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
2019-02-23 11:43:56	ga_ls8c_ard_3-0-0_114073_2019-02-23_final
2019-02-23 11:44:20	ga_ls8c_ard_3-0-0_114074_2019-02-23_final
2019-02-25 11:33:34	ga_ls8c_ard_3-0-0_112078_2019-02-25_final
2019-02-25 11:33:58	ga_ls8c_ard_3-0-0_112079_2019-02-25_final
2019-02-25 11:34:22	ga_ls8c_ard_3-0-0_112080_2019-02-25_final
2019-02-25 11:34:46	ga_ls8c_ard_3-0-0_112081_2019-02-25_final
2019-02-25 11:35:10	ga_ls8c_ard_3-0-0_112082_2019-02-25_final
2019-02-25 11:35:34	ga_ls8c_ard_3-0-0_112083_2019-02-25_final
2019-03-27 11:43:47	ga_ls8c_ard_3-1-0_114073_2019-03-27_final
2019-03-27 11:44:11	ga_ls8c_ard_3-1-0_114074_2019-03-27_final
2019-03-29 11:33:25	ga_ls8c_ard_3-1-0_112078_2019-03-29_final
2019-03-29 11:33:49	ga_ls8c_ard_3-1-0_112079_2019-03-29_final
2019-03-29 11:34:13	ga_ls8c_ard_3-1-0_112080_2019-03-29_final
2019-03-29 11:34:37	ga_ls8c_ard_3-1-0_112081_2019-03-29_final
2019-03-29 11:35:01	ga_ls8c_ard_3-1-0_112082_2019-03-29_final
2019-03-29 11:35:25	ga_ls8c_ard_3-1-0_112083_2019-03-29_final
2019-04-12 11:43:43	ga_ls8c_ard_3-1-0_114073_2019-04-12_final
2019-04-12 11:44:07	ga_ls8c_ard_3-1-0_114074_2019-04-12_final
2019-04-14 11:33:20	ga_ls8c_ard_3-1-0_112078_2019-04-14_final
2019-04-14 11:33:44	ga_ls8c_ard_3-1-0_112079_2019-04-14_final
2019-04-14 11:34:08	ga_ls8c_ard_3-1-0_112080_2019-04-14_final
2019-04-14 11:34:32	ga_ls8c_ard_3-1-0_112081_2019-04-14_final
2019-04-14 11:34:56	ga_ls8c_ard_3-1-0_112082_2019-04-14_final
2019-04-14 11:35:20	ga_ls8c_ard_3-1-0_112083_2019-04-14_final
2019-05-14 11:43:47	ga_ls8c_ard_3-0-0_114073_2019-05-14_final
2019-05-14 11:44:11	ga_ls8c_ard_3-0-0_114074_2019-05-14_final
2019-05-16 11:33:27	ga_ls8c_ard_3-0-0_112078_2019-05-16_final
2019-05-16 11:33:51	ga_ls8c_ard_3-0-0_112079_2019-05-16_final
2019-05-16 11:34:14	ga_ls8c_ard_3-0-0_112080_2019-05-16_final
2019-05-16 11:34:38	ga_ls8c_ard_3-0-0_112081_2019-05-16_final
2019-05-16 11:35:02	ga_ls8c_ard_3-0-0_112082_2019-05-16_final
2019-05-16 11:35:26	ga_ls8c_ard_3-0-0_112083_2019-05-16_final
2019-07-01 11:44:08	ga_ls8c_ard_3-1-0_114073_2019-07-01_final
2019-07-01 11:44:32	ga_ls8c_ard_3-1-0_114074_2019-07-01_final
2019-07-03 11:33:46	ga_ls8c_ard_3-1-0_112078_2019-07-03_final
2019-07-03 11:34:10	ga_ls8c_ard_3-1-0_112079_2019-07-03_final
2019-07-03 11:34:34	ga_ls8c_ard_3-1-0_112080_2019-07-03_final
2019-07-03 11:34:58	ga_ls8c_ard_3-1-0_112081_2019-07-03_final
2019-07-03 11:35:22	ga_ls8c_ard_3-1-0_112082_2019-07-03_final
2019-07-03 11:35:46	ga_ls8c_ard_3-1-0_112083_2019-07-03_final
2019-09-28 11:38:23	ga_ls8c_ard_3-1-0_113073_2019-09-28_final
2019-09-28 11:38:47	ga_ls8c_ard_3-1-0_113074_2019-09-28_final
2019-09-28 11:39:11	ga_ls8c_ard_3-1-0_113075_2019-09-28_final
2019-09-28 11:39:35	ga_ls8c_ard_3-1-0_113076_2019-09-28_final
2019-09-28 11:39:59	ga_ls8c_ard_3-1-0_113077_2019-09-28_final
2019-09-28 11:40:23	ga_ls8c_ard_3-1-0_113078_2019-09-28_final
2019-09-28 11:40:47	ga_ls8c_ard_3-1-0_113079_2019-09-28_final
2019-11-06 11:44:36	ga_ls8c_ard_3-1-0_114073_2019-11-06_final
2019-11-06 11:45:00	ga_ls8c_ard_3-1-0_114074_2019-11-06_final
2019-11-08 11:34:14	ga_ls8c_ard_3-1-0_112078_2019-11-08_final
