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
2018-05-27 10:06:36	ga_ls8c_ard_3-0-0_098079_2018-05-27_final
2018-05-27 10:07:00	ga_ls8c_ard_3-0-0_098080_2018-05-27_final
2018-05-27 10:07:24	ga_ls8c_ard_3-0-0_098081_2018-05-27_final
2018-05-27 10:07:47	ga_ls8c_ard_3-0-0_098082_2018-05-27_final
2018-05-27 10:08:11	ga_ls8c_ard_3-0-0_098083_2018-05-27_final
2018-05-27 10:08:35	ga_ls8c_ard_3-0-0_098084_2018-05-27_final
2018-05-27 10:08:59	ga_ls8c_ard_3-0-0_098085_2018-05-27_final
2018-06-12 10:06:35	ga_ls8c_ard_3-0-0_098079_2018-06-12_final
2018-06-12 10:06:59	ga_ls8c_ard_3-0-0_098080_2018-06-12_final
2018-06-12 10:07:23	ga_ls8c_ard_3-0-0_098081_2018-06-12_final
2018-06-12 10:07:47	ga_ls8c_ard_3-0-0_098082_2018-06-12_final
2018-06-12 10:08:11	ga_ls8c_ard_3-0-0_098083_2018-06-12_final
2018-06-12 10:08:35	ga_ls8c_ard_3-0-0_098084_2018-06-12_final
2018-06-12 10:08:59	ga_ls8c_ard_3-0-0_098085_2018-06-12_final
2018-06-19 10:11:15	ga_ls8c_ard_3-0-0_099075_2018-06-19_final
2018-06-19 10:11:39	ga_ls8c_ard_3-0-0_099076_2018-06-19_final
2018-06-19 10:12:03	ga_ls8c_ard_3-0-0_099077_2018-06-19_final
2018-06-19 10:12:27	ga_ls8c_ard_3-0-0_099078_2018-06-19_final
2018-06-19 10:12:51	ga_ls8c_ard_3-0-0_099079_2018-06-19_final
2018-06-19 10:13:15	ga_ls8c_ard_3-0-0_099080_2018-06-19_final
2018-06-19 10:13:39	ga_ls8c_ard_3-0-0_099081_2018-06-19_final
2018-06-28 10:06:46	ga_ls8c_ard_3-0-0_098079_2018-06-28_final
2018-06-28 10:07:10	ga_ls8c_ard_3-0-0_098080_2018-06-28_final
2018-06-28 10:07:34	ga_ls8c_ard_3-0-0_098081_2018-06-28_final
2018-06-28 10:07:58	ga_ls8c_ard_3-0-0_098082_2018-06-28_final
2018-06-28 10:08:22	ga_ls8c_ard_3-0-0_098083_2018-06-28_final
2018-06-28 10:08:46	ga_ls8c_ard_3-0-0_098084_2018-06-28_final
2018-06-28 10:09:10	ga_ls8c_ard_3-0-0_098085_2018-06-28_final
2018-07-05 10:11:25	ga_ls8c_ard_3-0-0_099075_2018-07-05_final
2018-07-05 10:11:49	ga_ls8c_ard_3-0-0_099076_2018-07-05_final
2018-07-05 10:12:12	ga_ls8c_ard_3-0-0_099077_2018-07-05_final
2018-07-05 10:12:36	ga_ls8c_ard_3-0-0_099078_2018-07-05_final
2018-07-05 10:13:00	ga_ls8c_ard_3-0-0_099079_2018-07-05_final
2018-07-05 10:13:24	ga_ls8c_ard_3-0-0_099080_2018-07-05_final
2018-07-05 10:13:48	ga_ls8c_ard_3-0-0_099081_2018-07-05_final
2018-07-14 10:06:54	ga_ls8c_ard_3-1-0_098079_2018-07-14_final
2018-07-14 10:07:18	ga_ls8c_ard_3-1-0_098080_2018-07-14_final
2018-07-14 10:07:42	ga_ls8c_ard_3-1-0_098081_2018-07-14_final
2018-07-14 10:08:06	ga_ls8c_ard_3-1-0_098082_2018-07-14_final
2018-07-14 10:08:30	ga_ls8c_ard_3-0-0_098083_2018-07-14_final
2018-07-14 10:08:54	ga_ls8c_ard_3-0-0_098084_2018-07-14_final
2018-07-14 10:09:18	ga_ls8c_ard_3-0-0_098085_2018-07-14_final
2018-07-16 09:57:45	ga_ls8c_ard_3-0-0_096087_2018-07-16_final
2018-07-19 10:20:41	ga_ls8c_ard_3-0-0_101067_2018-07-19_final
