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
2022-04-03 09:21:25	ga_ls8c_ard_3-2-1_091072_2022-04-02_final
2022-04-03 09:21:49	ga_ls8c_ard_3-2-1_091073_2022-04-02_final
2022-04-03 09:22:13	ga_ls8c_ard_3-2-1_091074_2022-04-02_final
2022-04-03 09:22:37	ga_ls8c_ard_3-2-1_091075_2022-04-02_final
2022-04-03 09:23:01	ga_ls8c_ard_3-2-1_091076_2022-04-02_final
2022-04-03 09:23:25	ga_ls8c_ard_3-2-1_091077_2022-04-02_final
2022-04-03 09:23:49	ga_ls8c_ard_3-2-1_091078_2022-04-02_final
2022-04-03 09:24:13	ga_ls8c_ard_3-2-1_091079_2022-04-02_final
2022-04-05 09:09:53	ga_ls8c_ard_3-2-1_089074_2022-04-04_final
2022-04-05 09:10:17	ga_ls8c_ard_3-2-1_089075_2022-04-04_final
2022-04-05 09:10:41	ga_ls8c_ard_3-2-1_089076_2022-04-04_final
2022-04-05 09:11:05	ga_ls8c_ard_3-2-1_089077_2022-04-04_final
2022-04-05 09:11:29	ga_ls8c_ard_3-2-1_089078_2022-04-04_final
2022-04-05 09:11:53	ga_ls8c_ard_3-2-1_089079_2022-04-04_final
2022-04-05 09:12:16	ga_ls8c_ard_3-2-1_089080_2022-04-04_final
2022-04-05 09:12:40	ga_ls8c_ard_3-2-1_089081_2022-04-04_final
2022-04-05 09:13:04	ga_ls8c_ard_3-2-1_089082_2022-04-04_final
2022-04-05 09:13:28	ga_ls8c_ard_3-2-1_089083_2022-04-04_final
2022-04-05 09:13:52	ga_ls8c_ard_3-2-1_089084_2022-04-04_final
2022-04-05 09:14:16	ga_ls8c_ard_3-2-1_089085_2022-04-04_final
2022-04-05 09:14:40	ga_ls8c_ard_3-2-1_089086_2022-04-04_final
2022-04-10 09:27:16	ga_ls8c_ard_3-2-1_092071_2022-04-09_final
2022-04-10 09:27:40	ga_ls8c_ard_3-2-1_092072_2022-04-09_final
2022-04-10 09:28:04	ga_ls8c_ard_3-2-1_092073_2022-04-09_final
2022-04-10 09:28:28	ga_ls8c_ard_3-2-1_092074_2022-04-09_final
2022-04-10 09:28:52	ga_ls8c_ard_3-2-1_092075_2022-04-09_final
2022-04-12 09:16:07	ga_ls8c_ard_3-2-1_090074_2022-04-11_final
2022-04-12 09:16:31	ga_ls8c_ard_3-2-1_090075_2022-04-11_final
2022-04-12 09:16:55	ga_ls8c_ard_3-2-1_090076_2022-04-11_final
2022-04-12 09:17:19	ga_ls8c_ard_3-2-1_090077_2022-04-11_final
2022-04-12 09:17:43	ga_ls8c_ard_3-2-1_090078_2022-04-11_final
2022-04-12 09:18:07	ga_ls8c_ard_3-2-1_090079_2022-04-11_final
2022-04-12 09:18:31	ga_ls8c_ard_3-2-1_090080_2022-04-11_final
2022-04-12 09:18:55	ga_ls8c_ard_3-2-1_090081_2022-04-11_final
2022-04-12 09:19:19	ga_ls8c_ard_3-2-1_090082_2022-04-11_final
2022-04-12 09:19:43	ga_ls8c_ard_3-2-1_090083_2022-04-11_final
2022-04-14 09:06:10	ga_ls8c_ard_3-2-1_088080_2022-04-13_final
2022-04-14 09:06:34	ga_ls8c_ard_3-2-1_088081_2022-04-13_final
2022-04-14 09:06:58	ga_ls8c_ard_3-2-1_088082_2022-04-13_final
2022-04-14 09:07:22	ga_ls8c_ard_3-2-1_088083_2022-04-13_final
2022-04-19 09:21:31	ga_ls8c_ard_3-2-1_091072_2022-04-18_final
2022-04-19 09:21:55	ga_ls8c_ard_3-2-1_091073_2022-04-18_final
2022-04-19 09:22:18	ga_ls8c_ard_3-2-1_091074_2022-04-18_final
2022-04-19 09:22:42	ga_ls8c_ard_3-2-1_091075_2022-04-18_final
2022-04-19 09:23:06	ga_ls8c_ard_3-2-1_091076_2022-04-18_final
2022-04-19 09:23:30	ga_ls8c_ard_3-2-1_091077_2022-04-18_final
2022-04-19 09:23:54	ga_ls8c_ard_3-2-1_091078_2022-04-18_final
2022-04-19 09:24:18	ga_ls8c_ard_3-2-1_091079_2022-04-18_final
2022-04-21 09:09:56	ga_ls8c_ard_3-2-1_089074_2022-04-20_final
2022-04-21 09:10:20	ga_ls8c_ard_3-2-1_089075_2022-04-20_final
