
2020-04-14 11:44:14	ga_ls8c_ard_3-1-0_114074_2020-04-14_final
2020-04-14 11:44:38	ga_ls8c_ard_3-1-0_114075_2020-04-14_final
2020-04-14 11:45:02	ga_ls8c_ard_3-1-0_114076_2020-04-14_final
2020-04-14 11:45:26	ga_ls8c_ard_3-1-0_114077_2020-04-14_final
2020-04-14 11:45:50	ga_ls8c_ard_3-1-0_114078_2020-04-14_final
2020-04-16 11:34:39	ga_ls8c_ard_3-1-0_112081_2020-04-16_final
2020-04-16 11:35:03	ga_ls8c_ard_3-1-0_112082_2020-04-16_final
2020-04-16 11:35:27	ga_ls8c_ard_3-1-0_112083_2020-04-16_final
2020-04-16 11:35:51	ga_ls8c_ard_3-1-0_112084_2020-04-16_final
2020-04-16 11:36:15	ga_ls8c_ard_3-1-0_112085_2020-04-16_final
2020-05-07 11:49:49	ga_ls8c_ard_3-1-0_115073_2020-05-07_final
2020-05-09 11:38:38	ga_ls8c_ard_3-1-0_113076_2020-05-09_final
2020-05-09 11:39:02	ga_ls8c_ard_3-1-0_113077_2020-05-09_final
2020-05-09 11:39:26	ga_ls8c_ard_3-1-0_113078_2020-05-09_final
2020-05-09 11:39:50	ga_ls8c_ard_3-1-0_113079_2020-05-09_final
2020-05-09 11:40:14	ga_ls8c_ard_3-1-0_113080_2020-05-09_final
2020-05-09 11:40:38	ga_ls8c_ard_3-1-0_113081_2020-05-09_final
2020-05-09 11:41:02	ga_ls8c_ard_3-1-0_113082_2020-05-09_final
2020-06-10 11:39:14	ga_ls8c_ard_3-1-0_113077_2020-06-10_final
2020-06-10 11:39:38	ga_ls8c_ard_3-1-0_113078_2020-06-10_final
2020-06-10 11:40:02	ga_ls8c_ard_3-1-0_113079_2020-06-10_final
2020-06-10 11:40:26	ga_ls8c_ard_3-1-0_113080_2020-06-10_final
2020-06-10 11:40:50	ga_ls8c_ard_3-1-0_113081_2020-06-10_final
2020-06-10 11:41:14	ga_ls8c_ard_3-1-0_113082_2020-06-10_final
2020-06-19 11:34:44	ga_ls8c_ard_3-1-0_112081_2020-06-19_final
2020-06-19 11:35:08	ga_ls8c_ard_3-1-0_112082_2020-06-19_final
2020-06-19 11:35:32	ga_ls8c_ard_3-1-0_112083_2020-06-19_final
2020-06-19 11:35:56	ga_ls8c_ard_3-1-0_112084_2020-06-19_final
2020-06-19 11:36:20	ga_ls8c_ard_3-1-0_112085_2020-06-19_final
2020-06-26 11:38:59	ga_ls8c_ard_3-1-0_113076_2020-06-26_final
2020-06-26 11:39:23	ga_ls8c_ard_3-1-0_113077_2020-06-26_final
2020-06-26 11:39:47	ga_ls8c_ard_3-1-0_113078_2020-06-26_final
2020-06-26 11:40:11	ga_ls8c_ard_3-1-0_113079_2020-06-26_final
2020-06-26 11:40:35	ga_ls8c_ard_3-1-0_113080_2020-06-26_final
2020-06-26 11:40:59	ga_ls8c_ard_3-1-0_113081_2020-06-26_final
2020-06-26 11:41:23	ga_ls8c_ard_3-1-0_113082_2020-06-26_final
2020-06-28 11:29:50	ga_ls8c_ard_3-1-0_111084_2020-06-28_final
2020-06-28 11:30:14	ga_ls8c_ard_3-1-0_111085_2020-06-28_final
2020-07-10 11:50:15	ga_ls8c_ard_3-1-0_115073_2020-07-10_final
2020-07-30 11:30:01	ga_ls8c_ard_3-1-0_111084_2020-07-30_final
2020-07-30 11:30:25	ga_ls8c_ard_3-1-0_111085_2020-07-30_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