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
2017-03-25 11:19:07	ga_ls8c_ard_3-0-0_110073_2017-03-25_final
2017-03-25 11:19:31	ga_ls8c_ard_3-0-0_110074_2017-03-25_final
2017-03-25 11:19:55	ga_ls8c_ard_3-0-0_110075_2017-03-25_final
2017-03-25 11:20:19	ga_ls8c_ard_3-0-0_110076_2017-03-25_final
2017-03-25 11:20:43	ga_ls8c_ard_3-0-0_110077_2017-03-25_final
2017-03-25 11:21:07	ga_ls8c_ard_3-0-0_110078_2017-03-25_final
2017-03-25 11:21:31	ga_ls8c_ard_3-0-0_110079_2017-03-25_final
2017-04-08 11:29:00	ga_ls8c_ard_3-0-0_112067_2017-04-08_final
2017-04-08 11:29:24	ga_ls8c_ard_3-0-0_112068_2017-04-08_final
2017-04-08 11:29:48	ga_ls8c_ard_3-0-0_112069_2017-04-08_final
2017-04-10 11:19:01	ga_ls8c_ard_3-0-0_110073_2017-04-10_final
2017-04-10 11:19:25	ga_ls8c_ard_3-0-0_110074_2017-04-10_final
2017-04-10 11:19:48	ga_ls8c_ard_3-0-0_110075_2017-04-10_final
2017-04-10 11:20:12	ga_ls8c_ard_3-0-0_110076_2017-04-10_final
2017-04-10 11:20:36	ga_ls8c_ard_3-0-0_110077_2017-04-10_final
2017-04-10 11:21:00	ga_ls8c_ard_3-0-0_110078_2017-04-10_final
2017-04-10 11:21:24	ga_ls8c_ard_3-0-0_110079_2017-04-10_final
2017-05-12 11:18:54	ga_ls8c_ard_3-0-0_110073_2017-05-12_final
2017-05-12 11:19:18	ga_ls8c_ard_3-0-0_110074_2017-05-12_final
2017-05-12 11:19:42	ga_ls8c_ard_3-0-0_110075_2017-05-12_final
2017-05-12 11:20:06	ga_ls8c_ard_3-0-0_110076_2017-05-12_final
2017-05-12 11:20:30	ga_ls8c_ard_3-0-0_110077_2017-05-12_final
2017-05-12 11:20:54	ga_ls8c_ard_3-0-0_110078_2017-05-12_final
2017-05-12 11:21:18	ga_ls8c_ard_3-0-0_110079_2017-05-12_final
2017-06-29 11:19:17	ga_ls8c_ard_3-0-0_110073_2017-06-29_final
2017-06-29 11:19:41	ga_ls8c_ard_3-0-0_110074_2017-06-29_final
2017-06-29 11:20:04	ga_ls8c_ard_3-0-0_110075_2017-06-29_final
2017-06-29 11:20:28	ga_ls8c_ard_3-0-0_110076_2017-06-29_final
2017-06-29 11:20:52	ga_ls8c_ard_3-0-0_110077_2017-06-29_final
2017-06-29 11:21:16	ga_ls8c_ard_3-0-0_110078_2017-06-29_final
2017-06-29 11:21:40	ga_ls8c_ard_3-0-0_110079_2017-06-29_final
2018-06-02 11:09:31	ga_ls8c_ard_3-0-0_108082_2018-06-02_final
2018-06-02 11:09:55	ga_ls8c_ard_3-0-0_108083_2018-06-02_final
2018-06-02 11:10:19	ga_ls8c_ard_3-0-0_108084_2018-06-02_final
2018-06-02 11:10:43	ga_ls8c_ard_3-0-0_108085_2018-06-02_final
2018-06-27 11:04:46	ga_ls8c_ard_3-0-0_107085_2018-06-27_final
2018-07-29 11:05:01	ga_ls8c_ard_3-0-0_107085_2018-07-29_final
2018-08-26 11:23:36	ga_ls8c_ard_3-0-0_111069_2018-08-26_final
2018-08-26 11:24:00	ga_ls8c_ard_3-0-0_111070_2018-08-26_final
2018-08-26 11:24:24	ga_ls8c_ard_3-0-0_111071_2018-08-26_final
2018-08-26 11:24:48	ga_ls8c_ard_3-0-0_111072_2018-08-26_final
2018-08-26 11:25:12	ga_ls8c_ard_3-0-0_111073_2018-08-26_final
2018-08-26 11:25:36	ga_ls8c_ard_3-0-0_111074_2018-08-26_final
2018-08-28 11:14:51	ga_ls8c_ard_3-0-0_109078_2018-08-28_final
2018-08-28 11:15:15	ga_ls8c_ard_3-0-0_109079_2018-08-28_final
2018-08-28 11:15:39	ga_ls8c_ard_3-0-0_109080_2018-08-28_final
2018-08-28 11:16:03	ga_ls8c_ard_3-0-0_109081_2018-08-28_final
2018-08-28 11:16:27	ga_ls8c_ard_3-0-0_109082_2018-08-28_final
2018-08-28 11:16:51	ga_ls8c_ard_3-0-0_109083_2018-08-28_final
2018-09-06 11:10:19	ga_ls8c_ard_3-0-0_108082_2018-09-06_final
