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
2018-02-17 09:31:51	ga_ls8c_ard_3-0-0_093067_2018-02-17_final
2018-02-17 09:32:15	ga_ls8c_ard_3-0-0_093068_2018-02-17_final
2018-02-17 09:33:26	ga_ls8c_ard_3-0-0_093071_2018-02-17_final
2018-02-17 09:33:50	ga_ls8c_ard_3-0-0_093072_2018-02-17_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
2018-02-21 09:14:41	ga_ls8c_ard_3-0-0_089086_2018-02-20_final
2018-02-21 09:15:05	ga_ls8c_ard_3-0-0_089087_2018-02-20_final
2018-02-21 09:15:29	ga_ls8c_ard_3-0-0_089088_2018-02-20_final
2018-02-21 09:15:52	ga_ls8c_ard_3-0-0_089089_2018-02-20_final
2018-02-24 09:37:58	ga_ls8c_ard_3-0-0_094067_2018-02-24_final
2018-03-12 09:37:50	ga_ls8c_ard_3-0-0_094067_2018-03-12_final
2018-03-14 09:27:02	ga_ls8c_ard_3-0-0_092071_2018-03-13_final
2018-03-14 09:27:26	ga_ls8c_ard_3-0-0_092072_2018-03-13_final
2018-03-14 09:27:50	ga_ls8c_ard_3-1-0_092073_2018-03-13_final
2018-03-14 09:28:14	ga_ls8c_ard_3-0-0_092074_2018-03-13_final
2018-03-14 09:28:38	ga_ls8c_ard_3-0-0_092075_2018-03-13_final
2018-03-14 09:29:02	ga_ls8c_ard_3-0-0_092076_2018-03-13_final
2018-03-28 09:37:43	ga_ls8c_ard_3-0-0_094067_2018-03-28_final
2018-04-29 09:37:25	ga_ls8c_ard_3-0-0_094067_2018-04-29_final
2018-05-17 09:26:27	ga_ls8c_ard_3-0-0_092071_2018-05-16_final
2018-07-02 09:37:17	ga_ls8c_ard_3-0-0_094067_2018-07-02_final
2018-07-27 09:31:17	ga_ls8c_ard_3-0-0_093067_2018-07-27_final
2018-07-27 09:31:41	ga_ls8c_ard_3-0-0_093068_2018-07-27_final
2018-09-13 09:31:40	ga_ls8c_ard_3-0-0_093067_2018-09-13_final
2018-09-13 09:32:04	ga_ls8c_ard_3-0-0_093068_2018-09-13_final
2018-09-22 09:27:07	ga_ls8c_ard_3-0-0_092071_2018-09-21_final
2018-09-22 09:27:31	ga_ls8c_ard_3-0-0_092072_2018-09-21_final
2018-09-22 09:27:55	ga_ls8c_ard_3-0-0_092073_2018-09-21_final
2018-09-22 09:28:19	ga_ls8c_ard_3-0-0_092074_2018-09-21_final
2018-09-22 09:28:43	ga_ls8c_ard_3-0-0_092075_2018-09-21_final
2018-09-22 09:29:07	ga_ls8c_ard_3-0-0_092076_2018-09-21_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
2018-09-24 09:19:10	ga_ls8c_ard_3-0-0_090082_2018-09-23_final
2018-09-24 09:19:34	ga_ls8c_ard_3-0-0_090083_2018-09-23_final
2018-09-24 09:19:58	ga_ls8c_ard_3-0-0_090084_2018-09-23_final
2018-09-24 09:20:22	ga_ls8c_ard_3-0-0_090085_2018-09-23_final
2018-10-03 09:13:28	ga_ls8c_ard_3-0-0_089083_2018-10-02_final
2018-10-03 09:13:52	ga_ls8c_ard_3-0-0_089084_2018-10-02_final
2018-10-03 09:14:16	ga_ls8c_ard_3-0-0_089085_2018-10-02_final
2018-10-03 09:14:40	ga_ls8c_ard_3-0-0_089086_2018-10-02_final
2018-10-03 09:15:04	ga_ls8c_ard_3-0-0_089087_2018-10-02_final
2018-10-03 09:15:28	ga_ls8c_ard_3-0-0_089088_2018-10-02_final
2018-10-03 09:15:52	ga_ls8c_ard_3-0-0_089089_2018-10-02_final
2018-10-22 09:38:06	ga_ls8c_ard_3-0-0_094067_2018-10-22_final
2018-10-24 09:27:21	ga_ls8c_ard_3-0-0_092071_2018-10-23_final
2018-10-24 09:27:45	ga_ls8c_ard_3-0-0_092072_2018-10-23_final
2018-10-24 09:28:09	ga_ls8c_ard_3-0-0_092073_2018-10-23_final
2018-10-24 09:28:33	ga_ls8c_ard_3-0-0_092074_2018-10-23_final
