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
2018-02-21 09:12:17	ga_ls8c_ard_3-0-0_089080_2018-02-20_final
2018-02-21 09:12:41	ga_ls8c_ard_3-0-0_089081_2018-02-20_final
2018-02-21 09:13:05	ga_ls8c_ard_3-0-0_089082_2018-02-20_final
2018-02-21 09:13:29	ga_ls8c_ard_3-0-0_089083_2018-02-20_final
2018-02-21 09:13:53	ga_ls8c_ard_3-0-0_089084_2018-02-20_final
2018-02-21 09:14:17	ga_ls8c_ard_3-0-0_089085_2018-02-20_final
2018-02-26 09:25:36	ga_ls8c_ard_3-0-0_092067_2018-02-25_final
2018-02-26 09:26:00	ga_ls8c_ard_3-0-0_092068_2018-02-25_final
2018-02-26 09:27:12	ga_ls8c_ard_3-0-0_092071_2018-02-25_final
2018-02-26 09:27:36	ga_ls8c_ard_3-0-0_092072_2018-02-25_final
2018-03-25 09:12:01	ga_ls8c_ard_3-0-0_089080_2018-03-24_final
2018-03-25 09:12:25	ga_ls8c_ard_3-0-0_089081_2018-03-24_final
2018-03-25 09:12:49	ga_ls8c_ard_3-0-0_089082_2018-03-24_final
2018-03-25 09:13:13	ga_ls8c_ard_3-0-0_089083_2018-03-24_final
2018-03-25 09:13:37	ga_ls8c_ard_3-0-0_089084_2018-03-24_final
2018-03-25 09:14:01	ga_ls8c_ard_3-0-0_089085_2018-03-24_final
2018-04-01 09:16:09	ga_ls8c_ard_3-0-0_090075_2018-03-31_final
2018-04-01 09:16:33	ga_ls8c_ard_3-0-0_090076_2018-03-31_final
2018-04-01 09:16:57	ga_ls8c_ard_3-0-0_090077_2018-03-31_final
2018-04-01 09:17:21	ga_ls8c_ard_3-1-0_090078_2018-03-31_final
2018-04-01 09:17:45	ga_ls8c_ard_3-0-0_090079_2018-03-31_final
2018-04-01 09:18:09	ga_ls8c_ard_3-0-0_090080_2018-03-31_final
2018-04-01 09:18:33	ga_ls8c_ard_3-0-0_090081_2018-03-31_final
2018-04-03 09:06:58	ga_ls8c_ard_3-0-0_088083_2018-04-02_final
2018-04-03 09:07:22	ga_ls8c_ard_3-0-0_088084_2018-04-02_final
2018-04-06 09:31:27	ga_ls8c_ard_3-0-0_093067_2018-04-06_final
2018-04-10 09:11:53	ga_ls8c_ard_3-0-0_089080_2018-04-09_final
2018-04-10 09:12:17	ga_ls8c_ard_3-0-0_089081_2018-04-09_final
2018-04-15 09:25:11	ga_ls8c_ard_3-0-0_092067_2018-04-14_final
2018-04-15 09:25:35	ga_ls8c_ard_3-0-0_092068_2018-04-14_final
2018-04-15 09:26:47	ga_ls8c_ard_3-0-0_092071_2018-04-14_final
2018-04-15 09:27:11	ga_ls8c_ard_3-0-0_092072_2018-04-14_final
2018-04-24 09:20:55	ga_ls8c_ard_3-0-0_091072_2018-04-23_final
2018-04-24 09:21:19	ga_ls8c_ard_3-0-0_091073_2018-04-23_final
2018-04-24 09:21:43	ga_ls8c_ard_3-0-0_091074_2018-04-23_final
2018-04-24 09:22:07	ga_ls8c_ard_3-0-0_091075_2018-04-23_final
2018-04-24 09:22:30	ga_ls8c_ard_3-0-0_091076_2018-04-23_final
2018-05-03 09:15:51	ga_ls8c_ard_3-0-0_090075_2018-05-02_final
2018-05-03 09:16:15	ga_ls8c_ard_3-0-0_090076_2018-05-02_final
2018-05-03 09:16:39	ga_ls8c_ard_3-0-0_090077_2018-05-02_final
2018-05-03 09:17:03	ga_ls8c_ard_3-0-0_090078_2018-05-02_final
2018-05-03 09:17:27	ga_ls8c_ard_3-0-0_090079_2018-05-02_final
2018-05-03 09:17:51	ga_ls8c_ard_3-0-0_090080_2018-05-02_final
2018-05-03 09:18:14	ga_ls8c_ard_3-0-0_090081_2018-05-02_final
2018-05-05 09:06:40	ga_ls8c_ard_3-0-0_088083_2018-05-04_final
2018-05-05 09:07:04	ga_ls8c_ard_3-0-0_088084_2018-05-04_final
2018-05-08 09:31:09	ga_ls8c_ard_3-0-0_093067_2018-05-08_final
2018-05-10 09:20:45	ga_ls8c_ard_3-0-0_091072_2018-05-09_final
2018-05-10 09:21:09	ga_ls8c_ard_3-0-0_091073_2018-05-09_final
2018-05-10 09:21:33	ga_ls8c_ard_3-0-0_091074_2018-05-09_final