2018-09-06 11:10:43	ga_ls8c_ard_3-0-0_108083_2018-09-06_final
2018-09-06 11:11:07	ga_ls8c_ard_3-0-0_108084_2018-09-06_final
2018-09-06 11:11:31	ga_ls8c_ard_3-0-0_108085_2018-09-06_final
2019-06-19 11:19:21	ga_ls8c_ard_3-1-0_110073_2019-06-19_final
2019-06-19 11:19:45	ga_ls8c_ard_3-1-0_110074_2019-06-19_final
2019-06-19 11:20:09	ga_ls8c_ard_3-1-0_110075_2019-06-19_final
2019-06-19 11:20:33	ga_ls8c_ard_3-1-0_110076_2019-06-19_final
2019-06-19 11:20:57	ga_ls8c_ard_3-1-0_110077_2019-06-19_final
2019-06-19 11:21:21	ga_ls8c_ard_3-1-0_110078_2019-06-19_final
2019-06-19 11:21:45	ga_ls8c_ard_3-1-0_110079_2019-06-19_final
2019-06-21 11:10:36	ga_ls8c_ard_3-1-0_108082_2019-06-21_final
2019-06-21 11:11:00	ga_ls8c_ard_3-1-0_108083_2019-06-21_final
2019-06-21 11:11:24	ga_ls8c_ard_3-1-0_108084_2019-06-21_final
2019-06-21 11:11:48	ga_ls8c_ard_3-1-0_108085_2019-06-21_final
2019-07-05 11:19:25	ga_ls8c_ard_3-1-0_110073_2019-07-05_final
2019-07-05 11:19:49	ga_ls8c_ard_3-1-0_110074_2019-07-05_final
2019-07-05 11:20:13	ga_ls8c_ard_3-1-0_110075_2019-07-05_final
2019-07-05 11:20:37	ga_ls8c_ard_3-1-0_110076_2019-07-05_final
2019-07-05 11:21:01	ga_ls8c_ard_3-1-0_110077_2019-07-05_final
2019-07-05 11:21:25	ga_ls8c_ard_3-1-0_110078_2019-07-05_final
2019-07-05 11:21:49	ga_ls8c_ard_3-1-0_110079_2019-07-05_final
2019-07-07 11:10:40	ga_ls8c_ard_3-1-0_108082_2019-07-07_final
2019-07-07 11:11:04	ga_ls8c_ard_3-1-0_108083_2019-07-07_final
2019-07-07 11:11:28	ga_ls8c_ard_3-1-0_108084_2019-07-07_final
2019-07-07 11:11:51	ga_ls8c_ard_3-1-0_108085_2019-07-07_final
2019-08-06 11:19:35	ga_ls8c_ard_3-1-0_110073_2019-08-06_final
2019-08-06 11:19:59	ga_ls8c_ard_3-1-0_110074_2019-08-06_final
2019-08-06 11:20:23	ga_ls8c_ard_3-1-0_110075_2019-08-06_final
2019-08-06 11:20:47	ga_ls8c_ard_3-1-0_110076_2019-08-06_final
2019-08-06 11:21:11	ga_ls8c_ard_3-1-0_110077_2019-08-06_final
2019-08-06 11:21:35	ga_ls8c_ard_3-1-0_110078_2019-08-06_final
2019-08-06 11:21:59	ga_ls8c_ard_3-1-0_110079_2019-08-06_final
2019-08-08 11:10:50	ga_ls8c_ard_3-1-0_108082_2019-08-08_final
2019-08-08 11:11:14	ga_ls8c_ard_3-1-0_108083_2019-08-08_final
2019-08-08 11:11:38	ga_ls8c_ard_3-1-0_108084_2019-08-08_final
2019-08-08 11:12:02	ga_ls8c_ard_3-1-0_108085_2019-08-08_final
2019-08-17 11:05:54	ga_ls8c_ard_3-1-0_107085_2019-08-17_final
2019-08-20 11:29:38	ga_ls8c_ard_3-1-0_112067_2019-08-20_final
2019-08-20 11:30:02	ga_ls8c_ard_3-1-0_112068_2019-08-20_final
2019-08-20 11:30:26	ga_ls8c_ard_3-1-0_112069_2019-08-20_final
2019-08-22 11:19:40	ga_ls8c_ard_3-1-0_110073_2019-08-22_final
2019-08-22 11:20:04	ga_ls8c_ard_3-1-0_110074_2019-08-22_final
2019-08-22 11:20:28	ga_ls8c_ard_3-1-0_110075_2019-08-22_final
2019-08-22 11:20:52	ga_ls8c_ard_3-1-0_110076_2019-08-22_final
2019-08-22 11:21:16	ga_ls8c_ard_3-1-0_110077_2019-08-22_final
2019-08-22 11:21:40	ga_ls8c_ard_3-1-0_110078_2019-08-22_final
2019-08-22 11:22:04	ga_ls8c_ard_3-1-0_110079_2019-08-22_final
2019-08-24 11:10:55	ga_ls8c_ard_3-1-0_108082_2019-08-24_final
2019-08-24 11:11:19	ga_ls8c_ard_3-1-0_108083_2019-08-24_final
2019-08-24 11:11:42	ga_ls8c_ard_3-1-0_108084_2019-08-24_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