2022-04-21 09:10:44	ga_ls8c_ard_3-2-1_089076_2022-04-20_final
2022-04-21 09:11:08	ga_ls8c_ard_3-2-1_089077_2022-04-20_final
2022-04-21 09:11:32	ga_ls8c_ard_3-2-1_089078_2022-04-20_final
2022-04-21 09:11:56	ga_ls8c_ard_3-2-1_089079_2022-04-20_final
2022-04-21 09:12:20	ga_ls8c_ard_3-2-1_089080_2022-04-20_final
2022-04-21 09:12:44	ga_ls8c_ard_3-2-1_089081_2022-04-20_final
2022-04-21 09:13:08	ga_ls8c_ard_3-2-1_089082_2022-04-20_final
2022-04-21 09:13:32	ga_ls8c_ard_3-2-1_089083_2022-04-20_final
2022-04-21 09:13:56	ga_ls8c_ard_3-2-1_089084_2022-04-20_final
2022-04-21 09:14:20	ga_ls8c_ard_3-2-1_089085_2022-04-20_final
2022-04-21 09:14:44	ga_ls8c_ard_3-2-1_089086_2022-04-20_final
2022-04-26 09:27:15	ga_ls8c_ard_3-2-1_092071_2022-04-25_final
2022-04-26 09:27:39	ga_ls8c_ard_3-2-1_092072_2022-04-25_final
2022-04-26 09:28:02	ga_ls8c_ard_3-2-1_092073_2022-04-25_final
2022-04-26 09:28:26	ga_ls8c_ard_3-2-1_092074_2022-04-25_final
2022-04-26 09:28:50	ga_ls8c_ard_3-2-1_092075_2022-04-25_final
2022-04-28 09:16:04	ga_ls8c_ard_3-2-1_090074_2022-04-27_final
2022-04-28 09:16:27	ga_ls8c_ard_3-2-1_090075_2022-04-27_final
2022-04-28 09:16:51	ga_ls8c_ard_3-2-1_090076_2022-04-27_final
2022-04-28 09:17:15	ga_ls8c_ard_3-2-1_090077_2022-04-27_final
2022-04-28 09:17:39	ga_ls8c_ard_3-2-1_090078_2022-04-27_final
2022-04-28 09:18:03	ga_ls8c_ard_3-2-1_090079_2022-04-27_final
2022-04-28 09:18:27	ga_ls8c_ard_3-2-1_090080_2022-04-27_final
2022-04-28 09:18:51	ga_ls8c_ard_3-2-1_090081_2022-04-27_final
2022-04-28 09:19:15	ga_ls8c_ard_3-2-1_090082_2022-04-27_final
2022-04-28 09:19:39	ga_ls8c_ard_3-2-1_090083_2022-04-27_final
2022-04-30 09:06:06	ga_ls8c_ard_3-2-1_088080_2022-04-29_final
2022-04-30 09:06:30	ga_ls8c_ard_3-2-1_088081_2022-04-29_final
2022-04-30 09:06:54	ga_ls8c_ard_3-2-1_088082_2022-04-29_final
2022-04-30 09:07:18	ga_ls8c_ard_3-2-1_088083_2022-04-29_final
2022-05-05 09:21:31	ga_ls8c_ard_3-2-1_091072_2022-05-04_final
2022-05-05 09:21:55	ga_ls8c_ard_3-2-1_091073_2022-05-04_final
2022-05-05 09:22:19	ga_ls8c_ard_3-2-1_091074_2022-05-04_final
2022-05-05 09:22:43	ga_ls8c_ard_3-2-1_091075_2022-05-04_final
2022-05-05 09:23:07	ga_ls8c_ard_3-2-1_091076_2022-05-04_final
2022-05-05 09:23:31	ga_ls8c_ard_3-2-1_091077_2022-05-04_final
2022-05-05 09:23:55	ga_ls8c_ard_3-2-1_091078_2022-05-04_final
2022-05-05 09:24:19	ga_ls8c_ard_3-2-1_091079_2022-05-04_final
2022-05-07 09:09:59	ga_ls8c_ard_3-2-1_089074_2022-05-06_final
2022-05-07 09:10:23	ga_ls8c_ard_3-2-1_089075_2022-05-06_final
2022-05-07 09:10:47	ga_ls8c_ard_3-2-1_089076_2022-05-06_final
2022-05-07 09:11:11	ga_ls8c_ard_3-2-1_089077_2022-05-06_final
2022-05-07 09:11:35	ga_ls8c_ard_3-2-1_089078_2022-05-06_final
2022-05-07 09:11:59	ga_ls8c_ard_3-2-1_089079_2022-05-06_final
2022-05-07 09:12:22	ga_ls8c_ard_3-2-1_089080_2022-05-06_final
2022-05-07 09:12:46	ga_ls8c_ard_3-2-1_089081_2022-05-06_final
2022-05-07 09:13:10	ga_ls8c_ard_3-2-1_089082_2022-05-06_final
2022-05-07 09:13:34	ga_ls8c_ard_3-2-1_089083_2022-05-06_final
2022-05-07 09:13:58	ga_ls8c_ard_3-2-1_089084_2022-05-06_final
2022-05-07 09:14:22	ga_ls8c_ard_3-2-1_089085_2022-05-06_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