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
2022-03-30 09:49:20	ga_ls8c_ard_3-2-1_095080_2022-03-30_final
2022-03-30 09:49:44	ga_ls8c_ard_3-2-1_095081_2022-03-30_final
2022-03-30 09:50:08	ga_ls8c_ard_3-2-1_095082_2022-03-30_final
2022-03-30 09:50:32	ga_ls8c_ard_3-2-1_095083_2022-03-30_final
2022-03-30 09:50:56	ga_ls8c_ard_3-2-1_095084_2022-03-30_final
2022-03-30 09:51:20	ga_ls8c_ard_3-2-1_095085_2022-03-30_final
2022-03-30 09:51:44	ga_ls8c_ard_3-2-1_095086_2022-03-30_final
2022-03-30 09:52:08	ga_ls8c_ard_3-2-1_095087_2022-03-30_final
2022-04-01 09:39:46	ga_ls8c_ard_3-2-1_093087_2022-04-01_final
2022-04-01 09:40:10	ga_ls8c_ard_3-2-1_093088_2022-04-01_final
2022-04-02 10:16:38	ga_ls8c_ard_3-2-1_100071_2022-04-02_final
2022-04-02 10:17:02	ga_ls8c_ard_3-2-1_100072_2022-04-02_final
2022-04-02 10:17:26	ga_ls8c_ard_3-2-1_100073_2022-04-02_final
2022-04-02 10:17:50	ga_ls8c_ard_3-2-1_100074_2022-04-02_final
2022-04-04 10:02:42	ga_ls8c_ard_3-2-1_098067_2022-04-04_final
2022-04-04 10:03:06	ga_ls8c_ard_3-2-1_098068_2022-04-04_final
2022-04-04 10:03:30	ga_ls8c_ard_3-2-1_098069_2022-04-04_final
2022-04-04 10:03:54	ga_ls8c_ard_3-2-1_098070_2022-04-04_final
2022-04-04 10:04:18	ga_ls8c_ard_3-2-1_098071_2022-04-04_final
2022-04-04 10:04:42	ga_ls8c_ard_3-2-1_098072_2022-04-04_final
2022-04-04 10:05:05	ga_ls8c_ard_3-2-1_098073_2022-04-04_final
2022-04-04 10:05:29	ga_ls8c_ard_3-2-1_098074_2022-04-04_final
2022-04-04 10:05:53	ga_ls8c_ard_3-2-1_098075_2022-04-04_final
2022-04-04 10:06:17	ga_ls8c_ard_3-2-1_098076_2022-04-04_final
2022-04-04 10:06:41	ga_ls8c_ard_3-2-1_098077_2022-04-04_final
2022-04-04 10:07:05	ga_ls8c_ard_3-2-1_098078_2022-04-04_final
2022-04-04 10:07:29	ga_ls8c_ard_3-2-1_098079_2022-04-04_final
2022-04-04 10:07:53	ga_ls8c_ard_3-2-1_098080_2022-04-04_final
2022-04-04 10:08:17	ga_ls8c_ard_3-2-1_098081_2022-04-04_final
2022-04-04 10:08:41	ga_ls8c_ard_3-2-1_098082_2022-04-04_final
2022-04-06 09:53:33	ga_ls8c_ard_3-2-1_096075_2022-04-06_final
2022-04-06 09:53:57	ga_ls8c_ard_3-2-1_096076_2022-04-06_final
2022-04-06 09:54:21	ga_ls8c_ard_3-2-1_096077_2022-04-06_final
2022-04-06 09:54:45	ga_ls8c_ard_3-2-1_096078_2022-04-06_final
2022-04-06 09:55:09	ga_ls8c_ard_3-2-1_096079_2022-04-06_final
2022-04-06 09:55:33	ga_ls8c_ard_3-2-1_096080_2022-04-06_final
2022-04-06 09:55:57	ga_ls8c_ard_3-2-1_096081_2022-04-06_final
2022-04-06 09:56:21	ga_ls8c_ard_3-2-1_096082_2022-04-06_final
2022-04-06 09:56:45	ga_ls8c_ard_3-2-1_096083_2022-04-06_final
2022-04-06 09:57:09	ga_ls8c_ard_3-2-1_096084_2022-04-06_final
2022-04-06 09:57:33	ga_ls8c_ard_3-2-1_096085_2022-04-06_final
2022-04-06 09:57:57	ga_ls8c_ard_3-2-1_096086_2022-04-06_final
2022-04-08 09:44:48	ga_ls8c_ard_3-2-1_094084_2022-04-08_final
2022-04-08 09:45:12	ga_ls8c_ard_3-2-1_094085_2022-04-08_final
2022-04-08 09:45:36	ga_ls8c_ard_3-2-1_094086_2022-04-08_final
2022-04-08 09:46:00	ga_ls8c_ard_3-2-1_094087_2022-04-08_final
2022-04-11 10:08:57	ga_ls8c_ard_3-2-1_099067_2022-04-11_final
2022-04-11 10:09:21	ga_ls8c_ard_3-2-1_099068_2022-04-11_final
2022-04-11 10:09:45	ga_ls8c_ard_3-2-1_099069_2022-04-11_final
2022-04-11 10:10:09	ga_ls8c_ard_3-2-1_099070_2022-04-11_final
