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
2015-08-23 11:41:36	ga_ls8c_ard_3-0-0_114067_2015-08-23_final
2015-09-24 11:41:49	ga_ls8c_ard_3-0-0_114067_2015-09-24_final
2015-10-21 11:27:20	ga_ls8c_ard_3-0-0_111077_2015-10-21_final
2015-10-21 11:27:44	ga_ls8c_ard_3-0-0_111078_2015-10-21_final
2015-10-21 11:28:08	ga_ls8c_ard_3-0-0_111079_2015-10-21_final
2015-10-21 11:28:32	ga_ls8c_ard_3-0-0_111080_2015-10-21_final
2015-10-21 11:28:56	ga_ls8c_ard_3-0-0_111081_2015-10-21_final
2015-10-21 11:29:20	ga_ls8c_ard_3-0-0_111082_2015-10-21_final
2015-10-23 11:17:47	ga_ls8c_ard_3-0-0_109084_2015-10-23_final
2015-10-23 11:18:11	ga_ls8c_ard_3-0-0_109085_2015-10-23_final
2019-06-28 11:17:36	ga_ls8c_ard_3-1-0_109084_2019-06-28_final
2019-06-28 11:18:00	ga_ls8c_ard_3-1-0_109085_2019-06-28_final
2019-07-12 11:27:13	ga_ls8c_ard_3-1-0_111077_2019-07-12_final
2019-07-12 11:27:37	ga_ls8c_ard_3-1-0_111078_2019-07-12_final
2019-07-12 11:28:01	ga_ls8c_ard_3-1-0_111079_2019-07-12_final
2019-07-12 11:28:25	ga_ls8c_ard_3-1-0_111080_2019-07-12_final
2019-07-12 11:28:49	ga_ls8c_ard_3-1-0_111081_2019-07-12_final
2019-07-12 11:29:13	ga_ls8c_ard_3-1-0_111082_2019-07-12_final
2019-07-14 11:17:39	ga_ls8c_ard_3-1-0_109084_2019-07-14_final
2019-07-14 11:18:03	ga_ls8c_ard_3-1-0_109085_2019-07-14_final
2019-07-28 11:27:18	ga_ls8c_ard_3-1-0_111077_2019-07-28_final
2019-07-28 11:27:42	ga_ls8c_ard_3-1-0_111078_2019-07-28_final
2019-07-28 11:28:06	ga_ls8c_ard_3-1-0_111079_2019-07-28_final
2019-07-28 11:28:30	ga_ls8c_ard_3-1-0_111080_2019-07-28_final
2019-07-28 11:28:54	ga_ls8c_ard_3-1-0_111081_2019-07-28_final
2019-07-28 11:29:18	ga_ls8c_ard_3-1-0_111082_2019-07-28_final
2019-08-13 11:27:24	ga_ls8c_ard_3-1-0_111077_2019-08-13_final
2019-08-13 11:27:48	ga_ls8c_ard_3-1-0_111078_2019-08-13_final
2019-08-13 11:28:12	ga_ls8c_ard_3-1-0_111079_2019-08-13_final
2019-08-13 11:28:36	ga_ls8c_ard_3-1-0_111080_2019-08-13_final
2019-08-13 11:29:00	ga_ls8c_ard_3-1-0_111081_2019-08-13_final
2019-08-13 11:29:24	ga_ls8c_ard_3-1-0_111082_2019-08-13_final
2019-08-15 11:17:51	ga_ls8c_ard_3-1-0_109084_2019-08-15_final
2019-08-15 11:18:15	ga_ls8c_ard_3-1-0_109085_2019-08-15_final
2019-09-30 11:27:38	ga_ls8c_ard_3-1-0_111077_2019-09-30_final
2019-09-30 11:28:02	ga_ls8c_ard_3-1-0_111078_2019-09-30_final
2019-09-30 11:28:26	ga_ls8c_ard_3-1-0_111079_2019-09-30_final
2019-09-30 11:28:50	ga_ls8c_ard_3-1-0_111080_2019-09-30_final
2019-09-30 11:29:14	ga_ls8c_ard_3-1-0_111081_2019-09-30_final
2019-09-30 11:29:38	ga_ls8c_ard_3-1-0_111082_2019-09-30_final
2019-10-02 11:18:04	ga_ls8c_ard_3-1-0_109084_2019-10-02_final
2019-10-02 11:18:28	ga_ls8c_ard_3-1-0_109085_2019-10-02_final
2019-10-07 11:31:50	ga_ls8c_ard_3-1-0_112072_2019-10-07_final
2019-10-07 11:32:14	ga_ls8c_ard_3-1-0_112073_2019-10-07_final
2019-10-07 11:32:38	ga_ls8c_ard_3-1-0_112074_2019-10-07_final
2019-10-07 11:33:02	ga_ls8c_ard_3-1-0_112075_2019-10-07_final
2019-10-07 11:33:26	ga_ls8c_ard_3-1-0_112076_2019-10-07_final
2019-10-07 11:33:50	ga_ls8c_ard_3-1-0_112077_2019-10-07_final
2019-10-07 11:34:14	ga_ls8c_ard_3-1-0_112078_2019-10-07_final
2019-10-21 11:42:14	ga_ls8c_ard_3-1-0_114067_2019-10-21_final
