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
2023-10-14 10:21:04	ga_ls8c_ard_3-2-1_100081_2023-10-14_final
2023-10-14 10:21:28	ga_ls8c_ard_3-2-1_100082_2023-10-14_final
2023-10-15 09:23:27	ga_ls8c_ard_3-2-1_091076_2023-10-14_final
2023-10-15 09:24:15	ga_ls8c_ard_3-2-1_091078_2023-10-14_final
2023-10-15 09:24:38	ga_ls8c_ard_3-2-1_091079_2023-10-14_final
2023-10-16 10:06:18	ga_ls8c_ard_3-2-1_098075_2023-10-16_final
2023-10-16 10:06:42	ga_ls8c_ard_3-2-1_098076_2023-10-16_final
2023-10-16 10:08:42	ga_ls8c_ard_3-2-1_098081_2023-10-16_final
2023-10-16 10:09:30	ga_ls8c_ard_3-2-1_098083_2023-10-16_final
2023-10-16 11:47:35	ga_ls8c_ard_3-2-1_114081_2023-10-16_final
2023-10-17 09:11:28	ga_ls8c_ard_3-2-1_089077_2023-10-16_final
2023-10-17 09:11:52	ga_ls8c_ard_3-2-1_089078_2023-10-16_final
2023-10-17 09:12:16	ga_ls8c_ard_3-2-1_089079_2023-10-16_final
2023-10-17 09:12:40	ga_ls8c_ard_3-2-1_089080_2023-10-16_final
2023-10-17 09:13:04	ga_ls8c_ard_3-2-1_089081_2023-10-16_final
2023-10-17 09:13:28	ga_ls8c_ard_3-2-1_089082_2023-10-16_final
2023-10-17 09:14:16	ga_ls8c_ard_3-2-1_089084_2023-10-16_final
2023-10-17 09:14:40	ga_ls8c_ard_3-2-1_089085_2023-10-16_final
2023-10-17 09:15:04	ga_ls8c_ard_3-2-1_089086_2023-10-16_final
2023-10-17 09:16:16	ga_ls8c_ard_3-2-1_089089_2023-10-16_final
2023-10-17 09:16:40	ga_ls8c_ard_3-2-1_089090_2023-10-16_final
2023-10-17 10:46:22	ga_ls8c_ard_3-2-1_105067_2023-10-17_final
2023-10-17 10:46:46	ga_ls8c_ard_3-2-1_105068_2023-10-17_final
2023-10-17 10:47:10	ga_ls8c_ard_3-2-1_105069_2023-10-17_final
2023-10-17 10:47:58	ga_ls8c_ard_3-2-1_105071_2023-10-17_final
2023-10-17 10:48:46	ga_ls8c_ard_3-2-1_105073_2023-10-17_final
2023-10-17 10:49:10	ga_ls8c_ard_3-2-1_105074_2023-10-17_final
2023-10-17 10:49:33	ga_ls8c_ard_3-2-1_105075_2023-10-17_final
2023-10-17 10:49:57	ga_ls8c_ard_3-2-1_105076_2023-10-17_final
2023-10-17 10:50:45	ga_ls8c_ard_3-2-1_105078_2023-10-17_final
2023-10-17 10:51:09	ga_ls8c_ard_3-2-1_105079_2023-10-17_final
2023-10-17 10:51:57	ga_ls8c_ard_3-2-1_105081_2023-10-17_final
2023-10-17 10:52:21	ga_ls8c_ard_3-2-1_105082_2023-10-17_final
2023-10-17 10:52:45	ga_ls8c_ard_3-2-1_105083_2023-10-17_final
2023-10-18 09:51:56	ga_ls8c_ard_3-2-1_096070_2023-10-18_final
2023-10-18 09:53:08	ga_ls8c_ard_3-2-1_096073_2023-10-18_final
2023-10-18 09:53:32	ga_ls8c_ard_3-2-1_096074_2023-10-18_final
2023-10-18 09:54:44	ga_ls8c_ard_3-2-1_096077_2023-10-18_final
2023-10-18 09:55:08	ga_ls8c_ard_3-2-1_096078_2023-10-18_final
2023-10-18 09:55:32	ga_ls8c_ard_3-2-1_096079_2023-10-18_final
2023-10-18 09:56:19	ga_ls8c_ard_3-2-1_096081_2023-10-18_final
2023-10-18 09:57:07	ga_ls8c_ard_3-2-1_096083_2023-10-18_final
2023-10-18 09:57:31	ga_ls8c_ard_3-2-1_096084_2023-10-18_final
2023-10-18 09:57:55	ga_ls8c_ard_3-2-1_096085_2023-10-18_final
2023-10-19 10:34:23	ga_ls8c_ard_3-2-1_103068_2023-10-19_final
2023-10-19 10:34:47	ga_ls8c_ard_3-2-1_103069_2023-10-19_final
2023-10-19 10:35:11	ga_ls8c_ard_3-2-1_103070_2023-10-19_final
2023-10-19 10:35:35	ga_ls8c_ard_3-2-1_103071_2023-10-19_final
2023-10-19 10:35:59	ga_ls8c_ard_3-2-1_103072_2023-10-19_final
2023-10-19 10:36:23	ga_ls8c_ard_3-2-1_103073_2023-10-19_final