2018-07-19 10:21:05	ga_ls8c_ard_3-0-0_101068_2018-07-19_final
2018-07-19 10:21:29	ga_ls8c_ard_3-0-0_101069_2018-07-19_final
2018-07-19 10:21:53	ga_ls8c_ard_3-0-0_101070_2018-07-19_final
2018-07-19 10:22:17	ga_ls8c_ard_3-0-0_101071_2018-07-19_final
2018-07-23 10:02:22	ga_ls8c_ard_3-0-0_097083_2018-07-23_final
2018-07-23 10:02:46	ga_ls8c_ard_3-0-0_097084_2018-07-23_final
2018-07-23 10:03:10	ga_ls8c_ard_3-0-0_097085_2018-07-23_final
2018-07-23 10:03:34	ga_ls8c_ard_3-0-0_097086_2018-07-23_final
2018-07-30 10:07:01	ga_ls8c_ard_3-0-0_098079_2018-07-30_final
2018-07-30 10:07:25	ga_ls8c_ard_3-0-0_098080_2018-07-30_final
2018-07-30 10:07:49	ga_ls8c_ard_3-0-0_098081_2018-07-30_final
2018-08-04 10:20:49	ga_ls8c_ard_3-0-0_101067_2018-08-04_final
2018-08-04 10:21:13	ga_ls8c_ard_3-0-0_101068_2018-08-04_final
2018-08-04 10:21:37	ga_ls8c_ard_3-0-0_101069_2018-08-04_final
2018-08-04 10:22:01	ga_ls8c_ard_3-0-0_101070_2018-08-04_final
2018-08-04 10:22:25	ga_ls8c_ard_3-0-0_101071_2018-08-04_final
2018-08-06 10:11:40	ga_ls8c_ard_3-0-0_099075_2018-08-06_final
2018-08-06 10:12:04	ga_ls8c_ard_3-0-0_099076_2018-08-06_final
2018-08-06 10:12:28	ga_ls8c_ard_3-0-0_099077_2018-08-06_final
2018-08-06 10:12:52	ga_ls8c_ard_3-0-0_099078_2018-08-06_final
2018-08-06 10:13:16	ga_ls8c_ard_3-0-0_099079_2018-08-06_final
2018-08-06 10:13:40	ga_ls8c_ard_3-0-0_099080_2018-08-06_final
2018-08-06 10:14:04	ga_ls8c_ard_3-0-0_099081_2018-08-06_final
2018-08-31 10:07:17	ga_ls8c_ard_3-0-0_098079_2018-08-31_final
2018-08-31 10:07:41	ga_ls8c_ard_3-0-0_098080_2018-08-31_final
2018-08-31 10:08:05	ga_ls8c_ard_3-0-0_098081_2018-08-31_final
2018-08-31 10:08:29	ga_ls8c_ard_3-0-0_098082_2018-08-31_final
2018-08-31 10:08:53	ga_ls8c_ard_3-0-0_098083_2018-08-31_final
2018-08-31 10:09:17	ga_ls8c_ard_3-0-0_098084_2018-08-31_final
2018-08-31 10:09:41	ga_ls8c_ard_3-0-0_098085_2018-08-31_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
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
2022-08-19 10:03:41	ga_ls8c_ard_3-2-1_097083_2022-08-19_final
2022-08-19 10:04:05	ga_ls8c_ard_3-2-1_097084_2022-08-19_final
2022-08-19 10:04:29	ga_ls8c_ard_3-2-1_097085_2022-08-19_final
2022-11-05 10:12:58	ga_ls8c_ard_3-2-1_099075_2022-11-05_final
2022-11-05 10:13:22	ga_ls8c_ard_3-2-1_099076_2022-11-05_final
2022-11-05 10:13:46	ga_ls8c_ard_3-2-1_099077_2022-11-05_final
2022-11-05 10:14:09	ga_ls8c_ard_3-2-1_099078_2022-11-05_final
2022-11-05 10:14:33	ga_ls8c_ard_3-2-1_099079_2022-11-05_final
2022-11-05 10:14:57	ga_ls8c_ard_3-2-1_099080_2022-11-05_final
2022-11-05 10:15:21	ga_ls8c_ard_3-2-1_099081_2022-11-05_final
2022-11-07 10:03:47	ga_ls8c_ard_3-2-1_097083_2022-11-07_final
2022-11-07 10:04:11	ga_ls8c_ard_3-2-1_097084_2022-11-07_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