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 11:16:44	ga_ls8c_ard_3-0-0_110067_2017-03-25_final
2017-03-25 11:17:08	ga_ls8c_ard_3-0-0_110068_2017-03-25_final
2017-04-10 11:16:37	ga_ls8c_ard_3-0-0_110067_2017-04-10_final
2017-05-12 11:16:30	ga_ls8c_ard_3-0-0_110067_2017-05-12_final
2017-06-13 11:16:48	ga_ls8c_ard_3-0-0_110067_2017-06-13_final
2018-09-29 11:10:39	ga_ls8c_ard_3-0-0_109067_2018-09-29_final
2018-09-29 11:11:03	ga_ls8c_ard_3-0-0_109068_2018-09-29_final
2018-09-29 11:11:27	ga_ls8c_ard_3-0-0_109069_2018-09-29_final
2018-09-29 11:11:51	ga_ls8c_ard_3-0-0_109070_2018-09-29_final
2018-09-29 11:12:15	ga_ls8c_ard_3-0-0_109071_2018-09-29_final
2018-09-29 11:12:39	ga_ls8c_ard_3-0-0_109072_2018-09-29_final
2018-10-01 11:01:54	ga_ls8c_ard_3-0-0_107076_2018-10-01_final
2018-10-01 11:02:18	ga_ls8c_ard_3-0-0_107077_2018-10-01_final
2018-10-01 11:02:42	ga_ls8c_ard_3-0-0_107078_2018-10-01_final
2018-10-01 11:03:06	ga_ls8c_ard_3-0-0_107079_2018-10-01_final
2018-10-01 11:03:30	ga_ls8c_ard_3-0-0_107080_2018-10-01_final
2018-10-01 11:03:54	ga_ls8c_ard_3-0-0_107081_2018-10-01_final
2018-10-15 11:10:46	ga_ls8c_ard_3-0-0_109067_2018-10-15_final
2018-10-15 11:11:10	ga_ls8c_ard_3-0-0_109068_2018-10-15_final
2018-10-15 11:11:34	ga_ls8c_ard_3-0-0_109069_2018-10-15_final
2018-10-15 11:11:58	ga_ls8c_ard_3-0-0_109070_2018-10-15_final
2018-10-15 11:12:22	ga_ls8c_ard_3-0-0_109071_2018-10-15_final
2018-10-15 11:12:46	ga_ls8c_ard_3-0-0_109072_2018-10-15_final
2018-10-17 11:02:01	ga_ls8c_ard_3-0-0_107076_2018-10-17_final
2018-10-17 11:02:25	ga_ls8c_ard_3-0-0_107077_2018-10-17_final
2018-10-17 11:02:49	ga_ls8c_ard_3-0-0_107078_2018-10-17_final
2018-10-17 11:03:12	ga_ls8c_ard_3-0-0_107079_2018-10-17_final
2018-10-17 11:03:36	ga_ls8c_ard_3-0-0_107080_2018-10-17_final
2018-10-17 11:04:00	ga_ls8c_ard_3-0-0_107081_2018-10-17_final
2018-10-24 11:06:14	ga_ls8c_ard_3-0-0_108071_2018-10-24_final
2018-10-24 11:06:38	ga_ls8c_ard_3-0-0_108072_2018-10-24_final
2018-10-24 11:07:02	ga_ls8c_ard_3-0-0_108073_2018-10-24_final
2018-10-24 11:07:26	ga_ls8c_ard_3-0-0_108074_2018-10-24_final
2018-10-24 11:07:50	ga_ls8c_ard_3-0-0_108075_2018-10-24_final
2018-10-24 11:08:14	ga_ls8c_ard_3-0-0_108076_2018-10-24_final
2018-10-24 11:08:38	ga_ls8c_ard_3-0-0_108077_2018-10-24_final
2018-10-26 10:57:28	ga_ls8c_ard_3-0-0_106080_2018-10-26_final
2018-10-26 10:57:52	ga_ls8c_ard_3-0-0_106081_2018-10-26_final
2018-10-26 10:58:16	ga_ls8c_ard_3-0-0_106082_2018-10-26_final
2018-10-26 10:58:40	ga_ls8c_ard_3-0-0_106083_2018-10-26_final
2018-10-26 10:59:04	ga_ls8c_ard_3-0-0_106084_2018-10-26_final
2018-10-31 11:10:51	ga_ls8c_ard_3-0-0_109067_2018-10-31_final
2018-10-31 11:11:15	ga_ls8c_ard_3-0-0_109068_2018-10-31_final
2018-10-31 11:11:38	ga_ls8c_ard_3-0-0_109069_2018-10-31_final
2018-10-31 11:12:02	ga_ls8c_ard_3-0-0_109070_2018-10-31_final
2018-10-31 11:12:26	ga_ls8c_ard_3-0-0_109071_2018-10-31_final
2018-10-31 11:12:50	ga_ls8c_ard_3-0-0_109072_2018-10-31_final
2018-11-02 11:02:05	ga_ls8c_ard_3-0-0_107076_2018-11-02_final
2018-11-02 11:02:29	ga_ls8c_ard_3-0-0_107077_2018-11-02_final
2018-11-02 11:02:53	ga_ls8c_ard_3-0-0_107078_2018-11-02_final