2018-10-24 09:28:57	ga_ls8c_ard_3-0-0_092075_2018-10-23_final
2018-10-24 09:29:21	ga_ls8c_ard_3-0-0_092076_2018-10-23_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
2018-10-26 09:18:59	ga_ls8c_ard_3-0-0_090081_2018-10-25_final
2018-10-26 09:19:23	ga_ls8c_ard_3-0-0_090082_2018-10-25_final
2018-10-26 09:19:47	ga_ls8c_ard_3-0-0_090083_2018-10-25_final
2018-10-26 09:20:11	ga_ls8c_ard_3-0-0_090084_2018-10-25_final
2018-10-26 09:20:35	ga_ls8c_ard_3-0-0_090085_2018-10-25_final
2018-11-16 09:31:59	ga_ls8c_ard_3-0-0_093067_2018-11-16_final
2018-11-16 09:32:23	ga_ls8c_ard_3-0-0_093068_2018-11-16_final
2018-12-20 09:22:45	ga_ls8c_ard_3-0-0_091075_2018-12-19_final
2018-12-20 09:23:09	ga_ls8c_ard_3-0-0_091076_2018-12-19_final
2018-12-20 09:23:33	ga_ls8c_ard_3-0-0_091077_2018-12-19_final
2018-12-20 09:23:57	ga_ls8c_ard_3-0-0_091078_2018-12-19_final
2018-12-20 09:24:21	ga_ls8c_ard_3-0-0_091079_2018-12-19_final
2018-12-20 09:24:45	ga_ls8c_ard_3-0-0_091080_2018-12-19_final
2018-12-20 09:25:09	ga_ls8c_ard_3-0-0_091081_2018-12-19_final
2018-12-29 09:18:34	ga_ls8c_ard_3-0-0_090080_2018-12-28_final
2018-12-29 09:18:58	ga_ls8c_ard_3-0-0_090081_2018-12-28_final
2018-12-29 09:19:22	ga_ls8c_ard_3-0-0_090082_2018-12-28_final
2018-12-29 09:19:46	ga_ls8c_ard_3-0-0_090083_2018-12-28_final
2018-12-29 09:20:10	ga_ls8c_ard_3-0-0_090084_2018-12-28_final
2018-12-29 09:20:34	ga_ls8c_ard_3-0-0_090085_2018-12-28_final
2019-01-07 09:13:34	ga_ls8c_ard_3-0-0_089083_2019-01-06_final
2019-01-07 09:13:58	ga_ls8c_ard_3-0-0_089084_2019-01-06_final
2019-01-07 09:14:22	ga_ls8c_ard_3-0-0_089085_2019-01-06_final
2019-01-07 09:14:46	ga_ls8c_ard_3-0-0_089086_2019-01-06_final
2019-01-07 09:15:10	ga_ls8c_ard_3-0-0_089087_2019-01-06_final
2019-01-07 09:15:34	ga_ls8c_ard_3-0-0_089088_2019-01-06_final
2019-01-07 09:15:58	ga_ls8c_ard_3-0-0_089089_2019-01-06_final
2019-01-30 09:18:28	ga_ls8c_ard_3-0-0_090080_2019-01-29_final
2019-01-30 09:18:52	ga_ls8c_ard_3-0-0_090081_2019-01-29_final
2019-01-30 09:19:16	ga_ls8c_ard_3-0-0_090082_2019-01-29_final
2019-01-30 09:19:40	ga_ls8c_ard_3-0-0_090083_2019-01-29_final
2019-01-30 09:20:04	ga_ls8c_ard_3-0-0_090084_2019-01-29_final
2019-01-30 09:20:28	ga_ls8c_ard_3-0-0_090085_2019-01-29_final
2021-02-02 09:27:35	ga_ls8c_ard_3-2-0_092071_2021-02-01_final
2021-02-02 09:27:59	ga_ls8c_ard_3-2-0_092072_2021-02-01_final
2021-02-02 09:28:23	ga_ls8c_ard_3-2-0_092073_2021-02-01_final
2021-02-02 09:28:47	ga_ls8c_ard_3-2-0_092074_2021-02-01_final
2021-02-02 09:29:11	ga_ls8c_ard_3-2-0_092075_2021-02-01_final
2021-02-02 09:29:35	ga_ls8c_ard_3-2-0_092076_2021-02-01_final
2021-04-09 09:18:26	ga_ls8c_ard_3-2-0_090080_2021-04-08_final
2021-04-09 09:18:50	ga_ls8c_ard_3-2-0_090081_2021-04-08_final
2021-04-09 09:19:13	ga_ls8c_ard_3-2-0_090082_2021-04-08_final
2021-04-09 09:19:37	ga_ls8c_ard_3-2-0_090083_2021-04-08_final
2021-04-09 09:20:01	ga_ls8c_ard_3-2-0_090084_2021-04-08_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