2019-11-08 11:34:38	ga_ls8c_ard_3-1-0_112079_2019-11-08_final
2019-11-08 11:35:02	ga_ls8c_ard_3-1-0_112080_2019-11-08_final
2019-11-08 11:35:26	ga_ls8c_ard_3-1-0_112081_2019-11-08_final
2019-11-08 11:35:50	ga_ls8c_ard_3-1-0_112082_2019-11-08_final
2019-11-08 11:36:14	ga_ls8c_ard_3-1-0_112083_2019-11-08_final
2019-11-15 11:38:24	ga_ls8c_ard_3-1-0_113073_2019-11-15_final
2019-11-15 11:38:48	ga_ls8c_ard_3-1-0_113074_2019-11-15_final
2019-11-15 11:39:12	ga_ls8c_ard_3-1-0_113075_2019-11-15_final
2019-11-15 11:39:35	ga_ls8c_ard_3-1-0_113076_2019-11-15_final
2019-11-15 11:39:59	ga_ls8c_ard_3-1-0_113077_2019-11-15_final
2019-11-15 11:40:23	ga_ls8c_ard_3-1-0_113078_2019-11-15_final
2019-11-15 11:40:47	ga_ls8c_ard_3-1-0_113079_2019-11-15_final
2019-12-08 11:44:32	ga_ls8c_ard_3-1-0_114073_2019-12-08_final
2019-12-08 11:44:56	ga_ls8c_ard_3-1-0_114074_2019-12-08_final
2019-12-26 11:34:07	ga_ls8c_ard_3-1-0_112078_2019-12-26_final
2019-12-26 11:34:31	ga_ls8c_ard_3-1-0_112079_2019-12-26_final
2019-12-26 11:34:55	ga_ls8c_ard_3-1-0_112080_2019-12-26_final
2019-12-26 11:35:19	ga_ls8c_ard_3-1-0_112081_2019-12-26_final
2019-12-26 11:35:43	ga_ls8c_ard_3-1-0_112082_2019-12-26_final
2019-12-26 11:36:07	ga_ls8c_ard_3-1-0_112083_2019-12-26_final
2020-03-15 11:33:43	ga_ls8c_ard_3-1-0_112078_2020-03-15_final
2020-03-15 11:34:07	ga_ls8c_ard_3-1-0_112079_2020-03-15_final
2020-03-15 11:34:31	ga_ls8c_ard_3-1-0_112080_2020-03-15_final
2020-03-15 11:34:55	ga_ls8c_ard_3-1-0_112081_2020-03-15_final
2020-03-15 11:35:19	ga_ls8c_ard_3-1-0_112082_2020-03-15_final
2020-03-15 11:35:43	ga_ls8c_ard_3-1-0_112083_2020-03-15_final
2020-05-16 11:44:03	ga_ls8c_ard_3-1-0_114074_2020-05-16_final
2020-05-18 11:33:17	ga_ls8c_ard_3-1-0_112078_2020-05-18_final
2020-05-18 11:33:41	ga_ls8c_ard_3-1-0_112079_2020-05-18_final
2020-05-18 11:34:05	ga_ls8c_ard_3-1-0_112080_2020-05-18_final
2020-05-18 11:34:29	ga_ls8c_ard_3-1-0_112081_2020-05-18_final
2020-05-18 11:34:53	ga_ls8c_ard_3-1-0_112082_2020-05-18_final
2020-05-18 11:35:17	ga_ls8c_ard_3-1-0_112083_2020-05-18_final
2020-09-14 11:38:17	ga_ls8c_ard_3-1-0_113073_2020-09-14_final
2020-09-14 11:38:41	ga_ls8c_ard_3-1-0_113074_2020-09-14_final
2020-09-14 11:39:05	ga_ls8c_ard_3-1-0_113075_2020-09-14_final
2020-09-14 11:39:29	ga_ls8c_ard_3-1-0_113076_2020-09-14_final
2020-09-14 11:39:53	ga_ls8c_ard_3-1-0_113077_2020-09-14_final
2020-09-14 11:40:17	ga_ls8c_ard_3-1-0_113078_2020-09-14_final
2020-09-14 11:40:41	ga_ls8c_ard_3-1-0_113079_2020-09-14_final
2020-11-10 11:34:09	ga_ls8c_ard_3-1-0_112078_2020-11-10_final
2020-11-10 11:34:33	ga_ls8c_ard_3-1-0_112079_2020-11-10_final
2020-11-10 11:34:56	ga_ls8c_ard_3-1-0_112080_2020-11-10_final
2020-11-10 11:35:20	ga_ls8c_ard_3-1-0_112081_2020-11-10_final
2020-11-10 11:35:44	ga_ls8c_ard_3-1-0_112082_2020-11-10_final
2020-11-10 11:36:08	ga_ls8c_ard_3-1-0_112083_2020-11-10_final
2020-12-21 11:29:36	ga_ls8c_ard_3-2-0_111082_2020-12-21_final
2020-12-21 11:30:00	ga_ls8c_ard_3-2-0_111083_2020-12-21_final
2020-12-21 11:30:24	ga_ls8c_ard_3-2-0_111084_2020-12-21_final
2020-12-21 11:30:48	ga_ls8c_ard_3-2-0_111085_2020-12-21_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