2018-11-02 11:03:17	ga_ls8c_ard_3-0-0_107079_2018-11-02_final
2018-11-02 11:03:40	ga_ls8c_ard_3-0-0_107080_2018-11-02_final
2018-11-02 11:04:04	ga_ls8c_ard_3-0-0_107081_2018-11-02_final
2018-11-25 11:06:41	ga_ls8c_ard_3-0-0_108072_2018-11-25_final
2018-11-25 11:07:04	ga_ls8c_ard_3-0-0_108073_2018-11-25_final
2018-11-25 11:07:28	ga_ls8c_ard_3-0-0_108074_2018-11-25_final
2018-11-25 11:07:52	ga_ls8c_ard_3-0-0_108075_2018-11-25_final
2018-11-25 11:08:16	ga_ls8c_ard_3-0-0_108076_2018-11-25_final
2018-11-25 11:08:40	ga_ls8c_ard_3-0-0_108077_2018-11-25_final
2018-11-27 10:57:30	ga_ls8c_ard_3-0-0_106080_2018-11-27_final
2018-11-27 10:57:54	ga_ls8c_ard_3-0-0_106081_2018-11-27_final
2018-11-27 10:58:18	ga_ls8c_ard_3-0-0_106082_2018-11-27_final
2018-11-27 10:58:42	ga_ls8c_ard_3-0-0_106083_2018-11-27_final
2018-11-27 10:59:06	ga_ls8c_ard_3-0-0_106084_2018-11-27_final
2018-12-04 11:02:04	ga_ls8c_ard_3-0-0_107076_2018-12-04_final
2018-12-04 11:02:28	ga_ls8c_ard_3-0-0_107077_2018-12-04_final
2018-12-04 11:02:52	ga_ls8c_ard_3-0-0_107078_2018-12-04_final
2018-12-04 11:03:16	ga_ls8c_ard_3-0-0_107079_2018-12-04_final
2018-12-04 11:03:40	ga_ls8c_ard_3-0-0_107080_2018-12-04_final
2018-12-04 11:04:04	ga_ls8c_ard_3-0-0_107081_2018-12-04_final
2018-12-11 11:06:37	ga_ls8c_ard_3-0-0_108072_2018-12-11_final
2018-12-11 11:07:01	ga_ls8c_ard_3-0-0_108073_2018-12-11_final
2018-12-11 11:07:25	ga_ls8c_ard_3-0-0_108074_2018-12-11_final
2018-12-11 11:07:49	ga_ls8c_ard_3-0-0_108075_2018-12-11_final
2018-12-11 11:08:13	ga_ls8c_ard_3-0-0_108076_2018-12-11_final
2018-12-11 11:08:37	ga_ls8c_ard_3-0-0_108077_2018-12-11_final
2018-12-13 10:57:27	ga_ls8c_ard_3-0-0_106080_2018-12-13_final
2018-12-13 10:57:51	ga_ls8c_ard_3-0-0_106081_2018-12-13_final
2018-12-13 10:58:15	ga_ls8c_ard_3-0-0_106082_2018-12-13_final
2018-12-13 10:58:39	ga_ls8c_ard_3-0-0_106083_2018-12-13_final
2018-12-13 10:59:03	ga_ls8c_ard_3-0-0_106084_2018-12-13_final
2018-12-18 11:10:48	ga_ls8c_ard_3-0-0_109067_2018-12-18_final
2018-12-18 11:11:12	ga_ls8c_ard_3-0-0_109068_2018-12-18_final
2018-12-18 11:11:36	ga_ls8c_ard_3-0-0_109069_2018-12-18_final
2018-12-18 11:12:00	ga_ls8c_ard_3-0-0_109070_2018-12-18_final
2018-12-18 11:12:24	ga_ls8c_ard_3-0-0_109071_2018-12-18_final
2018-12-18 11:12:48	ga_ls8c_ard_3-0-0_109072_2018-12-18_final
2018-12-25 11:16:59	ga_ls8c_ard_3-0-0_110067_2018-12-25_final
2018-12-27 11:06:37	ga_ls8c_ard_3-0-0_108072_2018-12-27_final
2018-12-29 10:57:27	ga_ls8c_ard_3-0-0_106080_2018-12-29_final
2018-12-29 10:57:51	ga_ls8c_ard_3-0-0_106081_2018-12-29_final
2018-12-29 10:58:15	ga_ls8c_ard_3-0-0_106082_2018-12-29_final
2018-12-29 10:58:39	ga_ls8c_ard_3-0-0_106083_2018-12-29_final
2018-12-29 10:59:03	ga_ls8c_ard_3-0-0_106084_2018-12-29_final
2024-03-14 11:06:11	ga_ls8c_ard_3-2-1_108071_2024-03-14_final
2024-03-14 11:06:35	ga_ls8c_ard_3-2-1_108072_2024-03-14_final
2024-03-14 11:06:59	ga_ls8c_ard_3-2-1_108073_2024-03-14_final
2024-03-14 11:07:23	ga_ls8c_ard_3-2-1_108074_2024-03-14_final
2024-03-14 11:07:47	ga_ls8c_ard_3-2-1_108075_2024-03-14_final
2024-03-14 11:08:11	ga_ls8c_ard_3-2-1_108076_2024-03-14_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