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
2018-02-22 09:58:20	ga_ls8c_ard_3-0-0_096087_2018-02-22_final
2018-02-25 10:21:14	ga_ls8c_ard_3-0-0_101067_2018-02-25_final
2018-02-25 10:21:38	ga_ls8c_ard_3-0-0_101068_2018-02-25_final
2018-02-25 10:22:01	ga_ls8c_ard_3-0-0_101069_2018-02-25_final
2018-02-25 10:22:25	ga_ls8c_ard_3-0-0_101070_2018-02-25_final
2018-02-25 10:22:49	ga_ls8c_ard_3-0-0_101071_2018-02-25_final
2018-02-25 10:23:13	ga_ls8c_ard_3-1-0_101072_2018-02-25_final
2018-03-06 10:16:34	ga_ls8c_ard_3-0-0_100071_2018-03-06_final
2018-03-06 10:16:58	ga_ls8c_ard_3-0-0_100072_2018-03-06_final
2018-03-06 10:17:22	ga_ls8c_ard_3-0-0_100073_2018-03-06_final
2018-03-06 10:17:46	ga_ls8c_ard_3-0-0_100074_2018-03-06_final
2018-03-06 10:18:10	ga_ls8c_ard_3-0-0_100075_2018-03-06_final
2018-03-06 10:18:33	ga_ls8c_ard_3-0-0_100076_2018-03-06_final
2018-03-13 10:21:05	ga_ls8c_ard_3-0-0_101067_2018-03-13_final
2018-03-13 10:21:29	ga_ls8c_ard_3-0-0_101068_2018-03-13_final
2018-03-13 10:21:52	ga_ls8c_ard_3-0-0_101069_2018-03-13_final
2018-03-13 10:22:16	ga_ls8c_ard_3-0-0_101070_2018-03-13_final
2018-03-13 10:22:40	ga_ls8c_ard_3-0-0_101071_2018-03-13_final
2018-03-13 10:23:04	ga_ls8c_ard_3-0-0_101072_2018-03-13_final
2018-04-21 10:26:55	ga_ls8c_ard_3-0-0_102067_2018-04-21_final
2018-04-23 10:16:09	ga_ls8c_ard_3-0-0_100071_2018-04-23_final
2018-04-23 10:16:33	ga_ls8c_ard_3-0-0_100072_2018-04-23_final
2018-04-23 10:16:56	ga_ls8c_ard_3-0-0_100073_2018-04-23_final
2018-04-23 10:17:20	ga_ls8c_ard_3-0-0_100074_2018-04-23_final
2018-04-23 10:17:44	ga_ls8c_ard_3-0-0_100075_2018-04-23_final
2018-04-23 10:18:08	ga_ls8c_ard_3-0-0_100076_2018-04-23_final
2018-05-02 10:11:29	ga_ls8c_ard_3-0-0_099075_2018-05-02_final
2018-05-02 10:11:53	ga_ls8c_ard_3-0-0_099076_2018-05-02_final
2018-05-02 10:12:17	ga_ls8c_ard_3-0-0_099077_2018-05-02_final
2018-05-02 10:12:41	ga_ls8c_ard_3-0-0_099078_2018-05-02_final
2018-05-04 10:02:17	ga_ls8c_ard_3-0-0_097083_2018-05-04_final
2018-05-04 10:02:41	ga_ls8c_ard_3-0-0_097084_2018-05-04_final
2018-05-04 10:03:05	ga_ls8c_ard_3-0-0_097085_2018-05-04_final
2018-05-04 10:03:29	ga_ls8c_ard_3-0-0_097086_2018-05-04_final
2018-05-18 10:11:18	ga_ls8c_ard_3-0-0_099075_2018-05-18_final
2018-05-18 10:11:42	ga_ls8c_ard_3-0-0_099076_2018-05-18_final
2018-05-18 10:12:06	ga_ls8c_ard_3-0-0_099077_2018-05-18_final
2018-05-18 10:12:30	ga_ls8c_ard_3-0-0_099078_2018-05-18_final
2018-05-18 10:12:54	ga_ls8c_ard_3-0-0_099079_2018-05-18_final
2018-05-18 10:13:18	ga_ls8c_ard_3-0-0_099080_2018-05-18_final
2018-05-18 10:13:42	ga_ls8c_ard_3-0-0_099081_2018-05-18_final
2018-05-20 10:02:06	ga_ls8c_ard_3-0-0_097083_2018-05-20_final
2018-05-20 10:02:30	ga_ls8c_ard_3-0-0_097084_2018-05-20_final
2018-05-20 10:02:54	ga_ls8c_ard_3-0-0_097085_2018-05-20_final
2018-05-20 10:03:18	ga_ls8c_ard_3-0-0_097086_2018-05-20_final
2018-09-16 10:07:22	ga_ls8c_ard_3-0-0_098079_2018-09-16_final
2018-09-16 10:07:46	ga_ls8c_ard_3-0-0_098080_2018-09-16_final
2018-09-16 10:08:10	ga_ls8c_ard_3-0-0_098081_2018-09-16_final
2018-09-16 10:08:34	ga_ls8c_ard_3-0-0_098082_2018-09-16_final
2018-09-16 10:08:58	ga_ls8c_ard_3-0-0_098083_2018-09-16_final