2018-05-10 09:21:57	ga_ls8c_ard_3-0-0_091075_2018-05-09_final
2018-05-10 09:22:21	ga_ls8c_ard_3-0-0_091076_2018-05-09_final
2018-05-12 09:11:10	ga_ls8c_ard_3-0-0_089079_2018-05-11_final
2018-05-12 09:11:34	ga_ls8c_ard_3-0-0_089080_2018-05-11_final
2018-05-12 09:11:58	ga_ls8c_ard_3-0-0_089081_2018-05-11_final
2018-05-12 09:12:22	ga_ls8c_ard_3-0-0_089082_2018-05-11_final
2018-05-12 09:12:46	ga_ls8c_ard_3-0-0_089083_2018-05-11_final
2018-05-12 09:13:10	ga_ls8c_ard_3-0-0_089084_2018-05-11_final
2018-05-12 09:13:34	ga_ls8c_ard_3-0-0_089085_2018-05-11_final
2018-05-26 09:20:33	ga_ls8c_ard_3-0-0_091072_2018-05-25_final
2018-05-26 09:20:57	ga_ls8c_ard_3-0-0_091073_2018-05-25_final
2018-05-26 09:21:21	ga_ls8c_ard_3-0-0_091074_2018-05-25_final
2018-05-26 09:21:45	ga_ls8c_ard_3-0-0_091075_2018-05-25_final
2018-05-26 09:22:09	ga_ls8c_ard_3-0-0_091076_2018-05-25_final
2018-06-02 09:24:39	ga_ls8c_ard_3-0-0_092067_2018-06-01_final
2018-06-02 09:25:03	ga_ls8c_ard_3-0-0_092068_2018-06-01_final
2018-06-02 09:26:15	ga_ls8c_ard_3-0-0_092071_2018-06-01_final
2018-06-18 09:24:47	ga_ls8c_ard_3-0-0_092067_2018-06-17_final
2018-06-18 09:25:11	ga_ls8c_ard_3-0-0_092068_2018-06-17_final
2018-06-18 09:26:23	ga_ls8c_ard_3-0-0_092071_2018-06-17_final
2018-07-22 09:15:55	ga_ls8c_ard_3-0-0_090075_2018-07-21_final
2018-07-22 09:16:19	ga_ls8c_ard_3-0-0_090076_2018-07-21_final
2018-07-22 09:16:43	ga_ls8c_ard_3-0-0_090077_2018-07-21_final
2018-07-22 09:17:06	ga_ls8c_ard_3-0-0_090078_2018-07-21_final
2018-07-22 09:17:30	ga_ls8c_ard_3-0-0_090079_2018-07-21_final
2018-07-22 09:17:54	ga_ls8c_ard_3-0-0_090080_2018-07-21_final
2018-07-22 09:18:18	ga_ls8c_ard_3-0-0_090081_2018-07-21_final
2018-07-29 09:20:57	ga_ls8c_ard_3-0-0_091072_2018-07-28_final
2018-07-29 09:21:21	ga_ls8c_ard_3-0-0_091073_2018-07-28_final
2018-07-29 09:21:45	ga_ls8c_ard_3-0-0_091074_2018-07-28_final
2018-07-29 09:22:09	ga_ls8c_ard_3-0-0_091075_2018-07-28_final
2018-07-29 09:22:33	ga_ls8c_ard_3-0-0_091076_2018-07-28_final
2018-09-15 09:21:18	ga_ls8c_ard_3-0-0_091072_2018-09-14_final
2018-09-15 09:21:42	ga_ls8c_ard_3-0-0_091073_2018-09-14_final
2018-09-15 09:22:06	ga_ls8c_ard_3-0-0_091074_2018-09-14_final
2018-09-15 09:22:30	ga_ls8c_ard_3-0-0_091075_2018-09-14_final
2018-09-15 09:22:54	ga_ls8c_ard_3-0-0_091076_2018-09-14_final
2018-09-24 09:16:22	ga_ls8c_ard_3-0-0_090075_2018-09-23_final
2018-09-24 09:16:46	ga_ls8c_ard_3-0-0_090076_2018-09-23_final
2018-09-24 09:17:10	ga_ls8c_ard_3-0-0_090077_2018-09-23_final
2018-09-24 09:17:34	ga_ls8c_ard_3-0-0_090078_2018-09-23_final
2018-09-24 09:17:58	ga_ls8c_ard_3-0-0_090079_2018-09-23_final
2018-09-24 09:18:22	ga_ls8c_ard_3-0-0_090080_2018-09-23_final
2018-09-24 09:18:46	ga_ls8c_ard_3-0-0_090081_2018-09-23_final
2018-10-26 09:16:36	ga_ls8c_ard_3-0-0_090075_2018-10-25_final
2018-10-26 09:16:59	ga_ls8c_ard_3-0-0_090076_2018-10-25_final
2018-10-26 09:17:23	ga_ls8c_ard_3-0-0_090077_2018-10-25_final
2018-10-26 09:17:47	ga_ls8c_ard_3-0-0_090078_2018-10-25_final
2018-10-26 09:18:11	ga_ls8c_ard_3-0-0_090079_2018-10-25_final
2018-10-26 09:18:35	ga_ls8c_ard_3-0-0_090080_2018-10-25_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years