2023-10-19 10:37:11	ga_ls8c_ard_3-2-1_103075_2023-10-19_final
2023-10-19 10:38:47	ga_ls8c_ard_3-2-1_103079_2023-10-19_final
2023-10-19 10:39:35	ga_ls8c_ard_3-2-1_103081_2023-10-19_final
2023-10-19 10:39:59	ga_ls8c_ard_3-2-1_103082_2023-10-19_final
2023-10-20 09:41:33	ga_ls8c_ard_3-2-1_094075_2023-10-20_final
2023-10-20 09:41:57	ga_ls8c_ard_3-2-1_094076_2023-10-20_final
2023-10-20 09:42:21	ga_ls8c_ard_3-2-1_094077_2023-10-20_final
2023-10-20 09:42:45	ga_ls8c_ard_3-2-1_094078_2023-10-20_final
2023-10-20 09:43:09	ga_ls8c_ard_3-2-1_094079_2023-10-20_final
2023-10-20 09:43:33	ga_ls8c_ard_3-2-1_094080_2023-10-20_final
2023-10-20 09:43:57	ga_ls8c_ard_3-2-1_094081_2023-10-20_final
2023-10-20 09:44:21	ga_ls8c_ard_3-2-1_094082_2023-10-20_final
2023-10-20 09:44:45	ga_ls8c_ard_3-2-1_094083_2023-10-20_final
2023-10-20 09:45:33	ga_ls8c_ard_3-2-1_094085_2023-10-20_final
2023-10-20 09:45:57	ga_ls8c_ard_3-2-1_094086_2023-10-20_final
2023-10-20 09:46:21	ga_ls8c_ard_3-2-1_094087_2023-10-20_final
2023-10-20 11:18:27	ga_ls8c_ard_3-2-1_110070_2023-10-20_final
2023-10-20 11:18:51	ga_ls8c_ard_3-2-1_110071_2023-10-20_final
2023-10-20 11:19:15	ga_ls8c_ard_3-2-1_110072_2023-10-20_final
2023-10-20 11:19:38	ga_ls8c_ard_3-2-1_110073_2023-10-20_final
2023-10-20 11:20:26	ga_ls8c_ard_3-2-1_110075_2023-10-20_final
2023-10-20 11:20:50	ga_ls8c_ard_3-2-1_110076_2023-10-20_final
2023-10-20 11:21:14	ga_ls8c_ard_3-2-1_110077_2023-10-20_final
2023-10-20 11:21:38	ga_ls8c_ard_3-2-1_110078_2023-10-20_final
2023-10-20 11:22:26	ga_ls8c_ard_3-2-1_110080_2023-10-20_final
2023-10-20 11:23:14	ga_ls8c_ard_3-2-1_110082_2023-10-20_final
2023-10-20 11:24:02	ga_ls8c_ard_3-2-1_110084_2023-10-20_final
2023-10-20 11:24:26	ga_ls8c_ard_3-2-1_110085_2023-10-20_final
2023-10-24 10:53:22	ga_ls8c_ard_3-2-1_106069_2023-10-24_final
2023-10-24 10:58:10	ga_ls8c_ard_3-2-1_106081_2023-10-24_final
2023-10-24 10:58:34	ga_ls8c_ard_3-2-1_106082_2023-10-24_final
2023-10-25 09:57:46	ga_ls8c_ard_3-2-1_097069_2023-10-25_final
2023-10-25 09:58:10	ga_ls8c_ard_3-2-1_097070_2023-10-25_final
2023-10-25 09:58:33	ga_ls8c_ard_3-2-1_097071_2023-10-25_final
2023-10-25 09:58:57	ga_ls8c_ard_3-2-1_097072_2023-10-25_final
2023-10-25 09:59:21	ga_ls8c_ard_3-2-1_097073_2023-10-25_final
2023-10-25 10:00:57	ga_ls8c_ard_3-2-1_097077_2023-10-25_final
2023-10-25 10:04:09	ga_ls8c_ard_3-2-1_097085_2023-10-25_final
2023-10-25 11:38:38	ga_ls8c_ard_3-2-1_113074_2023-10-25_final
2023-10-25 11:39:02	ga_ls8c_ard_3-2-1_113075_2023-10-25_final
2023-10-25 11:39:26	ga_ls8c_ard_3-2-1_113076_2023-10-25_final
2023-10-25 11:39:50	ga_ls8c_ard_3-2-1_113077_2023-10-25_final
2023-10-25 11:40:14	ga_ls8c_ard_3-2-1_113078_2023-10-25_final
2023-10-25 11:40:38	ga_ls8c_ard_3-2-1_113079_2023-10-25_final
2023-10-25 11:41:02	ga_ls8c_ard_3-2-1_113080_2023-10-25_final
2023-10-25 11:41:26	ga_ls8c_ard_3-2-1_113081_2023-10-25_final
2023-10-25 11:41:50	ga_ls8c_ard_3-2-1_113082_2023-10-25_final
2023-10-25 11:42:14	ga_ls8c_ard_3-2-1_113083_2023-10-25_final
2023-10-26 09:06:32	ga_ls8c_ard_3-2-1_088080_2023-10-25_final
2023-10-26 09:06:56	ga_ls8c_ard_3-2-1_088081_2023-10-25_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