2022-08-19 11:38:11	ga_ls8c_ard_3-2-1_113072_2022-08-19_final
2022-08-19 11:38:35	ga_ls8c_ard_3-2-1_113073_2022-08-19_final
2022-08-21 11:27:25	ga_ls8c_ard_3-2-1_111076_2022-08-21_final
2022-08-21 11:27:49	ga_ls8c_ard_3-2-1_111077_2022-08-21_final
2022-08-21 11:28:13	ga_ls8c_ard_3-2-1_111078_2022-08-21_final
2022-08-21 11:28:37	ga_ls8c_ard_3-2-1_111079_2022-08-21_final
2022-08-21 11:29:01	ga_ls8c_ard_3-2-1_111080_2022-08-21_final
2022-08-21 11:29:25	ga_ls8c_ard_3-2-1_111081_2022-08-21_final
2022-08-21 11:29:49	ga_ls8c_ard_3-2-1_111082_2022-08-21_final
2022-10-22 11:38:14	ga_ls8c_ard_3-2-1_113072_2022-10-22_final
2022-10-22 11:38:38	ga_ls8c_ard_3-2-1_113073_2022-10-22_final
2022-10-24 11:27:53	ga_ls8c_ard_3-2-1_111077_2022-10-24_final
2022-10-24 11:28:17	ga_ls8c_ard_3-2-1_111078_2022-10-24_final
2022-10-24 11:28:41	ga_ls8c_ard_3-2-1_111079_2022-10-24_final
2022-10-24 11:29:05	ga_ls8c_ard_3-2-1_111080_2022-10-24_final
2022-10-24 11:29:29	ga_ls8c_ard_3-2-1_111081_2022-10-24_final
2022-10-24 11:29:53	ga_ls8c_ard_3-2-1_111082_2022-10-24_final
2022-10-26 11:18:20	ga_ls8c_ard_3-2-1_109084_2022-10-26_final
2022-10-31 11:32:07	ga_ls8c_ard_3-2-1_112072_2022-10-31_final
2022-10-31 11:32:31	ga_ls8c_ard_3-2-1_112073_2022-10-31_final
2022-10-31 11:32:55	ga_ls8c_ard_3-2-1_112074_2022-10-31_final
2022-10-31 11:33:18	ga_ls8c_ard_3-2-1_112075_2022-10-31_final
2022-10-31 11:33:42	ga_ls8c_ard_3-2-1_112076_2022-10-31_final
2022-10-31 11:34:06	ga_ls8c_ard_3-2-1_112077_2022-10-31_final
2022-10-31 11:34:30	ga_ls8c_ard_3-2-1_112078_2022-10-31_final
2022-11-02 11:23:21	ga_ls8c_ard_3-2-1_110081_2022-11-02_final
2022-11-02 11:23:45	ga_ls8c_ard_3-2-1_110082_2022-11-02_final
2022-11-02 11:24:09	ga_ls8c_ard_3-2-1_110083_2022-11-02_final
2022-11-02 11:24:32	ga_ls8c_ard_3-2-1_110084_2022-11-02_final
2022-11-02 11:24:56	ga_ls8c_ard_3-2-1_110085_2022-11-02_final
2022-11-07 11:38:17	ga_ls8c_ard_3-2-1_113072_2022-11-07_final
2022-11-07 11:38:41	ga_ls8c_ard_3-2-1_113073_2022-11-07_final
2023-03-31 11:37:26	ga_ls8c_ard_3-2-1_113072_2023-03-31_final
2023-03-31 11:37:50	ga_ls8c_ard_3-2-1_113073_2023-03-31_final
2023-04-02 11:27:02	ga_ls8c_ard_3-2-1_111077_2023-04-02_final
2023-04-02 11:27:26	ga_ls8c_ard_3-2-1_111078_2023-04-02_final
2023-04-02 11:27:50	ga_ls8c_ard_3-2-1_111079_2023-04-02_final
2023-04-02 11:28:14	ga_ls8c_ard_3-2-1_111080_2023-04-02_final
2023-04-02 11:28:38	ga_ls8c_ard_3-2-1_111081_2023-04-02_final
2023-04-02 11:29:02	ga_ls8c_ard_3-2-1_111082_2023-04-02_final
2023-07-21 11:37:21	ga_ls8c_ard_3-2-1_113072_2023-07-21_final
2023-07-21 11:37:45	ga_ls8c_ard_3-2-1_113073_2023-07-21_final
2023-07-25 11:17:29	ga_ls8c_ard_3-2-1_109084_2023-07-25_final
2023-08-06 11:37:30	ga_ls8c_ard_3-2-1_113072_2023-08-06_final
2023-08-06 11:37:54	ga_ls8c_ard_3-2-1_113073_2023-08-06_final
2023-08-08 11:27:08	ga_ls8c_ard_3-2-1_111077_2023-08-08_final
2023-08-08 11:27:32	ga_ls8c_ard_3-2-1_111078_2023-08-08_final
2023-08-08 11:27:56	ga_ls8c_ard_3-2-1_111079_2023-08-08_final
2023-08-08 11:28:20	ga_ls8c_ard_3-2-1_111080_2023-08-08_final
2023-08-08 11:28:44	ga_ls8c_ard_3-2-1_111081_2023-08-08_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years