2022-04-11 10:10:33	ga_ls8c_ard_3-2-1_099071_2022-04-11_final
2022-04-11 10:10:57	ga_ls8c_ard_3-2-1_099072_2022-04-11_final
2022-04-11 10:11:20	ga_ls8c_ard_3-2-1_099073_2022-04-11_final
2022-04-11 10:11:44	ga_ls8c_ard_3-2-1_099074_2022-04-11_final
2022-04-11 10:12:08	ga_ls8c_ard_3-2-1_099075_2022-04-11_final
2022-04-11 10:12:32	ga_ls8c_ard_3-2-1_099076_2022-04-11_final
2022-04-11 10:12:56	ga_ls8c_ard_3-2-1_099077_2022-04-11_final
2022-04-11 10:13:20	ga_ls8c_ard_3-2-1_099078_2022-04-11_final
2022-04-13 09:58:36	ga_ls8c_ard_3-2-1_097072_2022-04-13_final
2022-04-13 09:59:48	ga_ls8c_ard_3-2-1_097075_2022-04-13_final
2022-04-13 10:00:11	ga_ls8c_ard_3-2-1_097076_2022-04-13_final
2022-04-13 10:00:35	ga_ls8c_ard_3-2-1_097077_2022-04-13_final
2022-04-13 10:00:59	ga_ls8c_ard_3-2-1_097078_2022-04-13_final
2022-04-13 10:01:23	ga_ls8c_ard_3-2-1_097079_2022-04-13_final
2022-04-13 10:01:47	ga_ls8c_ard_3-2-1_097080_2022-04-13_final
2022-04-13 10:02:11	ga_ls8c_ard_3-2-1_097081_2022-04-13_final
2022-04-13 10:02:35	ga_ls8c_ard_3-2-1_097082_2022-04-13_final
2022-04-13 10:02:59	ga_ls8c_ard_3-2-1_097083_2022-04-13_final
2022-04-13 10:03:23	ga_ls8c_ard_3-2-1_097084_2022-04-13_final
2022-04-13 10:03:47	ga_ls8c_ard_3-2-1_097085_2022-04-13_final
2022-04-15 09:49:26	ga_ls8c_ard_3-2-1_095080_2022-04-15_final
2022-04-15 09:49:50	ga_ls8c_ard_3-2-1_095081_2022-04-15_final
2022-04-15 09:50:14	ga_ls8c_ard_3-2-1_095082_2022-04-15_final
2022-04-15 09:50:38	ga_ls8c_ard_3-2-1_095083_2022-04-15_final
2022-04-15 09:51:02	ga_ls8c_ard_3-2-1_095084_2022-04-15_final
2022-04-15 09:51:26	ga_ls8c_ard_3-2-1_095085_2022-04-15_final
2022-04-15 09:51:50	ga_ls8c_ard_3-2-1_095086_2022-04-15_final
2022-04-15 09:52:14	ga_ls8c_ard_3-2-1_095087_2022-04-15_final
2022-04-17 09:39:52	ga_ls8c_ard_3-2-1_093087_2022-04-17_final
2022-04-17 09:40:16	ga_ls8c_ard_3-2-1_093088_2022-04-17_final
2022-04-18 10:16:44	ga_ls8c_ard_3-2-1_100071_2022-04-18_final
2022-04-18 10:17:08	ga_ls8c_ard_3-2-1_100072_2022-04-18_final
2022-04-18 10:17:32	ga_ls8c_ard_3-2-1_100073_2022-04-18_final
2022-04-18 10:17:56	ga_ls8c_ard_3-2-1_100074_2022-04-18_final
2022-04-20 10:02:46	ga_ls8c_ard_3-2-1_098067_2022-04-20_final
2022-04-20 10:03:10	ga_ls8c_ard_3-2-1_098068_2022-04-20_final
2022-04-20 10:03:34	ga_ls8c_ard_3-2-1_098069_2022-04-20_final
2022-04-20 10:03:58	ga_ls8c_ard_3-2-1_098070_2022-04-20_final
2022-04-20 10:04:22	ga_ls8c_ard_3-2-1_098071_2022-04-20_final
2022-04-20 10:04:46	ga_ls8c_ard_3-2-1_098072_2022-04-20_final
2022-04-20 10:05:10	ga_ls8c_ard_3-2-1_098073_2022-04-20_final
2022-04-20 10:05:34	ga_ls8c_ard_3-2-1_098074_2022-04-20_final
2022-04-20 10:05:58	ga_ls8c_ard_3-2-1_098075_2022-04-20_final
2022-04-20 10:06:22	ga_ls8c_ard_3-2-1_098076_2022-04-20_final
2022-04-20 10:06:46	ga_ls8c_ard_3-2-1_098077_2022-04-20_final
2022-04-20 10:07:10	ga_ls8c_ard_3-2-1_098078_2022-04-20_final
2022-04-20 10:07:34	ga_ls8c_ard_3-2-1_098079_2022-04-20_final
2022-04-20 10:07:58	ga_ls8c_ard_3-2-1_098080_2022-04-20_final
2022-04-20 10:08:21	ga_ls8c_ard_3-2-1_098081_2022-04-20_final
2022-04-20 10:08:45	ga_ls8c_ard_3-2-1_098082_2022-04-20_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