2018-09-16 10:09:21	ga_ls8c_ard_3-0-0_098084_2018-09-16_final
2018-09-16 10:09:45	ga_ls8c_ard_3-0-0_098085_2018-09-16_final
2018-10-04 09:58:20	ga_ls8c_ard_3-0-0_096087_2018-10-04_final
2018-10-07 10:21:16	ga_ls8c_ard_3-0-0_101067_2018-10-07_final
2018-10-07 10:21:40	ga_ls8c_ard_3-0-0_101068_2018-10-07_final
2018-10-07 10:22:04	ga_ls8c_ard_3-0-0_101069_2018-10-07_final
2018-10-07 10:22:28	ga_ls8c_ard_3-0-0_101070_2018-10-07_final
2018-10-07 10:22:52	ga_ls8c_ard_3-0-0_101071_2018-10-07_final
2018-12-26 10:21:22	ga_ls8c_ard_3-0-0_101067_2018-12-26_final
2018-12-26 10:21:46	ga_ls8c_ard_3-0-0_101068_2018-12-26_final
2018-12-26 10:22:10	ga_ls8c_ard_3-0-0_101069_2018-12-26_final
2018-12-26 10:22:34	ga_ls8c_ard_3-0-0_101070_2018-12-26_final
2018-12-26 10:22:58	ga_ls8c_ard_3-0-0_101071_2018-12-26_final
2019-01-06 10:07:36	ga_ls8c_ard_3-0-0_098079_2019-01-06_final
2019-01-06 10:08:00	ga_ls8c_ard_3-0-0_098080_2019-01-06_final
2019-01-06 10:08:24	ga_ls8c_ard_3-0-0_098081_2019-01-06_final
2019-01-06 10:08:48	ga_ls8c_ard_3-0-0_098082_2019-01-06_final
2019-01-06 10:09:12	ga_ls8c_ard_3-0-0_098083_2019-01-06_final
2019-01-06 10:09:36	ga_ls8c_ard_3-0-0_098084_2019-01-06_final
2019-01-06 10:10:00	ga_ls8c_ard_3-0-0_098085_2019-01-06_final
2023-08-18 10:22:14	ga_ls8c_ard_3-2-1_101069_2023-08-18_final
2023-08-18 10:22:38	ga_ls8c_ard_3-2-1_101070_2023-08-18_final
2023-08-18 10:23:02	ga_ls8c_ard_3-2-1_101071_2023-08-18_final
2023-09-19 10:22:22	ga_ls8c_ard_3-2-1_101069_2023-09-19_final
2023-09-19 10:22:45	ga_ls8c_ard_3-2-1_101070_2023-09-19_final
2023-09-19 10:23:09	ga_ls8c_ard_3-2-1_101071_2023-09-19_final
2023-09-21 10:12:23	ga_ls8c_ard_3-2-1_099075_2023-09-21_final
2023-09-21 10:12:47	ga_ls8c_ard_3-2-1_099076_2023-09-21_final
2023-09-21 10:13:11	ga_ls8c_ard_3-2-1_099077_2023-09-21_final
2023-09-21 10:13:35	ga_ls8c_ard_3-2-1_099078_2023-09-21_final
2023-09-21 10:13:59	ga_ls8c_ard_3-2-1_099079_2023-09-21_final
2023-09-21 10:14:23	ga_ls8c_ard_3-2-1_099080_2023-09-21_final
2023-09-21 10:14:47	ga_ls8c_ard_3-2-1_099081_2023-09-21_final
2023-09-23 10:03:13	ga_ls8c_ard_3-2-1_097083_2023-09-23_final
2023-09-23 10:03:37	ga_ls8c_ard_3-2-1_097084_2023-09-23_final
2023-09-23 10:04:01	ga_ls8c_ard_3-2-1_097085_2023-09-23_final
2023-09-28 10:17:01	ga_ls8c_ard_3-2-1_100071_2023-09-28_final
2023-09-28 10:17:25	ga_ls8c_ard_3-2-1_100072_2023-09-28_final
2023-09-28 10:17:49	ga_ls8c_ard_3-2-1_100073_2023-09-28_final
2023-09-28 10:18:13	ga_ls8c_ard_3-2-1_100074_2023-09-28_final
2023-09-28 10:18:37	ga_ls8c_ard_3-2-1_100075_2023-09-28_final
2023-09-28 10:19:01	ga_ls8c_ard_3-2-1_100076_2023-09-28_final
2023-10-05 10:22:24	ga_ls8c_ard_3-2-1_101069_2023-10-05_final
2023-10-05 10:22:48	ga_ls8c_ard_3-2-1_101070_2023-10-05_final
2023-10-05 10:23:12	ga_ls8c_ard_3-2-1_101071_2023-10-05_final
2023-10-14 10:17:04	ga_ls8c_ard_3-2-1_100071_2023-10-14_final
2023-10-14 10:17:28	ga_ls8c_ard_3-2-1_100072_2023-10-14_final
2023-10-14 10:17:52	ga_ls8c_ard_3-2-1_100073_2023-10-14_final
2023-10-14 10:18:16	ga_ls8c_ard_3-2-1_100074_2023-10-14_final
2023-10-14 10:18:40	ga_ls8c_ard_3-2-1_100075_2023-10-14_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